[House Hearing, 115 Congress]
[From the U.S. Government Publishing Office]







               PROS AND CONS OF RESTRICTING SNAP PURCHASES

=======================================================================

                                HEARING

                               BEFORE THE

                        COMMITTEE ON AGRICULTURE
                        HOUSE OF REPRESENTATIVES

                     ONE HUNDRED FIFTEENTH CONGRESS

                             FIRST SESSION

                               ----------                              

                           FEBRUARY 16, 2017

                               ----------                              

                            Serial No. 115-2

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          Printed for the use of the Committee on Agriculture
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              PROS AND CONS OF RESTRICTING SNAP PURCHASES

=======================================================================

                                HEARING

                               BEFORE THE

                        COMMITTEE ON AGRICULTURE
                        HOUSE OF REPRESENTATIVES

                     ONE HUNDRED FIFTEENTH CONGRESS

                             FIRST SESSION

                               __________

                           FEBRUARY 16, 2017

                               __________

                            Serial No. 115-2



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]





          Printed for the use of the Committee on Agriculture
                         agriculture.house.gov






                                ______

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                        COMMITTEE ON AGRICULTURE

                  K. MICHAEL CONAWAY, Texas, Chairman

GLENN THOMPSON, Pennsylvania         COLLIN C. PETERSON, Minnesota, 
    Vice Chairman                    Ranking Minority Member
BOB GOODLATTE, Virginia,             DAVID SCOTT, Georgia
FRANK D. LUCAS, Oklahoma             JIM COSTA, California
STEVE KING, Iowa                     TIMOTHY J. WALZ, Minnesota
MIKE ROGERS, Alabama                 MARCIA L. FUDGE, Ohio
BOB GIBBS, Ohio                      JAMES P. McGOVERN, Massachusetts
AUSTIN SCOTT, Georgia                FILEMON VELA, Texas, Vice Ranking 
ERIC A. ``RICK'' CRAWFORD, Arkansas  Minority Member
SCOTT DesJARLAIS, Tennessee          MICHELLE LUJAN GRISHAM, New Mexico
VICKY HARTZLER, Missouri             ANN M. KUSTER, New Hampshire
JEFF DENHAM, California              RICHARD M. NOLAN, Minnesota
DOUG LaMALFA, California             CHERI BUSTOS, Illinois
RODNEY DAVIS, Illinois               SEAN PATRICK MALONEY, New York
TED S. YOHO, Florida                 STACEY E. PLASKETT, Virgin Islands
RICK W. ALLEN, Georgia               ALMA S. ADAMS, North Carolina
MIKE BOST, Illinois                  DWIGHT EVANS, Pennsylvania
DAVID ROUZER, North Carolina         AL LAWSON, Jr., Florida
RALPH LEE ABRAHAM, Louisiana         TOM O'HALLERAN, Arizona
TRENT KELLY, Mississippi             JIMMY PANETTA, California
JAMES COMER, Kentucky                DARREN SOTO, Florida
ROGER W. MARSHALL, Kansas            LISA BLUNT ROCHESTER, Delaware
DON BACON, Nebraska
JOHN J. FASO, New York
NEAL P. DUNN, Florida
JODEY C. ARRINGTON, Texas

                                 ______

                   Matthew S. Schertz, Staff Director

                 Anne Simmons, Minority Staff Director

                                  (ii)
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                                  
                             C O N T E N T S

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                                                                   Page
Conaway, Hon. K. Michael, a Representative in Congress from 
  Texas, opening statement.......................................     1
    Prepared statement...........................................     2
    Submitted report.............................................   153
Peterson, Hon. Collin C., a Representative in Congress from 
  Minnesota, opening statement...................................     3

                               Witnesses

Rachidi, Ph.D., Angela K., Research Fellow in Poverty Studies, 
  American Enterprise Institute, Washington, D.C.................     4
    Prepared statement...........................................     5
Schanzenbach, Ph.D., Diane Whitmore, Director and Senior Fellow, 
  Economic Studies, Brookings Institution; Professor of Social 
  Policy and of Economics, The Hamilton Project, Northwestern 
  University, Washington, D.C....................................    11
    Prepared statement...........................................    12
    Submitted question...........................................   395
Sarasin, Leslie G., President and Chief Executive Officer, Food 
  Marketing Institute, Arlington, VA.............................    17
    Prepared statement...........................................    19
Weidman, John, Deputy Executive Director, The Food Trust, 
  Philadelphia, PA...............................................    29
    Prepared statement...........................................    31
Wansink, Ph.D., Brian, John S. Dyson Professor of Marketing and 
  Director, Cornell University Food and Brand Lab, Ithaca, NY....    33
    Prepared statement...........................................    34

                           Submitted Material

Feeding Texas, submitted policy brief............................   282
Secretaries' Innovation Group, submitted statement...............   283
Allison, Ph.D., David B., Distinguished Quetelet Endowed 
  Professor; Associate Dean for Research & Science; Director, 
  Office of Energetics; Director, Nutrition & Obesity Research 
  Center, Department of Nutrition Sciences, School of Health 
  Professions, University of Alabama at Birmingham, submitted 
  letter.........................................................   284

 
              PROS AND CONS OF RESTRICTING SNAP PURCHASES

                              ----------                              


                      THURSDAY, FEBRUARY 16, 2017

                          House of Representatives,
                                  Committee on Agriculture,
                                                   Washington, D.C.
    The Committee met, pursuant to other business, at 10:24 
a.m., in Room 1300 of the Longworth House Office Building, Hon. 
K. Michael Conaway [Chairman of the Committee] presiding.
    Members present: Representatives Conaway, Thompson, 
Goodlatte, King, Rogers, Gibbs, Austin Scott of Georgia, 
Crawford, Hartzler, Denham, LaMalfa, Davis, Yoho, Allen, Bost, 
Rouzer, Kelly, Comer, Marshall, Bacon, Faso, Dunn, Arrington, 
Peterson, David Scott of Georgia, Costa, Walz, Fudge, McGovern, 
Lujan Grisham, Kuster, Nolan, Bustos, Maloney, Plaskett, Adams, 
Evans, Lawson, O'Halleran, Panetta, Soto, and Blunt Rochester.
    Staff present: Bart Fischer, Caleb Crosswhite, Callie 
McAdams, Haley Graves, Jackie Barber, Jadi Chapman, Jennifer 
Tiller, Mary Rose Conroy, Stephanie Addison, Keith Jones, 
Kellie Adesina, Lisa Shelton, Troy Phillips, John Konya, Nicole 
Scott, and Carly Reedholm.

OPENING STATEMENT OF HON. K. MICHAEL CONAWAY, A REPRESENTATIVE 
                     IN CONGRESS FROM TEXAS

    The Chairman. This hearing of the Committee on Agriculture 
entitled, Pros and Cons of Restricting SNAP Purchases, will 
come to order. Thank you.
    I want to welcome our witnesses to today's hearing, and 
thank them for taking the time to share their views on a very 
timely and somewhat sensitive topic, the idea of restricting 
SNAP purchases. This hearing is a continuation of the 
conversation had at a Member roundtable last October. There are 
good arguments to be made on both sides of this issue, and this 
discussion will be yet another addition to the Committee's 
commitment to strengthening the Supplemental Nutrition 
Assistance Program.
    On November 18 of last year, USDA released a report 
entitled, Foods Typically Purchased by Supplemental Nutrition 
Assistance Program Households. This study analyzed food 
purchase data collected at the point of sale to assess 
differences in the purchasing patterns of SNAP and non-SNAP 
households. Ultimately, the report found that about 40 of 
every dollar of every purchase dollar was spent on basic items 
like meat, fruits, vegetables, milk, eggs, and bread. Another 
20 was spent on sweetened drinks, desserts, salty snacks, 
candy, and sugar. The remaining 40 was spent on a variety of 
items such as cereal, prepared foods, other dairy products, 
rice, beans, and other cooking ingredients. To be clear, when 
comparing spending on broad food categories, the data show that 
both SNAP and non-SNAP households make similar food choices. 
However, the report also confirms that there are differences in 
spending in individual food categories. One can also reasonably 
infer from the report that billions in taxpayer dollars are 
being spent on items like sweetened beverages and prepared 
desserts.
    This report, while not the sole basis of this hearing, begs 
the question of whether certain food or beverage items should 
be restricted as eligible food items in SNAP. While it is 
important to have this discussion, we can all agree that no one 
in America ought to go hungry, and SNAP is essential to 
providing nutrition to the most vulnerable citizens during 
tough times.
    Our goal is to provide much-needed nutrition and to 
encourage Americans to eat healthier. To that end, this 
Committee has historically advocated for nutrition education 
and healthy eating incentive programs. Today, we will consider 
whether additional restrictions should be added to that mix.
    Thank you again to the witnesses for being here today. We 
look forward to your testimony.
    [The prepared statement of Mr. Conaway follows:]

  Prepared Statement of Hon. K. Michael Conaway, a Representative in 
                          Congress from Texas
    I want to welcome our witnesses to today's hearing and thank them 
for taking the time to share their views on a very timely and somewhat 
sensitive topic--the idea of restricting SNAP purchases. This hearing 
is a continuation of the conversation had in a Member roundtable last 
October. There are good arguments to be made on both sides of this 
issue, and this discussion will be yet another addition to the 
Committee's commitment to strengthening the Supplemental Nutrition 
Assistance Program.
    On November 18th of last year, USDA released a report entitled, 
Foods Typically Purchased by Supplemental Nutrition Assistance Program 
Households. This study analyzed food purchase data collected at the 
point of sale to assess differences in the purchasing patterns of SNAP 
and non-SNAP households.
    Ultimately, the report found that about 40 of every food purchase 
dollar was spent on basic items like meat, fruits, vegetables, milk, 
eggs, and bread.
    Another 20 was spent on sweetened drinks, desserts, salty snacks, 
candy, and sugar. The remaining 40 was spent on a variety of items 
such as cereal, prepared foods, other dairy products, rice, beans, and 
other cooking ingredients.
    To be clear, when comparing spending on broad food categories, the 
data show that both SNAP and non-SNAP households made similar food 
choices. However, the report also confirms that there are differences 
in spending on individual food categories. One can also reasonably 
infer from the report that billions in taxpayer dollars are being spent 
on items like sweetened beverages and prepared desserts.
    The report, while not the sole basis of this hearing, begs the 
question of whether certain food or beverage items should be restricted 
as eligible food items in SNAP. While it's important to have this 
discussion, we can all agree that no one in America ought to go hungry, 
and SNAP is essential in providing nutrition to the most vulnerable 
citizens during tough times.
    Our goal is to provide much needed nutrition and to encourage 
Americans to eat healthier. To that end, this Committee has 
historically advocated for nutrition education and healthy eating 
incentive programs. Today, we will consider whether additional 
restrictions should be added to that mix. Thank you again to the 
witnesses for being here today. We look forward to your testimony.
    With that, I now turn to the Ranking Member for any comments he 
would like to make.

    The Chairman. I now turn to the Ranking Member for any 
comments that he would like to make.

   STATEMENT OF HON. COLLIN C. PETERSON, A REPRESENTATIVE IN 
              CONGRESS FROM THE STATE OF MINNESOTA

    Mr. Peterson. Thank you, Mr. Chairman.
    We have had 16 SNAP hearings, we are now taking a look at 
how SNAP recipients are purchasing food, what kind of food they 
are purchasing with their SNAP dollars.
    Before we get too far, though, I think it is important to 
again note that the overwhelming theme of the testimony we have 
heard in the last Congress is that while there are some areas 
for improvement, SNAP works. We heard testimony opposing 
efforts to block grant SNAP and on the importance of keeping 
SNAP within the farm bill.
    Those of us who have been around a while know that this is 
a complicated program, and I would urge Members to keep that in 
mind as we work on the farm bill this next year. I don't think 
there is one single issue that is the problem, and I don't 
think there is one single solution that will magically somehow 
improve SNAP efficiency.
    Looking specifically at SNAP food choice, it would seem 
pretty straightforward that we not allow SNAP dollars to be 
spent on junk food. But the problem is, how do you define that? 
This is something that I took a look at when I was Chairman.
    In Minnesota, they tried this. Somehow or another they 
requested a waiver from FNS to disallow candy, I don't know how 
they did this, but when they were defining candy, if the candy 
didn't contain wheat it was banned, but if it did contain 
wheat, it wasn't. So a Kit-Kat bar was okay under what they 
were doing, and a Hershey bar was not. So I don't know. When 
you go down this route, you are opening a real can of worms, 
and from what I can tell talking to my folks back home, that 
grocery stores have really no interest in being the food 
police. USDA has been resistant to this effort as well. And 
from what I know, when you look at how, and the kind of food, 
SNAP recipients buy, it is really not different from the food 
of people that are not on SNAP. The underlying issue is all of 
us in the United States do a bad job of deciding what to eat, 
and we can all use some guidance probably. But I am not sure 
the government is the way to provide that.
    So I am hopeful that we can be open-minded. The discussion 
on these issues can continue and our efforts can continue, so 
that we learn more about how SNAP actually works, and I look 
forward to hearing today's witnesses and yield back.
    The Chairman. I thank the gentleman. The chair would remind 
or request that other Members submit their opening statements 
for the record so witnesses may begin their testimony to ensure 
that there is ample time for questioning.
    I want to thank our panel for being here. It is, by all 
arguments, some of the best informed folks, and it is a 
balanced panel. We have folks on both sides of the issue, and 
we have folks who have to administer the program, whatever it 
is we come up with. So we have a terrific panel and I am 
excited to hear from them after reading their testimony last 
night.
    Today, we have with us Dr. Angela Rachidi. She is a 
Research Fellow, Poverty Studies at American Enterprise 
Institute here in Washington, D.C. We have Diane Whitmore 
Schanzenbach, Director of The Hamilton Project, Senior Fellow, 
Economic Studies, the Brookings Institute here in D.C. We have 
Leslie Sarasin, CEO of the Food Marketing Institute in 
Arlington, Virginia. We have Mr. John Weidman, who is the 
Deputy Executive Director, The Food Trust, Philadelphia, 
Pennsylvania. And we have Brian Wansink, the Director of 
Cornell University Food and Brand Lab at Ithaca, New York. And 
given everyone's last names, I came sort of close to getting 
some of those right. So Dr. Rachidi, if you will, please, 5 
minutes.

        STATEMENT OF ANGELA K. RACHIDI, Ph.D., RESEARCH
         FELLOW IN POVERTY STUDIES, AMERICAN ENTERPRISE
                  INSTITUTE, WASHINGTON, D.C.

    Dr. Rachidi. Thank you. Chairman Conaway, Ranking Member 
Peterson, and other Members of the Committee, thank you for the 
opportunity to testify this morning on restrictions on 
purchases in the Supplemental Nutrition Assistance Program, or 
SNAP. My name is Angela Rachidi, and I am a Research Fellow in 
Poverty Studies at the American Enterprise Institute, or AEI. 
Prior to joining AEI, I was the Deputy Commissioner for Policy 
and Evaluation at the New York City Department of Human 
Resources, or HRA. HRA administers SNAP, and during my time 
there, we provided benefits to almost two million New Yorkers 
each month.
    Most relevant for my testimony today is my experience 
drafting a proposal for a demonstration project in New York 
City to restrict the use of SNAP benefits to purchase sweetened 
beverages. Regrettably, it was denied by the U.S. Department of 
Agriculture in 2011.
    I will make four main points today. First, obesity and the 
related health problems remain one of the most challenging 
public health issues of our time, with sweetened beverages 
identified as one of the main contributors. Second, the 
integrity of SNAP as a publicly funded program rests on how 
well its implementation matches the stated goals of the 
program. Third, this problem is not unique to low-income 
households, but SNAP offers one opportunity for government to 
play a positive role. And fourth, a demonstration project to 
test a restriction on sweetened beverages in SNAP is consistent 
with bipartisan efforts to support evidence-based policy 
making.
    For my oral testimony, I won't go through all of the 
research on obesity, the related health problems, and its 
connection to sweetened beverages. But I do want to say, 
however, that obesity is a major public health crisis that 
affects all Americans, no matter their income status, and for 
this reason, it requires a multi-faceted public health 
approach.
    High sweetened beverage consumption is not unique to SNAP 
households, but supporting such purchases, especially at the 
levels suggested in the data, directly contradicts the stated 
goals of the program. The Food Stamp Act of 1977 states that 
the goal is to provide for improved levels of nutrition among 
low-income households through a cooperative Federal-state 
program of food assistance. This purpose holds today.
    For a program with a stated goal of improving nutrition, 
accepting such a large percentage of spending on beverages with 
no nutritional value seems counterintuitive and likely 
undermines public support for the program. Estimates suggest 
SNAP households spend almost ten percent of their food budgets 
on these products. Allowing the purchase of sweetened beverages 
also directly competes with nutritional education programming, 
and it competes against costs associated with obesity, which 
sweetened beverages are a large contributor to; estimates 
suggest that obesity costs $147 billion per year.
    Placing restrictions on SNAP should be part of a broader 
approach to address this problem. Some believe that educating 
SNAP recipients on healthy eating is a better approach. I would 
argue that it should not be one or the other, and the USDA's 
own research supports this. The USDA's Healthy Incentives 
Program, which gave financial incentives to SNAP households to 
purchase fruits and vegetables had no effect on sweetened 
beverage consumption, even though these households did eat more 
fruits and vegetables. The Summer EBT for Children Program 
found that a WIC-based model which provided restrictions was 
more effective than a SNAP-based model, which did not allow 
restrictions. And another study not conducted through the USDA 
found that restrictions plus incentives was most effective in 
reducing sweetened beverage intake.
    As part of a broader approach toward evidence-based policy 
making, a demonstration project is needed. I believe that with 
cooperation from the USDA and funding from Congress, a 
demonstration project is feasible. A random assignment 
experiment similar to the Healthy Incentives Pilot could be 
conducted. With the technology that exists today, this would 
not be overly burdensome on retailers. In fact, when we 
developed the proposal in New York City, we spoke to retailers 
and they told us that it would not be that difficult to 
implement such a restriction, since they program their EBT 
systems anyway.
    In conclusion, with a new Congress and Administration, I am 
hopeful that a demonstration project in a few states will be 
allowed in order to test whether a restriction could be 
effective. At a time when leaders of both parties are promoting 
evidence-based policy making, testing such an idea and 
rigorously evaluating the results should receive broad support.
    Thank you, and I can respond to any questions that you may 
have.
    [The prepared statement of Dr. Rachidi follows:]

  Prepared Statement of Angela K. Rachidi, Ph.D., Research Fellow in 
    Poverty Studies, American Enterprise Institute, Washington, D.C.
The Supplemental Nutrition Assistance Program (SNAP): Time to Test a 
        Sweetened Beverage Restriction
    Chairman Conaway, Ranking Member Peterson, and other Members of the 
Committee, thank you for the opportunity to testify this morning on 
restrictions on purchases in the Supplemental Nutrition Assistance 
Program or SNAP.
    My name is Angela Rachidi, and I am a Research Fellow in Poverty 
Studies at the American Enterprise Institute (AEI). Prior to joining 
AEI, I spent almost a decade at the New York City Human Resources 
Administration (HRA) as the Deputy Commissioner for Policy and 
Evaluation. HRA is New York City's main social service agency and 
administers SNAP. During my time at HRA, the city provided SNAP 
benefits to almost two million New Yorkers each month.
    In my role, I studied all aspects of the program. Most relevant for 
today is my experience--under the direction of then-Mayor Michael 
Bloomberg, Commissioners for Health Thomas Friedan and Thomas Farley, 
and HRA Commissioner Robert Doar--drafting a proposal for a 
demonstration project in New York City to restrict the use of SNAP 
benefits to purchase sweetened beverages. We proposed a restriction as 
a way to support the overarching goal of the program, which is to 
improve nutrition. Regrettably, it was denied by the U.S. Department of 
Agriculture (USDA) in 2011.
    In the years since I left HRA, the public health problems caused by 
sweetened beverages have not solved themselves. I am here today to urge 
the Committee to support demonstration projects that test whether a 
sweetened beverage restriction in SNAP can improve the health and well-
being of SNAP recipients.
    I will make four main points to support this recommendation:

  1.  Obesity and related health problems remain one of the most 
            challenging public health issues of our time, affecting 
            millions of poor and non-poor Americans, with sweetened 
            beverages identified as one the main contributors.

  2.  The integrity of SNAP as a publicly-funded program rests on how 
            well its implementation matches the stated goals of the 
            program. Congress has stated that the purpose of SNAP is to 
            support nutrition among low-income households, which is 
            directly contradicted by allowing sweetened beverages to be 
            purchased.

  3.  This public health problem is complex and requires a 
            comprehensive approach that includes multiple strategies, 
            including changes to SNAP.

  4.  A demonstration project to test a sweetened beverage restriction 
            in SNAP is consistent with bipartisan efforts to support 
            evidence-based policymaking. Through rigorous evaluation, a 
            demonstration project could assess whether government 
            efforts can achieve potential gains, such as better health, 
            without adversely affecting other measures of well-being.

    Before I get to these main points, I want to state clearly that 
SNAP is one of the more effective Federal safety net programs in the 
U.S. A large body of research shows that it reduces poverty, improves 
food security among low-income households, and has positive effects on 
infant health and long-term benefits for children who receive it.\1\ In 
the average month in 2016, 44.2 million Americans received SNAP for a 
total cost of $70.9 billion.\2\ Among American households, 12.7 percent 
were food-insecure in 2015 and 5.0 percent had very low food 
insecurity; percentages which likely would be much higher without 
SNAP.\3\ In 2015, SNAP lifted almost 4.6 million people out of poverty, 
according to the Supplemental Poverty Measure.\4\
---------------------------------------------------------------------------
    \1\ See Judith Bartfield, et al., eds, SNAP Matters: How Food 
Stamps Affect Health and Well-Being (Stanford, CA: Stanford University 
Press, 2015); Douglas Almond, Hilary W. Hoynes, and Diane Whitmore 
Schanzenbach, ``Inside the War on Poverty: The Impact of Food Stamps on 
Birth Outcomes,'' Review of Economics and Statistics 93, no. 2 (May 
2011): 387-403; and Hilary Hoynes, Diane Whitmore Schanzenbach, and 
Douglas Almond, ``Long-Run Impacts of Childhood Access to the Safety 
Net,'' American Economic Review 106, no. 4 (April 2016): 903-34.
    \2\ U.S. Department of Agriculture, Food and Nutrition Service 
``Supplemental Nutrition Assistance Program Participation and Costs,'' 
February 3, 2017, https://www.fns.usda.gov/sites/default/files/pd/
SNAPsummary.pdf.
    \3\ Alisha Coleman-Jensen, et al., ``Household Food Security in the 
United States in 2015,'' U.S. Department of Agriculture, Economic 
Research Services, September 2016, https://www.ers.usda.gov/webdocs/
publications/err215/err-215.pdf?v=42636.
    \4\ Trudi Renwick and Liana Fox, ``The Supplemental Poverty 
Measure: 2015,'' U.S. Census Bureau, September 2016, http://
www.census.gov/content/dam/Census/library/publications/2016/demo/p60-
258.pdf.
---------------------------------------------------------------------------
    Beyond these national statistics, I saw first-hand the positive 
impacts that SNAP had on individuals and families in New York City. It 
serves a wide variety of households, including the elderly, the 
disabled, and working families. However, as with any government 
program, it can always be improved. And as a nutrition assistance 
program, SNAP could do more to support healthy eating among recipient 
households, especially children.
Obesity, Health Problems, and the Connection to Sweetened Beverages
    The National Institutes of Health has termed obesity ``a 
devastating public-health crisis for the United States,'' \5\ and for 
good reason. Among all Americans, 37.9 percent of adults (age 20 or 
older) were obese in 2013-2014 and over 70 percent were overweight or 
obese.\6\ Among children, 20.6 percent of 12-19 year olds and 17.4 
percent of 6-11 year olds were obese in those same years.\7\ According 
to the Centers for Disease Control and Prevention (CDC), people who are 
obese are a greater risk for a variety of health issues, including type 
2 diabetes, heart disease, stroke, some cancers, low quality of life, 
and certain mental illnesses.\8\
---------------------------------------------------------------------------
    \5\ National Institutes of Health, ``About We Can! Background,'' 
February 13, 2013, https://www.nhlbi.nih.gov/health/educational/wecan/
about-wecan/background.htm.
    \6\ Centers for Disease Control and Prevention, National Center for 
Health Statistics, ``Obesity and Overweight,'' June 13, 2016, https://
www.cdc.gov/nchs/fastats/obesity-overweight.htm.
    \7\ Ibid.
    \8\ Centers for Disease Control and Prevention, ``The Health 
Effects of Overweight and Obesity,'' June 5, 2015, https://www.cdc.gov/
healthyweight/effects/.
---------------------------------------------------------------------------
    Excessive sugar consumption is considered one of the primary causes 
of obesity, with sugar-sweetened beverages specifically linked to 
excessive weight gain and obesity, and the related health problems that 
result.\9\ Because of these known associations and because sweetened 
beverages have no nutritional value, the White House Task Force on 
Childhood Obesity issued a report in 2010 that included recommendations 
calling for the nation's food assistance programs to be part of the 
solution by encouraging access to nutritious foods and offering 
incentives and eliminating disincentives to healthy eating habits.\10\ 
In addition, according to the 2015-2020 Dietary Guidelines for 
Americans:
---------------------------------------------------------------------------
    \9\ Brian K. Kit, et al., ``Trends in Sugar-Sweetened Beverage 
Consumption Among Youth and Adults in the United States: 1999-2010,'' 
American Journal of Clinical Nutrition 98, no. 1 (May 2013): 180-88.
    \10\ White House Task Force on Childhood Obesity, ``Solving the 
Problem of Childhood Obesity Within a Generation,'' May 2010, https://
letsmove.obamawhitehouse.archives.gov/sites/letsmove.gov/files/
TaskForce_on_Childhood_Obesity_May2010_FullReport.pdf.

          The two main sources of added sugars in U.S. diets are sugar-
        sweetened beverages and snacks and sweets. Many foods high in 
        calories from added sugars provide few or no essential 
        nutrients or dietary fiber and, therefore, may contribute to 
        excess calorie intake without contributing to diet quality; 
        intake of these foods should be limited to help achieve healthy 
        eating patterns within calorie limits. There is room for 
        Americans to include limited amounts of added sugars in their 
        eating patterns, including to improve the palatability of some 
        nutrient-dense foods, such as fruits and vegetables that are 
        naturally tart (e.g., cranberries and rhubarb). Healthy eating 
        patterns can accommodate other nutrient-dense foods with small 
        amounts of added sugars, such as whole-grain breakfast cereals 
        or fat-free yogurt, as long as calories from added sugars do 
        not exceed ten percent per day, total carbohydrate intake 
        remains within the AMDR [Acceptable Macronutrient Distribution 
        Range], and total calorie intake remains within limits.\11\
---------------------------------------------------------------------------
    \11\ U.S. Department of Agriculture, Dietary Guidelines for 
Americans 2015-2010, December 2015, 31, https://health.gov/
dietaryguidelines/2015/resources/2015-2020_Dietary_
Guidelines.pdf.

    The USDA's Dietary Guidelines go on to note that the ``the major 
source of added sugars in typical U.S. diets is beverages, which 
include soft drinks, fruit drinks, sweetened coffee and tea, energy 
drinks, alcoholic beverages, and flavored waters.'' \12\ In fact, 
almost \1/2\ of added sugars consumed by the U.S. population come from 
sweetened beverages.\13\
---------------------------------------------------------------------------
    \12\ Ibid.
    \13\ Ibid.
---------------------------------------------------------------------------
    This is why it is so alarming that such a notable percentage of 
food/beverage purchases in American households are for sweetened 
beverages, according to a recent USDA study.\14\ Among SNAP households, 
9.25 percent of food purchases were for sweetened beverages and 7.10 
percent of non-SNAP households were for the same. SNAP households spent 
more on sweetened beverages than fruits and milk combined. According to 
the National Health and Nutrition Examination Survey (NHANES), low-
income children are more likely to consume sweetened beverages and 
intake more calories from sweetened beverages than higher-income 
children.\15\ Children participating in SNAP in particular were more 
likely than nonparticipants to consume sweetened beverages,\16\ and 63 
percent of adults receiving SNAP consumed a sweetened beverage on the 
day of the NHANES.\17\ Also according to the NHANES, more than \1/2\ of 
adult SNAP recipients drank regular soda and 24 percent drank another 
sweetened beverage on the day of the survey.\18\ Sweetened beverage 
consumption is high among all American households, with low-income 
households and SNAP recipients no exception.
---------------------------------------------------------------------------
    \14\ U.S. Department of Agriculture, Food and Nutrition Service, 
``Foods Typically Purchased by Supplemental Nutrition Assistance 
Program (SNAP) Households,'' November 2016, https://www.fns.usda.gov/
sites/default/files/ops/SNAPFoodsTypicallyPurchased.pdf.
    \15\ Euna Han and Lisa M. Powell, ``Consumption Patterns of Sugar-
Sweetened Beverages in the United States,'' Journal of the Academy of 
Nutrition and Dietetics 113, no. 1 (January 2013): 43-53.
    \16\ Cindy Leung, et al., ``Associations of Food Stamp 
Participation with Diet Quality and Obesity in Children,'' Pediatrics 
131, no. 3 (March 2013): 463-72.
    \17\ Sara N. Bleich, Seanna Vine, and Julia A. Wolfson, ``American 
Adults Eligible for SNAP Consume More Sugary Beverages Than Ineligible 
Adults,'' Preventative Medicine 57, no. 6 (December 2013), https://
www.ncbi.nlm.nih.gov/pmc/articles/PMC3842507/.
    \18\ U.S. Department of Agriculture, Food and Nutrition Service, 
``Diet Quality Among SNAP Recipients by SNAP Participation Status: Data 
from the National Health and Nutrition Examination Survey, 2007-2010,'' 
May 2015, https://www.fns.usda.gov/sites/default/files/ops/NHANES-
SNAP07-10.pdf.
---------------------------------------------------------------------------
Program Integrity
    High sweetened beverage consumption is not unique to SNAP 
households. But supporting such purchases, especially at levels 
suggested in the data, directly contradicts the stated goals of the 
program. The Food Stamp Act of 1977, which outlines the purpose of the 
program, states that the goal is ``to provide for improved levels of 
nutrition among low-income households through a cooperative Federal-
state program of food assistance.'' \19\
---------------------------------------------------------------------------
    \19\ Food Stamp Program Act of 1977, https://www.fns.usda.gov/
sites/default/files/PL_106-580.pdf.
---------------------------------------------------------------------------
    Public health experts have clearly determined that sweetened 
beverages have no nutritional value and are a major contributor to 
obesity and related health problems. Few can argue the reverse. Yet, 
almost ten percent of food and beverage spending among SNAP households 
is on these products.
    To be fair, it is unclear whether SNAP households would make these 
purchases with their own money if they were restricted from SNAP or 
even in the absence of SNAP. However, for a program with a stated goal 
of improving nutrition, accepting such a large percentage of spending 
on beverages with no nutritional value seems counterintuitive and 
likely undermines public support for the program.
    Beyond these concerns, allowing the purchase of sweetened beverages 
directly competes with the USDA's nutrition education programming at 
the Federal and state level. Approximately $350 million is spent per 
year on SNAP Nutrition Education activities, with more spent by the 
states.\20\ The Farm Bill of 2008 authorized an additional $20 million 
to test demonstration projects designed to increase healthy eating. 
Federal dollars dedicated to improving nutrition are in direct 
competition with benefit dollars being spent to purchase sweetened 
beverages.
---------------------------------------------------------------------------
    \20\ U.S. Department of Agriculture, Economic Research Service, 
``Nutrition Education,'' October 12, 2016, https://www.ers.usda.gov/
topics/food-nutrition-assistance/supplemental-nutrition-assistance-
program-snap/nutrition-education/.
---------------------------------------------------------------------------
    Separately from SNAP, not confronting the problems created by 
obesity has substantial impacts on Federal medical expenditures. 
Medical costs associated with obesity (which largely fall on Medicare 
and Medicaid) are estimated to be at least $147 billion per year.\21\ 
Not only is SNAP contributing to sweetened beverage consumption, but it 
may be adding to other Federal expenditures related to medical costs 
associated with obesity.
---------------------------------------------------------------------------
    \21\ See Eric A. Finkelstein, et al., ``Annual Medical Spending 
Attributable to Obesity: Payer and Service-Specific Estimates,'' Health 
Affairs 28, no. 5 (2009): w822-31, http://content.healthaffairs.org/
content/28/5/w822.full.pdf.
---------------------------------------------------------------------------
Problem Is Complex and Requires a Comprehensive Approach
    As I already mentioned, the public health challenges posed by 
sweetened beverages are not unique to low-income households. But 
restrictions could be part of a broader approach to address the 
problem. Already, the USDA pilot tested a Healthy Incentive program, 
which gave financial incentives to SNAP households to purchase fruits 
and vegetables. The results of the evaluation found that the financial 
incentives increased consumption of certain fruits and vegetables by a 
small, but statistically significant amount.\22\ It also found that 
retailers had little trouble implementing the pilot. But the incentives 
had no effect on added sugars, which included no change to sweetened 
beverage consumption.
---------------------------------------------------------------------------
    \22\ See U.S. Department of Agriculture, Food and Nutrition 
Service, Healthy Incentives Pilot Final Evaluation Report, September 
2014, https://www.fns.usda.gov/snap/healthy-incentives-pilot-final-
evaluation-report.
---------------------------------------------------------------------------
    In another study, researchers randomly assigned low-income 
households not receiving SNAP into four different groups to test 
incentives, restrictions, and both. They found that the incentive plus 
restriction group (the restriction was on sweetened beverages and other 
sweets) had positive effects on fruit consumption and reduced sweetened 
beverage and other sweets intake.\23\ The incentive-alone and 
restriction-alone group showed no difference compared with the control 
group. Although this was not conducted with SNAP households (given that 
the USDA has not allowed testing restrictions), it suggests that 
restrictions could be used to reduce sweetened beverage consumption.
---------------------------------------------------------------------------
    \23\ Lisa Harnack, et al., ``Effects of Subsidies and Prohibitions 
on Nutrition in a Food Benefit Program: A Randomized Clinical Trial,'' 
JAMA Internal Medicine 176, no. 11 (November 2016): 1610-19.
---------------------------------------------------------------------------
    Similarly, although not the main purpose, a study of the Summer 
Electronic Benefit Transfer for Children Program published in 2016 
found that only a Women, Infant, and Children (WIC)-based model, which 
restricted what could be purchased with benefits, including sweetened 
beverages, led to a reduction in sweetened beverage consumption among 
families who participated.\24\ The SNAP-based model, which had no 
restrictions, did not reduce sweetened beverage consumption.
---------------------------------------------------------------------------
    \24\ U.S. Department of Agriculture, Food and Nutrition Service, 
``Summer Electronic Benefit Transfer for Children (SEBTC) 
Demonstration: Summary Report,'' May 2016, https://www.fns.usda.gov/
sites/default/files/ops/sebtcfinalreport.pdf.
---------------------------------------------------------------------------
    Another recent study surveyed SNAP and non-SNAP participants on 
their perceptions of the program and areas for improvement around 
nutrition. Just over \1/2\ of SNAP participants supported removing 
sweetened beverages from products allowed under SNAP, and almost 80 
percent of non-SNAP participants supported the same.\25\ In 2011, we 
surveyed New York City SNAP participants on their consumption patterns 
and attitudes around restrictions. We found that almost 70 percent of 
surveyed SNAP participants supported restricting sweetened beverages 
from SNAP (49 percent) or didn't care one way or the other (16 
percent).
---------------------------------------------------------------------------
    \25\ Cindy W. Leung, et al., ``Improving the Nutritional Impact of 
SNAP: Perspectives from the Participants,'' American Journal of 
Preventive Medicine 52, no. 2 (February 2017): 252.
---------------------------------------------------------------------------
    This research suggests that a restriction may be beneficial, but 
likely as part of other efforts to achieve the same. It also suggests 
that combining a restriction with incentives, broader nutrition 
education programs, and public messaging may reduce sweetened beverage 
consumption among those exposed.
SNAP Demonstration Project to Test Restrictions
    For these reasons, and as part of a broader approach toward 
evidence-based policymaking, a demonstration project to test a 
sweetened beverage restriction in SNAP is needed. It could involve a 
few states or localities to assess whether the potential gains, such as 
better health, can be achieved without adverse effects on other 
measures of well-being. In a bipartisan effort in 2010, under the 
direction of Governor David Patterson and Mayor Michael Bloomberg, and 
in partnership with the New York City Department of Health, we 
submitted a proposal to the USDA to administer a demonstration project 
in New York City that would restrict sweetened beverages from SNAP.
    Our main objective was to test whether a restriction would lead to 
changes in consumption of sweetened beverages and other food groups 
among SNAP recipients, as well as whether a restriction could be 
implemented. We designed a rigorous evaluation to compare like counties 
within New York City (one would experience the restriction while the 
other would not), as well as to assess whether retailers could 
appropriately implement the restriction and whether participants could 
follow the changes. We proposed using survey data and retailer data to 
assess changes in consumption patterns over time, as well as 
qualitative work to assess the retailer and participant experience. 
Regrettably, our proposal, which was to be funded completely by the 
city and the state, was denied by the USDA in 2011.
    Since our proposal in 2010, we now know more about the Healthy 
Incentive[s] Pilot and the Summer EBT pilot. Both studies suggest that 
more can be done to improve nutrition and reduce sweetened beverage 
consumption among SNAP households. The logical next step is to conduct 
a study of SNAP restrictions. Given what was learned from those 
studies, a demonstration project is not only possible, but has been 
made more feasible. With cooperation from the USDA and funding from 
Congress, a demonstration project involving a few states could greatly 
expand our knowledge of what works in combating sweetened beverage 
consumption and the obesity crisis.
    To give you a sense of how this might work, the Healthy 
Incentive[s] Pilot operated in 2010-2012 reprogrammed EBT data systems 
at the retailer source to identify and calculate incentives as part of 
the program. A similar approach could be taken, but with restrictions. 
Participants assigned to the restriction group would receive special 
EBT cards and retailer EBT systems would be programmed to not allow 
sweetened beverage purchases among those SNAP households. With the 
technology systems in place today, implementing this type of 
demonstration project would not be overly burdensome on retailers. In 
fact, as part of the Healthy Incentive[s] Pilot, few retailers 
identified problems, and few said the pilot affected store operations. 
This type of design is not only possible, but it would provide a strong 
treatment and control study that would tell us whether any changes in 
sweetened beverage consumption were due the restrictions or not.
    When we developed the New York City proposal, retailers were 
consulted about the ease or difficulty of implementing such a 
restriction. Retailers with EBT systems indicated that it could be done 
fairly easily since restrictions are already in place for other 
purchases, such as alcohol or nonfood items. One concern was retailers 
who do not use EBT systems, instead using manual systems. But these 
retailers make up a small share of overall SNAP sales and, as part of a 
demonstration project, could be counseled to ensure that they 
understand who is restricted from purchasing sweetened beverages and 
who is not. As part of the data collection effort, the evaluators would 
know whether households assigned to the restriction group were allowed 
to purchase sweetened beverages or not.
    With a new Congress and Administration, I am hopeful that a 
demonstration project in a few states be allowed in order to test 
whether a restriction could be effective. Given the problems of obesity 
and the toll it takes on our poor communities, this is an issue that 
receives bipartisan support. For example, the bipartisan National 
Commission on Hunger recommended in its 2015 report that Congress pass 
legislation to restrict sweetened beverages from SNAP. As a first step, 
Congress could authorize funding for demonstration projects.
Conclusion
    Some may ask why restrict sweetened beverages and no other foods 
with added sugar. Even though precedent exists in other government 
programs to determine what is nutritious and what is not, there are two 
reasons for starting with sweetened beverages. First, the research is 
clear that sweetened beverages are a much larger contributor to added 
sugars in the diets of Americans today (almost 50 percent of added 
sugars comes from these products) than other products. Second, the 
amount of spending on sweetened beverages far surpasses what is spent 
on other candies and sweets. And added sugars are often combined with 
other nutritious foods, such as whole grain cereals, yogurts, or nuts. 
The case against sweetened beverages in a nutrition assistance program 
seems clear.
    Some also argue that restrictions would be overly burdensome on 
retailers. While I respect the views of industry professionals, 
retailers already place restrictions on what can be purchased with SNAP 
benefits through their EBT systems, and the definition of sweetened 
beverage could be defined in a way that is very straightforward.
    In terms of how a restriction might affect low-income households, I 
am sympathetic to not wanting the government to stigmatize or unfairly 
targeted poor households. But SNAP is a government-funded program with 
a clearly stated goal: to improve the nutrition of low-income 
households. Not only is allowing sweetened beverages inconsistent with 
that goal, it actually may work against it by contributing to poor 
health. I also question how detrimental a restriction could be, given 
that certain restrictions already apply, other food assistance programs 
implement restrictions, and the majority of SNAP households either 
support the restriction or do not care when asked on surveys. It is 
also possible that SNAP benefits are fungible, and many SNAP households 
use their own money for food purchases, suggesting that a restriction 
may not have much effect on consumption. However, it is unclear how 
SNAP households would respond to a restriction until it is tested and 
rigorously evaluated.
    In conclusion, a restriction on sweetened beverages should be 
tested as part of a demonstration project for the purpose of improving 
public health. At a time when leaders of both parties are promoting 
evidence-based policymaking, testing such an idea and rigorously 
evaluating the results should receive broad support. I urge Congress to 
support pilot projects and urge the USDA to approve any requests from 
states.
    Thank you, and I can respond to any questions that you may have.

    The Chairman. Thank you, Dr. Rachidi.
    Dr. Schanzenbach?

        STATEMENT OF DIANE WHITMORE SCHANZENBACH, Ph.D.,
  DIRECTOR AND SENIOR FELLOW, ECONOMIC STUDIES, THE HAMILTON 
                PROJECT, BROOKINGS INSTITUTION;
   PROFESSOR OF SOCIAL POLICY AND OF ECONOMICS, NORTHWESTERN 
                  UNIVERSITY, WASHINGTON, D.C.

    Dr. Schanzenbach. Thank you. Chairman Conaway, Ranking 
Member Peterson, and Members of the Committee, thanks for the 
opportunity to appear before you today. My name is Diane 
Schanzenbach. I am the Director of The Hamilton Project, which 
is an economic policy initiative at Brookings Institution. I am 
also a Professor of Social Policy of Economics at Northwestern 
University in Illinois.
    SNAP is a highly efficient and effective program. It lifted 
nearly five million children out of poverty in 2014. SNAP is 
targeted efficiently to families who need benefits the most. It 
reduces the likelihood that families have trouble affording 
food, and serves as an automatic fiscal stabilizer in times of 
economic downturn. It also has extremely low rates of both 
error and fraud.
    A key reason for SNAP's success is that it relies on the 
private-sector to provide efficient access to food from grocery 
stores and other retail outlets. The reliance on the program on 
the free market system has been a feature of SNAP since the 
beginning. With a few restrictions, recipients have been able 
to optimize which items to purchase, and from which retail 
stores, subject to prevailing prices, and also to their own 
taste preferences and nutritional needs.
    SNAP also has long-term benefits to children. My own recent 
research study, which is the only long-term causal study on 
SNAP access, found that those who had access to SNAP benefits 
during childhood were more likely to graduate from high school, 
they grew up to be healthier, and for women in particular, they 
grew up to be more economically self sufficient as adults, all 
due to childhood access to SNAP benefits, because this is an 
investment in children.
    There has been much media discussion of the November 2016 
USDA report on the typical food purchase patterns by SNAP 
participants and non-participants. The top line finding of that 
report is that SNAP and non-SNAP families have extremely 
similar spending patterns. The study did not address the more 
fundamental question, namely, how does SNAP change the types of 
groceries that participants buy? By increasing a family's 
resources available to purchase groceries, SNAP is expected to 
increase not only the quantity, but also the quality of foods 
purchased. SNAP families are able to buy more nutritious foods 
that they otherwise could not afford.
    Additional restrictions on SNAP purchases will undermine 
the effectiveness and the efficiency of the program. In 
particular, SNAP restrictions will be difficult to structure 
and practice. In the case of a proposed ban on the purchase of 
soft drinks or sweetened beverages, it will be unlikely to 
change consumption patterns.
    So recall that SNAP benefits are modest. They are 
approximately $4.50 per person per day, and as a result, almost 
everyone who participates in the program has to supplement 
their SNAP purchases with groceries purchased out of their own 
cash income. So what will happen if a soft drink purchase is 
banned using SNAP benefits? Well, we would expect there to be 
no consumption change. A family could continue to purchase the 
same basket of goods. They will just have to make certain at 
the checkout line to pay for the soft drinks out of their cash 
instead of their SNAP benefits. In other words, a ban will 
likely increase the administrative cost of the program, both to 
the USDA and to retailers, and increase the stigma faced by 
recipients when they use SNAP, but not have the benefit of 
actually inducing any behavioral changes. It will be all costs 
and no benefits.
    I think there are better policy options that are more 
likely to improve the diets of SNAP recipients. Market-based 
policies that reduce the relative price of healthy foods can 
increase that consumption. For example, as you know, the 
Healthy Incentives Pilot in Massachusetts increased consumption 
of targeted healthy foods by 25 percent. Exploring ways to 
replicate or scale this type of program nationally would 
provide an effective and a market-based path forward toward 
achieving the goal of increasing healthy food consumption of 
SNAP recipients.
    Strengthening SNAP is a smart public investment that will 
improve both public health and economic growth, but banning 
certain foods will raise the administrative burdens and costs 
of the program, making it less efficient, but is unlikely to 
change consumption.
    By contrast, policy changes that strengthen the purchasing 
power of SNAP benefits and allow markets to function without 
undue interference are more likely to improve dietary choices 
of recipients and reduce food insecurity.
    Thank you, and I am looking forward to questions.
    [The prepared statement of Dr. Schanzenbach follows:]

Prepared Statement of Diane Whitmore Schanzenbach, Ph.D., Director and 
    Senior Fellow, Economic Studies, The Hamilton Project, Brookings
Institution; Professor of Social Policy and of Economics, Northwestern 
                      University, Washington, D.C.
    Chairman Conaway, Ranking Member Peterson, and Members of the 
Committee:
    Thank you for the opportunity to appear before you today at this 
hearing on the Pros and Cons of Restricting Purchases in the 
Supplemental Nutrition Assistance Program (SNAP).
    My name is Diane Schanzenbach, I am Director of the Hamilton 
Project, an economic policy initiative at the Brookings Institution, 
where I am also a Senior Fellow in Economic Studies.
    I am also a Professor of Social Policy and Economics at 
Northwestern University. For the past 2 decades, I have conducted and 
published numerous peer-reviewed research studies and book chapters on 
the U.S. safety net, including SNAP and the Food Stamp Program. I also 
study childhood obesity, food consumption, and food insecurity. I 
recently served as a member of the Institute of Medicine's Committee on 
Examination of the Adequacy of Food Resources and SNAP Allotments.
    My testimony today draws primarily from research that I have 
conducted or reviewed that considers the role of SNAP and other 
influences on food consumption and food insecurity.
    SNAP is a highly efficient and effective program. It lifted nearly 
five million people out of poverty in 2014 (the most recent data 
available).\1\ SNAP is targeted efficiently to families who need 
benefits the most, reduces the likelihood that families have trouble 
affording food, and serves as an automatic fiscal stabilizer in times 
of economic downturns.2-3 It has extremely low rates of both 
error and fraud.4-5 SNAP also has long-term benefits to 
children. My own recent research study found that those who had access 
to SNAP benefits during childhood were more likely to graduate from 
high school, grew up to be healthier, and women in particular were more 
likely to become economically self-sufficient due to childhood access 
to SNAP benefits, as shown in Figure 1.
---------------------------------------------------------------------------
    \1\  Sherman, Arloc. 2015, September 16. ``Safety Net Programs Lift 
Millions From Poverty, New Census Data Show.'' Center on Budget and 
Policy Priorities, Washington, D.C. Available at: http://www.cbpp.org/
blog/safety-net-programs-lift-millions-from-poverty-new-census-data-
show.
    \2\ Institute for Research on Poverty. 2015, November. ``SNAP, Food 
Security, and Health.'' Policy Brief No. 8, Institute for Research on 
Poverty, University of Wisconsin-Madison, Madison, WI. Available at: 
http://www.irp.wisc.edu/publications/policybriefs/pdfs/PB8-SNAPFoodSecu
rityHealth.pdf.
    \3\ Schanzenbach, Diane Whitmore, Lauren Bauer, and Greg Nantz. 
2016, April 21. ``Twelve Facts about Food Insecurity and SNAP.'' 
Economic Facts, The Hamilton Project, Washington, D.C. Available at: 
http://www.hamiltonproject.org/papers/twelve_facts_about_food_
insecurity_and_snap.
    \4\ Rosenbaum, Dottie. 2014, July 2. ``SNAP Error Rates at All-Time 
Lows.'' Report, Center on Budget and Policy Priorities, Washington, 
D.C. http://www.cbpp.org/research/snap-error-rates-at-all-time-lows.
    \5\ U.S. Department of Agriculture (USDA). 2013, August 15. ``USDA 
Releases New Report on Trafficking and Announces Additional Measures to 
Improve Integrity in the Supplemental Nutrition Assistance Program.'' 
Food and Nutrition Service, U.S. Department of Agriculture, Washington, 
D.C. Available at: https://www.fns.usda.gov/pressrelease/2013/fns-
001213.
---------------------------------------------------------------------------
Figure 1. Impact of Access to Food Stamps During Early Life on Adult 
        Health and Economic Outcomes
          Access to food stamps in early life improves health outcomes 
        in men and women and economic self-sufficiency in women in 
        later life.

[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]


        
          Sources: Hoyes, Schanzenbach, and Almond 2016.
          Note: Hollowed bars are not statistically significant.

    Generally, economists advise policymakers not to interfere in the 
private market unless there is a compelling reason to do so--such as a 
market failure or another inefficiency that would be improved through 
government intervention. In the case of SNAP, the fundamental problem 
the program is meant to address is not a market failure, but is instead 
a lack of resources available to purchase food. Government assistance 
is needed because some families, generally temporarily, do not have 
adequate resources to purchase enough food to sustain an active, 
healthy lifestyle. When they receive SNAP, participating families have 
more resources they can use to purchase groceries. Once the fundamental 
problem of resource adequacy is addressed, recipients can interact with 
the private market to obtain the food they need.
    A key reason for SNAP's success is that it relies on the private-
sector to provide efficient access to food, through grocery stores and 
other retail outlets. The reliance of the program on the free market 
system has been a feature of SNAP since the beginning. With few 
restrictions, recipients have been able to optimize which items to 
purchase and from what retail stores, subject to prevailing prices and 
their own tastes, preferences, and nutritional needs.
    In my opinion, additional restrictions on SNAP purchases will 
undermine the effectiveness and the efficiency of the program. In 
particular, based on my research on SNAP and food consumption I believe 
that SNAP restrictions: will be difficult to structure in practice, 
will be inefficiently targeted, and in many cases--such as a proposed 
ban of the purchase of soft drinks or sweetened beverages--will be 
unlikely to change consumption patterns. There are better policy 
options for promoting healthy eating patterns, both for SNAP recipients 
and for all Americans.
SNAP Restrictions will be Difficult to Structure in Practice
    There are a few broad types of restrictions that have gained policy 
traction. One set involves narrowly targeting the commodities that can 
be purchased with SNAP, another involves restricting the purchase of 
unhealthy foods broadly, or sodas or sugar sweetened beverages in 
particular, and another proposes banning purchases of certain luxury 
foods. Each of these will be difficult to implement in practice because 
of the complexities involved in determining which items would fall 
under the ban. In addition, the restrictions would increase the 
administrative burden on private businesses, and particularly on small 
establishments.
    The complexities arise in part because of the sheer number of 
products that would need to be classified. Consumers have vast 
differences in their tastes and preferences, and the market responds by 
providing variety. There are more than 650,000 food and beverage 
products on the market today, and 20,000 more are introduced 
annually.\6\ The complexity is multiplied because there is no clear 
standard for defining foods as ``healthy'' or ``unhealthy,'' or as 
luxury goods. Creating such standards would be difficult at best, and 
would entail substantial administrative costs to categorize and track 
the nutritional profile of each good to produce a SNAP-eligible foods 
list. The list would have to be maintained continuously and 
communicated to retailers and consumers in real time. My prediction is 
that the additional bureaucracy needed to support such an undertaking 
is not likely to save taxpayer money.
---------------------------------------------------------------------------
    \6\  USDA. 2016, October 12. ``New Products.'' Economic Research 
Service, U.S. Department of Agriculture, Washington, D.C. Available at: 
https://www.ers.usda.gov/topics/food-markets-prices/processing-
marketing/new-products/.
---------------------------------------------------------------------------
    Furthermore, items should not be classified in a manner that 
suggests a particular food is always ``good'' or ``bad.'' The Academy 
of Nutrition and Dietetics, the largest organization of food and 
nutrition professionals, has adopted a position statement that the 
``total diet'' or overall pattern of food eaten should be the most 
important focus of healthy eating.\7\ All foods can fit into a healthy 
diet if consumed in moderation and with appropriate portion size, and 
as a result no particular food should be always banned.
---------------------------------------------------------------------------
    \7\ Freeland-Graves, Jeanne H., and Susan Nitzke. 2013. ``Position 
of the Academy of Nutrition and Dietetics: Total Diet Approach to 
Healthy Eating.'' Journal of the Academy of Nutrition and Dietetics 113 
(2): 307-17. Available at: http://www.andjrnl.org/article/S2212-
2672(12)01993-4/abstract.
---------------------------------------------------------------------------
SNAP Improves Diets
    By focusing on the descriptive question of what SNAP participants 
buy, the USDA study did not address the more fundamental question--
namely how does SNAP change the types of groceries that participants 
buy? Economists have strong predictions about the impact of SNAP: by 
increasing a family's resources available to purchase groceries, SNAP 
is expected to increase both the quantity and the quality of foods 
purchased, and it has. When SNAP increases low-income families' grocery 
purchasing power, they are able to buy more nutritious foods they 
otherwise could not afford. While this is a surprisingly hard question 
to study empirically, a recent study found that a $30 increase in 
monthly SNAP benefits would increase participants' consumption of 
nutritious foods such as vegetables and healthy proteins, while 
reducing food insecurity and consumption of fast food, as shown in 
Figure 2 below.\8\
---------------------------------------------------------------------------
    \8\ Anderson, Patricia M., and Kristin F. Butcher. 2016, June 14. 
``The Relationships Among SNAP Benefits, Grocery Spending, Diet 
Quality, and the Adequacy of Low-Income Families' Resources.'' Report, 
Policy Futures, Center on Budget and Policy Priorities, Washington, 
D.C. Available at: http://www.cbpp.org/research/food-assistance/the-
relationships-among-snap-benefits-grocery-spending-diet-quality-and-
the.
---------------------------------------------------------------------------
Figure 2. Estimated Impact of a $30 Increase in Monthly Per Capita SNAP 
        Benefits
        
        
        
        [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
        
          Source: Anderson and Butcher 2016.
          Note: Percentages for the dark green bars represent change in 
        consumption. Food insecurity is defined as having difficulty at 
        some time during the year providing enough food for all 
        household members due to lack of resources. The hollowed bars 
        are not statistically significant.

    Similar impacts were found in a randomized controlled trial of a 
Summer EBT program that gave families $60 per month in benefits per 
eligible child during the summer months, to offset the loss of school 
meals. The study found that children assigned to receive additional 
benefits improved their diets, consuming more fruits, vegetables, whole 
grains, and dairy products, and fewer sugar-sweetened beverages.\9\
---------------------------------------------------------------------------
    \9\ Briefel, Ronette, Ann Collins and Anne Wolf. 2013, November 8. 
``Impact of the Summer Electronic Benefits Transfer for Children 
(SEBTC) Demonstration on Children's Nutritional Status.'' Panel Paper, 
Mathematica Policy Research and Abt Associates, Washington, D.C. 
Available at: https://appam.confex.com/appam/2013/webprogram/
Paper7254.html.
---------------------------------------------------------------------------
SNAP and Non-SNAP Households Have Similar Consumption
    There has been much media discussion of the November 2016 USDA 
report on typical food purchase patterns by SNAP participants and non-
participants.\10\ The top-line finding of that report is that SNAP and 
non-SNAP households have extremely similar food spending patterns. Out 
of every dollar spent by SNAP families:
---------------------------------------------------------------------------
    \10\ USDA. 2016, November 18. ``Foods Typically Purchased by 
Supplemental Nutrition Assistance Program (SNAP) Households.'' 
Nutrition Assistance Program Report, Office of Policy Support, Food and 
Nutrition Service, U.S. Department of Agriculture, Washington, D.C. 
Available at: https://www.fns.usda.gov/snap/foods-typically-purchased-
supplemental-nutrition-assistance-program-snap-households.

   Around 40 went to what the study classifies as ``basic 
---------------------------------------------------------------------------
        items'' such as meat, fruits, vegetables, eggs, bread and milk.

   Around 20 went to salty snacks, sugar, candy and sweetened 
        beverages, with 5 going to soft drinks.

   The remaining 40 spent on other goods, including prepared 
        foods, cereal, rice, beans, and dairy products.

    The USDA findings are consistent with my own published research 
using the Consumer Expenditure Survey that also found similar spending 
patterns across food categories for SNAP and non-SNAP households.\11\
---------------------------------------------------------------------------
    \11\ Hoynes, Hilary W., Leslie McGranahan, and Diane W. 
Schanzenbach. 2014. ``SNAP and Food Consumption.'' Discussion Paper 
2014-03, Center for Poverty Research, University of Kentucky, 
Lexington, KY. Available at: http://uknowledge.uky.edu/cgi/
viewcontent.cgi?article=
1008&context=ukcpr_papers.
---------------------------------------------------------------------------
    Public-health advocates rightly point out that sugar-sweetened 
beverages are the largest source of excess calories in the average 
American diet, and they provide no nutritional benefit.12-13 
The obesity epidemic has hit Americans across all income levels, and 
public-health advocates are right to call attention to our excessive 
consumption of sugar-sweetened beverages as one probable cause.\14\ The 
USDA study indicates that this is an issue across the income 
distribution, and there is no need to single out SNAP recipients for 
their consumption of soft drinks. Among the spending observed in the 
USDA study, about 5 of each dollar went to the purchase of soft 
drinks. This rate is similar to non-SNAP households, which spend an 
average of four percent of their grocery dollars on soft drinks.
---------------------------------------------------------------------------
    \12\  Welsh, J.A., A.J. Sharma, L. Grellinger, and M.B. Vos. 2011. 
``Consumption of Added Sugars is Decreasing in the United States.'' 
American Journal of Clinical Nutrition 94 (3): 726-34. Available at: 
https://www.ncbi.nlm.nih.gov/pubmed/21753067.
    \13\ The Nutrition Source. ``Public Health Concerns: Sugary 
Drinks.'' School of Public Health, Harvard University, Cambridge, MA. 
Available at: https://www.hsph.harvard.edu/nutritionsource/healthy-
drinks/beverages-public-health-concerns/.
    \14\ Center for Disease Control and Prevention. 2016, September 1. 
``Adult Obesity Facts.'' Center for Disease Control and Prevention, 
U.S. Department of Health & Human Services, Atlanta, GA. Available at: 
https://www.cdc.gov/obesity/data/adult.html.
---------------------------------------------------------------------------
A Soda Ban Will Not Reduce Soda Consumption
    Another option that has been proposed is to disallow only the 
purchase of soft drinks or sweetened beverages with SNAP benefits. 
These proposals exaggerate the potential impacts on consumption such 
bans would have, because the rationale for the bans is based on a false 
understanding of how SNAP benefits work. SNAP benefits are modest--
approximately $4.50 per person per day--and as a result nearly all 
families supplement their SNAP purchases with groceries purchased from 
their cash income. This occurs by design, and is why the program is 
called the Supplemental Nutrition Assistance Program; it is intended in 
most cases to extend a family's food purchasing power, not to cover 100 
percent of food purchases. Estimates suggest that 70 to 80 percent of 
participants, perhaps even higher, supplement their SNAP spending with 
cash.
    What will happen if soft drink purchases are banned using SNAP 
benefits? Take a typical family that spends the average amount--$12 per 
month--on soft drinks, and supplements their SNAP spending with 
spending out of cash resources. Our best prediction is that there will 
be no consumption change as a result of the SNAP restriction; such a 
family can continue to purchase the same basket of goods, but they 
would have to make certain to pay for the soft drinks out of their own 
cash instead of their SNAP benefits. In other words, a ban will likely 
increase the administrative costs of the program to both the USDA and 
retailers, and increase the stigma faced by recipients when they use 
the benefits, but not have the benefit of inducing any behavioral 
changes.
Recommendations
    There are better policy options that are more likely to improve the 
diets of SNAP recipients, particularly when you consider that, over the 
past decade, fresh fruits and vegetables have become relatively more 
expensive compared to foods that are considered less healthy, as shown 
in Figure 3 below. In response, market-based policies can increase the 
affordability of healthy foods and provide incentives for low-income 
families to purchase them.
    One approach that merits further consideration is the USDA's 
randomized controlled trial of the Healthy Incentives Pilot in 
Massachusetts. This pilot program gave SNAP recipients an immediate 30 
rebate for every dollar they spent on a narrowly defined group of 
fruits and vegetables.\15\ In response to this price rebate, 
consumption of the targeted healthy foods increased by 25 percent.\16\ 
In recent years, many local areas and even a few states have taken a 
similar approach by awarding bonus dollars for benefits used at 
farmers' markets, allowing recipients to stretch their food budget 
farther when they buy fresh produce. To date, these programs have been 
successful. Exploring ways to replicate or scale these types of 
programs nationally would provide a more constructive and effective 
path forward toward achieving the goal of increasing healthy food 
consumption by SNAP recipients.
---------------------------------------------------------------------------
    \15\ USDA. 2015, September 2. ``Healthy Incentives Pilot.'' Report, 
Food and Nutrition Service, U.S. Department of Agriculture, Washington, 
D.C. Available at: https://www.fns.usda.gov/hip/healthy-incentives-
pilot.
    \16\ Bartlett, Susan, Jacob Klerman, Parke Wilde, Lauren Olsho, 
Michelle Blocklin, Christopher Logan, and Ayesha Enver. 2013. ``Healthy 
Incentives Pilot (HIP) Program.'' Food and Nutrition Services, Office 
of Policy Support, U.S. Department of Agriculture, Washington, D.C. 
Available at: https://www.fns.usda.gov/sites/default/files/
HIP_Interim.pdf.
---------------------------------------------------------------------------
Figure 3. Price Levels by Food Category, 1980-2016



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Source: Bureau of Labor Statistics 2016.
          Note: Base year of the index (100) is the average for 1982-
        84.

    Strengthening SNAP and reducing food insecurity in the more than 22 
million U.S. households that receive nutritional assistance on a 
monthly basis is a smart public investment that will improve both 
public health and economic growth. Banning certain foods will raise the 
administrative burdens and cost of the program, but is unlikely to 
change consumption. By contrast, policy changes that strengthen the 
purchasing power of SNAP benefits and allow markets to function without 
undue interference are more likely to improve dietary choices of 
recipients and reduce food insecurity.
    Thank you, and I look forward to answering any questions you might 
have.

    The Chairman. Thank you.
    Ms. Sarasin, 5 minutes.

 STATEMENT OF LESLIE G. SARASIN, PRESIDENT AND CHIEF EXECUTIVE 
               OFFICER, FOOD MARKETING INSTITUTE,
                         ARLINGTON, VA

    Ms. Sarasin. Good morning. Thank you very much. I am Leslie 
Sarasin. I serve as President and CEO of FMI. Our members' 
grocery stores are located in every Congressional district in 
the country.
    Grocers play an important role in the efficient delivery of 
safe, affordable food for both the SNAP and the WIC Programs. 
We appreciate this Committee's work to better understand SNAP 
this morning.
    Becoming an authorized SNAP retailer is a complicated 
process. Retailers must submit specified paperwork and 
credentials, and adhere strictly to the SNAP operating rules 
and ongoing training for their associates. Violation of SNAP 
operating rules results in revocation of both the SNAP and the 
WIC licenses.
    SNAP authorized stores code all products within the 
electronic checkout system as either SNAP eligible or 
ineligible. When an eligible item is scanned, the system 
deducts the product's price from the customer's SNAP EBT card. 
When an ineligible item is scanned, the cashier is prompted to 
ask the customer for another form of payment. Approximately 50 
percent of SNAP transactions are multi-tendered, such that 
another form of payment is also used to pay for non-food items, 
ineligible items, or eligible food items that exceed the 
balance available on the SNAP EBT card. If a customer tries to 
purchase a tobacco or alcohol product with their SNAP EBT 
benefits, the electronic system will freeze until the product 
is actually removed. Within the electronic systems, WIC 
eligible items are charged against that benefit first, followed 
by those eligible for SNAP, and finally, the cashier must 
collect another form of payment: cash, check, debit, or credit 
for all remaining items.
    Grocery transactions for SNAP customers vary significantly 
throughout the month. Data indicate the first transaction of 
the month is usually the largest and may contain larger 
quantities of protein and perishables. By the last week of the 
month, customers typically purchase maximum calories at minimum 
cost.
    We appreciate the Committee's recognition of the role 
grocers play in the SNAP program. FMI has announced a new 
industry SNAP task force to identify areas where the program 
works well, and also to consider those that may require 
improvement. Some suggest that limiting what customers can buy 
with SNAP, making it more like WIC, may help achieve these 
goals. Doing so would place a tremendous burden, both on USDA 
and on food retailers, and likely would not achieve policy 
goals. Please consider two recent examples from the WIC 
Program.
    When USDA began the Fresh Fruits and Vegetables Cash Value 
Voucher Program, it subjectively decided all fresh fruits and 
vegetables were eligible, except white potatoes. As many of you 
will recall, this ban on white potatoes unleashed a great 
debate throughout Congress and the industry. In the end, after 
more than a year of debate and consideration of actual science, 
USDA reversed the ban to allow white potatoes to be purchased 
through WIC. This was one item out of the tens of thousands 
found in each of our members' stores that would have to be 
studied and debated before USDA can make a determination as to 
whether a product is in or out.
    Second, if our goal with SNAP is to provide short-term 
lifelines to needy Americans so they can get and keep a job to 
earn enough to support their families without government 
benefits, such limitations seem unlikely to help accomplish 
that goal at a reasonable cost. Doing so will require 
additional USDA staff to make these decisions for all products 
currently in market, as well as the estimated 20,000 new 
products introduced every year. USDA would also need to 
maintain a real time list downloadable to every electronic 
payment system in the country.
    I should note that in 2004, Congress directed USDA to 
create an electronically downloadable real time UPC database 
for all WIC eligible foods. Today, retailers are still waiting 
for this list. The fact that nearly 13 years later we are still 
waiting for the list shows the complexity of creating and 
keeping one updated in real time, even for a list of products 
as small as WIC's. A similar SNAP database would include more 
than 100 times the number of products, along with more than the 
20,000 that are introduced every year. Could it be done? 
Probably so, but we expect it would be both challenging and 
expensive.
    Finally, FMI members are incredible contributors to their 
communities. They are the largest contributors to our nation's 
food banks, create good paying jobs, and help build our future 
workforce. We look forward to working with the Committee on 
SNAP and other related issues, and I am also happy to answer 
any questions you may have.
    [The prepared statement of Ms. Sarasin follows:]

Prepared Statement of Leslie G. Sarasin, President and Chief Executive 
            Officer, Food Marketing Institute, Arlington, VA
    Chairman Conaway, Ranking Member Peterson, and Members of the 
Committee,

    My name is Leslie Sarasin, and I serve as President and Chief 
Executive Officer of Food Marketing Institute,\1\ a trade association 
that represents food retailers and wholesalers, as well as their 
suppliers of products and services. FMI members are located in every 
Congressional district across the country. FMI's maxim when referring 
to its member companies is ``Feeding Families and Enriching Lives,'' a 
responsibility we take very seriously.
---------------------------------------------------------------------------
    \1\ Food Marketing Institute proudly advocates on behalf of the 
food retail industry. FMI's U.S. members operate nearly 40,000 retail 
food stores and 25,000 pharmacies, representing a combined annual sales 
volume of almost $770 billion. Through programs in public affairs, food 
safety, research, education and industry relations, FMI offers 
resources and provides valuable benefits to more than 1,225 food retail 
and wholesale member companies in the United States and around the 
world. FMI membership covers the spectrum of diverse venues where food 
is sold, including single owner grocery stores, large multi-store 
supermarket chains and mixed retail stores. For more information, visit 
www.fmi.org and for information regarding the FMI foundation, visit 
www.fmifoundation.org.
---------------------------------------------------------------------------
Food Retail Role
    In the context of ``feeding families,'' our industry is pleased to 
maintain an important role in facilitating the efficient delivery in 
our stores of safe, affordable food products for both the Supplemental 
Nutrition Assistance Program (SNAP) and the Special Supplemental 
Nutrition Program (WIC). I appreciate the work this Committee is 
undertaking to better understand the operations of SNAP and the 
differences between a short-term hunger program as contemplated in SNAP 
and a longer-term nutrition program as contemplated in WIC.
    As you know, the WIC program serves mothers and their children up 
to age 5. FMI members redeem very specific food prescriptions designed 
to ensure moms and their babies have access to the early nutrition they 
need for optimum physical and mental development. This important 
nutrition program is overseen by the House Education and the Workforce 
Committee and is currently up for reauthorization.
    SNAP, the program under the full purview of this Committee, is one 
in which FMI members serve as the delivery mechanism for benefits. 
SNAP, a program created to address hunger among Americans, is designed 
to supplement the food budgets for seniors and/or families experiencing 
financial difficulty, or on a longer-term basis, individuals who are 
disabled.
    As designed, SNAP allows customers to purchase approved food 
products from a SNAP-authorized retailer. Becoming an authorized SNAP/
WIC retailer is not a simple process, and that process requires 
completion of specified paperwork and the providing of many 
credentials, including a business license, a photo ID for each owner of 
the business and proof of a social security number. This information 
may be requested at reauthorization or at any time throughout the 
process. Once approved, retaining SNAP/WIC authorization is not a 
foregone conclusion. The food retailer must agree to adhere strictly to 
the SNAP operating rules, violation of which results in having both the 
SNAP and WIC licenses revoked. Additionally, authorized retailers must 
agree to ongoing training programs for their associates to ensure they 
understand and adhere to all SNAP rules and regulations, as delineated 
in USDA's 25 page training guide.
    SNAP has been enhanced in recent years by moving from a paper-based 
program that issued ``food stamps'' to an electronic benefits transfer 
program known as ``EBT,'' through which benefits are downloaded 
electronically to a government-issued debit card which then may be 
utilized at store level by SNAP benefit recipients. This movement to 
EBT has increased the efficiency of the program and enhanced its 
accountability by reducing the opportunity for fraud and human error. 
The program also benefitted from the work of this Committee and then 
Nutrition Subcommittee Chairman Bob Goodlatte, whose efforts focused on 
ensuring interoperability and consistency of the program across state 
lines. The EBT Interoperability and Portability Act (P.L. 106-171), 
signed into law in 2000, ensures that EBT transactions operate 
consistently from state to state. This law has significantly reduced 
the incidence of error and has allowed shoppers living in border state 
areas to seek the best prices through which to stretch their SNAP 
benefits. It also has enabled those who must cross state lines for 
emergency reasons, such as to care for a sick relative or to escape the 
disastrous results of a natural event like Hurricane Sandy, to continue 
receiving benefits in a seamless manner.
    As the front line purveyors of SNAP, authorized retailers maintain 
a unique and special vantage point from which to see SNAP transactions. 
At the time of food purchase, SNAP recipients input their unique, 
secret PIN after swiping their card. As is the case with commercial 
debit cards, the PIN is an important added authentication to prevent a 
stolen card from being used by an unauthorized person.
    All products in SNAP-authorized stores are coded within the 
electronic checkout system as being either eligible or ineligible for 
purchase with SNAP benefits. This designation often can be seen on a 
paper receipt with the initials ``FS.'' When a SNAP customer places 
products on the checkout conveyor belt, the checkout system scans each 
item as either eligible or ineligible for SNAP. If an item is eligible, 
the system deducts the product's price from the customer's SNAP EBT 
card. If ineligible, it prompts the cashier to ask the customer for 
another form of payment. Examples of ineligible items include laundry 
detergent and diapers, since they are not food items, and a hot 
rotisserie chicken, since hot, ready-to-eat food items are not eligible 
for purchase with SNAP benefits.
    Data indicate that approximately 50% of supermarket customers using 
SNAP benefits when purchasing groceries also use other forms of 
payment, either to pay for non-food items, ineligible products or for 
eligible food items that exceed the remaining balance on the SNAP EBT 
card. It also is my understanding that if a customer attempts to 
purchase a tobacco product or alcoholic beverage, the electronic system 
will freeze and will not allow the transaction to continue until the 
tobacco or alcohol product is removed.
    Those not fully involved in the SNAP transactional process can find 
it baffling and can often be confused about products that are eligible 
and those that are ineligible and therefore paid for through other 
means, and even in some cases by products that are eligible but not 
paid for with SNAP benefits in a particular transaction. Under the 
electronic systems in place today, the items eligible for WIC are 
charged against that benefit first, followed by those eligible for SNAP 
benefits, and finally, the cashier must collect another form of 
payment--cash, check, debit or credit--for all remaining items not 
eligible under either of the programs and/or for items that exceed the 
dollar or prescription value of the benefits. As a result, while the 
items the electronic system charges to the SNAP benefit are eligible to 
be purchased with SNAP, they may not necessarily be designated by the 
customer to be the specific items purchased with SNAP benefits. This 
occurs, for example, when a SNAP customer places $100 worth of eligible 
items, such as bananas, eggs and bread, and has only $80 in benefits on 
the EBT card; the electronic system deducts $80 from the grand total of 
SNAP-eligible items, but does not necessarily attribute the $80 to a 
specific array of products on the checkout conveyor belt.
    It is worth noting that grocery transactions for SNAP customers 
vary significantly throughout the month. Data indicate the first 
transaction of the month is likely the largest and may contain larger 
quantities of protein, perishables, or even a splurge item. The 
purchases of second and third weeks of the month are often more 
balanced, and the purchases made in the last week of the month 
typically find customers purchasing maximum calories at minimum cost.
    This variation among purchases is particularly noteworthy in the 
seven states that continue to issue benefits to all recipients on only 
1 day of the month, rather than spreading issuance dates throughout the 
month. There are four states that distribute benefits on only 2 or 3 
days each month. Expanding the dates for issuing SNAP benefits allows 
supermarkets to better address supply chain issues on fresh and 
perishable items and allows labor needs to be spread throughout the 
month into full-time positions rather than having them concentrated in 
a segment of the month with multiple part-time positions to accommodate 
the volume of SNAP shoppers trying to redeem benefits on one day. A 
chart of state issuance time frames is attached to this testimony.
Need for Sound Public Policy
    FMI member companies appreciate the Committee's recognition that 
food retailers are engaged and informed partners in the SNAP and WIC 
programs, as evidenced by the invitation for this testimony. As your 
partners in this endeavor, we hope you will consider several issues of 
concern to food retailers.
    Against the backdrop of food retailers' commitment to enrich the 
lives of individuals in the communities they serve, we suggest that as 
the Committee examines SNAP, it keep in mind the larger goals and 
purpose of this hunger program. A strategic policy-oriented discussion 
could help make an already good program even better. If, however, the 
consideration becomes bogged down in energy zapping tactical questions 
of specific product(s) to be considered for elimination from SNAP, this 
program enhancement will be made much more difficult, if not 
impossible. FMI respectfully submits that changes to the program should 
be part of a broad policy discussion with clearly articulated desired 
results and delineation of the most effective and efficient means to 
achieve those results.
    We at FMI would be pleased to participate in that ``results'' 
discussion. To assist in that process, we have announced the 
development of an industry SNAP Task Force to identify areas of the 
program we find to be exceptional, to make sure those are not 
eliminated, and to consider those we believe may require improvement in 
order to achieve your policy goals.
    As I understand them, among the Committee goals are the following:

   To ensure no unfair penalty on individuals who find 
        themselves on the edge of the benefits cliff and who are trying 
        to move to a higher paying job;

   To ensure SNAP is the most efficient program possible, 
        eliminating fraud and opportunities for fraud on both the 
        delivery and recipient side;

   To make SNAP the least burdensome possible for individuals 
        whose participation in the program may actually reduce 
        government health care, social services, and education costs, 
        such as seniors with a fixed income, disabled individuals and 
        families supporting children under the age of 18; and

   To identify and prepare individuals who receive SNAP 
        benefits for enhanced employment opportunities.

    It has been suggested that achievement of these goals might be 
facilitated by development of a prescription of limitations for SNAP 
purchases, perhaps similar to those that exist in the WIC program. 
While this may seem an attractive option, I respectfully suggest that 
prior to doing so we first identify the result being sought in 
undertaking such a change in the program.
    To demonstrate how a tactical reaction may actually prove to be 
inconsistent with a policy goal, it is worthwhile to consider an 
anecdote from the most recent reauthorization of the WIC nutrition 
program. At that time, similar debates occurred regarding products that 
should or should not be authorized under the WIC program. There were a 
number of factions, including farmers touting the unique benefits of 
the crops they were growing. Ultimately, WIC was updated to allow for 
the first time a fresh fruits and vegetables benefit and all fruits and 
vegetables were allowed under this program, with one exception. The 
exception made was for white potatoes, deemed at the time not to be 
nutritionally significant. Yet, just 1 year later, the Institute of 
Medicine issued a report indicating that Americans suffer from 
relatively high incidences of a deficiency in potassium, for which 
white potatoes serve as a good source under definitions established by 
the Food and Drug Administration. Moreover, we are now in the process 
in this country of redesigning the Nutrition Facts Panel that appears 
on food products to add potassium as a required element so that 
consumers can begin to address this deficiency. In the last Congress, 
in 2015 a change was made to allow white potatoes as a vegetable in the 
WIC program.
    From experience previously in my career while serving as the 
President and Chief Executive Officer of the American Frozen Food 
Institute, I can relay anecdotes regarding the treatment of frozen 
foods, specifically frozen fruits and vegetables, that are 
nutritionally equivalent and in some cases nutritionally superior, to 
their unfrozen counterparts in not being declared WIC eligible by some 
states to the utter detriment of both the programs and the frozen fruit 
and vegetable industries.
    Of course, the discussions today will hardly illuminate specific 
issues such as these, but it is critical as we consider changes to 
Federal hunger programs such as SNAP that we identify the policy goals 
to be achieved, rather than just focus on a potentially desirable sound 
bite. I would respectfully suggest that if our goal with SNAP is to 
provide needy Americans a short-term lifeline to allow them to get and 
keep a job so they earn enough to support their families without 
government benefits, the unilateral limitation of any specific product 
is unlikely to help accomplish that goal. It is worth noting that doing 
so will also increase the need for additional USDA staff to make and 
encode these determinations for an estimated 20,000 new products 
introduced into the marketplace annually and then download these 
electronically on a real-time basis to every electronic payments system 
in the country.
    SNAP was designed and currently serves as a hunger program. It is a 
supplementary program for the customers whose circumstances require 
them to rely upon it for a season of their life, and for these 
individuals it is a life-saver. Eighty-two percent of all SNAP benefits 
in FY 2015 went to households that included a child, an elderly person 
or a person with disabilities.
    There have been a number of limitations suggested for this program 
whether it be no meats, no desserts, no snacks, no soft drinks and even 
no white bread. Not only do such limitations appear incongruous to the 
policy positioning of a program designed to provide temporary 
assistance addressing hunger considerations, but they also would prove 
an administrative nightmare, increasing the cost of acceptance and 
slowing down checkout lines in an industry that historically has 
experienced only just more than a 1% profit margin and in which every 
second of delay affects profitability and ultimately the number of 
associates that can be hired and the prices in a store.
    Language was included in the WIC reauthorization legislation in 
2004 directing the Secretary to develop an electronically downloadable 
list of WIC-eligible products on a state by state basis. This has still 
not been completed because of its complexity. A similar type of 
electronic list for SNAP would easily involve 100 times more products 
making it a 100 times more complex. Could it be done? Probably so. But 
if it hasn't been done in the WIC program in spite of a 15 year old 
Congressional directive, it likely would not be easy or inexpensive. 
And at the end of the day, we must ask ourselves what the policy goal 
is that this level of expenditure of time and money would achieve.
    We are truly blessed in this country with the safest, most abundant 
and most affordable food supply in the world. We believe that with that 
blessing comes the responsibility to lift up those individuals in our 
communities who may need an extra hand, with the goal that they might 
provide an extra hand for someone else at another time in the future.
    FMI member companies are the largest contributors to our nation's 
food banks. In 2016, food retailers donated more than 1.3 billion of 
the four billion meals Feeding America provided to families in need.\2\ 
We are also constantly developing new ways to enhance this donation 
level by decreasing food waste. In fact, we have spent much of the past 
year working with our supplier partners at the Grocery Manufacturers 
Association (GMA) on efforts to reduce customer confusion regarding 
product date labels, frequently misunderstood to be expiration dates. 
FMI and GMA have just announced an industry-driven voluntary program to 
reduce dozens of terms currently in use on date labels and move (to the 
extent possible) to two primary labels: ``BEST if used by'' to indicate 
quality and ``USE by'' for perishable products that may have potential 
degradation implications.
---------------------------------------------------------------------------
    \2\ Source: Feeding America, 2016 Annual Report, Available at 
http://www.feedingamerica.org/about-us/about-feeding-america/annual-
report/2016-feeding-america-annual-report.pdf, pp.13.
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    I am pleased to answer any questions you may have and to serve as a 
resource to this Committee as you work to make SNAP even more 
efficient. I also have to call out the exceptional FNS retailer 
management division at USDA headed by Andrea Gold. Through hurricanes, 
tornados and floods as well as new store openings or changes in 
ownership, we could not have had a better resource than Andrea and her 
team to help our members through their challenges.

          State-by-State Monthly SNAP Benefit Issuance Schedule
  (Current as of February 13, 2017; Food Marketing Institute Research)
------------------------------------------------------------------------
             State                 Day(s) of SNAP Benefit Distribution
------------------------------------------------------------------------
Alabama                         In August 2013, the state expanded their
                                 distribution dates, moving from the 4th
                                 to the 18th of the month to the 4th
                                 through the 23rd of the month. To
                                 assist in the transition, recipients
                                 received \1/2\ of their benefit on
                                 their original date and \1/2\ on their
                                 new date in the month.
Alaska **                       The main SNAP issuance is all on the
                                 first day of the month. Smaller
                                 supplemental issuances for new
                                 applicants and late recertifications
                                 occur daily throughout the month.
Arizona                         SNAP benefits are distributed over the
                                 first 13 days of the month by the first
                                 letter of the recipients' last name.
                                 For example: last names that begin with
                                 A or B are distributed on the first day
                                 of the month; 2nd day of the month: C
                                 and D; etc.
Arkansas                        Arkansans receive their benefits on
                                 these 8 days: 4th, 5th, 8th, 9th, 10th,
                                 11th, 12th or 13th of each month, based
                                 on the last number of their [S]ocial
                                 [S]ecurity [N]umber.
California                      California is different in that each
                                 county distributes SNAP to those who
                                 qualify. The payments go out to all
                                 those who qualify between the 1-10 of
                                 the month. Others (i.e., new
                                 applicants) get paid throughout the
                                 month depending on when they were
                                 accepted.
Colorado                        Food Stamp benefits are distributed on
                                 the first 10 days of the month by the
                                 recipient's last digit of their
                                 [S]ocial [S]ecurity [N]umber.
Connecticut                     SNAP benefits and cash are distributed
                                 on the first 3 days of the month, by
                                 the first letter of the recipient's
                                 last name. (A-F are available on the
                                 first; G-N on the second and O-Z are
                                 distributed on the third day of the
                                 month.)
Delaware                        Benefits are made available over 23
                                 days, beginning with the 2nd day of
                                 every month, based on the first letter
                                 of the client's last name.
District of Columbia            Benefits are made available from the 1st
                                 to the 10th of every month, based on
                                 the first letter of the client's last
                                 name.
Florida                         All SNAP recipients moved from a 15 day
                                 distribution to a 28 day distribution
                                 in April 2016. In March 2016, to assist
                                 in the new transition, benefits were
                                 ``split.'' Recipients received the
                                 first half of their benefits on their
                                 ``old'' date and received the second
                                 half of their monthly benefits on what
                                 was their ``new'' date going forward.
                                 The ACCESS Florida system assigns
                                 benefit availability dates based on the
                                 case number recipients received when
                                 they became eligible for the SNAP
                                 program.
Georgia                         In September 2012, SNAP benefits in
                                 Georgia expanded from the 5th to the
                                 14th, and then finally to the current
                                 5th to 23rd of each month, distributed
                                 every other day.
Hawaii                          Benefits are made available on the 3rd
                                 and the 5th of every month, based on
                                 the first letter of the client's last
                                 name.
Idaho                           Benefits were previously made available
                                 on the first day of every month. (Prior
                                 to August 2009, benefits were
                                 distributed on 5 consecutive days at
                                 the beginning of each month, but this
                                 was later moved to 1 day.) In 2014,
                                 H.B. 565 was enacted. The bill requires
                                 the state Department of Health and
                                 Welfare to issue SNAP benefits over the
                                 course of 10 consecutive days within a
                                 month. Bonus money received from USDA
                                 paid for the cost of the change.
                                Currently, and since July 1, 2016,
                                 benefits are distributed over the first
                                 10 days of each month based on the last
                                 number of the birth year of the
                                 recipient; for example, a birthday of 8/
                                 25/64 would receive benefits on the 4th
                                 day of each month.
Illinois                        SNAP benefits are made available on
                                 these 12 days of the month: 1st, 3rd,
                                 4th, 7th, 8th, 10th, 11th, 14th, 17th,
                                 19th, 21st, and 23rd of every month,
                                 based on a combination of the type of
                                 case and the case name.
Indiana                         On January 1, 2014, the state
                                 implemented an expanded schedule for
                                 the distribution of benefits during the
                                 fifth through the twenty-third day of
                                 each month, to be issued every-other-
                                 day, based on the first letter of the
                                 recipient's last name. For example: A
                                 or B = benefits available on the 5th;
                                 first Letter of the Last Name is: C or
                                 D = benefits available on the 7th.
                                 Previously, benefits were made
                                 available on the first 10 calendar days
                                 each month. (TANF is issued on the
                                 first of the month.)
Iowa                            Benefits are made available over the
                                 first 10 calendar days of every month,
                                 based on the first letter of the
                                 client's last name.
Kansas                          Benefits are made available over the
                                 first 10 calendar days of every month,
                                 based on the first letter of the
                                 client's last name.
Kentucky                        Benefits are made available over the
                                 first 19 calendar days of every month,
                                 based on the last digit of the client's
                                 case number. This was recently expanded
                                 from the previous 10 day distribution.
Louisiana                       Benefits are made available between the
                                 1st and the 14th of every month, based
                                 on the last digit of the client's SSN.
                                 (Elderly and disabled benefits are made
                                 available between the 1st and the 4th
                                 of every month.)
Maine                           Benefits are available the 10th to the
                                 14th of every month based on the last
                                 digit of the recipient's birthday.
Maryland                        In January 2016, the distribution
                                 schedule was changed. Benefits are now
                                 distributed from the 4th to the 23rd of
                                 every month, based on the first three
                                 letters of the client's last name.
                                 Previously, benefits were distributed
                                 from the 6th through the 15th of the
                                 month. This was accomplished through a
                                 5 month phase-in.
Massachusetts                   Distribution is based on the last digit
                                 of each recipient's [S]ocial [S]ecurity
                                 [N]umber and distributed over the first
                                 14 days of the month.
Michigan                        In January 2011, SNAP moved from a 7 day
                                 distribution to the current
                                 distribution, which is from the 3rd to
                                 the 21st, distributed every-other-day,
                                 based on the last digit of the head of
                                 household's recipient identification
                                 number. For example, clients' numbers
                                 ending with 0 will receive food
                                 benefits on the 3rd of the month;
                                 numbers ending with 1, food benefits
                                 will be available on the 5th of the
                                 month.
Minnesota                       Benefits are staggered over 10 calendar
                                 days, beginning on the 4th through the
                                 13th of every month, without regard to
                                 weekends or holidays, based on the last
                                 digit of the client's case number.
Mississippi                     Effective February 2017, benefits are
                                 made available from the 4th to the 21st
                                 of every month, based on the last two
                                 digits of the client's case number.
                                 Benefits were previously distributed
                                 from the 5th to the 19th (15 days) of
                                 every month.
Missouri                        Benefits are made available over the
                                 first 22 days of every month, based on
                                 the client's birth month and last name.
Montana                         Benefits are distributed over 5 days by
                                 the last number of the recipient's case
                                 number, from the 2nd to the 6th of
                                 every month.
Nebraska                        Nebraska distributes benefits during the
                                 first 5 calendar days of the month. The
                                 day of distribution is based on the
                                 last digit of the [S]ocial [S]ecurity
                                 [N]umber.
Nevada **                       In Nevada, food stamp benefits are
                                 issued on the first day of each month.
New Hampshire **                New Hampshire benefits are available on
                                 the 5th of every month.
New Jersey                      The monthly SNAP allotment is available
                                 over the first 5 days of the month. The
                                 day is based on the number in the 7th
                                 position of their case number. Some of
                                 the cases still receive their benefits
                                 based on the assignment at the time the
                                 county was converted to EBT. In Warren
                                 County, all benefits are made available
                                 on the 1st of the month.
New Mexico                      Benefits are made available over 20 days
                                 every month, based on the last two
                                 digits of the SSN.
New York                        The process is twofold as follows: in
                                 New York City, recipients receive their
                                 SNAP benefits within the first 13
                                 business days of the month, according
                                 to the last digit of their case number,
                                 not including Sundays or holidays. The
                                 actual dates change from 1 month to the
                                 next, so NYC publishes a 6 month
                                 schedule showing the exact availability
                                 dates. For the remainder of New York
                                 State, recipients receive their
                                 benefits within the first 9 days of the
                                 month, also according to the last digit
                                 of their case number, including Sundays
                                 and holidays.
North Carolina                  Effective July 2011, the state expanded
                                 its 10 day distribution schedule.
                                 Benefits are now distributed from the
                                 3rd to the 21st of every month, based
                                 on the last digit of the primary
                                 cardholder's Social Security Number.
North Dakota **                 Benefits are made available on the first
                                 day of every month.
Ohio                            In April 2014, Ohio expanded its SNAP
                                 distribution from the first 10 days of
                                 the month to the first 20 days of the
                                 month, staggered every 2 days. This
                                 only affected SNAP recipients who moved
                                 from one county to another; recipients
                                 who experienced a 1 day or more break
                                 in eligibility; and, all new
                                 recipients. Recipients who were on SNAP
                                 before April 2014 did not see a change.
Oklahoma                        Benefits are made available from the 1st
                                 to the 10th of every month, based on
                                 the last digit of the client's SNAP
                                 case number.
Oregon                          SNAP is distributed on the first 9 days
                                 of the month as such: [S]ocial
                                 [S]ecurity [N]umbers ending with ``0''
                                 or ``1'' distribute on the 1st day of
                                 the month, numbers ending with a ``2''
                                 are distributed on the 2nd day of the
                                 month and so on.
Pennsylvania                    Benefits are made available over the
                                 first 10 business days of every month
                                 (excluding weekends and holidays) based
                                 on the last digit of the client's case
                                 number.
Rhode Island **                 Benefits are made available on the first
                                 day of every month.
South Carolina                  In 2012, South Carolina expanded from a
                                 9 day to a 19 day issuance. Current
                                 recipients stayed within the 9 day
                                 distribution, but all new recipients
                                 were given a date that expanded into
                                 the 19 days.
South Dakota **                 Benefits are made available on the 10th
                                 day of every month.
Tennessee                       In October 2012, Tennessee expanded
                                 distribution from 10 to 20 days.
Texas                           Benefits are made available over the
                                 first 15 days of the month, based on
                                 the last digit of the client's SNAP
                                 case number.
Utah                            Benefits are made available on the 5th,
                                 11th, or 15th of every month, based on
                                 the first letter of the client's last
                                 name: A-G available on the 5th; H-O
                                 available on the 11th; P-Z available on
                                 the 15th.
Vermont **                      Vermont benefits are available on the
                                 first of every month.
Virginia                        On September 1, 2012, benefit
                                 distribution was moved from 1 day a
                                 month to 5 days, and then eventually to
                                 the current 1st to the 9th day of every
                                 month, based on the last digits of the
                                 client's case number.
Washington                      Benefits are staggered over the first 10
                                 days of the month based on the last
                                 digit of the households' assistance
                                 unit number. Weekends and holidays do
                                 not affect the schedule. However,
                                 beginning February 1, 2017, an
                                 expansion of distribution was fully
                                 implemented. Going forward, it will be
                                 the first 20 days of the month.
West Virginia                   Benefits are made available over the
                                 first 9 days of every month, based on
                                 the first letter of the client's last
                                 name.
Wisconsin                       Benefits are made available over the
                                 first 15 days of every month, based on
                                 the eighth digit of the client's SSN.
Wyoming                         SNAP is distributed on the first 4 days
                                 of the month.
------------------------------------------------------------------------
Notes:
** States with asterisks are those that only distribute benefits on 1
  day a month. There are seven that still do so. Warren County, New
  Jersey distributes only 1 day a month, although the rest of the state
  distributes over 5 days. Also, there are four states that distribute
  SNAP just 2 or 3 days a month.
Additional Distribution Information:
There is no limit on the number of days for stagger. The only condition
  in regulation is that no single household's issuance should exceed 40
  days between issuances.
Currently, benefit recipients may only be issued their benefits one time
  a month, or within 40 days.


               Supplemental Nutrition Assistance Program: One-Month Change in Total Participation
                            (Prepared by the Food Research and Action Center (FRAC))
                                          (Data as of January 6, 2017)
----------------------------------------------------------------------------------------------------------------
                                                                                        Percent Change September
              State                     September 2016              October 2016          2016 vs. October 2016
----------------------------------------------------------------------------------------------------------------
                   Kentucky                     657,389                    671,628                        2.2
                   Arkansas                     399,538                    403,376                        1.0
             South Carolina                     746,646                    752,030                        0.7
                      Texas                   3,864,686                  3,891,234                        0.7
                    Wyoming                      33,806                     33,977                        0.5
                     Kansas                     246,179                    247,281                        0.4
                     Nevada                     441,986                    443,138                        0.3
                    Montana                     119,863                    120,065                        0.2
                    Vermont                      78,034                     78,092                        0.1
              Massachusetts                     771,436                    771,512                        0.0
                 Washington                     952,711                    951,845                       ^0.1
                   Colorado                     467,426                    466,789                       ^0.1
                      Idaho                     176,217                    175,976                       ^0.1
               Pennsylvania                   1,858,232                  1,855,129                       ^0.2
                    Arizona                     964,979                    963,303                       ^0.2
                Mississippi                     555,278                    554,225                       ^0.2
                     Hawaii                     173,669                    173,289                       ^0.2
                    Florida                   3,287,446                  3,279,009                       ^0.3
              West Virginia                     351,391                    350,474                       ^0.3
                    Georgia                   1,688,832                  1,683,945                       ^0.3
                    Indiana                     710,738                    708,476                       ^0.3
                     Oregon                     712,084                    709,684                       ^0.3
                       Iowa                     378,478                    377,126                       ^0.4
                  Minnesota                     465,211                    463,461                       ^0.4
                   New York                   2,950,208                  2,938,258                       ^0.4
                 New Jersey                     857,779                    854,146                       ^0.4
                   Missouri                     770,944                    767,403                       ^0.5
                    Alabama                     830,742                    826,790                       ^0.5
                  Wisconsin                     712,582                    709,134                       ^0.5
                   Oklahoma                     621,462                    618,434                       ^0.5
                 California                   4,252,654                  4,230,399                       ^0.5
               South Dakota                      95,655                     95,153                       ^0.5
                Connecticut                     424,431                    422,181                       ^0.5
                   Maryland                     720,566                    716,620                       ^0.5
                   Delaware                     149,158                    148,340                       ^0.5
              New Hampshire                      95,393                     94,823                       ^0.6
                      Maine                     183,299                    182,095                       ^0.7
                       Ohio                   1,564,498                  1,553,901                       ^0.7
                   Virginia                     811,949                    806,332                       ^0.7
                       Utah                     214,505                    212,903                       ^0.7
                   Michigan                   1,434,550                  1,423,008                       ^0.8
               North Dakota                      54,622                     54,124                       ^0.9
                  Tennessee                   1,083,880                  1,071,344                       ^1.2
                   Illinois                   1,931,575                  1,907,969                       ^1.2
             North Carolina                   1,470,079                  1,450,485                       ^1.3
                 New Mexico                     480,493                    473,398                       ^1.5
               Rhode Island                     168,973                    166,365                       ^1.5
       District of Columbia                     132,308                    126,322                       ^4.5
                           Louisiana          1,042,876                    943,685                       ^9.5
                   Nebraska                     177,912                    153,419                      ^13.8
                     Alaska                      84,825                     71,768                      ^15.4
                                 -------------------------------------------------------------------------------
  Total.........................             43,493,149                 43,215,557                       ^0.6
----------------------------------------------------------------------------------------------------------------
The following areas receive Nutrition Assistance Grants which provide benefits analogous to the Supplemental
  Nutrition Assistance Program: Puerto Rico, American Samoa, and the Northern Mariana[ Islands]. In addition,
  2015 and 2016 data are preliminary and are subject to significant revision.
* State where October 2016 SNAP data include disaster assistance (D-SNAP).


                Supplemental Nutrition Assistance Program: One-Year Change in Total Participation
                            (Prepared by the Food Research and Action Center (FRAC))
                                          (Data as of January 6, 2017)
----------------------------------------------------------------------------------------------------------------
                                                                                         Percent Change  October
              State                      October 2015               October 2016         2015 vs.  October 2016
----------------------------------------------------------------------------------------------------------------
                           Louisiana            879,541                    943,685                        7.3
                    Montana                     113,462                    120,065                        5.8
                    Wyoming                      32,729                     33,977                        3.8
                      Texas                   3,777,317                  3,891,234                        3.0
                 New Mexico                     460,048                    473,398                        2.9
                     Alaska                      69,996                     71,768                        2.5
               North Dakota                      53,271                     54,124                        1.6
                     Nevada                     439,498                    443,138                        0.8
                   Delaware                     147,127                    148,340                        0.8
                   Oklahoma                     613,397                    618,434                        0.8
               Pennsylvania                   1,873,447                  1,855,129                       ^1.0
               South Dakota                      96,692                     95,153                       ^1.6
              Massachusetts                     786,492                    771,512                       ^1.9
                   New York                   2,996,649                  2,938,258                       ^1.9
                       Iowa                     384,685                    377,126                       ^2.0
              West Virginia                     359,001                    350,474                       ^2.4
                    Arizona                     991,567                    963,303                       ^2.9
                   Colorado                     481,892                    466,789                       ^3.1
                Connecticut                     439,210                    422,181                       ^3.9
               Rhode Island                     173,148                    166,365                       ^3.9
                   Virginia                     844,204                    806,332                       ^4.5
                  Minnesota                     485,317                    463,461                       ^4.5
                       Utah                     222,981                    212,903                       ^4.5
                       Ohio                   1,629,349                  1,553,901                       ^4.6
                 California                   4,436,189                  4,230,399                       ^4.6
                     Hawaii                     182,226                    173,289                       ^4.9
                   Illinois                   2,007,492                  1,907,969                       ^5.0
                 New Jersey                     899,481                    854,146                       ^5.0
                    Georgia                   1,774,540                  1,683,945                       ^5.1
                    Vermont                      82,364                     78,092                       ^5.2
             South Carolina                     793,218                    752,030                       ^5.2
                      Maine                     192,404                    182,095                       ^5.4
                   Kentucky                     713,911                    671,628                       ^5.9
                   Michigan                   1,513,129                  1,423,008                       ^6.0
                    Alabama                     881,402                    826,790                       ^6.2
                  Wisconsin                     756,434                    709,134                       ^6.3
                     Oregon                     759,386                    709,684                       ^6.5
                     Kansas                     265,478                    247,281                       ^6.9
              New Hampshire                     101,894                     94,823                       ^6.9
                      Idaho                     189,385                    175,976                       ^7.1
                   Maryland                     779,303                    716,620                       ^8.0
                  Tennessee                   1,168,238                  1,071,344                       ^8.3
                 Washington                   1,043,008                    951,845                       ^8.7
                   Missouri                     843,876                    767,403                       ^9.1
       District of Columbia                     140,654                    126,322                      ^10.2
                    Indiana                     799,663                    708,476                      ^11.4
                    Florida                   3,708,499                  3,279,009                      ^11.6
                Mississippi                     628,354                    554,225                      ^11.8
                   Arkansas                     457,380                    403,376                      ^11.8
             North Carolina                   1,647,808                  1,450,485                      ^12.0
                   Nebraska                     176,363                    153,419                      ^13.0
                                 -------------------------------------------------------------------------------
  Total.........................             45,368,265                 43,215,557                       ^4.7
----------------------------------------------------------------------------------------------------------------
The following areas receive Nutrition Assistance Grants which provide benefits analogous to the Supplemental
  Nutrition Assistance Program: Puerto Rico, American Samoa, and the Northern Mariana[ Islands]. In addition,
  2015 and 2016 data are preliminary and are subject to significant revision.
* State where October 2016 SNAP data include disaster assistance (D-SNAP).


                  Supplemental Nutrition Assistance Program: Five-Year Change in Participation
                            (Prepared by the Food Research and Action Center (FRAC))
                                          (Data as of January 6, 2017)
----------------------------------------------------------------------------------------------------------------
                                                                                         Percent Change  October
              State                      October 2011               October 2016         2011 vs.  October 2016
----------------------------------------------------------------------------------------------------------------
                     Nevada                     351,686                    443,138                       26.0
                 New Mexico                     432,289                    473,398                        9.5
                 California                   3,867,094                  4,230,399                        9.4
                Connecticut                     396,517                    422,181                        6.5
                   Illinois                   1,831,037                  1,907,969                        4.2
               Pennsylvania                   1,785,240                  1,855,129                        3.9
                           Louisiana            916,060                    943,685                        3.0
                   Delaware                     144,612                    148,340                        2.6
                     Hawaii                     169,405                    173,289                        2.3
                    Wyoming                      33,252                     33,977                        2.2
                    Florida                   3,225,957                  3,279,009                        1.6
              West Virginia                     347,064                    350,474                        1.0
                   Maryland                     709,681                    716,620                        1.0
                   Oklahoma                     624,112                    618,434                       ^0.9
               Rhode Island                     168,694                    166,365                       ^1.4
                    Montana                     121,992                    120,065                       ^1.6
                   Colorado                     480,566                    466,789                       ^2.9
                   New York                   3,060,107                  2,938,258                       ^4.0
                     Alaska                      74,792                     71,768                       ^4.0
                 New Jersey                     890,859                    854,146                       ^4.1
                       Iowa                     398,574                    377,126                       ^5.4
                      Texas                   4,174,348                  3,891,234                       ^6.8
               South Dakota                     103,282                     95,153                       ^7.9
              Massachusetts                     838,603                    771,512                       ^8.0
               North Dakota                      59,383                     54,124                       ^8.9
                    Alabama                     910,034                    826,790                       ^9.1
       District of Columbia                     140,003                    126,322                       ^9.8
                    Georgia                   1,870,781                  1,683,945                      ^10.0
                   Virginia                     896,420                    806,332                      ^10.0
                     Oregon                     798,772                    709,684                      ^11.2
                       Ohio                   1,766,584                  1,553,901                      ^12.0
                   Nebraska                     174,941                    153,419                      ^12.3
             North Carolina                   1,655,694                  1,450,485                      ^12.4
                  Minnesota                     531,728                    463,461                      ^12.8
                 Washington                   1,095,139                    951,845                      ^13.1
             South Carolina                     867,258                    752,030                      ^13.3
                Mississippi                     645,220                    554,225                      ^14.1
                  Wisconsin                     828,362                    709,134                      ^14.4
                    Arizona                   1,138,220                    963,303                      ^15.4
                  Tennessee                   1,280,908                  1,071,344                      ^16.4
              New Hampshire                     114,744                     94,823                      ^17.4
                    Vermont                      94,604                     78,092                      ^17.5
                   Arkansas                     490,487                    403,376                      ^17.8
                     Kansas                     302,633                    247,281                      ^18.3
                   Missouri                     950,725                    767,403                      ^19.3
                   Kentucky                     842,885                    671,628                      ^20.3
                    Indiana                     901,967                    708,476                      ^21.5
                   Michigan                   1,884,542                  1,423,008                      ^24.5
                      Idaho                     233,194                    175,976                      ^24.5
                       Utah                     285,695                    212,903                      ^25.5
                      Maine                     251,189                    182,095                      ^27.5
                                 -------------------------------------------------------------------------------
  Total.........................             46,224,722                 43,215,557                       ^6.5
----------------------------------------------------------------------------------------------------------------
The following areas receive Nutrition Assistance Grants which provide benefits analogous to the Supplemental
  Nutrition Assistance Program: Puerto Rico, American Samoa, and the Northern Mariana[ Islands]. In addition,
  2015 and 2016 data are preliminary and are subject to significant revision.
* State where October 2016 SNAP data include disaster assistance (D-SNAP).


                                    Share of Population Participating in SNAP
                            (Prepared by the Food Research and Action Center (FRAC))
                                          (Data as of January 6, 2017)
----------------------------------------------------------------------------------------------------------------
                                     Population Estimate         SNAP Participants,
              State                         (2015)                  October 2016           Share of Population
----------------------------------------------------------------------------------------------------------------
                 New Mexico                   2,085,109                    473,398                       22.7
                           Louisiana          4,670,724                    943,685                       20.2
              West Virginia                   1,844,128                    350,474                       19.0
       District of Columbia                     672,228                    126,322                       18.8
                Mississippi                   2,992,333                    554,225                       18.5
                     Oregon                   4,028,977                    709,684                       17.6
                    Alabama                   4,858,979                    826,790                       17.0
                    Georgia                  10,214,860                  1,683,945                       16.5
                  Tennessee                   6,600,299                  1,071,344                       16.2
                    Florida                  20,271,272                  3,279,009                       16.2
                   Oklahoma                   3,911,338                    618,434                       15.8
               Rhode Island                   1,056,298                    166,365                       15.7
                   Delaware                     945,934                    148,340                       15.7
             South Carolina                   4,896,146                    752,030                       15.4
                     Nevada                   2,890,845                    443,138                       15.3
                   Kentucky                   4,425,092                    671,628                       15.2
                   New York                  19,795,791                  2,938,258                       14.8
                   Illinois                  12,859,995                  1,907,969                       14.8
               Pennsylvania                  12,802,503                  1,855,129                       14.5
             North Carolina                  10,042,802                  1,450,485                       14.4
                   Michigan                   9,922,576                  1,423,008                       14.3
                      Texas                  27,469,114                  3,891,234                       14.2
                    Arizona                   6,828,065                    963,303                       14.1
                      Maine                   1,329,328                    182,095                       13.7
                   Arkansas                   2,978,204                    403,376                       13.5
                       Ohio                  11,613,423                  1,553,901                       13.4
                 Washington                   7,170,351                    951,845                       13.3
                   Missouri                   6,083,672                    767,403                       12.6
                    Vermont                     626,042                     78,092                       12.5
                  Wisconsin                   5,771,337                    709,134                       12.3
                     Hawaii                   1,431,603                    173,289                       12.1
                       Iowa                   3,123,899                    377,126                       12.1
                   Maryland                   6,006,401                    716,620                       11.9
                Connecticut                   3,590,886                    422,181                       11.8
                    Montana                   1,032,949                    120,065                       11.6
              Massachusetts                   6,794,422                    771,512                       11.4
               South Dakota                     858,469                     95,153                       11.1
                 California                  39,144,818                  4,230,399                       10.8
                    Indiana                   6,619,680                    708,476                       10.7
                      Idaho                   1,654,930                    175,976                       10.6
                     Alaska                     738,432                     71,768                        9.7
                   Virginia                   8,382,993                    806,332                        9.6
                 New Jersey                   8,958,013                    854,146                        9.5
                   Colorado                   5,456,574                    466,789                        8.6
                     Kansas                   2,911,641                    247,281                        8.5
                  Minnesota                   5,489,594                    463,461                        8.4
                   Nebraska                   1,896,190                    153,419                        8.1
               North Dakota                     756,927                     54,124                        7.2
              New Hampshire                   1,330,608                     94,823                        7.1
                       Utah                   2,995,919                    212,903                        7.1
                    Wyoming                     586,107                     33,977                        5.8
                                 -------------------------------------------------------------------------------
  Total.........................            321,418,820                 43,215,557                       13.4
----------------------------------------------------------------------------------------------------------------
The following areas receive Nutrition Assistance Grants which provide benefits analogous to the Supplemental
  Nutrition Assistance Program: Puerto Rico, American Samoa, and the Northern Mariana[ Islands]. In addition,
  2015 and 2016 data are preliminary and are subject to significant revision.
* State where October 2016 SNAP data include disaster assistance (D-SNAP).


    The Chairman. Thank you.
    Mr. Weidman, 5 minutes.

STATEMENT OF JOHN WEIDMAN, DEPUTY EXECUTIVE DIRECTOR, THE FOOD 
                    TRUST, PHILADELPHIA, PA

    Mr. Weidman. Thank you, Chairman Conaway and Ranking Member 
Peterson, for inviting me to testify. My name is John Weidman. 
I am Deputy Executive Director for The Food Trust, a 
Pennsylvania-based nonprofit working nationally to improve 
access to healthy food.
    This year through a grant from the Robert Wood Johnson 
Foundation, we have launched the Center for Healthy Food 
Access, a national collaborative effort aimed at improving the 
health of children. I am here today to talk about strategies 
The Food Trust has been employing to improve health and 
encourage healthy eating among SNAP participants.
    We believe that to have the greatest impact, it takes a 
comprehensive approach that includes access, education, and 
incentives. In Pennsylvania, we have been improving access by 
opening farmers' markets, working with corner stores to stock 
healthier products, and incentivizing new supermarket 
development. Our team of nutrition educators is providing 
innovative and engaging programing through SNAP-Ed to teach 
children and adults how to eat healthy, cook, and shop on a 
budget. And we run a successful Food Bucks Program that 
provides $2 worth of free produce for every $5 spent with SNAP 
at farmers' markets and a local supermarket.
    Based on research, this comprehensive approach is working. 
A peer-reviewed study published in the journal Pediatrics found 
that our SNAP-Ed program reduced childhood overweight by 50 
percent. More recently, data collected on the BMI of 
Philadelphia children is showing that after decades of rising 
childhood obesity rates, we are finally seeing them drop. The 
strategies that are being implemented, access to healthy food, 
nutrition education, SNAP incentives, are happening all around 
the country and they are not only changing eating habits and 
preventing diet-related disease, but they are also creating 
jobs and spurring economic development.
    I want to share a brief story about Nicole Speller, a 
participant in one of our free 6 week SNAP-Ed cooking workshops 
that take place in over 500 community sites across southeastern 
Pennsylvania. Nicole had decided to make a change and improve 
her health. She also happened to be a fantastic cook, and each 
week she would share the recipe she was learning with her 
neighbors and her church. Upon completing the workshop series, 
Nicole started her own healthy cooking class at her church. 
This is just one example of how SNAP-Ed is helping to create a 
culture of health, and it is happening in innovative ways in 
every state in the nation.
    Of course, understanding how to eat healthy is only part of 
the problem. Accessing healthy food continues to be a challenge 
for millions of Americans. Over the last decade, we have seen 
incredible success through public-private partnerships to 
incentivize grocery stores to meet the need for better access. 
In Pennsylvania, through the leadership of now-Congressman 
Dwight Evans, we have the Pennsylvania Fresh Financing 
Initiative, which funded 88 grocery store projects in urban and 
rural areas, and created 5,000 jobs. Based on this successful 
model, there is now the Federal HFFI and programs in many other 
states.
    Most recently through Governor Kasich's Ohio Fresh Food 
Program, Vinton County, a rural county in southeast Ohio, is 
now slated for a new grocery store to open after the only store 
in the entire county had previously closed. This store will now 
serve seniors and working families who have been unable to 
satisfy the very basic human need of going to the store to buy 
food.
    The same grocers who we work with on HFFI programs also 
stress the need of the importance of nutrition education. It 
makes sense if grocers open a store and stock it with fresh 
produce, they need nutrition education to drive demand for 
healthy food. This is why both access and education go hand-in-
hand, not only to drive better health outcomes, but also to 
ensure that stores are profitable and serve as economic 
anchors.
    Last, I want to discuss incentives that help make healthy 
choices more affordable. In Philadelphia, 73 percent of Philly 
Food Bucks users report eating more fruits and vegetables, and 
SNAP sales at our farmers' markets have increased 300 percent 
since we launched the program. In Michigan, the Double Up Food 
Bucks Program is available throughout the state at farmers' 
markets and supermarkets, and around the country, hospitals are 
now participating in Veggie  programs, allowing physicians 
to prescribe fruits and vegetables to low-income patients. The 
USDA FINI Program has supported the expansion of these SNAP 
incentive programs. Making healthier food more affordable makes 
it easier for low-income families to make healthier choices. 
Many parents might try putting a plate of fresh carrots in 
front of a toddler. If he doesn't like it, they can just fix 
him something else to eat. But imagine if you only have enough 
money to afford one plate of food. The decision to try new 
things becomes much more difficult.
    In closing, there is no silver bullet to prevent diet-
related disease like obesity and diabetes, but the costs are 
real. A recent study calculated the cost of diet-related 
disease at $427 billion. A comprehensive approach that combines 
access, nutrition education, incentives, and includes public-
private partnerships holds the most promise for stemming these 
rising healthcare costs. Congress has moved forward to address 
obesity and diabetes through innovative programs like SNAP-Ed, 
FINI, and HFFI. SNAP is the foundation of this comprehensive 
approach and keeps millions of families from going hungry, and 
it is a critical economic pillar in low-income urban and rural 
communities. Without SNAP, stores would close, jobs would be 
lost, families would go hungry, and it would increase the need 
for food stamps. Quite a vicious cycle, if there ever was one, 
but by expanding access to healthy food, nutrition education, 
and SNAP incentives in the next farm bill, we can improve 
health, increase revenues for American farmers, create jobs in 
urban and rural areas, and control rising healthcare costs.
    Thank you for asking me to testify.
    [The prepared statement of Mr. Weidman follows:]

Prepared Statement of John Weidman, Deputy Executive Director, The Food 
                        Trust, Philadelphia, PA
    Thank you, Chairman Conaway and Ranking Member Peterson, for 
inviting me to testify. My name is John Weidman, and I am the Deputy 
Executive Director of The Food Trust, a Pennsylvania based nonprofit 
that works nationally to improve access to affordable nutritious food. 
We were founded in 1992, and 2017 marks our 25th Anniversary. This 
year, through a grant from the Robert Wood Johnson Foundation we have 
launched the Center for Healthy Food Access: a national collaborative 
effort aimed at improving the health of children in America. I am here 
today to talk about the strategies that The Food Trust has been 
employing to improve health and encourage healthy eating among SNAP 
participants. We believe that to have the greatest impact it takes a 
comprehensive approach that includes improving access, providing 
nutrition education, and utilizing SNAP incentives. In Pennsylvania, we 
have been improving access by opening and maintaining farmers['] 
markets in low-income neighborhoods, working with small food stores to 
stock healthier products, and incentivizing new supermarket development 
through the Pennsylvania Fresh Food Financing Initiative, the national 
model for Healthy Food Financing programs. Our team of dieticians and 
nutrition educators is providing innovative and engaging programming 
through the SNAP-Ed program to teach children and adults how to eat 
healthy, how to cook, and how to shop on a budget. And we run a 
successful Food Bucks program that provides $2 worth of free fruits and 
vegetables for every $5 spent with SNAP at Philadelphia farmers['] 
markets and a local supermarket chain.
    Based on research that has been conducted in Philadelphia, this 
comprehensive approach is working. A peer-reviewed study published in 
the journal Pediatrics found that our SNAP-Ed funded school nutrition 
education program reduced childhood overweight by 50%.\1\ More 
recently, data collected on the Body Mass Index (BMI) of Philadelphia 
children is showing that after decades of rising childhood obesity 
rates, we are finally seeing them drop.\2\ The strategies that are 
being implemented in Pennsylvania--access to healthy food, nutrition 
education, and SNAP Incentives--are happening all around the country, 
and they are not only changing eating habits and preventing diet-
related diseases like heart disease and diabetes, but they are also 
creating jobs and spurring economic development in struggling urban and 
rural communities.
---------------------------------------------------------------------------
    \1\ Foster, G.D., Sherman, S., Borradaile, K.E., Grundy, K.M., 
Veur, S.S., Nachmani, J., Karpyn, A., Kumanyika, S., Shults, J. (2008). 
A Policy-Based School Intervention to Prevent Overweight and Obesity. 
Pediatrics, 121(4). doi:10.1542/peds.2007-1365.
    \2\ Robbins, J.M., Mallya G., Wagner A., Buehler J.W. Prevalence, 
Disparities, and Trends in Obesity and Severe Obesity Among Students in 
the School District of Philadelphia, Pennsylvania, 2006-2013. Prev. 
Chronic. Dis. 2015; 12; 150185. DOI; http://dx.doi.org/10.5888/
pcd12.150185.
---------------------------------------------------------------------------
    I want to share a brief story about Nicole Speller, a participant 
in one of our free 6 week SNAP-Ed cooking workshops that take place in 
over 500 community sites: libraries, community centers, and churches 
across southeastern Pennsylvania. Nicole had decided to make a change 
and improve her health. She also happened to be a fantastic cook, and 
each week she would share the recipes and nutrition tips she was 
learning with her neighbors and her church group. Upon completing the 
workshop series, Nicole started her own healthy cooking class at her 
church. This is just one example of how SNAP-Ed is helping to create a 
culture of health, and it is happening in innovative ways in every 
state in the nation. In addition to our cooking workshops, we also use 
Share Our Strength's excellent Cooking Matters program to teach how to 
shop healthy in the supermarket and make healthy choices on a budget. 
We also work directly with thousands of school children each year to 
teach them about food, farming, and eating healthy.
    Of course, understanding how to eat healthier is only part of the 
problem for many SNAP participants. Accessing healthy food continues to 
be a challenge for millions of Americans. Over the last decade, we have 
seen incredible success through public-private partnerships to 
incentivize grocery stores, farmers['] markets, and other healthy food 
retail solutions to meet the need for better access. In Pennsylvania, 
thanks in large part to now-Congressman Dwight Evans, our Fresh Food 
Financing Initiative funded 88 grocery store projects in urban and 
rural areas and created 5,000 jobs. Based on this successful model, we 
now have the Federal Healthy Food Financing Initiative (HFFI) and 
programs in New York, Illinois, Mississippi, Colorado, and other 
states. Most recently, through Governor Kasich's Ohio Fresh Food 
Program, Vinton County--a rural county in southeast Ohio--is now slated 
for a new grocery store to open after the only store in the county had 
previously closed. This store will now serve seniors and working 
families who have been unable to satisfy the very basic human need of 
going to the store to buy food.
    While the HFFI model was developed working directly with grocers 
who want to improve access in under-served areas, they also stress the 
importance of nutrition education. It makes sense: if grocers open a 
store and stock it with fresh produce, they need nutrition education 
programs to drive demand for purchasing healthy food. For this reason, 
some grocers are now hiring registered dieticians to guide consumers in 
the store. Grocers understand the need to improve eating habits, but at 
the end of the day they cannot stock food that does not sell. This is 
why both access and education go hand-in-hand, not only to drive better 
health outcomes, but also to ensure that stores are profitable and 
serve as economic anchors for small towns and urban neighborhoods.
    In addition to the vital role the Federal Government plays, 
partnerships with the private sector are a critical component of the 
solution. Consumer demand for healthy products is growing, and many 
operators and manufacturers are shifting their product portfolios in a 
healthier direction. At the same time, retailers are developing 
innovative ways to sell these products. Grocers, bodega owners, and 
farmers have been indispensable partners in all of the efforts I have 
been discussing. We are partnering with food manufacturers such as 
Campbell Soup Company, which is spearheading a 10 year initiative in 
Camden, New Jersey, to improve health and reduce food insecurity. GSK 
(GlaxoSmithKline), another corporate partner, is funding a city-wide 
initiative called Get HYPE Philly! that is focused on youth leadership 
development, healthy eating and exercise, and education and job skills. 
We need more of these innovative partnerships in the years ahead.
    Last, I want to discuss incentives that encourage SNAP participants 
to try healthier foods and that make healthier choices more affordable. 
As I mentioned, The Food Trust launched our Philly Food Bucks program 
in 2011, and it has been a huge success. Seventy-three percent of 
Philly Food Bucks users report eating more fruits and vegetables, and 
SNAP sales at farmers['] markets have increased 300% since the start of 
the program. Based in Michigan, the Fair Food Network has greatly 
expanded their Double Up Food Bucks program in farmers' markets and 
grocery stores across the country. Wholesome Wave, based in 
Connecticut, is bringing SNAP incentives to health care, allowing 
physicians to ``prescribe'' fruits and vegetables to low-income 
patients for redemption at local farmers['] markets. In 2014, USDA 
launched FINI, the Food Insecurity Nutrition Incentive program, which 
has supported research, piloting, and expansion of SNAP incentive 
programs. Making healthier food more affordable makes it easier for 
low-income families to take risks when trying new foods. Many parents 
might try putting a plate of fresh carrots and peas in front of a 
toddler. If he sticks out his tongue and says yuck, they can just fix 
him something else to eat. (This is based on personal experience. I 
have a 3 year old). But imagine if you only have enough money to afford 
one plate of food--the decision to try new things becomes much more 
difficult.
    In closing, there is no silver bullet to prevent diet-related 
diseases like obesity and diabetes, but the costs are real. A recent 
study by the Milken Institute calculated the direct medical costs for 
diet-related disease in 2014 at $427.8 billion.\3\ Soda and sugary 
drinks are a big driver of the problem and Congress has moved forward 
to address obesity and diabetes through innovative programs like SNAP-
Ed, FINI and HFFI. A comprehensive approach that combines access, 
nutrition education, and SNAP incentives holds the most promise for 
stemming these rising healthcare costs and building new, healthier 
habits. SNAP is the foundation of this comprehensive approach. It keeps 
millions of families from going hungry and is a critical economic 
pillar for lower income urban and rural communities. Without SNAP, 
stores would close, jobs would be lost, more families would drop into 
poverty, and more people would need food stamps. A vicious cycle, if 
there ever was one. By expanding access to healthy food, nutrition 
education, and incentives in the next farm bill we can improve health, 
increase revenues for American farmers, create jobs in urban and rural 
areas, and control rising healthcare costs.
---------------------------------------------------------------------------
    \3\ Waters, H., & DeVol, R. (2016). Weighing Down America: The 
Health and Economic Impact of Obesity. Retrieved from Milken Institute: 
http://assets1c.milkeninstitute.org/assets/Publication/ResearchReport/
PDF/Weighing-Down-America-WEB.pdf.
---------------------------------------------------------------------------
    Thank you for the opportunity to testify, I look forward to your 
questions.

    The Chairman. Thank you very much.
    Dr. Wansink?

        STATEMENT OF BRIAN WANSINK, Ph.D., JOHN S. DYSON
          PROFESSOR OF MARKETING AND DIRECTOR, CORNELL
           UNIVERSITY FOOD AND BRAND LAB, ITHACA, NY

    Dr. Wansink. Thank you for giving me the opportunity to 
present my perspective on the pros and cons of restricting SNAP 
purchases. I will be addressing three questions today: first, 
what happens when food purchases are restricted; second, who 
has the most potential to shop healthier; and third, how can 
this be best encouraged? Thank you.
    First, as a behavioral scientist and Director of the 
Cornell Food and Brand Lab, I focus on changing behaviors in a 
practical way. But as former USDA Executive Director from the 
Center for Nutrition Policy and Promotion, the Dietary 
Guidelines, I focused on changing eating behaviors in a 
scalable way. What I want to emphasize is our best and worst 
eating habits start in the grocery store. If we can change what 
people bring home, we change what they eat.
    Now how do food restrictions influence people? Well, I have 
two exhibits. First, how does shopping behavior change after 
versus before people receive SNAP benefits? Well, there is a 
new 6 year study of SNAP recipients in Rhode Island that shows 
that spending on SNAP eligible products went up once they 
received the benefits, but the general purchase of SNAP 
ineligible benefits, the soft drinks and things like this, did 
not go down. What they do is they trace some of this to people 
buying more convenient products when they get SNAP benefits.
    Exhibit 2 looks at incentives. When we specifically 
financially incentivize shoppers to buy more fruits and 
vegetables, what happens? In one 6 month study of 208 families 
in Utica, New York, we gave shoppers ten percent more money 
back in a debit card when they bought healthy foods like fruits 
and vegetables. When low-income shoppers were given this, they 
spent $33 more per week with $12 of that being on healthier 
foods, but $21 being on less healthy foods such as snack foods. 
The money they saved on healthy foods, they also spent on less 
healthy foods.
    Now these are both preliminary reports. They do show that 
when people are incentivized to buy healthy foods, they do, but 
they also buy less healthy foods.
    What I want to look at is who has the biggest potential to 
eat better? Now we make a mistake when we only look at all SNAP 
recipients as a homogenous group of shoppers. Instead, people 
are in a pyramid like this. It goes in a hierarchy of healthy 
disposition. If you see something like this, there are people 
at the top who are very vigilant shoppers. These are people who 
know the number of calories in a Coke, the number of calories 
in Fritos. They care about what they eat. No change is going to 
influence what they buy. At the very bottom, you have health 
disinterested shoppers. Again, these are people who are either 
resigned or they are disinterested in shopping healthier, and 
again, no change is going to have much impact on what they buy. 
Who we can influence is this middle group, the health 
predisposed shoppers, because these are the people who want to 
eat better, but they just need the help and the nudge to do so.
    Now if we look at what is going to work best for these 
health predisposed shoppers, the question is how do we do this? 
Will the restriction work? And second, will something else work 
better?
    Now I said earlier it is not clear whether the hassles of 
related retailing shopper dignity would merit a change, but 
there might be a solution to this. So for instance, one option 
would be to give a SNAP recipient an option. They can use 100 
percent of their SNAP benefits to purchase whatever they 
wanted, or if they agreed themselves to restricting--let's just 
say to produce. Maybe they get a bonus. They get 125 percent 
more. Now we are not sure how this would work, and it does 
merit testing as mentioned earlier, but a second option is far 
easier to implement and can be scaled very quickly. It involves 
providing simple guidelines to retailers, maybe even a 
certification on how to make it easier for SNAP shoppers, all 
shoppers, to buy healthier foods by making it more convenient, 
attractive, and normal to do so.
    There is a precedent for this healthier by design shopping 
program that is beginning to work in food deserts. Last year, 
the National Association of Convenience Stores developed and 
launched a new tool kit of evidence-based tactics that could be 
used to increase the sales of healthier foods. It is one reason 
why when you buy gas, you often find a basket of bananas next 
to the cash register. That is because of this program. These 
are small, easy changes to make, and they are win-win benefits 
for both retailers, SNAP recipients, and us. But systematically 
giving other retailers the guidance on how to make these 
healthy nudges and credit them for doing so would benefit SNAP 
shoppers just as well as it is benefitting us.
    Another way this retail program is underway is the Nordic 
solution to sustainability and obesity, it is related to the 
EAT Foundation and GreeNudge. And over there, supermarkets are 
being guided to make small changes in signage, service, and 
structure, and it has increased fruits and vegetables 
consumption for that.
    Now in summary, and this is a third alternative, but I will 
give three things. SNAP recipients get benefits and restricted 
benefits, but they do not necessarily buy only healthier foods. 
They buy everything else. Second, there are three segments of 
shoppers; and third, there are different ways to best encourage 
this health predisposed segment.
    Thanks for this opportunity to talk with you.
    [The prepared statement of Dr. Wansink follows:]

Prepared Statement of Brian Wansink, Ph.D., John S. Dyson Professor of 
Marketing and Director, Cornell University Food and Brand Lab, Ithaca, 
                                   NY
    Good morning, Chairman Conway, Ranking Member Peterson, Members of 
the Committee: Thank you for giving me the opportunity to present my 
perspective on the pros and cons of restricting SNAP purchases. I will 
be addressing three questions today: (1) What happens when food 
purchases are restricted? (2) Who has the most potential to shop 
healthier, and (3) How can this be best encouraged?
When Happens When Food Purchases are Restricted?
    As a behavioral scientist and Director of the Cornell Food and 
Brand Lab, I focus on changing eating behaviors in a practical way. As 
the former USDA Executive Director for the Center for Nutrition Policy 
and Promotion--the Dietary Guidelines--I focused on changing eating 
behaviors in a scalable way.
    When Food Stamps were first introduced, their purpose was to fill 
bellies with calories. Seventy years later we have another important 
opportunity. Fill bellies with the right calories. With increasing 
health care costs threatening the future of the American economy, one 
place we can begin turning this around--starting tonight--is with what 
we eat in our homes. Of all the health concerns that face Americans, 
diet-related disease and obesity are the ones that we can tackle most 
immediately.
    What is critical to remember, however, is this: Our best and worse 
eating habits start in the grocery store. If we can change what people 
bring home from the grocery store or market, we can change how they 
eat.
    Do people shop differently when they're given extra money--such as 
a rebate or SNAP benefits? Two preliminary studies give us some insight 
here.
    Exhibit No. 1. How does shopping behavior change after versus 
before people receive SNAP benefits? A new 6 year study of SNAP 
recipients in Rhode Island showed that the spending on SNAP eligible 
products went up once they received benefits, but the general purchase 
of SNAP ineligible benefits did not go down (Hastings and Shaprio 
2017). Further unpublished analyses (learned through conversation) also 
suggest that purchase of convenient-to-eat foods goes up once a person 
receives SNAP benefits. They trade their SNAP benefits for convenience.
    Exhibit No. 2 looks at incentives. What if we specifically 
financially incentivize shoppers to buy more fruits and vegetables? In 
one 6 month study of 208 families in Utica, NY, we gave shoppers a 10% 
bonus--10% more money back on their debit card--when they bought 
healthy foods such as fruits and vegetables. When low-income shoppers 
(poverty ratio less than 1.3) were given this extra money as a subsidy, 
they spent $33 more per week on healthier foods--including fruits and 
vegetables, but they also spent $21 more per week on less healthy 
foods, such as snack foods (Cawley, et al., 2016). Some of the money 
they saved on the healthy foods, they appeared to spend on less healthy 
foods.
    Although both of these are single, preliminary white papers in the 
National Bureau of Economic Research, they point at the idea that extra 
money--in the form of SNAP benefits or subsidies--changes the way 
people shop. They do buy more of the healthy, incentivized foods, but 
they also buy more of the less healthy foods. They just use their own 
money instead.
    A key question, however, is ``Who has the most potential to eat 
better?''
The Hierarchy of Health Predisposition
    When I was the Executive Director of the USDA's Center for 
Nutrition Policy and Promotion, I saw people off-handedly dismiss 
potentially useful ideas for new initiatives if they would not benefit 
100% of the population under discussion.
    In trying to solve difficult problems, it is very useful to not 
view 100% of all people--such as all SNAP benefit recipients--as the 
same. Some people already eat very healthy, some people do not want to 
eat healthy, and some people want to, but they need help. When trying 
to predict how a SNAP shopper would respond to a restriction, it is 
useful to understand that there is a Hierarchy of Health 
Predisposition.
    Not all SNAP shoppers shop alike and we can view them--like all 
shoppers--on how predisposed they are to wanting to make a healthier 
shopping decision. We can view them as belonging to one of three fluid 
groups within a Hierarchy of Health Predisposition. The top segment of 
this hierarchy are Health Vigilant shoppers. They are highly informed, 
conscious of calories, and they are influenced by nutrition 
information. At the bottom extreme, Health Disinterested shoppers have 
little interest in changing their eating choices because of either the 
effort, sacrifice, or perceived futility of doing so. The segment in 
the middle are the Health Predisposed shoppers. They would prefer to 
make healthier food choices, but they have difficulty consistently 
doing so unless it involves very little sacrifice on their part. This 
Predisposed segment is the one that buys the 100 calorie packages of 
snacks and the sugar-free yogurt. For all people, this segment is 
larger on New Years Day than it was in December; it was larger this 
past Monday morning than it was during the prior Friday night's 
shopping trip.
The Hierarchy of Health Predisposition


[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

    One reason nutrition guidance systems (such traffic lights or 
Guiding Stars) have had only modest influences on the sales of healthy 
food may be because they mainly resonate with only the top of the 
Hierarchy. Health Disinterested shoppers ignore these programs, and 
Heath Predisposed shoppers inconsistently follow them. If the only 
segment they reach are the Vigilant shoppers, interventions like this 
will have hardly any impact on sales since this segment is already 
shopping in a healthy way.
    This is important because SNAP restrictions may not have the same 
impact on healthy shopping behavior that we desire. The Health Vigilant 
shoppers will already be shopping healthy, and they do not need them. 
At the other extreme, Healthy Disintereseted shoppers might simply 
rechannel their own money toward what they would have bought anyway. 
What this importantly raises is the question as to whether there other 
ways to guide SNAP shoppers to eat healthier--particularly those in 
this middle section.
Non-Restrictive Options to Encourage Healthier SNAP Shopping Patterns
    One extreme way to try and encourage SNAP shoppers to eat better is 
to restrict what they can purchase. Some people might say this is not 
practical for retailers. Other people might say this is not respectful 
of the dignity or free choice of SNAP shoppers.
    What is not asked when it comes to restricting SNAP purchases is, 
``Will it even work?'' As just noted, for the Health Vigilant, it 
wouldn't have any impact because they already eat healthy. At the other 
end, for the Health Disinterested, it may not work because they will 
simply spend their cash on what they would have otherwise bought 
anyway. There are two open questions: (1) Will a restriction work with 
the Health Predisposed--this middle segment, and (2) Would something 
else work better?
    First, as said earlier, it is not clear if the retail hassles and 
the shopper dignity and free choice issues related to a restriction 
would merit a change. There may be a solution to this, however. Suppose 
a nutritionally predisposed shopper had one of two options. One option 
would be to have 100% of their SNAP benefits to purchase whatever they 
wanted (foods that are currently eligible). A second option would be 
that they could agree to self-restrict themselves from buying certain 
foods in exchange for, say, 125% of their SNAP benefits. In effect, if 
they agreed to restrict their SNAP benefits to buy only predetermined 
healthy foods--say fruits, vegetables, whole grains, lean meat and 
dairy--they would get more 25% (or however much) more buying power. 
Such a system would still give people an option--they could either 
choose the 100% unrestricted plan or they could choose the 125% 
restricted plan--and it would help those who wanted to eat better to 
more easily do so. Of course, we have no evidence of how effective this 
would be in practice, but it is an idea that merits pilot testing. It 
lets people be free to choose while also providing them an incentive to 
eat better. The SNAP recipient chooses what they want.
    A second option is far easier to implement and can be scaled 
quickly. It involves providing simple guidelines to retailers--perhaps 
even a certification--on how to make it easier for SNAP shoppers (and 
all shoppers) to buy healthier foods by making it more convenient, 
attractive, and normal (the CAN framework) to do so. This notion of 
``Healthy Shopping by Design'' is fashioned off of the Smarter 
Lunchroom Movement which is a USDA-sponsored initiative that trains 
food service directors on the dozens of ways they can guide students 
toward making healthier selections in the school lunchroom (Hanks, et 
al., 2013). The 66-point scorecard shows whether the way they set up, 
serve, and promote foods make kids fit or fat. For instance, a score of 
25 out of 66 indicates there is easy room for improvement, but also 
points at the 41 other changes they could make (Appendix).
    There is precedent for a Healthy Shopping by Design program that is 
beginning to work in food deserts. In 2016, the National Association of 
Convenience Stores, working with the Cornell Food and Brand Lab 
developed and launched a new toolkit titled, ``Ideas That Work to Grow 
Better-for-You Sales,'' and they include evidence-based tactics to 
increase the sales of healthier foods. It is one reason you can often 
buy a banana when you buy gas--they are sitting right next to the cash 
register (Lenard and Schare 2016). These are small easy changes to 
make, but they are win-win and benefit both retailers and (food desert) 
shoppers.
    Systematically giving other retailers the guidance of how to make 
healthy nudges, and the credit for doing so could change healthy 
shopping for SNAP shoppers just as the Smarter Lunchroom Movement is 
changing lunchtime for school children (Wansink 2017; 2014). In Norway, 
this is currently underway as a Nordic Solution to sustainability and 
obesity (which is related to the EAT Foundation and GreeNudge). Over 
there, supermarkets are being guided how to make small changes to the 
signage, structure, and service, and the results have been increased 
fruit and vegetable sales for all (Wansink, Karvold, and Tran 2017).
Summary
  1.  Giving SNAP recipients more benefits or restricted benefits may 
            not lead them to only buy healthier food (they will also 
            buy more convenient foods and less healthier foods).

  2.  There are three segments of shoppers: the Health Vigilant, the 
            Health Predisposed, and the Health Disinterested. The 
            easiest win will be to focus efforts programming on the 
            Health Predisposed segment.

  3.  There are at least two ways to try and influence the Health 
            Predisposed segment. One might be giving them 100% of their 
            unrestricted benefits, or 130% of restricted benefits. A 
            second would be to work with retailers to show them how 
            they can be even more profitable by making it convenient, 
            attractive, and normal for SNAP shoppers--indeed all 
            shoppers--to shop healthier. Just as this program is 
            responsible for putting bananas by the convenience store 
            checkouts, and more vegetables in Norwegian shopping carts, 
            it could be successful on a larger scale with supermarkets 
            and other stores accepting SNAP benefits.

    Thank you for this opportunity to share my perspective with you.
References
    Cawley, John, Andrew S. Hanks, David R. Just, and Brian Wansink 
(2016), ``Incentivizing Nutrition Diets: A Field Experiment of Relative 
Price Changes and How They Are Framed,'' National Bureau of Economics 
Research, Working paper 21929.
    Hanks, Andrew S., David R. Just, and Brian Wansink (2013), 
``Smarter Lunchrooms Can Address New School Lunchroom Guidelines and 
Childhood Obesity,'' Journal of Pediatrics, 162: 4 (April), 867-869.
    Hastings, Justine and Jesse M. Shapiro (2017), ``How are SNAP 
Benefits Spent? Evidence from a Retail Panel,'' National Bureau of 
Economic Research, Working paper.
    Lenard, Jeff and Carolyn Schnare (2016), ``Eight Low-Cost--and 
Proven--Tactics for How C-Store Operators and Grow Their Healthy 
Offer,'' NACS Magazine, August, 30-36.
    NACS (2016), ``NACS Toolkit Helps C-Stores Grown Better-for-You 
Sales,'' May 26 http://www.nacsonline.com/Media/Daily/Pages/
ND0526161.aspx#.WKPMM
neZNPs.
    Wansink, Brian (2014), Slim by Design--Mindless Eating Solutions 
for Everyday Life, New York, NY: William Morrow.
    Wansink, Brian, Knut Karevold, and Huy Tran (2017), ``Supermarket 
Interventions to Sell Sustainable Fruits and Vegetables: The Nordic 
Solution to Healthier Shopping,'' Cornell Food and Brand Lab, working 
paper.
    Wansink, Brian (2017), ``Healthy Profits: An Interdisciplinary 
Retail Framework that Increases the Sales of Healthy Foods, Journal of 
Retailing, in press.
    Appendix. Example of Scorecards that Encourage Healthier Choices

[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]




                               Exhibit 1
How Are SNAP Benefits Spent? Evidence from a Retail Panel
Justine S. Hastings, Jesse M. Shapiro
Working Paper 23112
http://www.nber.org/papers/w23112

    This work has been supported (in part) by awards from the Russell 
Sage Foundation, the Robert Wood Johnson Foundation's Policies for 
Action program, and the Laura and John Arnold Foundation. Any opinions 
expressed are those of the author(s) alone and should not be construed 
as representing the opinions of these Foundations. This project 
benefited from the suggestions of Ken Chay, Raj Chetty, David Cutler, 
Amy Finkelstein, Xavier Gabaix, Peter Ganong, Ed Glaeser, Nathan 
Hendren, Hilary Hoynes, Larry Katz, David Laibson, Kevin Murphy, Mandy 
Pallais, Devin Pope, Diane Whitmore Schanzenbach, and Andrei Shleifer, 
from audience comments at Brown University, Clark University, Harvard 
University, the Massachusetts Institute of Technology, and the 
Quantitative Marketing and Economics Conference, and from comments by 
discussant J.P. Dube. We thank our dedicated research assistants for 
their contributions. The views expressed herein are those of the 
authors and do not necessarily reflect the views of the National Bureau 
of Economic Research.
    At least one co-author has disclosed a financial relationship of 
potential relevance for this research. Further information is available 
online at http://www.nber.org/papers/w23112.ack.
    NBER working papers are circulated for discussion and comment 
purposes. They have not been peer-reviewed or been subject to the 
review by the NBER Board of Directors that accompanies official NBER 
publications.
    2017 by Justine S. Hastings and Jesse M. Shapiro. All rights 
reserved. Short sections of text, not to exceed two paragraphs, may be 
quoted without explicit permission provided that full credit, including 
 notice, is given to the source.
Abstract
    We use a novel retail panel with more than 6 years of detailed 
transaction records to study the effect of participation in the 
Supplemental Nutrition Assistance Program (SNAP) on household spending. 
We frame our approach using novel administrative data from the state of 
Rhode Island. The marginal propensity to consume SNAP-eligible food 
(MPCF) out of SNAP benefits is 0.5 to 0.6. The MPCF out of cash is much 
smaller. These patterns obtain even for households for whom SNAP 
benefits are economically equivalent to cash in the sense that benefits 
do not cover all food spending. We reject the hypothesis that 
households respect the fungibility of money in a semiparametric setup. 
A post-hoc model of mental accounting rationalizes these facts and 
others.

 
 
 
Justine S. Hastings,                 Jesse M. Shapiro,
Brown University,                    Economics Department,
Department of Economics,             Box B,
64 Waterman Street,                  Brown University,
Providence, RI 02912,                Providence, RI 02912,
and NBER,                            and NBER,
[email protected];          [email protected].
 

    A online appendix is available at http://www.nber.org/data-
appendix/w23112.
1  Introduction
    This paper studies how receipt of benefits from the Supplemental 
Nutrition Assistance Program (SNAP) affects household spending. SNAP is 
of special interest to economists for at least two reasons. First, the 
program is economically important: it is the second-largest means-
tested program in the United States after Medicaid (Congressional 
Budget Office 2013), enrolling 19.6 percent of households in fiscal 
2014.\1\
---------------------------------------------------------------------------
    \1\ There were 22,743,911 participating households in fiscal 2014 
(FNS 2016a) and 116,211,092 households in the U.S. on average from 
2010-2014 (U.S. Census Bureau 2016).
---------------------------------------------------------------------------
    Second, the program's stated objectives sit awkwardly with economic 
theory. On signing the bill to implement the predecessor Food Stamp 
Program, President Lyndon Johnson declared that the program would 
``enable low-income families to increase their food expenditures'' 
(Johnson 1964). The Food and Nutrition Service of the USDA says that 
SNAP is important for ``helping low-income families put food on the 
table'' (FNS 2012). Yet although SNAP benefits can only be spent on 
food, textbook demand theory (Mankiw 2000; Browning and Zupan 2004) 
predicts that, for the large majority of SNAP recipients who spend more 
on food than they receive in benefits,\2\ SNAP benefits are 
economically equivalent to cash.\3\ As typical estimates of the 
marginal propensity to consume food (MPCF) out of cash income are close 
to 0.1,\4\ the textbook treatment says that SNAP benefits should mostly 
subsidize non-food spending.
---------------------------------------------------------------------------
    \2\ Hoynes, et al., (2015) find that spending on food at home is at 
or above the SNAP benefit level for 84 percent of SNAP recipient 
households. Trippe and Ewell (2007) report that 73 to 78 percent of 
SNAP recipients spend at least ten percent more on food than they 
receive in SNAP benefits.
    \3\ Consider a household with monthly income y and SNAP benefits b. 
If the household spends  on SNAP-eligible food then she has 
y^max (0,^b) available to buy other goods. Let U 
(,n) denote the household's strictly monotone, 
differentiable, and strictly quasiconcave utility function defined over 
the dollar amount of SNAP-eligible food consumption  and 
other consumption n. Suppose that there is a solution 
* = arg max  U 
(,y^max(0,^b)) such that *>b. 
The first-order necessary condition for this program is a necessary and 
sufficient condition for a solution to the program max fU 
(;y+b^) in which the benefits are given in cash. 
Therefore * = arg max 
fU(,y+b^).
    \4\ Castner and Mabli (2010) estimate an MPCF out of cash income of 
0.07 for SNAP participants. Hoynes and Schanzenbach (2009) estimate an 
MPCF out of cash income of 0.09-0.10 for populations with a high 
likelihood of participating in the Food Stamp Program.
---------------------------------------------------------------------------
    Estimating the effect of SNAP benefits on spending is challenging 
because it requires good measurement of household spending and suitably 
exogenous variation in program participation or benefits. Survey-based 
measures of household spending are error-prone and sensitive to the 
mode of elicitation (Ahmed, et al., 2006; Browning, et al., 2014; 
Battistin and Padula 2016). Important components of SNAP eligibility 
and benefit rules are set nationally, and major program changes have 
often coincided with other policy changes or economic shocks 
(Congressional Budget Office 2012), making it difficult to separate the 
effect of SNAP from the effect of these contextual factors.
    In this paper we analyze a novel panel consisting of detailed 
transaction records from February 2006 to December 2012 for nearly \1/
2\ million regular customers of a large U.S. grocery retailer. The data 
contain information on method of payment, including whether payment was 
made using a government benefit card. We use the panel to study the 
effect of transitions on and off of SNAP, and of legislated changes in 
SNAP benefits, on household spending.
    We adopt three approaches to isolating the causal effect of SNAP on 
spending: a panel event-study design using trends prior to SNAP 
adoption to diagnose confounds, an instrumental variables design 
exploiting plausibly exogenous variation in the timing of program exit, 
and a differences-in-differences design exploiting legislated changes 
to benefit schedules.
    We motivate each of these approaches with findings from novel Rhode 
Island administrative data. The data show that household income and 
size change in the months preceding a household's transition on to 
SNAP, motivating our panel event-study design. The data also show that 
SNAP spell lengths are typically divisible by 6 months because of the 
recertification process, motivating our instrumental-variables design. 
National administrative records show discrete jumps in SNAP benefits 
associated with legislated program changes in 2008 and 2009, motivating 
our differences-in-differences design.
    By construction our retail panel includes purchases at a single 
grocery chain. Rhode Island administrative data show that it is 
possible to reliably infer transitions on to SNAP using data from a 
single grocery chain, by focusing on consecutive periods of non-SNAP 
use followed by consecutive periods of SNAP use. Additional data, 
including a survey conducted by the retailer, show that SNAP 
participation is only weakly related to a household's choice of 
retailer.
    Graphical analysis of our panel event-study design shows that after 
adoption of SNAP, households in the retailer panel increase SNAP-
eligible spending by about $110 a month, equivalent to a bit more than 
\1/2\ of their monthly SNAP benefit. There is no economically 
meaningful trend in SNAP-eligible spending prior to adoption of SNAP. 
Graphical analysis of our instrumental-variables and differences-in-
differences designs also implies an MPCF out of SNAP in the range of 
0.5 to 0.6.
    We exploit large swings in gasoline prices during our sample period 
to estimate the MPCF out of cash for the retail panelists. We observe 
gasoline spending at the retailer and confirm that increases in 
gasoline prices lead to significant additional out-of-pocket expenses 
for panelist households. We estimate that every $100 per month of 
additional gasoline spending reduces food spending by less than $10, in 
line with past estimates of the MPCF out of cash for the SNAP-recipient 
population (e.g., Castner and Mabli 2010) but far below the estimated 
MPCF out of SNAP.
    Turning to SNAP-ineligible spending at the retailer, we estimate an 
MPC of 0.02 out of SNAP benefits, and a (statistically 
indistinguishable) MPC of 0.04 out of cash.
    We develop an economic model of food spending by households for 
whom SNAP benefits do not cover all food spending and are therefore 
fungible with cash. We show how to test the hypothesis of fungibility, 
allowing for the endogeneity of cash income and SNAP benefits, and for 
the possibility that different households' consumption functions do not 
share a common parameterization or parametric structure. Our tests 
consistently reject the null hypothesis that households treat SNAP 
benefits as fungible with other income.
    We extend our economic model to include mental accounting following 
the approach in Farhi and Gabaix (2015). The extension is post-hoc. By 
design, it rationalizes the finding that the MPCF is greater out of 
SNAP benefits than out of cash. It also predicts that, following SNAP 
receipt, households will allocate relatively less effort to bargain-
hunting in the food domain than in the non-food domain. We find that 
SNAP receipt reduces the store-brand share of expenditures and the 
share of items on which coupons are redeemed, but only for SNAP-
eligible foods.
    We also discuss the responses from qualitative interviews conducted 
at a food pantry as part of a Rhode Island pilot proposal to modify 
SNAP benefit timing. Respondents were not scientifically sampled, and 
it is not appropriate to derive general conclusions from these 
interviews. Nevertheless, we find that they provide useful context for 
our analysis.
    This paper contributes to a large literature on the effects of SNAP 
and the predecessor Food Stamp Program on food spending, recently 
reviewed by Bitler (2015) and Hoynes and Schanzenbach (2016). There are 
four strands to this literature. The first strand studies the effect of 
converting food stamp benefits to cash. Moffitt (1989) finds that a 
cashout in Puerto Rico did not affect food spending. Wilde and Ranney 
(1996) find that behavior in two randomized cashout interventions is 
not consistent with fungibility; Schanzenbach (2002) finds that 
behavior in these same interventions is consistent with fungibility.\5\ 
The second strand, reviewed in Fox, et al. (2004), either compares 
participants to nonparticipants or relates food spending to the size of 
a household's benefit, either across households or over time. Wilde 
(2001) and Hoynes and Schanzenbach (2009), among others, criticize this 
strand of the literature for using a source of variation in program 
benefits that is likely related to non-program determinants of 
spending.\6\ The third strand studies randomized evaluations of program 
extensions or additions. Collins, et al. (2016) study a randomized 
evaluation of the Summer Electronic Benefit Transfer for Children 
program and use survey data to estimate an MPCF out of program benefits 
of 0.58.
---------------------------------------------------------------------------
    \5\ Fox, et al. (2004) question the validity of the findings from 
Puerto Rico and one of the randomized interventions, arguing that the 
best evidence indicates that cashout reduces food spending.
    \6\ Wilde, et al. (2009) address the endogeneity of program 
benefits by exploiting variation in whether household food spending is 
constrained by program rules. Li, et al. (2014) use panel data to study 
the evolution of child food insecurity in the months before and after 
family entry into the food stamp program.
---------------------------------------------------------------------------
    The fourth strand exploits policy variation in program availability 
and generosity. Studying the initial rollout of the Food Stamp Program 
using survey data, Hoynes and Schanzenbach (2009) estimate an MPCF out 
of food stamps of 0.16 to 0.32, with confidence interval radius ranging 
from 0.17 to 0.27. Hoynes and Schanzenbach (2009) estimate an MPCF out 
of cash income of 0.09 to 0.10 and cannot reject the hypothesis that 
the MPCF out of food stamps is equal to the MPCF out of cash income. 
Studying the effect of a 2009 SNAP benefit expansion using survey data, 
Beatty and Tuttle (2015) estimate an MPCF out of SNAP benefits of 0.53 
to 0.64 (they do not report a confidence interval on these values) and 
an MPCF out of cash income of 0.15.\7\ Closest to our study, Bruich 
(2014) uses retail scanner data with method-of-payment information to 
study the effect of a 2013 SNAP benefit reduction, estimating an MPCF 
out of SNAP benefits of 0.3 with confidence interval radius of 0.15.\8\ 
Bruich (2014) does not report an MPCF out of cash income. We estimate 
an MPCF out of SNAP benefits of 0.5 to 0.6 with confidence interval 
radius as low as 0.015, and an MPCF out of cash income of no more than 
0.1.
---------------------------------------------------------------------------
    \7\ Nord and Prell (2011) estimate the effect of the 2009 benefit 
expansion on food security and food expenditures. Ratcliffe, et al. 
(2011) and Yen, et al. (2008) estimate the effect of SNAP and food 
stamps, respectively, on food insecurity, using state-level policy 
variables as excluded instruments.
    \8\ Andreyeva, et al. (2012) and Garasky, et al. (2016) use retail 
scanner data to describe the food purchases of SNAP recipients, but not 
to estimate the causal effect of SNAP on spending.
---------------------------------------------------------------------------
    This paper contributes new evidence of violations of fungibility in 
a large-stakes real-world decision with significant policy relevance. 
That households mentally or even physically separate different income 
sources according to spending intentions is well-documented in 
hypothetical-choice scenarios (e.g., Heath and Soll 1996; Thaler 1999) 
and ethnographic studies (e.g., Rainwater, et al., 1959). Much of the 
recent literature documenting this behavior in real-world markets 
focuses on consumer choice settings with little direct policy relevance 
(e.g., Milkman and Bashears 2009; Hastings and Shapiro 2013; Abeler and 
Marklein forthcoming). Important exceptions include Kooreman's (2000) 
study of a child tax credit in the Netherlands, Feldman's (2010) study 
of a change in U.S. Federal income tax withholding, and Benhassine, et 
al.'s (2015) study of a labeled cash transfer in Morocco.
    Methodologically, this paper shows how to test for the fungibility 
of money without assuming that the consumption function takes a 
particular parametric form or that the consumption function is 
identical for all households.\9\ Our approach nests Kooreman's (2000), 
but avoids the concern that a rejection of fungibility is due to 
misspecification of functional forms (Ketcham, et al., 2016).
---------------------------------------------------------------------------
    \9\ Whereas classical tests of consumer rationality (Varian 1983; 
Blundell, et al., 2003) require observing price changes, we provide a 
set of intuitive sufficient conditions on the model and the measurement 
process that permit testing based on income variation alone.
---------------------------------------------------------------------------
    Finally, the paper presents new evidence from novel administrative 
data on SNAP recipients in Rhode Island, including the first evidence 
we are aware of from state administrative data on how household wage 
income evolves before and after entry into SNAP.\10\ Although we 
present these findings primarily as background, they are of interest in 
their own right as evidence on the contextual factors associated with 
SNAP adoption.
---------------------------------------------------------------------------
    \10\ Other recent studies analyzing linked unemployment insurance 
and SNAP data include Anderson, et al., (2012) and Leung and O'Leary 
(2015).
---------------------------------------------------------------------------
2  Background and Evidence from Administrative and Survey Data
2.1  Rhode Island Administrative Data
    We use Rhode Island state administrative records housed in a secure 
facility at the Rhode Island Innovative Policy Laboratory at Brown 
University. Personally identifiable information has been removed from 
the data and replaced with secure identifiers that make it possible to 
link different records associated with the same individual or 
household. These records are not linked to our retail panel.
    We obtain the state's SNAP records from October 2004 through June 
2016. These data define the months of benefit receipt and the 
collection of individuals associated with every household on SNAP in 
every month. We assume that a household's composition is unchanged 
prior to its first benefit receipt and that it does not change from its 
most recent composition between the end of any given period of benefit 
receipt and the start of the next period. We exclude from our analysis 
any household whose membership we cannot uniquely identify in every 
month,\11\ or whose adult composition changes during the sample period. 
The final sample consists of 185,534 unique households.
---------------------------------------------------------------------------
    \11\ This can occur either because we lack a unique identifier for 
a member individual or because a given individual is associated with 
multiple households in the same month.
---------------------------------------------------------------------------
    From SNAP records we compute, for each household and month, the 
total number of children in the household under 5 years old. From the 
records of the state unemployment insurance system we compute, for each 
household and quarter,\12\ the sum of total unemployment insurance 
benefits received from and total earnings reported to the state 
unemployment insurance system by all individuals who are in the 
household as of the quarter's end.\13\ We refer to this total as 
household income, but we note that it excludes income not reported to 
the Rhode Island unemployment insurance system, such as social security 
benefits and out-of-state earnings.
---------------------------------------------------------------------------
    \12\ Data on earnings are missing from our database for the fourth 
quarter of 2004 and the second quarter of 2011.
    \13\ We exclude from our analysis any household-quarter in which 
the household's total quarterly earnings exceed the 99.9999th 
percentile or in which unemployment insurance benefits in any month of 
the quarter exceed three times the 4 week equivalent of the 2016 
maximum weekly benefit of $707 (Rhode Island Department of Labor and 
Training 2016).
---------------------------------------------------------------------------
    We also obtain records of all debits and credits to SNAP Electronic 
Benefit Transfer (EBT) cards for the period September 2012 through 
October 2015. From these we identify all household-months in which the 
household received a SNAP benefit and all household-months in which the 
household spent SNAP benefits at a large, anonymous retailer in Rhode 
Island (``Rhode Island Retailer'') chosen to be similar to the retailer 
that provided our retail panel. Although these data can be linked to 
the SNAP records using a household identifier, we do not exploit that 
link in the analysis that follows.
2.2  Changes in Household Circumstances Around SNAP Adoption
    Household income and household size are major determinants of SNAP 
eligibility (FNS 2016b). We therefore hypothesize that entry into SNAP 
is associated with a decline in household income and a rise in 
household size. Figure 1 shows that this hypothesis is confirmed in our 
administrative data. The figure shows panel event-study plots of 
household income and number of children as a function of time relative 
to SNAP adoption, which we define to occur on the first quarter or 
month, respectively, of a household's first SNAP spell. In the period 
of SNAP adoption, household income declines and the number of children 
rises, on average.
    Past research shows that greater household size and lower household 
income are associated, respectively, with greater and lower at-home 
food expenditures among the SNAP-recipient population (Castner and 
Mabli 2010).\14\ It is therefore unclear whether these contextual 
factors should contribute a net rise or fall in food expenditures in 
the period of SNAP adoption. Because Figure 1 shows that these factors 
trend substantially in the periods preceding SNAP adoption, we can 
assess their net effect by studying trends in spending prior to 
adoption.
---------------------------------------------------------------------------
    \14\ Past research also finds that unemployment--a likely cause of 
the decline in income associated with SNAP adoption--is associated with 
a small decline in spending on food for home consumption. Using cross-
sectional variation in the Continuing Survey of Food Intake by 
Individuals, Aguiar and Hurst (2005) estimate that unemployment is 
associated with nine percent lower at-home food expenditure. Using 
pseudo-panel variation in the Family Expenditure Survey, Banks, et al. 
(1998) estimate that unemployment is associated with a 7.6 percent 
decline in the sum of food consumed in the home and domestic energy. 
Using panel variation in the Panel Study of Income Dynamics, Gough 
(2013) estimates that unemployment is associated with a statistically 
insignificant one to four percent decline in at-home food expenditure. 
Using panel variation in checking account records, Ganong and Noel 
(2016) estimate that the onset of unemployment is associated with a 3.1 
percent decline in at-home food expenditure. Aggregate data seem to 
confirm these findings: real average annual at-home food expenditure 
fell by 1.6 percent from 2006 to 2009, during which time the 
unemployment rate more than doubled (Kumcu and Kaufman 2011).
---------------------------------------------------------------------------
    Figure 1 therefore motivates our panel event-study research design, 
in which we use trends in spending prior to SNAP adoption to diagnose 
the direction and plausible magnitude of confounds.
2.3  Length of SNAP Spells and the Certification Process
    When a state agency determines that a household is eligible for 
SNAP, the agency sets a certification period at the end of which 
benefits will terminate if the household has not documented continued 
eligibility.\15\ The certification period may not exceed 24 months for 
households whose adult members are elderly or disabled, and may not 
exceed 12 months otherwise (FNS 2014). In practice, households are 
frequently certified for exactly these lengths of time, or for other 
lengths divisible by 6 months (Mills, et al., 2014).
---------------------------------------------------------------------------
    \15\ Federal rules state that ``the household's certification 
period must not exceed the period of time during which the household's 
circumstances (e.g., income, household composition, and residency) are 
expected to remain stable'' (FNS 2014).
---------------------------------------------------------------------------
    Figure 2 shows the distribution of SNAP spell lengths in Rhode 
Island administrative data. The figure shows clear spikes in the 
density at spell lengths divisible by 6 months.
    Figure 2 motivates our instrumental variables research design, 
which exploits the 6 month divisibility of certification periods as a 
source of plausibly exogenous timing of program exit.
2.4 Legislated Changes in SNAP Benefit Schedules
    Appendix Figure 1 shows the average monthly SNAP benefit per U.S. 
household from February 2006 to December 2012, which coincides with the 
time frame of our retail panel. The series exhibits two discrete jumps, 
which correspond to two legislated changes in the benefit schedule: an 
increase in October 2008 due to the 2008 Farm Bill and an increase in 
April 2009 due to the American Recovery and Reinvestment Act.
    Appendix Figure 1 motivates our differences-in-differences research 
design, which exploits these legislated benefit increases.
2.5  Inferring SNAP Adoption from Single-Retailer Data
    Households can spend SNAP at any authorized retailer. We will 
conduct our analysis of food spending using data from a single retail 
chain. Changes in a household's choice of retailer could be mistaken 
for program entry and exit in single-retailer data. We use our EBT 
panel to evaluate the importance of these mistakes and to determine how 
best to infer program transitions in single-retailer data.
    For each K . 1,-,12  and for each household in our EBT panel, we 
identify all cases of K consecutive months without SNAP spending at the 
Rhode Island Retailer followed by K consecutive months with SNAP 
spending at the Rhode Island Retailer. We then compute the share of 
these transition periods in which the household newly enrolled in SNAP 
within 2 months of the start of SNAP spending at the retailer, where we 
define new enrollment as receipt of at least $10 in SNAP benefits 
following a period of at least 3 consecutive months with no benefit.
    Figure 3 plots the share of households newly enrolling in SNAP as a 
function of the radius K of the transition period. For low values of K, 
many transitions reflect retailer-switching rather than new enrollments 
in SNAP. The fraction of transitions that represent new enrollments 
increases with K. For K = 6 and above, the fraction constituting new 
enrollments is over 86 percent. When we focus on households who do the 
majority of their SNAP spending at the retailer in question--arguably a 
sample more comparable to the households in our retail panel--this 
fraction rises to 96 percent.
    Figure 3 motivates our definition of SNAP adoption in the retailer 
data.
2.6  SNAP Participation and Choice of Retailer
    Even if we isolate suitably exogenous changes in SNAP participation 
and benefits, our analysis of single-retailer data could be misleading 
if SNAP participation directly affects retail choice.
    Ver Ploeg, et al. (2015) study the types of stores at which SNAP 
recipients shop using nationally representative survey data collected 
from April 2012 through January 2013. For 46 percent of SNAP 
recipients, the primary grocery retailer is a supercenter, for 43 
percent it is a supermarket, for three percent it is another kind of 
store, and for eight percent it is unknown. The corresponding values 
for all U.S. households are 45 percent, 44 percent, four percent, and 
seven percent. As with primary stores, the distribution of alternate 
store types is nearly identical between SNAP recipients and the 
population as a whole. SNAP recipients' choice of store type is also 
nearly identical to that of low-income non-recipients. While this 
evidence does not speak directly to the causal effect of SNAP on choice 
of store type, it seems to cast doubt on the hypothesis that SNAP 
receipt per se is a major factor determining where households shop.
    As further evidence, a companion note to this paper analyzes 
Nielsen Homescan data and finds little relationship at the state-year 
level between changes in the market shares of major retailers and 
changes in the number of SNAP recipients in the state.
    In the next section we present further evidence on retailer 
substitution using survey data collected by the retailer that supplied 
our panel.
3  Retailer Data and Definitions
3.1  Purchases and Demographics
    We obtained anonymized transaction-level data from a large U.S. 
grocery retailer with gasoline stations on site. The data comprise all 
purchases in five states made using loyalty cards by households who 
shop at one of the retailer's stores at least every other month. We 
observe 6.02 billion purchases made on 608 million purchase occasions 
by 486,570 households from February 2006 through December 2012. We 
exclude from our analysis the 1,214 households who spend more than 
$5,000 in a single month.
    For each household, we observe demographic characteristics 
including age, household composition, and ZIP [C]ode. We use these data 
in robustness checks and to study heterogeneity in our estimates.
    For each item purchased, we observe the quantity, the pre-tax 
amount paid, a flag for the use of WIC, and the dollar amount of 
coupons or other discounts applied to the purchase. For each purchase 
occasion, we observe the date, a store identifier, and a classification 
of the store into a retailer division, a grouping based on the store's 
brand and distribution geography. We also observe the main payment 
method used for the purchase, defined as the payment method (e.g., 
cash, check, government benefit) accounting for the greatest share of 
expenditure. For purchase occasions in March 2009 and later, we 
additionally observe the exact breakdown of spending by payment method.
    We classify a purchase occasion as a SNAP purchase occasion if the 
main payment method is a government benefit and WIC is not used. Using 
the detailed payment data for purchase occasions in March 2009 and 
later, we calculate that SNAP is used in only 0.23 percent of the 
purchase occasions that we do not classify as SNAP purchase occasions. 
The appendix table shows that our key results are not sensitive to 
excluding WIC users from the sample.
    We define a SNAP month as any household-month with positive total 
spending across SNAP purchase occasions.\16\ Of the household-months in 
our panel, 7.8 percent are SNAP months. Of the households in our panel, 
43 percent experience at least 1 SNAP month.
---------------------------------------------------------------------------
    \16\ Using our detailed payment data for March 2009 and later, we 
can alternatively define a SNAP month as any month in which a household 
uses SNAP. This definition agrees with our principal definition in all 
but 0.27 percent of household-months.
---------------------------------------------------------------------------
3.2  Product Characteristics
    The retailer provided us with data on the characteristics of each 
product purchased, including an indicator for whether the product is 
store-brand, a text description of the product, and the product's 
location within a taxonomy.
    We classify products as SNAP-eligible or SNAP-ineligible based on 
the retailer's taxonomy and the guidelines for eligibility published on 
the USDA website.\17\ Among all non-fuel purchases in our data, 71 
percent of spending goes to SNAP-eligible products, 25 percent goes to 
SNAP-ineligible products, and the remainder goes to products that we 
cannot classify.
---------------------------------------------------------------------------
    \17\ Grocery and prepared food items intended for home consumption 
are generally SNAP-eligible (FNS 2017). Alcohol, tobacco, pet food, and 
prepared food intended for on-premise consumption are SNAP-ineligible 
(FNS 2017).
---------------------------------------------------------------------------
    We use our detailed payment data for purchases made in SNAP months 
in March 2009 or later to validate our product eligibility 
classification. Among all purchases made at least partly with SNAP in 
which we classify all products as eligible or ineligible, in 98.6 
percent of cases the expenditure share of SNAP-eligible products is at 
least as large as the expenditure share paid with SNAP. Among purchases 
made entirely with SNAP, in 98.7 percent of cases we classify no items 
as SNAP-ineligible. Among purchases in which all items are classified 
as SNAP-ineligible, in more than 99.9 percent of cases SNAP is not used 
as a payment method.
3.3  Shopping Effort
    For each household and month we compute the store-brand share of 
expenditures and the share of items for which coupons are redeemed for 
both SNAP-eligible and SNAP-ineligible purchases. Prior evidence 
suggests that both of these can serve as a proxy for households' 
efforts to save money.\18\ We adjust these measures for the composition 
of purchases as follows. For each item purchased, we compute the store-
brand share of expenditure among other households buying an item in the 
same product category in the same retailer division and the same 
calendar month and week. The expenditure-weighted average of this 
measure across purchases by a given household in a given month is the 
predicted store-brand share, i.e., the share of expenditures that would 
be store-brand if the household acted like others in the panel who buy 
the same types of goods. Likewise, we compute the share of other 
households buying the same item in the same retailer division, month, 
and week who redeem coupons, and compute the average of this measure 
across purchases by a given household in a given month to form a 
predicted coupon use. We subtract the predicted from the actual value 
of each shopping effort measure to form measures of adjusted store-
brand share and adjusted coupon redemption share.
---------------------------------------------------------------------------
    \18\ Store-brand items tend to be less expensive than national-
brand alternatives, and correspondingly are more popular among lower-
income households (Bronnenberg, et al., 2015). Coupon use rose during 
the Great Recession, reflecting households' greater willingness to 
trade time for money (Nevo and Wong 2015).
---------------------------------------------------------------------------
3.4  Monthly Spending and Benefits
    For each household in our panel we calculate total monthly spending 
on SNAP-eligible items, fuel, and SNAP-ineligible items excluding fuel. 
We calculate each household's total monthly SNAP benefits as the 
household's total spending across all SNAP purchase occasions within 
the month.\19\
---------------------------------------------------------------------------
    \19\ Our concept of total SNAP benefits has a correlation of 0.98 
with the exact amount of SNAP spending calculated using detailed 
payment information in SNAP months March 2009 and later.
---------------------------------------------------------------------------
    Our data corroborate prior evidence (e.g., Hoynes, et al., 2015) 
that, for most households, SNAP benefits do not cover all SNAP-eligible 
spending. For 93 percent of households who ever use SNAP, average SNAP-
eligible spending in non-SNAP months exceeds average SNAP benefits in 
SNAP months. SNAP-eligible spending exceeds SNAP benefits by at least 
$10 in 93 percent of SNAP months and by at least five percent in 92 
percent of SNAP months. The appendix table reports estimates of key 
parameters for the subset of households for whom, according to various 
definitions, SNAP benefits are inframarginal to total food spending.
3.5  SNAP Adoption
    Motivated by the analysis in section 2.5, we define a SNAP adoption 
as a period of 6 or more consecutive non-SNAP months followed by a 
period of 6 or more consecutive SNAP months. We refer to the first SNAP 
month in an adoption as an adoption month. We define a SNAP adopter as 
a household with at least one SNAP adoption. Our panel contains a total 
of 24,456 SNAP adopters.
    Panel A of Figure 4 shows the share of SNAP adopters with positive 
SNAP spending in each of the 12 months before and after a household's 
first SNAP adoption. Panel B of Figure 4 shows average SNAP benefits 
before and after adoption. Following adoption, the average household 
receives about $200 in monthly SNAP benefits. For comparison, the 
average U.S. SNAP benefit per household in fiscal 2009, roughly at the 
midpoint of our sample period, was $276 (FNS 2016a).
    We conduct the bulk of our analysis using the sample of SNAP 
adopters. The appendix tablepresents our key results for alternative 
samples.
3.6  Retailer Share of Wallet
    Spending patterns suggest that panelists buy a large fraction of 
their groceries at the retailer. Mabli and Malsberger (2013) estimate 
average 2010 spending on food at home by SNAP recipients of $380 per 
month using data from the Consumer Expenditure Survey. Hoynes et al. 
(2015) find that average per-household food expenditures are 20 to 25 
percent lower in the Consumer Expenditure Survey than in the 
corresponding aggregates from the National Income and Product Accounts. 
In the 6 months following a SNAP adoption, average monthly SNAP-
eligible spending in our data is $469.
    Panelists also seem to buy a large fraction of their gasoline at 
the retailer: average monthly fuel spending at the retailer is $97 in 
the 6 months following SNAP adoption, as compared to Mabli and 
Malsberger's (2013) estimate of $115.
    Survey data from the retailer suggest that SNAP use is associated 
with a reduction in the retailer's share of overall category spending. 
During the period June 2009 to December 2011, the retailer conducted an 
online survey on a convenience sample of customers. The survey asked:

          About what percentage of your total overall expenses for 
        groceries, household supplies, or personal care items do you, 
        yourself, spend in the following stores?

Respondents were presented with a list of retail chains including the 
one from which we obtained our data. Excluding responses in which the 
reported percentages do not sum to 100, we observe at least one 
response from 961 of the households in our panel. Among survey 
respondents that ever use SNAP, the average reported share of wallet 
for the retailer is 0.61 for those surveyed during non-SNAP months (N = 
311 survey responses) and 0.53 for those surveyed during SNAP months (N 
= 80 survey responses).\20\ The same qualitative pattern obtains among 
SNAP adopters, and in responses to a retrospective question about 
shopping frequency.\21\
---------------------------------------------------------------------------
    \20\ The difference in means is statistically significant (t = 
2.15, p = 0.032).
    \21\ The question asks, ``In your opinion, do you think you, 
yourself have been shopping more, less, or about the same amount at the 
retailer over the past 3 months?'' Among households surveyed in a SNAP 
month, 60 percent report that their frequency of shopping at the 
retailer has stayed ``about the same.'' Among those saying that it has 
not stayed the same, a majority (59 percent) say that it has decreased.
---------------------------------------------------------------------------
    Taken at face value, these findings suggest that retailer 
substitution will tend, if anything, to bias downward the estimated 
effect of SNAP participation on food spending. In the appendix table we 
verify that our results are robust to restricting attention to 
households with relatively few supermarkets in their county, for whom 
opportunities to substitute across retailers are presumably more 
limited.
4  Descriptive Evidence
4.1  Marginal Propensity To Consume Out of SNAP Benefits
    Figure 5 shows the evolution of monthly spending before and after 
SNAP adoption for our sample of SNAP adopters. Each plot shows 
coefficients from a regression of spending on a vector of indicators 
for months relative to the household's first SNAP adoption. Panel A 
shows that SNAP-eligible spending increases by approximately $110 in 
the first few months following SNAP adoption. Recall from Figure 4 that 
the average household receives monthly SNAP benefits of approximately 
$200 following SNAP adoption. Taking the ratio of the increase in 
spending to the benefit amount, we estimate an MPCF out of SNAP 
benefits between 0.5 and 0.6.
    Panel B shows that SNAP-ineligible spending increases by 
approximately $5 following SNAP adoption, implying an MPC of a few 
percentage points. The increase in SNAP-ineligible spending is smaller 
in both absolute and proportional terms than the increase in SNAP-
eligible spending. The online appendix shows directly that the share of 
spending devoted to SNAP-eligible items increases significantly 
following SNAP adoption. This finding is not consistent with the 
hypothesis that SNAP leads to a proportional increase in spending 
across all categories due to substitution away from competing 
retailers.
    Following the analysis in section 2.2, trends in spending prior to 
adoption should provide a sense of the influence of changes in 
contextual factors on spending. Panel A shows very little trend in 
SNAP-eligible spending prior to SNAP adoption. Panel B shows, if 
anything, a slight decline in SNAP-ineligible spending prior to 
adoption, perhaps due to economic hardship. Neither of these patterns 
seems consistent with the hypothesis that the large increase in SNAP-
eligible spending that occurs at SNAP adoption is driven by changes in 
contextual factors.
    Figure 6 shows the evolution of monthly spending during a monthly 
clock that begins at SNAP adoption and resets every 6 months. Panels A 
and B show that SNAP participation and benefits fall especially quickly 
in the first month of the clock, consistent with the finding in section 
2.3 that SNAP spell lengths tend to be divisible by 6 months. 
Participation and benefits also fall more quickly in the sixth month, 
perhaps reflecting error in our classification of adoption dates.
    Panel C of Figure 6 shows that the pattern of SNAP-eligible 
spending closely follows that of SNAP benefits. Benefits decline by 
about $12 more in the first month of the cycle than in the second. 
Correspondingly, SNAP-eligible spending declines by $6 to $7 more in 
the first month than in the second. Taking the ratio of these two 
values implies an MPCF out of SNAP benefits between 0.5 and 0.6, 
consistent with the evidence in Figure 5.
    Appendix Figure 2 plots the evolution of SNAP-eligible spending 
around the legislated benefit changes described in section 2.4. The 
plot shows that likely SNAP recipients' SNAP-eligible spending 
increases relative to that of likely non-recipients around the periods 
of benefit increases. The online appendix reports the results of a 
differences-in-differences analysis of these changes in the spirit of 
Bruich (2014) and Beatty and Tuttle (2015). We estimate an MPCF out of 
SNAP benefits of 0.53, and if anything a negative effect of benefit 
expansions on SNAP-ineligible spending.
4.2  Marginal Propensity To Consume Out of Cash
    Two pieces of indirect evidence suggest that an MPCF out of SNAP of 
0.5 to 0.6 is too large to be consistent with households treating SNAP 
benefits as fungible with other income.
    The first is that, for the average SNAP recipient, food at home 
represents only 22 percent of total expenditure (Castner and Mabli 
2010). Engel's Law (Engel 1857; Houthakker 1957) holds that the budget 
share of food declines with total resources, and hence that the budget 
share exceeds the MPCF. Engel's Law is not consistent with a budget 
share of 0.22 and an MPCF of 0.5 to 0.6.
    The second is that prior estimates of the MPCF out of cash for low-
income populations are far below 0.5. Castner and Mabli (2010) estimate 
an MPCF of 0.07 for SNAP recipients. Hoynes and Schanzenbach (2009) 
estimate an MPCF of 0.09-0.10 for populations with a high likelihood of 
entering the Food Stamp Program. Assessing the literature, Hoynes and 
Schanzenbach (2009) note that across ``a wide range of data (cross 
sectional, time series) and econometric methods'' past estimates of the 
MPCF out of cash income are in a ``quite tight'' range from 0.03 to 
0.17 for low-income populations.
    For more direct evidence, we study the effect on spending of the 
large changes in gasoline prices during our sample period. These 
changes affect the disposable income available to households and 
therefore give us a window into the MPCF out of cash income.
    Panel A of Figure 7 shows the time-series relationship between 
gasoline prices and fuel expenditure for SNAP adopters at different 
quartiles of the distribution of average fuel expenditure. Those 
households in the upper quartiles exhibit substantial changes in fuel 
expenditure when the price of gasoline changes. For example, during the 
run-up in fuel prices in 2007, part of an upward trend often attributed 
to increasing demand for oil from Asian countries (e.g., Kilian 2010), 
households in the top quartile of fuel spending increased their 
spending on fuel by almost $100 per month. Households in lower 
quartiles increased their fuel spending by much less.
    Panel B of Figure 7 shows the time-series relationship between 
gasoline prices and SNAP-eligible expenditure for the same groups of 
households. The relationship between the two series does not appear 
consistent with an MPCF out of cash income of 0.5 to 0.6. For example, 
if the MPCF out of cash income were 0.5 we would expect households in 
the top quartile of fuel spending to decrease SNAP-eligible spending 
significantly during the run-up in fuel prices in 2007. In fact, we see 
no evidence of such a pattern, either looking at the top quartile in 
isolation, or comparing it to the lower quartiles.
    The absence of a strong response of SNAP-eligible spending to fuel 
prices is consistent with prior evidence of a low MPCF out of cash. It 
is not consistent with the hypothesis that changes in income drive 
large changes in the retailer's share of wallet, as such income effects 
would lead to a relationship between gasoline prices and measured SNAP-
eligible spending.
4.3  Quantitative Summary
    Table 1 presents two-stage least squares (2SLS) estimates of a 
series of linear regression models. In each model the dependent 
variable is the change in spending from the preceding month to the 
current month. The endogenous regressors are the change in the SNAP 
benefit and the change in the additive inverse of fuel spending. The 
coefficients on these endogenous regressors can be interpreted as MPCs. 
Each model includes calendar month fixed effects. (Household fixed 
effects are implicit in the first-differencing of the variables in the 
model.)
    All models use the interaction of the change in the price of 
regular gasoline and the household's average monthly number of gallons 
of gasoline purchased as an excluded instrument. This instrument 
permits estimating the MPC out of cash following the logic of Figure 7.
    Models (1), (2), and (3) of Table 1 all use the change in SNAP-
eligible spending as the dependent variable. The models differ in the 
choice of excluded instruments for SNAP benefits. In model (1), the 
instrument is an indicator for whether the month is an adoption month. 
In model (2), it is an indicator for whether the month is the first 
month of the 6 month SNAP clock. These instruments permit estimating 
the MPCF out of SNAP following the logic of Figures 5 and 6, 
respectively. In model (3), both of these instruments are used.
    Estimates of models (1), (2), and (3) indicate an MPCF out of SNAP 
between 0.55 and 0.59 and an MPCF out of cash close to 0. In model (3), 
confidence intervals exclude an MPCF out of SNAP below 0.57 and an MPCF 
out of cash above 0.1. In all cases, we reject the null hypothesis that 
the MPCF out of SNAP is equal to the MPCF out of cash.
    Model (4) parallels model (3) but uses SNAP-ineligible spending as 
the dependent variable. We estimate an MPC out of SNAP of 0.02 and an 
MPC out of cash of 0.04. We cannot reject the hypothesis that these two 
MPCs are equal.
    The appendix table shows that the conclusion that the MPCF out of 
SNAP exceeds the MPCF out of cash holds when we exclude households for 
whom SNAP benefits may not be economically equivalent to cash, and 
restrict to single-adult households to limit the role of intra-
household bargaining.
    The online appendix reports that the implied MPCF out of SNAP is 
slightly higher in the household's first SNAP adoption than in 
subsequent SNAP adoptions. We cannot reject the hypothesis that the 
MPCF is equal between first and subsequent adoptions. The online 
appendix also reports estimates of the MPCF out of SNAP and cash for 
various demographic groups.
5  Model and Tests for Fungibility
5.1  Model
    In each month t . 1,-,T , household i receives SNAP benefits 
bit % 0 and disposable cashincome yit > 0. The 
household chooses food expenditure fit and nonfood expenditure nit to 
solve
(1)


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where jit is a preference shock and Ui () is a 
utility function strictly increasing in  and n. The variables 
(bit,yit, xit) are random with support 
Vi.
    Assumption 1. For each household i, optimal food spending can be 
written as
(2)



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where fi () is a function with range [0,yit + 
bit].
    A sufficient condition for assumption 1 is that, for each household 
i, at any point (b,y,j) . Vi the function Ui 
( ,y+b^;j) is smooth and strictly concave in 
 and has a stationary point * > b. Then 
optimal food spending exceeds the level of SNAP benefits even if 
benefits are disbursed as cash, so the ``kinked'' budget constraint in 
(1) does not affect the choice of fit.
    For each household and month, an econometrician observes data 
(it,bit,yit,zit) 
where zit is a vector of instruments. A concern is that 
xit is determined partly by contextual factors such as job 
loss that directly affect yit and bit.
    Assumption 2. Let nit = 
(yit+bit)^E(yit+bit D 
zit). For each household i, the instruments zit 
satisfy
(3)



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    Proposition 1. Under assumptions 1 and 2, for each household i
(4)



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for some function qi ().
    Proof. Let Pi denote the CDF of 
(jit,vit). Then




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where the first equality follows from assumption 1 and the second from 
assumption 2. See Blundell and Powell (2003, p. 330).
    Example. (Cobb-Douglas) Suppose that for each household i there is 
bi . (0,1) such that:
(5)





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with bi (y+b)+j > b and (1^bi) (y+b) > j at all 
points in Vi. Then assumption 1 holds with
(6)


and, under assumption 2, proposition 1 applies with
(7)




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for ai 6 E(jit).
    Remark 1. In his study of a child tax credit in the Netherlands, 
Kooreman (2000) assumes a version of (6), which he estimates via 
ordinary least squares using cross-sectional data under various 
restrictions on ai, bi, and jit.
5.2  Testing for Fungibility
    Index a family of perturbations to the model by g. Let 
git be food spending under perturbation g, with
(8)




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for i () the function defined in assumption 1. We 
may think of g as the excess sensitivity of food spending to SNAP 
benefits. The null hypothesis that the model holds is equivalent under 
(8) to g = 0.
    Let Yit = E(yit + 
bitDzit) and Bit = 
E(bitDzit) and observe that
(9)



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where E(eitDYit,Bit) = 0. The nuisance 
terms qi () have been ``partialled out'' of (9) as in 
Robinson (1988). The target g can be estimated via OLS regression of 
(git ^ E 
(gitDYit)) on (Bit ^E 
(BitDYit)).
    Remark 2. It is possible to allow for measurement error in 
it that depends on 
(yit+bit). Say that for known function m(), 
unobserved measurement error hit independent of 
zit, and unknown function lit () we have that 
measured food spending fit follows
(10)



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Then under perturbations m((git) = 
m(it) + gbit an analogue of (9) holds, 
replacing git with m(git). 
Examples include additive measurement error, where m() is the identity 
function, and multiplicative measurement error, where m() is the 
natural logarithm. The latter case has a simple interpretation as one 
in which the econometrician observes spending at a single retailer 
whose share of total household food spending is given by exp (lit 
(yit+bit,hit)).
    Remark 3. The reasoning above is unchanged if bit and 
yit are each subject to an additive measurement error that 
is mean-independent of zit. In this case, we can simply let 
Yit and Bit represent the conditional 
expectations of the corresponding mismeasured variables.
5.3  Implementation and Results
    With (9) in mind, estimation proceeds in three steps:




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    We let git be SNAP-eligible spending, bit 
be SNAP benefits, and yit be the additive inverse of fuel 
spending. We let the instruments zit be given by the number 
of SNAP adoptions experienced by household i as of calendar month t, 
and the product of the average price of regular gasoline with the 
household's average monthly number of gallons of gasoline purchased.
    In step 1, we estimate (Yit,Bit) via first-
differenced regression of (yit+bit) and bit 
on zit.
    In step 2, we consider four specifications for estimating 
(E(gitDYit) , 
E(BitDYit)). In the first, we estimate these via 
first-differenced regression of git and Bit 
on Yit, pooling across households. In the second, we 
estimate these via first-differenced regression of git 
and Bit on Yit, separately by household. In the 
third, we estimate these via first-differenced regression of 
git and Bit on indicators for the 
quintiles of Yit, separately by household. In the fourth, we 
estimate these via locally weighted polynomial regression of 
git and Bit on Yit, 
separately by household. Thus, the first specification implicitly 
treats qi as linear and homogeneous across households, the 
second treats qi as linear and heterogeneous across 
households, and the third and fourth allow qi to be 
nonlinear and heterogeneous across households.



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    Table 2 presents the results. Across all three specifications, our 
estimates of g are 0.5 or greater, and in all cases we can reject the 
null hypothesis that g = 0 with a high level of confidence.
6  Interpretation
    We speculate that households treat SNAP benefits as part of a 
separate mental account, psychologically earmarked for spending on 
food. In this section we discuss results of qualitative interviews 
conducted at a food pantry in Rhode Island. We then present 
quantitative evidence that we think suggests a mental accounting 
explanation, and present a post-hoc model of mental accounting that 
rationalizes this evidence.
6.1  Qualitative Interviews with SNAP-Recipient Households
    As part of preparation related to a state proposal to pilot a 
change to SNAP benefit distribution, Rhode Island Innovative Policy 
Laboratory staff conducted a series of qualitative interviews at a 
large food pantry in Rhode Island in May, July, and August 2016. 
Interviewees were approached in the waiting room of the pantry and were 
offered a $5 gift card to a grocery retailer in exchange for 
participating. Interviews were conducted in English and Spanish.
    Interviewees were selected from those waiting to be served at the 
food pantry and were not sampled scientifically. Interviews were 
conducted primarily to inform the implementation of the pilot program 
and the responses should not be taken to imply any generalizable 
conclusions. We report them here as context for our quantitative 
evidence.
    Of the 25 interviews conducted, 19 were with current SNAP 
recipients. Of these, all but three reported spending non-SNAP funds on 
groceries each month, with an average out-of-pocket spending of $100 
for those reporting positive out-of-pocket spending.
    Each interviewee was asked the following two questions, which we 
refer to as SNAP and CASH:

          (SNAP) Imagine that in addition your current benefit, you 
        received an extra $100 in SNAP benefits at the beginning of the 
        month. How would this change the way that you spend your money 
        during the month? [emphasis added]
          (CASH) Imagine that you received an additional $100 in cash 
        at the beginning of the month. How would this change the way 
        that you spend your money during the month? [emphasis added]

Of the 16 SNAP-recipient interviewees who report nonzero out-of-pocket 
spending on groceries, 14 chose to answer questions SNAP and CASH.
    Interviewers recorded verbal responses to each question as 
faithfully as possible. The most frequently occurring word in response 
to the SNAP question is ``food,'' which occurs in eight of the 14 
responses. Incorporating mentions of specific foods or food-related 
terms like ``groceries,'' the fraction mentioning food rises to ten out 
of 14 responses. The word ``food'' occurs in three of the 14 responses 
to CASH; more general food related terms occur in five of the 14 
responses to CASH.
    Several responses seem to suggest a difference in how the household 
would spend $100 depending on the form in which it arrives. For 
example, in response to question SNAP one interviewee said ``[I would] 
buy more food.'' In response to CASH the same interviewee said ``[I 
would buy] more household necessities.'' Another interviewee said in 
response to SNAP that ``[I would buy] more food, but the same type of 
expenses. If I bought $10 of sugar, now [I would buy] $20.'' In 
response to CASH, the same interviewee said that ``[I would spend it 
on] toilet paper, soap, and other necessary home stuff, or medicine.'' 
A third interviewee said in response to SNAP that ``I would buy more 
food and other types of food . . .'' and in response to CASH that ``I 
could buy basic things that I can't buy with [SNAP].'' \22\
---------------------------------------------------------------------------
    \22\ The bracketed term is a translation for the Spanish word 
cupones. This word is literally translated as ``coupons'' but is often 
used to refer to SNAP. (See, for example, Project Bread 2016.)
---------------------------------------------------------------------------
    Some responses suggest behavior consistent with inframarginality. 
For example one interviewee's answer to SNAP included the observation 
that ``I would probably spend $100 less out of pocket,'' although this 
interviewee also mentions increasing household expenditures on seafood 
and produce. Another interviewee answered SNAP with ``[I] would spend 
all in food, and also buy soap [and] things for [my] two kids.''
6.2  Quantitative Evidence on Shopping Effort
    If SNAP recipients consider SNAP benefits to be earmarked for food, 
they may view a dollar saved on food as less valuable than a dollar 
saved on non-food purchases. To test this hypothesis, we study the 
effect of SNAP on bargain-seeking behavior.
    Figure 8 shows the evolution of the adjusted store-brand share 
before and after SNAP receipt for our sample of SNAP adopters. Each 
plot shows coefficients from a regression of the adjusted store-brand 
share on a vector of indicators for months relative to SNAP adoption. 
Among SNAP-eligible items, panel A shows a trend towards a greater 
store-brand share prior to SNAP adoption, perhaps reflecting the 
deterioration in households' economic well-being that normally triggers 
entry into a means-tested program. Once households adopt SNAP, there is 
a marked and highly statistically significant drop in the store-brand 
share. Because we have adjusted store-brand share for the composition 
of purchases, this decline is driven not by changes in the categories 
of goods purchased, but by a change in households' choice of brand 
within a category.
    Panel B of Figure 8 shows an analogous plot for SNAP-ineligible 
items. The adjusted storebrand share of SNAP-ineligible expenditure 
rises before SNAP adoption and does not decline significantly following 
adoption. Regression analysis presented in the online appendix shows 
that we can confidently reject the hypothesis that the change in 
adjusted store-brand share at SNAP adoption is equal between SNAP-
eligible and SNAP-ineligible products.
    Figure 9 shows analogous evidence for coupon use. Following SNAP 
adoption, the average adjusted coupon redemption share declines for 
both SNAP-eligible and SNAP-ineligible products, but the decline is 
more economically and statistically significant for SNAP-eligible 
products than for SNAP-ineligible products. Because we have adjusted 
the coupon redemption share for the basket of goods purchased, these 
patterns are not driven by changes in the goods purchased, but rather 
by households' propensity to redeem coupons for a given basket of 
goods. Regression analysis presented in the online appendix shows that 
we can reject the hypothesis that the change in the adjusted coupon 
redemption share at SNAP adoption is equal between SNAP-eligible and 
SNAP-ineligible products.
6.3  Post-Hoc Model of Mental Accounting
    To fix ideas and rationalize the preceding evidence, we specify a 
model of mental accounting based on Farhi and Gabaix (2015). Return to 
the setup of section 5, considering for ease of notation a single 
household and time period, and ignoring the preference shock j. Let 
preferences over food consumption  and non-food consumption n 
be Cobb-Douglas, and suppose that the household can exert effort 
sf % 0 and sn % 0, respectively, to reduce the 
cost of a given unit of consumption in the food and non-food domains, 
respectively. Finally, suppose that the household exhibits a distaste 
for deviating from a psychological default level of food spending, 
determined in part by the earmarking of SNAP benefits. Formally, write 
the household's problem as
(11)



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Here, the function c (), which is smooth and strictly increasing in its 
argument, describes the cost of shopping effort. The function d (), 
which is smooth, strictly decreasing and strictly convex, describes the 
return to shopping effort in terms of prices paid. The parameter k > 0 
indexes the importance of sticking to the household's default plan to 
spend amount b of SNAP benefits and amount by of cash income on food.



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

    In this sense, the model in (11) can rationalize both the tendency 
to consume food out of SNAP in greater proportion than out of cash 
income, and the tendency to reduce bargain-hunting in the food domain 
(relative to the non-food domain) after receipt of SNAP. The model is 
post-hoc in that the specification of the target spending (by + b) is 
arbitrary and does not derive from portable psychological primitives.
7  Conclusions
    We use data from a novel retail panel to study the effect of the 
receipt of SNAP benefits on household spending behavior. Novel 
administrative data motivates three approaches to causal inference. We 
find that the MPCF out of SNAP benefits is 0.5 to 0.6 and larger than 
the MPCF out of cash. We argue that these findings are not consistent 
with households treating SNAP funds as fungible with non-SNAP funds, 
and we support this claim with formal tests of fungibility that allow 
different households to have different consumption functions.
    We speculate that households treat SNAP benefits as part of a 
separate mental account. Responses to hypothetical choice scenarios in 
qualitative interviews suggest that some households plan to spend SNAP 
benefits differently from cash. Quantitative evidence shows that, after 
SNAP receipt, households reduce shopping effort for SNAP-eligible 
products more so than for SNAP-ineligible products. A post-hoc model of 
mental accounting based on Farhi and Gabaix (2015) rationalizes these 
facts.

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Table 1: Estimated Marginal Propensities To Consume



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Table 2: Tests of Fungibility

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Figure 1: Household income and size before and after SNAP adoption
Panel A: Household Income

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Panel B: Number of Children Under Five Years of Age

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          Notes: Data are from Rhode Island administrative records from 
        October 2004 through June 2016. See section 2.1 for details on 
        sample definition and variable construction. Each panel plots 
        coefficients from a regression of the dependent variable on a 
        vector of lead and lagged indicators for periods relative to 
        SNAP adoption, defined as the first period in which the 
        household receives SNAP. The period immediately prior to 
        adoption (``^1'') is the omitted category. Each regression 
        includes time period fixed effects, household fixed effects, 
        and indicators for observations more than 1 year before or 
        after adoption. In panel A, a time period is a calendar quarter 
        and the unit of analysis is a household-quarter. In panel B, a 
        time period is a month and the unit of analysis is the 
        household-month. In both panels, the error bars are R2 
        coefficient standard errors and standard errors are clustered 
        by household. Dotted lines show the sample mean of the 
        dependent variable across observations within 1 year (4 
        quarters or 12 months) of SNAP adoption. Each coefficient 
        series is shifted by a constant so that the observation-count-
        weighted mean of the regression coefficients is equal to the 
        sample mean of the corresponding dependent variable.
Figure 2: Distribution of Lengths of SNAP Spells



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          Notes: Data are from Rhode Island administrative records from 
        October 2004 through June 2016. See section 2.1 for details on 
        sample definition and variable construction. The plot shows a 
        histogram of the distribution of SNAP spell lengths, where a 
        spell is defined as a set of consecutive months in which the 
        household is entitled to a SNAP benefit in each month according 
        to state program records. Spells longer than 36 months are 
        excluded from the sample.
Figure 3: Inferring SNAP Adoption from Single-Retailer Data



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          Notes: Data are from Rhode Island EBT transaction records 
        from September 2012 through October 2015. See section 2.1 for 
        details on sample definition and variable construction. The 
        figure plots the fraction of transition periods of a given 
        radius in which the household newly enrolled in SNAP within 2 
        months of the start of SNAP spending at the Rhode Island 
        Retailer. We define new enrollment as the receipt of at least 
        $10 in SNAP benefits following a period of at least 3 
        consecutive months with no benefit. A transition period of 
        radius K is a period in which a household exhibits K 
        consecutive months without SNAP spending at the Rhode Island 
        Retailer followed by K consecutive months with SNAP spending at 
        the Rhode Island Retailer. Households who mainly spend SNAP at 
        the Rhode Island Retailer are those who spend at least \1/2\ of 
        their total EBT expenditures between September 2012 and October 
        2015 at the Rhode Island Retailer.
Figure 4: SNAP Use and Benefits Before and After SNAP Adoption
Panel A: SNAP Use
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Panel B: SNAP Benefits
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          Notes: The sample is the set of SNAP adopters. Panel A plots 
        the share of households with positive SNAP spending in each of 
        the 12 months before and after the household's first SNAP 
        adoption. Panel B plots the average SNAP benefit in each of the 
        12 months before and after the first SNAP adoption.
Figure 5: Monthly Expenditure Before and After SNAP Adoption, By SNAP 
        Eligibility of Product
Panel A: SNAP-Eligible Spending
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Panel B: SNAP-Ineligible Spending
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          Notes: Each figure plots coefficients from a regression of 
        SNAP-eligible or SNAP-ineligible spending on a vector of lead 
        and lagged indicators for month relative to the household's 
        first SNAP adoption, with the month prior to SNAP adoption 
        (``^1'') as the omitted category. The unit of observation for 
        each regression is the household-month. Error bars are R2 
        coefficient standard errors. Standard errors are clustered by 
        household. Each regression includes calendar month fixed 
        effects, household fixed effects, and two indicators for 
        observations before and after 12 months of SNAP adoption. The 
        dotted lines show the sample mean of household monthly 
        expenditure across observations within 12 months of SNAP 
        adoption. Each coefficient series is shifted by a constant so 
        that the observation-count-weighted mean of the regression 
        coefficients is equal to the sample mean of the corresponding 
        dependent variable.
Figure 6: Participation, Benefits, and Spending Over the 6 Month SNAP 
        Clock
Panel A: SNAP Use
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Panel B: SNAP Benefits
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Panel C: SNAP-Eligible Spending
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          Notes: Each figure plots coefficients from a regression of 
        the dependent variable on a vector of indicators for the 
        position of the current month in a monthly clock that begins in 
        the most recent adoption month and resets every 6 months or at 
        the next SNAP adoption, whichever comes first. The unit of 
        observation for each regression is the household-month. The 
        sample is the set of SNAP adopters. Error bars are R2 
        coefficient standard errors. Standard errors are clustered by 
        household. Each regression includes calendar month fixed 
        effects. The omitted category consists of the first 6 months 
        (inclusive of the adoption month) after the household's most 
        recent SNAP adoption, all months after the first 24 months 
        (inclusive of the adoption month) following the household's 
        most recent adoption, and all months for which there is no 
        preceding adoption. In Panel A, the dependent variable is the 
        change in an indicator for whether the household-month is a 
        SNAP month. In Panel B, the dependent variable is the change in 
        monthly SNAP benefits. In Panel C, the dependent variable is 
        the change in monthly SNAP-eligible spending.
Figure 7: Monthly Expenditure and the Price of Gasoline
Panel A: Fuel Spending
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Panel B: SNAP-Eligible Spending
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          Notes: Panel A plots average monthly fuel spending by 
        quartile of average monthly fuel spending. Panel B plots 
        average monthly SNAP-eligible spending by quartile of average 
        monthly fuel spending. The unit of observation is the 
        household-month and the sample is the set of SNAP adopters who 
        ever purchase fuel. The lower portion of both plots shows the 
        price of gasoline, computed as the quantity-weighted average 
        spending per gallon on regular grade gasoline among all 
        households before any discounts or coupons.
Figure 8: Store-Brand Share Before and After SNAP Adoption, By SNAP 
        Eligibility of product
Panel A: SNAP-Eligible Products
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Panel B: SNAP-Ineligible Products
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Notes: Each figure plots coefficients from a regression of 
        adjusted store-brand share of expenditures on a vector of lead 
        and lagged indicators for month relative to the household's 
        first SNAP adoption, with the month prior to SNAP adoption 
        (``^1'') as the omitted category. The unit of observation for 
        each regression is the household-month. Error bars are R2 
        coefficient standard errors. Standard errors are clustered by 
        household. Each regression includes calendar month fixed 
        effects, household fixed effects, and two indicators for 
        observations before and after 12 months of SNAP adoption. The 
        dotted line shows the sample mean of the store-brand share of 
        expenditure across observations within 12 months of SNAP 
        adoption. Each coefficient series is shifted by a constant so 
        that the observation-count-weighted mean of the regression 
        coefficients is equal to the sample mean of the store-brand 
        share of expenditure in the given SNAP eligibility group.
Figure 9: Coupon Use Before and After SNAP Adoption, By SNAP 
        Eligibility of Product
Panel A: SNAP-Eligible Products
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

Panel B: SNAP-ineligible products
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Notes: Each figure plots coefficients from a regression of 
        the adjusted coupon redemption share on a vector of lead and 
        lagged indicators for month relative to the household's first 
        SNAP adoption, with the month prior to SNAP adoption (``^1'') 
        as the omitted category. The unit of observation for each 
        regression is the household-month. Error bars are R2 
        coefficient standard errors. Standard errors are clustered by 
        household. Each regression includes calendar month fixed 
        effects, household fixed effects, and two indicators for 
        observations before and after 12 months of SNAP adoption. The 
        dotted line shows the sample mean of the share of purchases 
        using a coupon across observations within 12 months of SNAP 
        adoption. Each coefficient series is shifted by a constant so 
        that the observation-count-weighted mean of the regression 
        coefficients is equal to the sample mean of the share of 
        purchases using a coupon in the given SNAP eligibility group.
Appendix Table: Results for Alternative Samples and Specifications
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Appendix Figure 1: Legislated Changes in SNAP Benefits
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Notes: This figure plots the average monthly SNAP benefit per 
        U.S. household between February 2006 and December 2012. The 
        series was obtained directly from the United States Department 
        of Agriculture Food and Nutrition Service via http://
        www.fns.usda.gov/sites/default/files/pd/
        SNAPZip69throughCurrent.zip. The vertical lines at October 2008 
        and April 2009 denote the implementation dates of changes in 
        SNAP benefits due to the farm bill and American Recovery and 
        Reinvestment Act (ARRA), respectively.
Appendix Figure 2: Monthly SNAP Benefits and SNAP-Eligible Spending 
        Around Benefit Changes
        [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
        
          Notes: The sample includes all households in the retailer 
        panel that have at least 2 consecutive SNAP months during the 
        panel. The figure plots coefficients from a regression of SNAP 
        benefits and SNAP-eligible spending on interactions between the 
        share of calendar months between February 2006 and December 
        2007 during which each household used SNAP and calendar month 
        indicators, with the January 2008 interaction normalized to 
        zero. The unit of observation is the household-month and only 
        months from January 2008 to December 2009 are included in the 
        regression. Error bars and shaded region represent R2 
        coefficient standard errors. Standard errors are clustered by 
        household. Each regression includes household and calendar 
        month fixed effects. Each coefficient series is seasonally 
        adjusted by subtracting from each coefficient the corresponding 
        coefficient from an auxiliary regression of the dependent 
        variable on interactions between the share of months between 
        February 2006 and December 2007 during which each household 
        used SNAP and year and seasonal month indicators. The auxiliary 
        regressions include household, year, and seasonal month fixed 
        effects and are estimated using only data from January 2010 to 
        December 2012. Each coefficient series is shifted by a constant 
        so that the observation-count-weighted mean of the regression 
        coefficients is equal to the sample mean of the corresponding 
        dependent variable among households who used SNAP in every 
        month between February 2006 and December 2007. Vertical lines 
        at October 2008 and April 2009 denote the implementation dates 
        of changes in SNAP benefits due to the farm bill and American 
        Recovery and Reinvestment Act (ARRA), respectively.
                               Exhibit 2
Incentivizing Nutritious Diets: A Field Experiment of Relative Price 
        Changes and How They Are Framed
John Cawley, Andrew S. Hanks, David R. Just, Brian Wansink
Working Paper 21929
http://www.nber.org/papers/w21929

    We gratefully acknowledge financial support from the National 
Institutes of Health (NIH) grant 1RC1HD063370-01. The NIH played no 
other role in the conduct of the study. Cawley gratefully acknowledges 
support from an Investigator Award in Health Policy Research from the 
Robert Wood Johnson Foundation. The Cornell University Institutional 
Review Board approved the design of this study (Protocol 
ID#1110002491). For helpful comments and suggestions, we thank Heather 
Royer and participants at the American Society of Health Economists 
biennial conference, the NBER Summer Institute, the International 
Health Economics Association conference, the TIGER conference in 
Toulouse France, and seminar participants at the Indiana University, 
McGill University, University of Oxford, the University of 
Pennsylvania, and the University of Sydney. The views expressed herein 
are those of the authors and do not necessarily reflect the views of 
the National Bureau of Economic Research.
    At least one co-author has disclosed a financial relationship of 
potential relevance for this research. Further information is available 
online at http://www.nber.org/papers/w21929.ack.
    NBER working papers are circulated for discussion and comment 
purposes. They have not been peer-reviewed or been subject to the 
review by the NBER Board of Directors that accompanies official NBER 
publications.
    2016 by John Cawley, Andrew S. Hanks, David R. Just, and Brian 
Wansink. All rights reserved. Short sections of text, not to exceed two 
paragraphs, may be quoted without explicit permission provided that 
full credit, including  notice, is given to the source.
Abstract
    This paper examines how consumers respond to price incentives for 
nutritious relative to less-nutritious foods, and whether the framing 
of the price incentive as a subsidy for nutritious food or a tax on 
non-nutritious food influences consumers' responses. Analyzing 
transaction data from an 8 month randomized controlled field experiment 
involving 208 households, we find that a 10% relative price difference 
between nutritious and less nutritious food does not significantly 
affect overall purchases, although low-income households respond to the 
subsidy frame by buying more of both nutritious and less-nutritious 
food.

 
 
 
John Cawley,                         David R. Just,
2312 MVR Hall,                       Cornell University,
Department of Policy Analysis and    210C Warren Hall,
 Management and Department of        Ithaca, NY 14850,
 Economics,
Cornell University,                  [email protected];
Ithaca, NY 14853,
and NBER,
[email protected];
Andrew S. Hanks                      Brian Wansink,
Ohio State University                Cornell University,
130A Campbell Hall                   475H Warren Hall,
1787 Neil Ave.                       Ithaca, NY 14850,
Columbus, OH 43210                   [email protected].
[email protected];
 

Introduction
    Diet-related chronic disease is a global problem. Worldwide, the 
annual deaths due to high blood pressure total 7.5 million, high blood 
glucose (diabetes) 3.4 million, overweight and obesity 2.8 million, and 
high cholesterol 2.6 million (WHO, 2009). In the U.S., 37% of the adult 
population has cardiovascular disease, 16% has high total blood 
cholesterol, 34% has hypertension, 11% has diabetes, and it is 
estimated that 41% will be diagnosed with some form of cancer during 
their lifetime (USDA, 2010). Moreover, 35.1% of adults and 16.9% of 
youths in the U.S. are obese (Ogden, et al., 2014). Even in low-income 
countries, the top ten risk factors for preventable death include high 
blood pressure, high blood glucose, and high cholesterol (WHO, 2009). 
The problems with many modern diets, which contribute to these high 
rates of chronic disease (McCullough, et al., 2002), are that they 
contain too much saturated fats, cholesterol, added sugars, added 
sodium, and refined grains, and too little whole grains and fresh 
fruits and vegetables (USDA, 2010).
    As a result of the high rates of chronic disease, there have been 
calls for taxes on energy-dense less-nutritious foods from many medical 
and public health organizations, such as the World Health Organization 
(2015), U.S. Dietary Guidelines Advisory Committee (2015), British 
Medical Association (2015), Institute of Medicine (2009), and the 
International Obesity Task Force (2005), which urged all European Union 
member countries to enact taxes on energy-dense foods. There have also 
been numerous calls in medical journals for taxes to incentivize a 
healthy diet (e.g., Brownell and Frieden, 2009, and Jacobson and 
Brownell, 2000). Taxes on energy-dense foods are arguably the most 
commonly-advocated anti-obesity policy.
    Policymakers worldwide have responded to this call for action. 
Numerous countries, such as Australia, Canada, Denmark, Fiji, Finland, 
France, Hungary, Norway, and Mexico, have recently implemented taxes on 
energy-dense, less-nutritious foods (see e.g., World Health 
Organization, 2015, Sassi, et al., 2013, and Thow, et al., 2011). In 
the U.S., 34 states tax soft drinks sold in grocery stores, at an 
average rate of 4.02%, and 15 states tax snacks sold in grocery stores 
at an average rate of 1.2% (Chriqui, et al., 2008). In early 2015, 
Berkeley, California became the first U.S. city to impose an excise tax 
on sugar-sweetened beverages (Cawley and Frisvold, 2015).
    To some extent, an individual's diet and any resulting chronic 
disease or premature mortality can be seen as a private, individual 
decision. However, there are two economic rationales for government 
intervention to incentivize healthier diets. First, there are external 
costs of a poor diet that operate through private and public health 
insurance (Cawley, 2015). Premiums that fund private health insurance, 
and the taxes that fund public health insurance, are not a function of 
diet, and as a result, the costs of treating diet-related chronic 
disease are borne not only by those with the disease but also by others 
in the same insurance pools and by taxpayers. The exact magnitude of 
these external costs is not known, but they are undoubtedly large given 
the enormous medical care costs. Indeed, it is estimated that the 
annual direct medical care costs total $273 billion for cardiovascular 
disease (CDC, 2015a), $315.8 billion for obesity (Cawley, Meyerhoefer, 
et al., 2015), $116 billion for diabetes (CDC, 2015b), and $263.8 
billion for cancer (this includes both direct and indirect costs; CDC 
2015c). To pool these separate estimates would result in some degree of 
double-counting, but the overall cost of these diseases is clearly very 
high.
    Behavioral economics offers a second rationale for government 
intervention to incentivize healthier diets. Individuals may have time-
inconsistent preferences; they may want to eat a nutritious diet so as 
to be healthy in the future, but in the short run may be tempted by 
immediate gratification (Laibson, 2014). Some have argued that optimal 
taxes should reflect not only externalities but also internalities 
associated with time-inconsistent preferences, and that in such cases 
sin taxes can make those who engage in such activities happier because 
it helps them help themselves (Gruber and Mullainathan, 2005).
    Whether or not food taxes and subsidies are effective is an 
empirical question. However, it is challenging to estimate the effect 
of existing food taxes on purchases and consumption. In the U.S., 
state-level taxes are so small that it is very difficult to measure 
their effects (Fletcher, Frisvold, and Tefft, 2010; Chaloupka, et al., 
2011; Fletcher, et al., 2011). For national taxes, it is difficult to 
disentangle the effect of the tax from time effects; i.e., it is hard 
to identify a geographic control group. For both, policy endogeneity is 
a problem.
    As an alternative approach, researchers have used field experiments 
to measure consumer responsiveness to price changes. For example, the 
USDA's Healthy Incentives Pilot for recipients of the Supplemental 
Nutrition Assistance Program (SNAP) offered a 30 rebate to the 
Electronic Benefit Transfer card for each dollar spent on fruits and 
vegetables. The program resulted in 0.22 cups/day more fruits and 
vegetable consumed by participating adults (USDA, 2013). Other field 
experiments paired their price changes with related interventions such 
as signs or marketing, the effect of which is confounded with the price 
change. For example, a set of experiments conducted by researchers at 
the University of Minnesota manipulated prices in cafeterias and 
vending machines (but also increased signage) and found that a 50% 
subsidy for fruits and salads tripled sales, but sales fell to baseline 
after the subsidy was removed (French, et al., 1997; Jeffrey, et al., 
1994). Elbel, et al. (2013) opened their own store in a hospital, and 
imposed a 30% tax on unhealthy foods, which they juxtaposed next to 
healthier alternatives. They estimate that the tax increased the 
probability of consumers choosing healthier alternatives by 11 
percentage points. The generalizability is unclear given that the store 
was a researcher-created environment that involved deliberate 
juxtapositioning of healthier and less healthy options.
    This paper contributes to the literature that uses field 
experiments to measure consumer responsiveness to changes in food 
prices. A review of the literature by Epstein, et al. (2012) finds only 
four studies that manipulated prices of foods in supermarkets; all 
provided discounts for healthy foods, and three of the four examined 
only purchases of a subset of available foods. Other experiments 
manipulating food prices took place in laboratories, cafeterias and 
restaurants, farmer[s'] markets, and vending machines (Epstein, et al., 
2012). In a recent study, nutritious foods were subsidized 12.5% or 25% 
and less-nutritious items were taxed 12.5% or 25%, depending on the 
treatment, in a simulated online market place with 6000 food items. 
Calories purchased of taxed foods decreased and calories purchased of 
subsidized foods increased, but overall calories did not change between 
baseline and price change interventions, suggesting substitution of 
calories towards foods neither taxed nor subsidized. Yet, there is 
evidence of improved nutrient quality of foods purchased in the subsidy 
condition (Epstein, et al., 2015).
    Another relevant recent study is that of List, Samek, and Zhu 
(2015). They conducted a field experiment at a grocery store in a high-
poverty area of Chicago. They enlisted 222 participants for a 6.5 month 
study and examined the effect of two treatments: $1 incentive to 
purchase at least 5 cups of fresh fruits and vegetables on their 
shopping trip, and information on preparing fruits and vegetables. They 
find little effect from the information, but find large effects of the 
incentives (it doubles purchases of fresh fruits and vegetables) that 
persist after the incentives end.
    The contribution of this research is to estimate the responsiveness 
of consumers to a price change--with no other interventions such as 
additional signage or juxtapositioning of alternatives--in the 
consumer's usual retail environment. In other words, we observe 
consumers buying their usual items in the supermarket in which they 
typically shop. We observe all food purchases made at the supermarket 
(and provide incentives for subjects to do all of their food shopping 
at the supermarket), and we rely on an objective system that classifies 
food as nutritious and less-nutritious and which is already in place in 
the supermarket.
    We conduct a randomized controlled field experiment in order to 
measure the impact of a 10% relative price difference between 
nutritious and less-nutritious food in order to answer three research 
questions: (1) Are consumers' food purchases responsive to less-
nutritious food being made 10% more expensive than nutritious food? (2) 
Does that responsiveness depend on whether the price change is framed 
as a tax on less-nutritious food, a subsidy for nutritious food, or 
both? (3) Do the answers differ by the education or income of the 
consumer?
    We hypothesize that the relative price change will decrease 
purchases of less-nutritious foods and increase purchases of nutritious 
foods. We also hypothesize that those told that the 10% price 
difference is a tax will respond more, relative to those who are told 
that the 10% price difference is a subsidy; this is motivated by 
prospect theory, which posits that people interpret gains and losses 
relative to a reference point (Kahneman and Tversky, 1979). In 
particular, people may respond more when the tradeoff is framed as a 
loss rather than a foregone reward (Gachter, et al., 2009; Homonoff, 
2015), which suggests that people may be more responsive to the frame 
of a tax on less-nutritious food than that of a subsidy for nutritious 
food.
    Additionally, we hypothesize that responses to the relative price 
change may differ by socioeconomic status, measured by income and 
education, though the direction of the response is unclear. Consumer 
response may differ by income for several reasons. Mullainathan and 
Shafir (2013) argue that poverty consumes mental bandwidth, which 
implies that lower-income individuals may pay less attention to the 
price change. On the other hand, other evidence suggests that lower-
income individuals may be more responsive to the relative price change. 
Low-income individuals who receive public assistance (such as food 
stamps or social security) exhibit ``first of the month effects''--
their spending on food decreases as the month progresses (Hastings and 
Washington, 2010; Shapiro, 2005). This suggests that they may be credit 
constrained and perhaps price reductions could have substantial income 
effects. Furthermore, other research suggests that the income 
elasticity of body weight is greater for low-income individuals (Akee, 
et al., 2013; Schmeiser, 2009).
    Second, consumer response may also differ by education. The better 
educated tend to demand more health and be more efficient producers of 
their own health (Grossman, 1972) and thus may have a more elastic 
demand for nutritious food. In addition, the better educated may simply 
better understand the treatment or respond to changing prices in 
general.
Data and Methods
The Field Experiment
    Controlled field studies with random assignment have the potential 
to clearly identify causal effects (List, 2009, 2011) and can have high 
levels of both internal and external validity (Roe and Just 2009). 
Thus, these types of studies can be uniquely effective for measuring 
the impact of potential policy instruments.
Identifying Nutritious and Less-Nutritious Foods
    Any experiment designed to manipulate the prices of nutritious and 
less-nutritious foods faces the challenge of defining those two 
categories. We relied upon a supermarket shelf-label nutrition guidance 
system that had already been in place in the supermarket for several 
years prior to this experiment.* \2\ This proprietary system, called 
Guiding Stars, scores foods based on their nutritional value. More 
specifically, it takes into account vitamins, minerals, fiber and whole 
grains (which raise the score) and saturated fat, trans fat, 
cholesterol and added sugar and sodium (which lower the score). 
Ultimately, foods are rated on a scale from zero stars (poor 
nutritional value) to three stars (best nutritional value), and this 
score is displayed on the supermarket shelf label below each food item 
(retail price and unit price). Over 60,000 food items are rated. The 
few foods that are not rated are new (and thus not yet rated), seasonal 
(not consistently available), or have no calorie or nutrient content 
(such as dried spices or dried coffee or tea). For more information on 
Guiding Stars, see Fischer, et al. (2011).
---------------------------------------------------------------------------
    * Editor's note: There is no footnote no. 1 in this working paper, 
as submitted.
    \2\ Sales data suggest that consumers use and respond to the 
Guiding Stars information; see Cawley, Sweeney, Just, et al. (2015). 
However, this information was in place well before and throughout the 
experiment and is thus not confounded with the treatment effects we 
estimate.
---------------------------------------------------------------------------
    For our experiment, we defined less-nutritious food as that which 
receives zero stars, and defined nutritious food as that which receives 
any stars (one, two, or three). An incentive scheme could offer more 
finely-tuned subsidies based on whether the item received one, two, or 
three stars, but that would also involve the tradeoff of increased 
complexity that could cause confusion for study participants. We chose 
to make the intervention simple to understand, and divided foods into 
those with zero stars (which were made relatively more expensive) and 
those with one or more stars (which were made relatively cheaper).\3\ 
Of the rated food items observed in our data, 29% have at least one 
star and are thus classified as nutritious.
---------------------------------------------------------------------------
    \3\ The prices of unrated items were not altered.
---------------------------------------------------------------------------
Participation and Incentives
    Between May 1 and June 30, 2010, we recruited 239 loyalty card 
shoppers to participate in the study. Individuals were recruited via 
face-to-face contact at the entrances to two grocery stores in upstate 
New York. These stores are part of a regional supermarket chain that is 
located in the Northeast U.S. In order to ensure a diverse set of 
participants, subjects were recruited at various days and times, as 
well as at two different stores of the same chain in neighborhoods of 
differing socioeconomic status. In addition, to be eligible for 
inclusion in the study, participants had to have children under the age 
of 18 years living at home, do at least 75% of their shopping at the 
supermarket chain, and do a majority of the household's shopping.
    After enrollment, subjects were sent an e-mail with a link to 
complete a survey on their household characteristics and shopping 
patterns. After repeated requests, fourteen subjects did not complete 
the survey and were dropped. One household later attrited from the 
study and so we drop data for that household. In 16 households, two 
individuals claimed to each do \1/2\ of the household's shopping. Both 
were enrolled but purchases were aggregated to the household level. As 
a result, we have complete information, survey responses and 
expenditure data, for 208 households.
    Soon after enrollment, participating households received two 
cards.\4\ A scanner card (with the subject's name and photograph) was 
used to track purchases at the supermarket checkout lane. A debit card 
was used to deliver incentives and subsidies, which were electronically 
credited on a weekly basis. We observed households' food purchases 
(through their use of the scanner card) for a total of 33 weeks, 
including an 8 week baseline period before the relative prices of 
nutritious and less-nutritious foods were altered.\5\ To encourage 
households to conduct all of their food shopping at the participating 
supermarket, during this baseline period, they received a 10% discount 
on purchases of all rated food items, defined as any foods rated with 
0, 1, 2, or 3 stars.
---------------------------------------------------------------------------
    \4\ In the 16 households in which two members enrolled in the 
study, each enrollee received his/her own set of cards.
    \5\ Households signed up 5-8 weeks before the treatment period; 
thus, we have baseline data for every household for at least 4 weeks 
and up to 8 weeks for some households.
---------------------------------------------------------------------------
Treatment Conditions
    At the conclusion of the baseline period, subjects were randomized 
into one of four groups. The control group (N=52 households) continued 
to receive a 10% discount on all rated food items. For the treatment 
group (N=156), nutritious food was made 10% cheaper than less-
nutritious food. How this price wedge was framed differed based on the 
treatment group into which the subject was randomized. The tax group 
(N=51) was told that they received a 15% discount on all rated food 
items, but were taxed 10% (and thus received only a 5% discount) on 
less-nutritious food. The subsidy group (N=55) was told it received a 
5% discount on all rated food items, plus an additional 10% subsidy on 
nutritious food, for a total of 15% off nutritious food. The tax/
subsidy group (N=50) was told that it received a 10% discount on all 
rated food items, plus an additional 5% subsidy on nutritious food (for 
a total subsidy of 15%) but was taxed 5% on less-nutritious food (for a 
net subsidy of 5%). In all three treatment conditions, nutritious food 
was subsidized 15% and less-nutritious food was subsidized 5%; thus 
each group faced a 10% price wedge between nutritious and less-
nutritious food. The only way the treatments differed was in how that 
relative price difference was framed.
    Households were notified of their respective treatment via e-mail 
and phone calls. Out of concern that subjects may not check their e-
mail or voice messages, the enrolled representative from each household 
was also individually contacted by phone and notified directly; this 
process took 12 days. We removed these 2 weeks from analysis because 
some subjects during that time may not have yet been aware of their 
treatment condition.
    In a voluntary field experiment, it is not possible to impose taxes 
on less-nutritious foods greater than the participation incentive, or 
subjects would likely buy these foods elsewhere and such expenditures 
would not be recorded as part of the study. To address this, the 
participation incentive was always greater than the tax imposed, 
ensuring that shoppers could not be worse off by shopping at the study 
stores. Because the participation incentive was also offered during the 
baseline period, we are able to identify the effect of price changes 
using the relative price changes between nutritious and less-nutritious 
foods that were imposed between the baseline and treatment periods. See 
Table 1 for the relative price changes at baseline and during the 
treatment period, and details of the framing of the treatment.
    To clarify, prices on the supermarket shelves were not altered. The 
participating supermarket was understandably unwilling to allow the 
researchers to manipulate shelf prices for all of their customers. 
Instead, subjects' purchases were tracked using the scanner cards, and 
the discounts, net of taxes, were uploaded weekly to the debit card. To 
ensure the salience of the price changes, each subject received a 
weekly e-mail notifying them of the amount of incentive or subsidy they 
had received, and reminding them which foods were taxed and which were 
subsidized. We acknowledge that this may affect the generalizability of 
these results, an issue we return to in the Discussion. The treatment 
period lasted for 25 weeks and ended without prior notice. See Figure 1 
for a detailed timeline of the study.
Data
    Itemized grocery purchases of each subject were tracked by the 
supermarket for the entire 33 weeks of the study using the scanner 
cards. The item-level transaction data include: date, quantity of item, 
expenditures on item, Guiding Stars score of each item (0, 1, 2, or 3 
stars), and the description of the item. These transactions were 
aggregated by household and week, with weeks defined as Monday through 
Sunday. We merge the information from the baseline survey with the 
transaction data.
    We focus on two main outcomes: the household's expenditures 
(defined before any subsidies or taxes applied by the experiment) and 
quantity purchased. Quantity purchased is measured in units, which is a 
limited measure because it does not account for size differences. For 
example, a \1/2\ gallon and a gallon of milk each count as one unit, as 
do two different-sized boxes of the same cereal. Thus, this measure of 
quantity is a noisy measure of the quantity of food purchased. We 
examine these two outcomes for all food purchases, as well as 
separately for nutritious food and less-nutritious food.
    If a household did not buy any food in that category in that week, 
the values of expenditures and quantity purchased are set to zero. The 
exception to this occurred during the first 3 weeks of the baseline 
period when households were still being enrolled in the study. During 
these 3 weeks, weeks with no expenditures were treated as missing until 
the household recorded their first shopping trip.
Hypotheses and Empirical Methods
    We test the following hypotheses:

          H1: Increasing the price of less-nutritious food relative to 
        the price of nutritious food will decrease purchases of less-
        nutritious food and increase purchases of nutritious food;
          H2: Framing the relative price change as a subsidy for 
        nutritious food will increase the extent to which the price 
        change increases purchases of nutritious food;
          H3: Framing the relative price change as a tax on less-
        nutritious food will increase the extent to which the relative 
        price change decreases purchases of less-nutritious food;
          H4: These effects will vary by income and education.

    In order to test these hypotheses, we estimate difference-in-
differences models of expenditures and quantities. Randomization into 
the treatment and control groups allows for interpretation of the 
difference-in-differences estimator as a causal effect of the 
treatment. We first estimate these models assuming no framing effects 
and thus pool all three treatment conditions--tax, subsidy, and tax/
subsidy--into a single treatment condition. We then subsequently 
estimate the models testing for framing effects, with each of the three 
frames as a separate treatment.
    To estimate the average effect of the price change, ignoring the 
possibility of framing effects, we estimate the following two-way fixed 
effects model:
(1)
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

The data are aggregated by household (h) and week (w). The difference-
in-differences estimator is b0. This coefficient measures 
the change between the baseline and treatment period for the treatment 
group relative to the control group. In order to control for time-
invariant unobserved heterogeneity among households, the model controls 
for household fixed effects Ih. In order to control for time 
effects, such as the seasonal availability of fresh fruits and 
vegetables and changes in demand due to holidays, the model controls 
for week fixed effects Iw. The OLS regression model is 
estimated for all food purchases, as well as separately for purchases 
of nutritious food and less-nutritious food. The null hypothesis is 
that the 10% price wedge has no impact on purchases: b0=0. 
To account for possible correlation in errors for the same household 
over time, standard errors are clustered by household.
    In order to test whether the framing of the price change affects 
consumers' response to the price change, we estimate the following 
model, which estimates a separate difference-in-differences effect for 
each of the three treatment groups (tax, subsidy, tax and subsidy):
(2)
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

The null hypothesis is that the framing of the treatment as either a 
tax on less-nutritious food, a subsidy of nutritious food, or both, 
does not alter the treatment effect; i.e., that 
b1=b2=b3.
    To test whether the treatment effect varies by income, we estimate 
models (1) and (2) separately for those whose household income is (a) 
below or (b) above 130% of the Federal Poverty Line (FPL), which is the 
eligibility threshold for the Supplemental Nutrition Assistance Program 
(SNAP) and is close to the eligibility threshold for Medicaid (133% of 
FPL).
    To test whether the treatment effect varies by education, we 
estimate the model separately for those whose educational attainment is 
(a) a high school degree or less or (b) some college or more.
    We emphasize that, given our overall sample size, we have limited 
statistical power for subgroups. When we divide the sample by income, 
we have 36 households below and 155 households above 130% of the FPL. 
When we divide the sample by education, we have 18 participants with a 
high school education or less, and 182 participants with some college 
or more education (see Table 2). These subtotals do not sum to our 
total of 208 households because of non-response to the questions about 
income and education.
Empirical Results
Summary Statistics
    Tables 2 and 3 list summary statistics for the study participants, 
with columns for the whole sample, control group, all treatment groups 
pooled, and each treatment group separately. Table 2 reports sample 
sizes for the socioeconomic subgroups. Tables 3a and 3b report summary 
statistics for additional household characteristics, such as income, 
number of children at home, household size, marital status, and race/
ethnicity, which are all controlled for in our model through the 
inclusion of household fixed effects.
    The summary statistics indicate that our sample is relatively well 
educated (91% have more than a high school education) and white 
(93.7%). This is a reflection of the fact that our sample consists of 
individuals in upstate New York and the participating supermarket chain 
is relatively high-end. By construction, all families have at least one 
child under the age of 18 years in the household.
    Table 4 lists unconditional weekly expenditures on foods (overall, 
all rated, less nutritious, nutritious) for the entire sample and by 
group (control, all treatment, each treatment group). Household weekly 
food expenditures at this supermarket averaged $89.83 during the 
baseline period, and $100.88 during the treatment period. In 
comparison, data from the Consumer Expenditure Survey indicate that on 
average U.S. households spent $76 per week on food purchased for at-
home consumption in 2013 (BLS, 2015). Notably the BLS estimate is 
unconditional, whereas our sample consists of households with at least 
one child under the age of 18 years, and are thus likely to be above-
average in terms of food expenditures.
    The increase in average weekly food expenditures for all treatment 
groups ($10.95) is roughly equal to that for the control group 
($11.32); this unconditional difference-in-differences suggests that 
the treatment did not significantly affect overall expenditures on 
food. The increase in expenditures on nutritious food was also similar 
for all treatment groups pooled ($4.69) and the control group ($3.30).
Overall Effect of Relative Price Change
    Table 5 lists results of the difference-in-differences models for 
expenditures and quantities. Our hypothesis is that the 10% relative 
price change increased the quantity demanded of nutritious food, and 
decreased the quantity demanded of less-nutritious food. Table 5 shows 
that the point estimates of the coefficients are consistent with these 
hypotheses, but the coefficients are not statistically significant. For 
example, we find that creating a 10% price difference between 
nutritious and less-nutritious foods raised spending on nutritious food 
by $1.11 per week and lowered spending on less nutritious food by $1.55 
per week, neither of which is statistically significant. On net, 
spending on all food rated by Guiding Stars (whether nutritious or less 
nutritious) fell by $0.44 per week, which was not statistically 
significant. In terms of quantities, the 10% relative price difference 
increased weekly purchases of nutritious food by 0.95 units and lowered 
weekly purchases of less nutritious food by 0.87 units; overall 
purchases of foods rated by Guiding Stars rose by .08 units. None of 
those changes are statistically significant.
    In summary, we are unable to reject the null hypothesis of no 
effect of the relative price change on purchases of nutritious and 
less-nutritious foods.
Effect of Framing of Relative Price Change
    Next we test whether the effect of the relative price change 
differed by the way in which it was framed: as a tax on less-nutritious 
food, a subsidy for nutritious food, or both. It is possible that, 
because of loss aversion, the tax frame may exhibit a greater treatment 
effect than the subsidy frame. Moreover, given the difference in 
salience, we may see a greater increase in purchases of nutritious food 
for the subsidy frame, but a greater decrease in purchases of less-
nutritious food for the tax frame.
    Table 6 presents the results of the difference-in-difference models 
that estimate separate effects by frame. In no case are the treatment 
effects significantly different across frames (whether tax versus 
subsidy, tax versus tax/subsidy, or subsidy versus tax/subsidy). In 
addition, no estimated treatment effect for nutritious or less-
nutritious food is significantly different from zero. However, some 
point estimates are substantial; e.g., the effect of the relative price 
change for those in the tax frame to increase their weekly purchases of 
nutritious food by $4.52 (relative to a mean of $36.55) and for those 
in the tax/subsidy frame to decrease their weekly purchases of less 
nutritious food by $4.40 (relative to a mean of $49.59).
    In summary, we are unable to reject the null hypothesis of no 
framing effect for the relative price change.
Differences by Income and Education
    In our next analyses, we test whether the overall price treatment 
effects differed by income or education. For the sake of simplicity, we 
report results for expenditures (but not those for quantities). Table 7 
presents results of the overall price treatment effects separately for 
households with incomes below and above 130% of the Federal Poverty 
Line.
    Although the difference in results across income was not 
statistically significant, the point estimates suggest that the 
treatment was associated with lower-income households spending $7.03 
more per week on nutritious food and $7.11 more per week on less-
nutritious food. In contrast, higher-income households spent $1.27 less 
on nutritious food per week and $4.02 less on less-nutritious food per 
week. None of these point estimates are statistically significant.
    Table 8 presents the results of models estimated separately by 
education. Again, we find no statistically significant difference 
between the effect of the relative price change for the two 
socioeconomic groups. Moreover, the difference in point estimates is 
considerably smaller across education groups than across income groups.
    We next test whether framing effects differed by income or 
education. Table 9 reports results for the model that estimates 
treatment effects by frame, with the model estimated separately by 
income category. There are large and statistically significant 
differences in the effects of the frame by income. Specifically, low-
income households that were given the subsidy frame (i.e., told that 
the 10% relative price change represented a subsidy for nutritious 
food) significantly increased their purchases of less-nutritious food 
(by $21.23 per week). The increase in purchases of nutritious foods was 
$11.58, but not statistically significant. Overall, purchases of foods 
rated by Guiding Stars rose $32.81 per week on average for this group.
    In contrast, higher-income households that were given the subsidy 
frame decreased their weekly purchases of both nutritious food ($4.55) 
and less-nutritious food ($7.55), although these are not significantly 
different from zero. The effects of the price change on less nutritious 
foods and all rated foods are, however, significantly different for the 
low-income and high-income groups given the subsidy frame.
    In addition, within each income group, there is a significant 
difference in framing effects. As stated above, the low-income 
individuals given the subsidy frame significantly increased their 
purchases of less-nutritious food (by $21.23 per week); in contrast, 
the low-income individuals given the tax frame decreased their 
purchases of less-nutritious food (by $9.04, which is not statistically 
significant). That difference across frames is statistically 
significant. The responses of the tax and subsidy frame among the low-
income participants also significantly differed for expenditures on all 
rated items, unrated items, and all items. They did not significantly 
differ in their treatment effect on expenditures on nutritious foods.
    Table 10 presents results for models that estimate treatment 
effects by frame, with the models estimated separately by education 
category. There are no statistically significant differences in framing 
effects by education. Moreover, within educational group there are no 
statistically significant differences in framing effects; i.e., we 
cannot reject the null hypothesis that the effect was the same for each 
treatment group or frame.
    In summary, we find significant differences in framing effects by 
income. Specifically, the treatment effect is much greater for the low-
income households given the subsidy frame than those given the tax 
frame; they buy more of even what the relative price change was seeking 
to discourage: less-nutritious food.
Extension: Permutation Tests
    Given our sample size (208 households' weekly purchases over 8 
months) we seek additional confirmation of both the result of 
significant treatment effects among low-income households given the 
subsidy frame, and the inability to reject the null of no effect for 
the overall sample. To that end, we conducted permutation tests 
(Kaiser, 2007) in which households were randomly re-labeled as being in 
one of the three treatment groups or the control group, after which the 
expenditure models were re-estimated. This was repeated 1,000 times and 
we compare the statistical significance of the treatment effect in our 
primary models to the distribution of treatment effects estimated in 
the 1,000 permutations. A p value of (e.g.) 0.05 indicates that only 5% 
of the permutations yielded more statistically significant results than 
our primary models, which would suggest that the original result was 
not due to chance.
    The results of the permutation tests are provided in Appendix 
Tables 1-3. In general, these results confirm both of our major 
findings. First, for the overall sample we cannot reject the null 
hypothesis of no effect of the price change treatment. Appendix Table 1 
shows that, for both nutritious and less-nutritious foods, 70% or more 
of the permutations yielded more statistically significant treatment 
effects than the ones estimated in our primary model. Table 2 shows 
that the permutation tests are also consistent with our inability to 
reject the null hypothesis of no effect of framing for the overall 
sample. Appendix Table 3 shows that the permutation test confirms our 
finding of a significant positive effect of the treatment for low-
income households given the subsidy frame; specifically, the 
permutation test p value is 0.056, indicating that the finding in our 
primary model is more significant than 94.4% of the permutations based 
on random re-labeling of groups. The result for the purchase of 
nutritious foods by the low-income households given the subsidy frame 
falls just short of statistical significance (p=.102).
    Overall, the results of the permutation test confirm the earlier 
results--we cannot reject the null of a zero treatment effect for the 
overall sample, and we find evidence that low-income households given 
the subsidy frame buy significantly more less-nutritious foods.
Extension: Share of Purchases that was Nutritious
    As another extension, we examine the proportion of expenditures on 
nutritious foods (the denominator includes expenditures on all rated 
foods). Table 11 presents results for the difference-in-differences 
model in which the dependent variable is the percent of expenditures 
that was on nutritious foods. The effect of the relative price change 
was to increase the share of expenditures devoted to nutritious food by 
1.08 percentage points, relative to a mean of 42.5%. However, this 
increase was not statistically significant. Subsequent columns in the 
table list the effects for high and low-income, and the high and low 
education groups. In each case the change in the percent of nutritious 
purchases resulting from the tax is small and not statistically 
significant.
Extension: Purchases of Unrated Foods
    As described in the Data section, the Guiding Stars system rates 
virtually all foods in the supermarket. Those that are not rated 
include items that are new and have simply not yet been rated, or 
seasonal and therefore not consistently available. However, foods that 
have no calorie content are also not rated. This includes some items 
that are relatively uninteresting from a health perspective (e.g., 
dried spices) but it also includes bottled water, alcoholic beverages, 
and dried tea and coffee. These are of interest because after the 
relative price change consumers may shift away from sugar-sweetened 
beverages to these other drink options. In order to test for any such 
effects, we estimate difference-in-differences models of expenditures 
and quantities purchased in that category. The results appear as 
additional columns in each of the earlier tables. We also include a 
column for All Items, which includes not just rated foods but also 
unrated foods.
    Table 5 shows that the main effect of the treatment is a very small 
change in weekly expenditures on unrated items ($0.81), which is not 
statistically significant. However, the treatment results in an 
increase in the quantity of unrated foods purchased per week of 0.66 
units, which is statistically significant. Table 6 provides information 
on the effect of the framing of the relative price change. In five out 
of six cases, the effect of the treatment on purchases of unrated food 
items is not statistically significant; the exception is that those 
given the subsidy frame purchased 0.92 more units of unrated food per 
week. The results in Table 9 indicate that this effect is concentrated 
among the lower-income households in the subsidy frame, who increased 
their purchases of unrated food items by $5.78 per week.
Extension: Change in Treatment Effects over Time
    The dynamics of treatment effects can be interesting; a large 
initial effect that falls over time could be due to novelty or 
salience, while a small initial effect that increases over time is 
consistent with habit formation. To investigate this, we estimated our 
model of the overall treatment effect (i.e., ignoring framing effects) 
for each week, and plot the results in Figure 1. Although our sample 
size precludes us from drawing strong conclusions, the negligible 
effect in the first 7 weeks of the treatment, combined with the larger 
treatment effects later in the treatment period, are consistent with 
gradual habit formation.
Robustness Checks
    To verify our initial results, we conduct a variety of additional 
robustness checks. First, we re-estimate our models excluding the 
baseline data and find very similar results. Second, we estimate our 
original difference-in-differences models dropping the weeks with 
holidays (Thanksgiving, Christmas, and New Year's); the main difference 
is that the treatment effect is significant for low-income households' 
spending on nutritious foods (it rises by $9.43 per week). This is 
concentrated among the low-income households given the subsidy frame, 
who increase their spending on nutritious food by $16.80 per week. 
Third, most of the subjects are women, so we drop the men and re-
estimate the models using only the female subjects. The main difference 
is that the results for higher-income households become more 
significant; e.g., the high-income households in the subsidy frame 
decrease their spending on nutritious food ($8.87 less per week), less 
nutritious foods ($10.93 less per week), all rated foods ($19.80 less 
per week) and all items ($20.45 less per week). Fourth, we sought to 
investigate the large treatment effects exhibited by the low-income 
households given the subsidy frame. In particular, we investigated 
whether these households were buying non-perishables (stocking up for 
future consumption) or were buying perishables (for immediate 
consumption). Estimating our models separately for expenditures on 
perishables and non-perishables, we find that the low-income households 
given the subsidy frame generally bought more of everything, but the 
increases were statistically significant for perishables that were 
nutritious and less-nutritious, and for non-perishables that were less-
nutritious. In other words, the low-income households given the subsidy 
frame were not just using the treatment as an opportunity to ``stock 
up''; they were also buying more perishables for immediate consumption.
Extension: Subjects' Interpretations of the Relative Price Change
    In order to better understand why there might be framing effects, 
we examine the results of a survey we administered to study 
participants after the treatment period ended. Participants were asked 
how they interpreted the treatment. Specifically, they were presented 
with seven statements describing the treatment, and were asked to rate 
their agreement with each of them on a Likert scale that ranged from 1 
(strongly disagree) to 9 (strongly agree). Table 12 presents the 
unconditional mean responses for the entire sample as well as the 
control group, the entire treatment group, and each treatment group 
separately.
    One important result that stands out is that participants, no 
matter what their frame, tended to interpret the relative price change 
as a subsidy for nutritious food rather than a tax on less-nutritious 
food. For example, for the sample as a whole, the mean agreement that 
the debit card payments were a ``reward for eating healthy food'' 
averaged 6.2 on the nine-point scale, whereas ``penalty for eating 
unhealthy food'' averaged 2.9. In addition, for the sample as a whole, 
the mean agreement that it represented a ``discount for eating healthy 
foods'' was 6.4 out of 9, whereas the agreement that it was a ``tax on 
unhealthy foods'' was 3.4 out of 9.
    This is not to say that the framing had no effect on subjects' 
perceptions. There was a statistically significant difference in the 
mean agreement that the treatment was a ``penalty for eating unhealthy 
food'' (3.4 in the tax frame versus 2.4 in the subsidy frame) as well 
as in the mean agreement that the treatment was a ``tax on unhealthy 
foods'' (3.7 in the tax frame versus 2.8 in the subsidy frame). Thus, 
the frame did have a detectable effect on perceptions of the treatment, 
but participants in all groups tended to interpret the treatment as 
more of a subsidy of nutritious food than a tax on less-nutritious 
food.
Extension: Subjects' Interpretations of their Change in Shopping During 
        Treatment
    In the survey conducted after the treatment concluded, subjects 
were also asked whether or not participating in the study influenced 
their shopping. The unconditional means by group are reported in Table 
12. Those in the treatment groups (all pooled) expressed greater 
agreement with the statements that they were buying more starred 
(nutritious) foods, more healthier foods, and a higher percentage of 
healthier foods, but the difference between the treatment and control 
groups is not statistically significant in any of those cases.
    There are significant differences in the mean response to these 
questions by frame. Specifically, those in the tax/subsidy frame tend 
to express greater agreement that the study led them to buy more 
nutritious foods, buy healthier foods, and buy a higher percentage of 
healthier foods, relative to those in the subsidy frame. Notably, we 
did not see such a difference in our data in the actual expenditures 
and quantities purchased.
Discussion
    This paper contributes to the literature on the effects of food 
taxes and subsidies through an 8 month field experiment that created a 
10% price wedge between nutritious and less-nutritious foods. We find 
that, on the whole, expenditures and quantities purchased did not 
change significantly in response to the price change. The point 
estimates suggest that the treatment group spent slightly less on less-
nutritious food and slightly more on nutritious food, but these changes 
were not statistically significant. Some of the point estimates are 
substantial in magnitude, and their lack of statistical significance is 
due in part to imprecision of the estimates and to limited statistical 
power from 208 households.
    Although we hypothesized that the framing of the relative price 
change as either a subsidy for nutritious food or a tax on less-
nutritious food could alter the treatment effect, we find no 
significant differences in effects by frame. We do, however, find 
effects of framing by income. Specifically, lower income households to 
whom the relative price change was framed as a subsidy bought 
significantly more less-nutritious food (and more of all food) than 
low-income households to whom it was framed as a tax. Permutation tests 
are consistent with these results, suggesting that they are not due to 
chance.
    One possible explanation for lower-income households buying more of 
all food, including the relatively more expensive less-nutritious food, 
is that lower-income households may experience a large income effect of 
a price decrease. In a related finding, List, et al. (2015) estimate 
that a $1 reward for buying any fresh fruits and vegetables caused the 
patrons of a grocery store in a low-income neighborhood of Chicago to 
double their purchases of produce. Previous research has also 
documented that food purchases drop significantly in the course of the 
benefit month for low-income households (e.g., Hastings and Washington, 
2010, Shaprio, 2005) and that income increases obesity for low-income, 
but not other, households (see the review in Cawley, 2015). Another 
possibility is that poverty consumes mental bandwidth for low-income 
individuals (Mullainathan and Shafir, 2013) or causes distractions 
sufficient to result in cognitive deficits (Mani, et al., 2013), such 
that households may have misunderstood the subsidy for nutritious food 
as a general ``food subsidy.''
    Although we hypothesized that better educated individuals might 
respond differently to the treatment, we find no evidence of 
differences in the treatment effect or in the framing effects by 
education.
    Taxes on energy-dense foods are arguably the most commonly-
advocated anti-obesity policy. The results of this paper have several 
implications for such policies to promote more nutritious diets. First, 
taxes may need to be large to change behavior. In the U.S., taxes on 
soda pop and snacks average one to four percent (Chriqui, et al., 
2014), but we find no significant impact on expenditures or purchases 
from a ten percent relative price change. Second, price changes may 
have different impacts by income; we find that subsidies for nutritious 
food may lead low-income households to buy more of all food, including 
more of the less-nutritious food that the policy is attempting to 
discourage.
    It should be noted that even if taxes do not change behavior, these 
policy instruments can still internalize external costs, thereby 
addressing a market failure. Moreover, if consumers do not 
significantly alter their purchases, it implies that the tax results in 
relatively little deadweight loss and thus is a relatively efficient 
way for the government to collect revenue.
    Strengths of this study include a randomized controlled field 
experiment, with actual consumers making real purchases of actual 
products in their usual retail environment. Such controlled field 
experiments represent a strong design for estimating casual effects 
(List, 2009). The present study is a relatively long experiment of this 
type, with an 8 week baseline and 25 week treatment period.
    The greatest limitation of the study is the limited statistical 
power associated with observing 208 households for 33 weeks; this is 
particularly acute when studying subsamples and testing for differences 
between income or education groups. In some cases, we estimate 
substantial point estimates but because of their imprecision they are 
not statistically significant. Given our limits with statistical power, 
we cannot rule out price elasticities common in the literature.\6\ 
However, the permutation tests are consistent with our main results of 
a null effect for the overall sample but that low-income households 
given the subsidy frame spend more on less-nutritious food. Another 
limitation is a lack of data from after the intervention ended; 
however, we find no significant main effects of the treatment, so there 
is little reason to look for habit persistence after the treatment 
ended.
---------------------------------------------------------------------------
    \6\ The 95% confidence intervals for the implied price elasticities 
of demand are quite large: ^3.5, ^10.3) for nutritious food and (2.5, 
6.2) for less-nutritious foods.
---------------------------------------------------------------------------
    Readers should exercise caution when generalizing from the results 
associated with this relatively white, well-educated and high-income 
sample from upstate New York. In addition, although we observe detailed 
information on food purchases, we do not observe food consumption, 
which would be informative about the health consequences of taxes on 
energy-dense foods.
    Furthermore, the effects estimated in this paper may be influenced 
by the design of the experiment. Consumer responsiveness may have been 
attenuated by the fact that the price changes were less salient than 
usual. Our relative price changes were not reflected on supermarket 
shelves; consumers had to note the number of Guiding Stars for the item 
and take into account the subsidy or tax they received. This may have 
led to less responsiveness because of the mental cost of calculating 
the relative price change, or consumers may have overlooked the price 
change at times because it was less salient (Finkelstein, 2009).
    In addition, participation and subsidies, minus taxes, were paid 
weekly, and this departure from immediacy may have also muted consumer 
responsiveness. Given that participants knew they were participating in 
a study, they may have perceived the price changes as temporary and not 
bothered changing their usual food habits.
    In this study consumers were directed to the Guiding Stars 
nutrition guidance system to determine the amount of the tax or subsidy 
(if any). Thus, there was not only a price effect but also potentially 
an effect from nutrition information. This would also be true of any 
salient tax placed on energy-dense foods, such as a ``fat tax'' or tax 
on sugar-sweetened beverages. It also implies that the consumer 
responses we estimate may be greater than those that would be observed 
from a tax on certain foods that was implemented simply for revenue 
reasons and was not directly linked to the nutrition of the items.
    Important directions for future research include estimating the 
impacts of greater price changes, testing for changes in treatment 
effects over time (they may increase due to habit formation or decrease 
due to diminishing salience or novelty), and continuing to refine how 
to frame price changes to maximize their intended impact.

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Figure 1: Study Timeline
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Note: Weeks are defined as Monday through Sunday.
Figure 2: Estimated Coefficients for Overall Price Treatment by Week
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Notes: Week 11 is the first week of the intervention period 
        and begins on Mon, Sep. 20, 2010. Thanksgiving occurred during 
        week 20 and Christmas occurred during week 24.

           Table 1: Comparison of Treatment and Control Groups
------------------------------------------------------------------------
                                                              Treatment
                        Control     Treatment    Treatment     Group 3:
                         Group       Group 1:     Group 2:   Subsidy and
                                     Subsidy        Tax          Tax
------------------------------------------------------------------------
Discount on all Food          10%           5%          15%          10%
 Items as a Reward
 for Participation
Subsidy on                     --          10%           --           5%
 Nutritious Foods
Tax on Less-                   --           --          10%           5%
 Nutritious Foods
Reduction in the             None          10%          10%          10%
 Relative Price of
 Nutritious vs Less-
 Nutritious Foods
------------------------------------------------------------------------


               Table 2: Descriptive Measures of Household Demographic Variables Used in Regression
                                      (standard deviations in parentheses)
----------------------------------------------------------------------------------------------------------------
                                                               All
                              Whole Sample     Control      Treatment      Subsidy         Tax      Tax/ Subsidy
                                                             Groups
----------------------------------------------------------------------------------------------------------------
More than high school             91.00%        92.00%        90.70%        90.60%        91.80%        89.60%
 education
  St. dev.                        (0.287)       (0.274)       (0.292)       (0.295)       (0.277)       (0.309)
N (> HS ed.)                     182            46           136            48            45            43
N (5 HS ed.)                      18             4            14             5             4             5
Above 130% of FPL                 81.20%        75.00%        83.20%        82.40%        82.60%        84.80%
  St. dev.                        (0.392)       (0.438)       (0.375)       (0.385)       (0.383)       (0.363)
N (Above 130% of FPL)            155            36           119            42            48            39
N (At or below 130% of FPL)       36            12            24             9             8             7
Income > $80,000                  31.41%        27.08%        32.87%        25.49%        34.78%        39.13%
  St. dev.                        (0.465)       (0.449)       (0.471)       (0.440)       (0.482)       (0.493)
N (Inc. > $80K)                   60            13            47            13            16            18
N (Inc. <= $80K)                 131            35            96            38            30            28
More than one child under 18      58.70%        59.60%        58.40%        54.70%        56.90%        64.00%
  St. dev.                        (0.494)       (0.495)       (0.494)       (0.503)       (0.500)       (0.485)
N (> 1 child)                    121            31            90            29            29            32
N (= 1 child)                     85            21            64            24            22            18
----------------------------------------------------------------------------------------------------------------
* p<.1. ** p<0.05. *** p<0.01. Note that the asterisks represent differences of the annotated value from the
  corresponding value of the control group at the respective level of significance. FPL stands for Federal
  Poverty Line.


                               Table 3: Additional Household Demographic Measures
                                 a. Food Assistance, Household Size, and Income
                                      (standard deviations in parentheses)
----------------------------------------------------------------------------------------------------------------
                                                               All
                              Whole Sample     Control      Treatment      Subsidy         Tax      Tax/ Subsidy
                                                Group        Groups
----------------------------------------------------------------------------------------------------------------
% Households Enrolled in WIC       4.8%          5.8%          4.5%          1.8%          2.0%         10.2%
                                  (0.215)       (0.235)       (0.208)       (0.135)       (0.140)       (0.306)
% Households Enrolled in           4.3%          5.8%          3.9%          3.6%          3.9%          4.1%
 SNAP
                                  (0.204)       (0.235)       (0.194)       (0.189)       (0.196)       (0.200)
% Households Not Receiving        89.9%         87.7%         90.7%         94.4%         87.3%         89.8%
 Food Assistance
                                  (0.282)       (0.318)       (0.270)       (0.205)       (0.297)       (0.306)
Average Household Size             3.93          3.92          3.93          3.76          4.04          4.02
                                  (1.076)       (1.064)       (1.084)       (1.027)       (1.190)       (1.031)
Average Number of Children         2.2           1.8           2.3           3.0           1.9           1.8
 Under 18
                                  (3.852)       (0.936)       (4.412)       (7.295)       (1.051)       (0.889)
% Household Shopping at           83.58         82.09         84.07         83.15         82.24         87.02
 Hannaford
                                 (13.894)      (15.754)      (13.230)      (13.687)      (14.960)      (10.211)
$10K-$20K                          9.4%         10.4%          9.0%         11.8%          4.1%         10.9%
                                  (0.291)       (0.309)       (0.286)       (0.325)       (0.196)       (0.315)
$20K-$30K                         19.0%         19.5%         18.9%         19.6%         15.2%         21.7%
                                  (0.392)       (0.393)       (0.393)       (0.401)       (0.363)       (0.417)
$30K-$40K                          9.7%         10.4%          9.4%          7.8%         13.0%          7.6%
                                  (0.294)       (0.309)       (0.290)       (0.272)       (0.341)       (0.257)
$40K-$50K                          9.5%         12.5%          8.4%          3.9%         14.3%          7.6%
                                  (0.288)       (0.334)       (0.271)       (0.196)       (0.341)       (0.257)
$50K-$60K                         12.2%         11.5%         12.4%         10.9%         13.5%         13.0%
                                  (0.322)       (0.314)       (0.325)       (0.303)       (0.340)       (0.341)
$60K-$70K                         10.2%          8.3%         10.8%         12.7%          8.7%         10.9%
                                  (0.301)       (0.279)       (0.309)       (0.329)       (0.285)       (0.315)
$70K-$80K                          4.9%          8.3%          3.7%          3.9%          2.8%          4.3%
                                  (0.213)       (0.279)       (0.186)       (0.196)       (0.153)       (0.206)
$80K-$90K                         11.5%         10.2%         11.9%         21.6%          6.5%          6.5%
                                  (0.315)       (0.288)       (0.325)       (0.415)       (0.250)       (0.250)
$90K-$100K                         4.7%          2.1%          5.5%          0.0%          8.5%          8.7%
                                  (0.204)       (0.144)       (0.220)       (0.000)       (0.257)       (0.285)
>$100K                             6.4%          2.6%          7.7%          5.9%          8.7%          8.7%
                                  (0.244)       (0.148)       (0.267)       (0.238)       (0.285)       (0.285)
----------------------------------------------------------------------------------------------------------------
* p<0.1. ** p<0.05. *** p<0.01. Note that the asterisks represent differences of the annotated value from the
  corresponding value of the control group at the respective level of significance.


                               Table 3: Additional Household Demographic Measures
                                           b. Marital Status and Race
                                      (standard deviations in parentheses)
----------------------------------------------------------------------------------------------------------------
                                                               All
                              Whole Sample     Control      Treatment      Subsidy         Tax      Tax/ Subsidy
                                                Group        Groups
----------------------------------------------------------------------------------------------------------------
Divorced                           5.1%          8.0%          4.1%          5.7%          2.1%          4.3%
                                  (0.220)       (0.274)       (0.198)       (0.233)       (0.144)       (0.204)
Married                           80.2%         74.0%         82.3%         77.2%       * 87.3%         83.0%
                                  (0.381)       (0.419)       (0.366)       (0.409)       (0.297)       (0.380)
Separated                          1.5%          2.0%          1.4%          1.9%          2.1%          0.0%
                                  (0.122)       (0.141)       (0.116)       (0.137)       (0.144)       (0.000)
Widowed                            9.6%         12.0%          8.8%          9.4%          4.2%         12.8%
                                  (0.295)       (0.328)       (0.284)       (0.295)       (0.202)       (0.337)
Single                             1.0%          0.0%          1.4%          3.8%          0.0%          0.0%
                                  (0.100)       (0.000)       (0.116)       (0.192)       (0.000)       (0.000)
African American                   1.7%          2.0%          1.6%          1.9%          0.7%          2.1%
                                  (0.125)       (0.143)       (0.119)       (0.137)       (0.047)       (0.146)
American Indian or Alaska          0.5%          0.0%          0.7%          1.9%          0.0%          0.0%
 Native
                                  (0.071)       (0.000)       (0.082)       (0.137)       (0.000)       (0.000)
Asian                              1.5%          2.0%          1.4%          0.0%          0.0%          4.3%
                                  (0.123)       (0.143)       (0.116)       (0.000)       (0.000)       (0.204)
White                             93.7%         91.8%         94.3%         94.2%         94.9%         93.6%
                                  (0.214)       (0.236)       (0.207)       (0.208)       (0.162)       (0.247)
Hispanic or Latino                 0.5%          2.0%        * 0.0%          0.0%          0.0%          0.0%
                                  (0.071)       (0.141)       (0.000)       (0.000)       (0.000)       (0.000)
Not Hispanic or Latino            96.9%         94.0%       * 97.9%         98.0%         95.6%     ** 100.0%
                                  (0.127)       (0.193)       (0.094)       (0.089)       (0.134)       (0.000)
----------------------------------------------------------------------------------------------------------------
* p<0.1. ** p<0.05. *** p<0.01. Note that the asterisks represent differences of the annotated value from the
  corresponding value of the control group at the respective level of significance.


                      Table 4: Weekly Expenditures: Unconditional Means by Treatment Group
                                      (standard deviations in parentheses)
----------------------------------------------------------------------------------------------------------------
                                                               All
                              Whole Sample     Control      Treatment      Subsidy         Tax      Tax/ Subsidy
                                                Group        Groups
----------------------------------------------------------------------------------------------------------------
                                                 Baseline Period
----------------------------------------------------------------------------------------------------------------
All Foods                        $89.83        $89.90        $89.81        $99.99        $81.82        $86.76
                                (116.035)      (95.315)     (122.488)     (119.643)      (81.283)     (157.529)
All Rated Foods                  $78.80        $78.25        $79.00        $88.59        $70.25        $77.43
                                (105.460)      (83.229)     (112.223)     (113.315)      (69.960)     (143.396)
Foods Rated Less Nutritious      $45.65        $44.72        $45.98        $50.73        $41.51        $45.35
                                 (62.311)      (48.867)      (66.384)      (65.884)      (43.122)      (85.031)
Foods Rated Nutritious           $33.15        $33.52        $33.02        $37.86      * $28.74        $32.08
                                 (47.030)      (40.335)      (49.170)      (51.713)      (31.500)      (60.313)
----------------------------------------------------------------------------------------------------------------
                                                Treatment Period
----------------------------------------------------------------------------------------------------------------
All Foods                       $100.88       $101.22       $100.76     ** $109.56       $98.97     ** $92.91
                                (102.566)     (108.558)     (100.503)     (102.659)      (97.627)     (100.332)
All Rated Foods                  $88.13        $88.31        $88.08     ** $95.53        $86.33      * $81.66
                                 (89.686)      (94.830)      (87.917)      (89.599)      (85.050)      (88.394)
Foods Rated Less Nutritious      $50.65        $51.49        $50.37        $54.65        $49.37     ** $46.68
                                 (54.582)      (57.214)      (53.681)      (53.898)      (53.374)      (53.471)
Foods Rated Nutritious           $37.48        $36.82        $37.71     ** $40.88        $36.95        $34.98
                                 (40.427)      (42.804)      (39.606)      (41.832)      (37.198)      (39.259)
----------------------------------------------------------------------------------------------------------------
Because weeks were classified as Monday through Sunday, the baseline period ended with week 8, which is the full
  week prior to households receiving notice of their treatment group. In the baseline period, values are set to
  missing prior to the first shopping trip in the first 3 weeks. Once all households were enrolled in the study
  (by week 4), any missing value was set to zero. Since households received their notices between September 7-
  15, weeks including these dates were omitted from the analysis. As a result, the treatment period begins with
  week 11, which is after all households received notice of their treatment.
* p<0.1. ** p<0.05. *** p<0.01. Note that the asterisks represent differences of the annotated value from the
  corresponding value of the control group at the respective level of significance.


                                 Table 5: Overall Price Effect on Weekly Household Expenditures and Quantities Purchased
                                                            (standard errors in parentheses)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                   Expenditures                                                                  Quantities
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                     Less        All Rated                   All                      Less        All Rated
                    Nutritious    Nutritious       Items        Unrated     Items    Nutritious    Nutritious       Items        Unrated      All Items
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Treatment          $1.11        ^$1.55        ^$0.44         $0.81      $0.37        0.951        ^0.873         0.078       * 0.661         0.739
 Groups
                       (3.010)       (4.042)       (6.780)       (1.138)   (7.606)      (1.347)       (1.607)       (2.822)       (0.387)       (3.091)
Weekly Dummy                                                                   
 Variables                                                                      e
N                   6,572         6,572         6,572         6,572         6,572    6,572         6,572         6,572         6,572         6,572
Unconditional         $36.55        $49.59        $86.14        $11.86     $98.50       16.132        18.853        34.985         3.609        38.744
 mean of
 dependent
 variable
--------------------------------------------------------------------------------------------------------------------------------------------------------
Participants in the intervention conditions were all combined. Regression coefficients were estimated using a fixed effects regression with weekly dummy
  variables. For the sake of space, coefficients from the weekly dummy variables were not included in the table. Because weeks were classified as Monday
  through Sunday, the baseline period ended with week 8, which is the full week prior to households receiving notice of their treatment group. In the
  baseline period, values are set to missing prior to the first shopping trip in the first 3 weeks. Once all households were enrolled in the study (by
  week 4), any missing value was set to zero. Since households received their notices between September 7-15, weeks including these dates were omitted
  from the analysis. As a result, the treatment period begins with week 11, which is after all households received notice of their treatment.
* p<0.1. ** p<0.05. *** p<0.01.


                                         Table 6: Impact of Price Frame on Expenditures and Quantities Purchased
                                                            (standard errors in parentheses)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                   Expenditures                                                                  Quantities
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                     Less        All Rated                   All                      Less        All Rated
                    Nutritious    Nutritious       Items        Unrated     Items    Nutritious    Nutritious       Items        Unrated      All Items
--------------------------------------------------------------------------------------------------------------------------------------------------------
Subsidy               ^$0.78        ^$2.29        ^$3.07         $1.60     ^$1.47        0.523        ^1.220        ^0.698      ** 0.917         0.220
                       (3.655)       (4.914)       (8.225)       (1.376)   (9.041)      (1.600)       (1.884)       (3.327)       (0.450)       (3.627)
Tax                    $4.52         $1.89         $6.41        ^$0.07      $6.34        2.287         0.896         3.182         0.306         3.489
                       (3.489)       (4.784)       (7.908)       (1.460)   (9.015)      (1.564)       (1.925)       (3.325)       (0.461)       (3.654)
Tax/Subsidy           ^$0.42        ^$4.40        ^$4.82         $0.84     ^$3.98       ^0.002        ^2.384        ^2.386         0.752        ^1.634
                       (4.371)       (5.831)       (9.942)       (1.466)   (11.010      (1.876)       (2.293)       (4.044)       (0.527)       (4.399)
                                                                                )
Weekly Dummy                                                                   
 Variables                                                                      e
N                   6,572         6,572         6,572         6,572         6,572    6,572         6,572         6,572         6,572         6,572
Unconditional         $36.55        $49.59        $86.14        $11.86     $98.50       16.132        18.853        34.985         3.609        38.744
 mean of
 dependent
 variable
--------------------------------------------------------------------------------------------------------------------------------------------------------
Participants in the intervention conditions were all combined. Regression coefficients were estimated using a fixed effects regression with weekly dummy
  variables. For the sake of space, coefficients from the weekly dummy variables were not included in the table. Because weeks were classified as Monday
  through Sunday, the baseline period ended with week 8, which is the full week prior to households receiving notice of their treatment group. In the
  baseline period, values are set to missing prior to the first shopping trip in the first 3 weeks. Once all households were enrolled in the study (by
  week 4), any missing value was set to zero. Since households received their notices between September 7-15, weeks including these dates were omitted
  from the analysis. As a result, the treatment period begins with week 11, which is after all households received notice of their treatment.
* p<0.1. ** p<0.05. *** p<0.01.
a p<0.05 for difference between Subsidy and Tax.
b p<0.05 for difference between Subsidy and Tax/Subsidy.
c p<0.05 for difference between Tax and Tax/Subsidy.


                                        Table 7: Overall Price Effect on Weekly Household Expenditures, by Income
                                                            (standard errors in parentheses)
--------------------------------------------------------------------------------------------------------------------------------------------------------
              Households at or Below 130% of the Federal Poverty Line                         Households Above 130% of the Federal Poverty Line
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                     Less        All Rated                   All                      Less        All Rated
                    Nutritious    Nutritious       Items        Unrated     Items    Nutritious    Nutritious       Items        Unrated      All Items
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Treatment          $7.03         $7.11        $14.14         $2.47     $16.61      ^$1.27        ^$4.02        ^$5.29         $0.24        ^$5.05
 Groups
                       (6.010)       (9.793)      (15.460)       (2.597)   (17.420      (3.707)       (4.543)       (7.898)       (1.313)       (8.893)
                                                                                )
Weekly Dummy                                                                   
 Variables                                                                      e
N                   1,141         1,141         1,141         1,141         1,141    4,904         4,904         4,904         4,904         4,904
Unconditional         $28.28        $41.04        $69.32         $9.17     $78.85      $38.36        $50.70        $89.06        $12.25       $101.81
 mean of
 dependent
 variable
--------------------------------------------------------------------------------------------------------------------------------------------------------
Participants in the intervention conditions were all combined. Regression coefficients were estimated using a fixed effects regression with weekly dummy
  variables. For the sake of space, coefficients from the weekly dummy variables were not included in the table. Because weeks were classified as Monday
  through Sunday, the baseline period ended with week 8, which is the full week prior to households receiving notice of their treatment group. In the
  baseline period, values are set to missing prior to the first shopping trip in the first 3 weeks. Once all households were enrolled in the study (by
  week 4), any missing value was set to zero. Since households received their notices between September 7-15, weeks including these dates were omitted
  from the analysis. As a result, the treatment period begins with week 11, which is after all households received notice of their treatment.
* p<0.1. ** p<0.05. *** p<0.01.
d p<0.05 difference of estimates for the same type of food (all items, all rated items, etc.) but across demographic comparisons.


                                      Table 8: Overall Price Effect on Weekly Household Expenditures, by Education
                                                            (standard errors in parentheses)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                           High School Education or Less                                               More than High School Education
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                     Less        All Rated                   All                      Less        All Rated
                    Nutritious    Nutritious       Items        Unrated     Items    Nutritious    Nutritious       Items        Unrated      All Items
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Treatment          $2.36        ^$4.02        ^$1.65         $6.18      $4.52       $0.52        ^$2.17        ^$1.65         $0.46        ^$1.19
 Groups
                      (11.190)      (20.950)      (31.600)       (4.130)   (34.200      (3.091)       (3.925)       (6.714)       (1.139)       (7.528)
                                                                                )
Weekly Dummy                                                                   
 Variables                                                                      e
N                     567           567           567           567           567    5,759         5,759         5,759         5,759         5,759
Unconditional         $25.16        $39.92        $65.08         $8.76     $74.23      $37.73        $50.41        $88.14        $12.05       $100.67
 mean of
 dependent
 variable
--------------------------------------------------------------------------------------------------------------------------------------------------------
Participants in the intervention conditions were all combined. Regression coefficients were estimated using a fixed effects regression with weekly dummy
  variables. For the sake of space, coefficients from the weekly dummy variables were not included in the table. Because weeks were classified as Monday
  through Sunday, the baseline period ended with week 8, which is the full week prior to households receiving notice of their treatment group. In the
  baseline period, values are set to missing prior to the first shopping trip in the first 3 weeks. Once all households were enrolled in the study (by
  week 4), any missing value was set to zero. Since households received their notices between September 7-15, weeks including these dates were omitted
  from the analysis. As a result, the treatment period begins with week 11, which is after all households received notice of their treatment.
* p<0.1. ** p<0.05. *** p<0.01.
d p<0.05 difference of estimates for the same type of food (all items, all rated items, etc.) but across demographic comparisons.


                                            Table 9: Impact of Price Frames on Weekly Expenditures, by Income
                                                            (standard errors in parentheses)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                          Poverty Income Ratio <= 1.3                                                   Poverty Income Ratio >1.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                 Less        All Rated                    All                       Less         All Rated
                Nutritious    Nutritious       Items         Unrated     Items    Nutritious     Nutritious        Items         Unrated      All Items
--------------------------------------------------------------------------------------------------------------------------------------------------------
Subsidy            11.58     * a $21.23    * a, d $32.81  ** a $5.78    ** a, d   a ^$4.548    * a d ^$7.546  a, d ^$12.09        $0.414    d ^$11.68
                                                                        $38.59
                   (6.914)      (10.780)       (16.990)       (2.802)   (18.990      (4.434)        (5.521)         (9.534)       (1.608)      (10.490)
                                                                             )
Tax                $0.30      a ^$9.037      a ^$8.735     a ^$3.38     a ^$12.    a $3.832         $3.62         a $7.451        $0.588        $8.039
                                                                            11
                   (8.190)      (12.470)       (20.380)       (4.138)   (23.370      (4.180)        (5.334)         (9.015)       (1.540)      (10.230)
                                                                             )
Tax/Subsidy        $9.14         $8.14         $17.28      ** $5.13     $22.40      ^$2.831        ^$7.931        ^$10.76        ^$0.327      ^$11.09
                   (6.874)       (9.965)       (16.310)       (2.039)   (17.710      (5.338)        (6.790)        (11.800)       (1.750)      (13.080)
                                                                             )
Weekly Dummy                                                                   
 Variables                                                                   e
N               1,141         1,141          1,141         1,141         1,141    4,904          4,904           4,904         4,904         4,904
Unconditional     $28.28        $41.04         $69.32         $9.17     $78.85      $38.36         $50.70          $89.06        $12.25       $101.81
 mean of
 dependent
 variable
--------------------------------------------------------------------------------------------------------------------------------------------------------
Participants in the intervention conditions were all combined. Regression coefficients were estimated using a fixed effects regression with weekly dummy
  variables. For the sake of space, coefficients from the weekly dummy variables were not included in the table. Because weeks were classified as Monday
  through Sunday, the baseline period ended with week 8, which is the full week prior to households receiving notice of their treatment group. In the
  baseline period, values are set to missing prior to the first shopping trip in the first 3 weeks. Once all households were enrolled in the study (by
  week 4), any missing value was set to zero. Since households received their notices between September 7-15, weeks including these dates were omitted
  from the analysis. As a result, the treatment period begins with week 11, which is after all households received notice of their treatment.
* p<0.1. ** p<0.05. *** p<0.01.
a p<0.05 for difference between Subsidy and Tax.
b p<0.05 for difference between Subsidy and Tax/Subsidy.
c p<0.05 for difference between Tax and Tax/Subsidy.
d p<0.05 difference of estimates for the same type of food (all items, all rated items, etc.) but across demographic comparisons.


                                          Table 10: Impact of Price Frame on Weekly Expenditures, by Education
                                                            (standard errors in parentheses)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                           High School Education or Less                                               More than High School Education
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                     Less        All Rated                   All                      Less        All Rated
                    Nutritious    Nutritious       Items        Unrated     Items    Nutritious    Nutritious       Items        Unrated      All Items
--------------------------------------------------------------------------------------------------------------------------------------------------------
Subsidy               ^$0.65        ^$3.86        ^$4.51         $7.38      $2.87      ^$0.97        ^$2.71        ^$3.68         $1.37        ^$2.31
                      (11.440)      (21.320)      (32.150)       (6.381)   (34.410      (3.824)       (4.986)       (8.414)       (1.343)       (9.226)
                                                                                )
Tax                    $2.26        ^$5.53        ^$3.26       * $6.79      $3.53       $4.19         $2.34         $6.53        ^$0.44         $6.09
                      (12.020)      (23.800)      (34.630)       (3.621)   (36.810      (3.536)       (4.636)       (7.781)       (1.523)       (8.963)
                                                                                )
Tax/Subsidy            $5.64        ^$2.81         $2.83         $4.35      $7.17      ^$1.81        ^$6.52        ^$8.33         $0.39        ^$7.94
                      (13.210)      (24.060)      (36.560)       (4.385)   (39.780      (4.705)       (5.961)      (10.400)       (1.533)      (11.470)
                                                                                )
Weekly Dummy                                                                   
 Variables                                                                      e
N                     567           567           567           567           567    5,759         5,759         5,759         5,759         5,759
Unconditional         $25.16        $39.92        $65.08         $8.76     $74.23      $37.73        $50.41        $88.14        $12.05       $100.67
 mean of
 dependent
 variable
--------------------------------------------------------------------------------------------------------------------------------------------------------
Participants in the intervention conditions were all combined. Regression coefficients were estimated using a fixed effects regression with weekly dummy
  variables. For the sake of space, coefficients from the weekly dummy variables were not included in the table. Because weeks were classified as Monday
  through Sunday, the baseline period ended with week 8, which is the full week prior to households receiving notice of their treatment group. In the
  baseline period, values are set to missing prior to the first shopping trip in the first 3 weeks. Once all households were enrolled in the study (by
  week 4), any missing value was set to zero. Since households received their notices between September 7-15, weeks including these dates were omitted
  from the analysis. As a result, the treatment period begins with week 11, which is after all households received notice of their treatment.
* p<0.1. ** p<0.05. *** p<0.01.
a p<0.05 for difference between Subsidy and Tax.
b p<0.05 for difference between Subsidy and Tax/Subsidy.
c p<0.05 for difference between Tax and Tax/Subsidy.
d p<0.05 difference of estimates for the same type of food (all items, all rated items, etc.) but across demographic comparisons.


      Table 11: Overall Price Effect on Shares of Expenditures on Nutritious Foods, by Income and Education
                                        (standard errors in parentheses)
----------------------------------------------------------------------------------------------------------------
                                                           At or Below   Above 130%    HS Educ. or  More than HS
                                                 All        130% FPL         FPL          Less          Educ.
----------------------------------------------------------------------------------------------------------------
All Treatments                                   0.0108        0.00359       0.00834      ^0.0057        0.00928
                                                (0.01)        (0.03)        (0.01)        (0.03)        (0.01)
Weekly Dummy Variables                                                      
N                                            4,816           769         3,637           342         4,266
Unconditional Mean Shares                        0.425         0.406         0.433         0.369         0.431
----------------------------------------------------------------------------------------------------------------
Shares of less nutritious and nutritious foods were calculated using only rated food purchases, thus the sign of
  the share is opposite when comparing nutritious and less nutritious foods. Participants in the intervention
  conditions were all combined. Regression coefficients were estimated using a fixed effects regression with
  weekly dummy variables. For the sake of space, coefficients for the constants and the weekly dummy variables
  were not included in the table. Because weeks were classified as Monday through Sunday, the baseline period
  ended with week 8, which is the full week prior to households receiving notice of their treatment group. In
  the baseline period, values are set to missing prior to the first shopping trip in the first 3 weeks. Once all
  households were enrolled in the study (by week 4), any missing value was set to zero. Since households
  received their notices between September 7-15, weeks including these dates were omitted from the analysis. As
  a result, the treatment period begins with week 11, which is after all households received notice of their
  treatment.
* p<0.1. ** p<0.05. *** p<0.01.
d p<0.05 difference of estimates for the same type of food (all items, all rated items, etc.) but across
  demographic comparisons.


                                   Table 12: Results of Post-Experiment Survey
                                            (on 9-point Likert Scale)
----------------------------------------------------------------------------------------------------------------
                                                               All
                              Whole Sample     Control      Treatment      Subsidy         Tax      Tax/ Subsidy
                                                Group        Groups
----------------------------------------------------------------------------------------------------------------
                                           Interpretation of Treatment
----------------------------------------------------------------------------------------------------------------
Penalty for eating unhealthy       2.9           2.6           3.0         a 2.4         a 3.4           3.2
 food
                                  (1.937)       (1.739)       (2.003)       (1.662)       (2.100)       (2.161)
Reward for eating healthy          6.2           6.1           6.3           6.0           6.0           6.9
 food
                                  (2.286)       (2.515)       (2.211)       (2.362)       (2.394)       (1.641)
Tax on unhealthy foods             3.4           2.8         * 3.6         b 2.8         * 3.7       **b 4.4
                                  (2.076)       (1.796)       (2.141)       (1.696)       (2.237)       (2.218)
Discount for eating healthy        6.4           5.8         * 6.6           6.7           6.2         * 6.9
 foods
                                  (2.225)       (2.543)       (2.077)       (2.157)       (2.313)       (1.595)
Effective in changing what I       4.5           4.2           4.6           4.8           4.2           5.0
 usually buy
                                  (2.419)       (2.444)       (2.413)       (2.250)       (2.452)       (2.568)
----------------------------------------------------------------------------------------------------------------
                         How much did being a part of the study influence your shopping?
----------------------------------------------------------------------------------------------------------------
Buy more starred foods             5.0           4.5           5.1         b 4.8         c 4.8      b, c 5.9
                                  (2.084)       (2.152)       (2.048)       (2.009)       (2.060)       (1.950)
Buy more non-starred foods         3.1           3.2           3.1           3.0           3.2           3.0
                                  (1.421)       (1.567)       (1.373)       (1.650)       (1.050)       (1.401)
Buy healthier food                 5.3           4.7           5.5         b 5.0           5.3         b 6.2
                                  (2.146)       (2.271)       (2.078)       (2.048)       (2.357)       (1.541)
Buy a higher percentage of         5.3           4.8           5.5         b 4.9           5.5         b 6.2
 healthy food
                                  (2.200)       (2.360)       (2.124)       (2.043)       (2.407)       (1.595)
----------------------------------------------------------------------------------------------------------------
                                       In general, over the entire program
----------------------------------------------------------------------------------------------------------------
Shopped healthier at the           3.3           3.1           3.4           3.4           3.1           3.6
 beginning than at the end
                                  (1.725)       (1.555)       (1.784)       (1.845)       (1.465)       (2.077)
----------------------------------------------------------------------------------------------------------------
Note that the asterisks represent differences of the annotated value from the corresponding value of the control
  group at the respective level of significance. All responses were based on a 9 point Likert scale from
  Strongly Disagree (1) to Strongly Agree (9).* p<0.1. ** p<0.05. *** p<0.01.
a p<0.05 for comparison between Subsidy and Tax groups.
b p<0.05 for comparison between Subsidy and Tax/Subsidy groups.
c p<0.05 for comparison between Tax and Tax/Subsidy groups.


     Appendix Table 1: Permutation Tests for Combined Interventions
------------------------------------------------------------------------
     Combined                             95% Lower         95% Upper
   Interventions         P-value      Confidence Level  Confidence Level
------------------------------------------------------------------------
All Households:
  Less-Nutritious.           0.700             0.671             0.728
  Nutritious......           0.724             0.695             0.752
At or below 130%
 FPL:
  Less-Nutritious.           0.481             0.450             0.512
  Nutritious......           0.253             0.226             0.281
Above 130% FPL:
  Less-Nutritious.           0.401             0.370             0.432
  Nutritious......           0.714             0.685             0.742
------------------------------------------------------------------------


      Appendix Table 2: Permutation Tests for Individual Treatments
------------------------------------------------------------------------
     Combined                             95% Lower         95% Upper
   Interventions         P-value      Confidence Level  Confidence Level
------------------------------------------------------------------------
Less-Nutritious:
  Subsidy.........           0.645             0.614             0.675
  Tax.............           0.709             0.680             0.737
  Tax/Subsidy.....           0.455             0.424             0.486
Nutritious:
  Subsidy.........           0.825             0.800             0.848
  Tax.............           0.193             0.169             0.219
  Tax/Subsidy.....           0.928             0.910             0.943
------------------------------------------------------------------------


Appendix Table 3: Permutation Tests for Separate Interventions When Data
                    Are Separated Into Income Groups
------------------------------------------------------------------------
     Combined                             95% Lower         95% Upper
   Interventions         P-value      Confidence Level  Confidence Level
------------------------------------------------------------------------
                          At or Below 130% FPL
------------------------------------------------------------------------
Less-Nutritious:
  Subsidy.........           0.056             0.043             0.072
  Tax.............           0.480             0.449             0.511
  Tax/Subsidy.....           0.448             0.417             0.479
Nutritious:
  Subsidy.........           0.102             0.084             0.122
  Tax.............           0.969             0.956             0.979
  Tax/Subsidy.....           0.204             0.179             0.230
------------------------------------------------------------------------
                             Above 130% FPL
------------------------------------------------------------------------
Less-Nutritious:
  Subsidy.........           0.179             0.156             0.204
  Tax.............           0.511             0.480             0.542
  Tax/Subsidy.....           0.242             0.216             0.270
Nutritious:
  Subsidy.........           0.298             0.270             0.327
  Tax.............           0.360             0.330             0.391
  Tax/Subsidy.....           0.611             0.580             0.641
------------------------------------------------------------------------

                              Attachment 1
Excerpt from Slim by Design_Mindless Eating Solutions for Everyday Life 
        *
---------------------------------------------------------------------------
    * Editor's note: The original format of the book, Slim by Design--
Mindless Eating Solutions for Everyday Life, has an entire section 
devoted to endnotes for all of the chapters. In this reproduction the 
endnotes are set as footnotes.
---------------------------------------------------------------------------
  slim by design. Copyright 2014 by Consumer Psych Labs, Inc. All 
rights reserved. Printed in the United States of America. No part of 
this book may be used or reproduced in any manner whatsoever without 
written permission except in the case of brief quotations embodied in 
critical articles and reviews. For information address HarperCollins 
Publishers, 195 Broadway, New York, NY 10007.
  HarperCollins books may be purchased for educational, business, or 
sales promotional use. For information please e-mail the Special 
Markets Department at [email protected].

First Edition
Designed by Paul Kepple and Ralph Geroni at Headcase Design
Illustrations by Mitch Blunt
Library of Congress Cataloging-in-Publication Data has been applied 
for.
ISBN 978-0-06-213652-7
14 15 16 17 18 ov/rrd 10 9 8 7 6 5 4 3 2 1
Contents
                Introduction
                
                [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
                
      One: Mindless Eating Solutions

                Your Food Radius
                Nobody Wants Us to Be Fat
                Chinese Buffet Confidential
                Starting Small to Get Slim
                Sixteen Pounds from Happiness
                Becoming Slim by Design
              
              [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
                
      Two: Your Slim-For-Life Home

                Fat-Proofing the Rich and Famous
                The Syracuse Study
                Step One: The Kitchen Makeover
                Step Two: Tablescape Redesign
                Step Three: Snack-Proofing
                Scoring Big at Home
              
              [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
                
      Three: Restaurant Dining By Design

                In Praise of Leftovers
                Show Me to a Slim Table
                One Antidote for Fast-Food Fever
                ``Can I Take Your Order?''
                Half-Plate Profits
                Smaller and Taller
                Bread and Water
                Faster Food and Happier Meals
                What Would Batman Eat?
                Transforming a Town
                Is Your Favorite Restaurant Making You Fat?
                
                [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
                
      Four: Supermarket Makeovers

                The Desserted Island of Denmark
                Half-Cart Solutions
                Healthy First and Green Line Guides
                Wide Aisles and High Products
                Groceries and Gum
                Lights, Stars, Numerology!
                Using the Half-Plate Rule
                The Three Checkouts
                Back to Bornholm
                How Your Grocery Store Can Make You Slim
               
               
               [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
                
      Five: Office Space and Workplace

                Move Away from the Desk
                Rethinking Corporate Wellness
                Break-Room Makeovers
                Trimming the Google-Plex of Food
                Cafeteria Cuisine
                The Company Health Club
                Coaching and Weight-Loss Programs
                Would You Sign a Health Conduct Code?
                Design Your New Boss's Job Description!
                Think Summer Camp, Not Boot Camp
                
                
                [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
                
      Six: Smarter Lunchrooms

                School Lunch 101
                When Chocolate Milk Attacks
                More Fruit by Design
                The Salad Bar Solution
                Lunch-Line Redesign, MTV-Style
                What's Your Lunchroom Score?
                The Lunchtime Report Card
                Designing a Smarter Lunchroom Tray
                Helping Your School Become Slim by Design
               
               
               
               [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
                
      Seven: Slim By Design for Life

                From Can't to CAN
                From Me to We
                Getting Started
                Design Trumps Discussion
                Sample Scripts
                Make It Happen

                Acknowledgments
                Notes
                Index
          * * * * *
Chapter Four
Supermarket Makeovers
    You've Never Seen A Kleenex Cam. That's why it works so well--it 
sees you, but you don't see it. It's helped us learn why the crazy 
things grocery shoppers do aren't as crazy as they seem.

    Back in 2001, I asked some clever engineering students at the 
University of Illinois at Urbana-Champaign to rig up a small, remotely 
controlled movie camera into what looked like an ordinary box of 
Kleenex.\1\ Using this invisible camera we could follow shoppers to 
learn exactly how they shop. We took our Kleenex Cams and stacked them 
on top of ``deserted'' shopping carts, hid them on shelves next to 
Fruity Pebbles cereal, and positioned them in our carts so we could 
follow shoppers as they moved through the aisles. The Kleenex Cams 
showed us what catches a person's eye, what they pick up and put back, 
why they buy things they'll never use,\2\ when shopping lists don't 
matter, and how they shop differently in the ``smelly'' parts of a 
grocery store. Again, these studies were all university approved.\3\
---------------------------------------------------------------------------
    \1\ The only remaining photo of the original Kleenex Cam is in this 
newspaper article below. By today's tech standards, it's pretty boring, 
but back then it was really souped up. Read about it at 
SlimByDesign.org/GroceryStores/.
    \2\ One interesting category of items that are most likely to 
become cabinet castaways are unusual foods that people are buying for a 
specific occasion. When that occasion never happens, the food just sits 
and sits. This is a neat article on that: Brian Wansink, S. Adam 
Brasel, and Stephen Amjad, ``The Mystery of the Cabinet Castaway: Why 
We Buy Products We Never Use,'' Journal of Family and Consumer Science 
92, no. 1 (2000): 104-8.
    \3\ All of these studies are preapproved. Today--compared to twenty 
or even 10 years ago--studies to be approved by a university's 
Institutional Review Board to make sure that they are safe and to make 
sure all of the data is collected anonymously and that no one will ever 
know about that day you bought that EPT kit and the two pints of 
Chocolate Fudge Swirl. Some studies--like many shopping studies--are 
observational, but others might ask a person to complete a 
questionnaire at the end of a trip in exchange for a small amount of 
money, free food, movie tickets, and so on.
---------------------------------------------------------------------------
    But let's back up and set the stage. Our best and worst eating 
habits start in a grocery store. Food that's bought here gets moved 
into our homes. Food in our homes gets eaten.\4\ If we bought more bags 
of fruit and fewer boxes of Froot Loops, we would eventually eat more 
of the first and less of the second. Although bad for the Froot Loops 
Corporation, it's great for us--and great for grocery stores. The 
typical grocery store makes more profit by selling you $10 more fruit 
than $10 more Froot Loops. There's a higher markup on fruit, and--
unlike the everlasting box of Froot Loops--fruit spoils, and spoiled 
fruit spoils profits. You have to sell it while you can.
---------------------------------------------------------------------------
    \4\ That is, about 88 percent of this food will be eaten. The 12 
percent that's wasted, however, isn't the candy, chips, and ice cream; 
it's typically the spoiled fruit and vegetables, leftovers, and cabinet 
castaways. Brian Wansink, ``Abandoned Products and Consumer Waste: How 
Did That Get into the Pantry?,'' Choices (October 2001): 46.
---------------------------------------------------------------------------
    So if a grocery store makes more by selling healthy foods like 
fruit, why don't they do a better job of it? They try--but what they 
really need is a healthy dose of redesign.

          Our best and worst eating habits start in a grocery store.

    We've been following grocery shoppers since 1995, and some things 
have changed since then. For one, we no longer have to wrestle with 
Kleenex Cams. Our newer cameras are so small they're embedded into 
Aquafina water bottles with false bottoms.\5\ The technology is sexier, 
but the results are e-x-a-c-t-l-y the same.\6\ Wherever we've done 
these studies--corner markets in Philadelphia or warehouse stores in 
France, Brazilian superstores or Taiwanese night markets--people pretty 
much shop in the same time-stressed, sensory-overwhelmed way. But 
knowing what can be done to get them to buy a healthier cartful of food 
is good for shoppers, for grocers, and even for governments.
---------------------------------------------------------------------------
    \5\ A cool example of all of these hidden cameras in use can be 
found at http://www.youtube.com/watch?v=2B0Ncy3Gz24. It's not at a 
grocery store but in a lunchroom. Same approach.
    \6\ Lots of people visit our Lab (even from way overseas) like it's 
some weird trip to Consumer Mecca. Something I've heard a number of 
times is ``Wow . . . this isn't really very high-tech!'' No, it isn't. 
What we'd like to think, however, is that insights trump glitzy 
technology every day of the week. We've got low-definition hidden 
cameras, hidden scales, counters, and timers, because we don't need 
holograms or brain-scan machines to nail down the reality--not the 
theory--of why people do what they do. You don't need infrared sensors 
to see someone eating twice as many Cheetos when you change what 
they're watching on TV.
---------------------------------------------------------------------------
    Wait. Governments?
    What jump-started a lot of our recent thinking was a request we 
received from the Danish Government. In April 2011, they sent a six-
person delegation out to my Lab. Their mission: to help Danish grocery 
stores make it easier for shoppers to shop healthier. Our mission, if 
we chose to accept it: develop a healthy supermarket makeover plan that 
would be cheap, easy, and profitable for Danish grocery stores to 
implement. Our makeover plan had to be profitable for stores because 
that's the only way it would work. But here's the cool clincher: They'd 
give us an entire island on which to test our plan.
The Desserted Island of Denmark
    Bornholm Is A Danish Island with forty-two thousand inhabitants 
that sits in the Baltic Sea, one hundred miles east of Copenhagen.\7\ 
The Government of Denmark wanted us to help change the grocery stores 
on the entire island so they could profitably help these islanders shop 
healthier. They wanted to turn it from a Dessert Isle into a Salad 
Aisle.
---------------------------------------------------------------------------
    \7\ Denmark Islands. Denmark actually has a number of little 
islands, but none like poor Bornholm. It never gets any peace. 
Strategically located in the Baltic Sea, it was occupied by the Germans 
during almost all of World War II and the Russians right after that. 
And probably by the Vikings way before that.

    Anyone who's read or seen H.G. Wells's The Island of Dr. Moreau 
knows that islands are a researcher's dream. You can do all sorts of 
crazy, mad scientist things on them and not worry about the rest of the 
world bothering you. You can change the shopping carts or layout of all 
the stores on the island, and if the sales of Crisco and Pixy Stix drop 
by 20 percent, you know it's not because people are swimming over to 
buy them in Lapland.
    Until they came to talk with us, the Danish Government was 
considering three types of changes: tax it, take it, or teach it.\8\ 
But taxing food or taking it away creates pushback. Shoppers don't like 
it, grocers don't like it, and so it can often backfire. For instance, 
when we did a 6 month study on taxing soft drinks in grocery stores in 
Utica, New York, a medium-size city in the United States, we found that 
the only people who bought fewer soft drinks were beer-buying 
households--and they just bought a lot more beer.\9\ People had to 
drink something with their pizza and burgers, and it wasn't going to be 
tap water or soy milk. They changed from Coke to Coors.
---------------------------------------------------------------------------
    \8\ People--whether public health professionals or politicians--can 
often get very dramatic in what they tell grocery stores they should 
do. Dramatic, but not always realistic or right.
    \9\ This is an interesting paper of unintended consequences: Brian 
Wansink et al., ``From Coke to Coors: A Field Study of a Sugar-
Sweetened Beverage Tax and Its Unintended Consequences,'' May 26, 2012, 
available at http://ssrn.com/abstract=2079840 or http://dx.doi.org/
10.2139/ssrn.2079840.
---------------------------------------------------------------------------
    And teaching doesn't work much better.\10\ As shoppers, we don't 
behave the way we're supposed to because (1) we love tasty food, and 
(2) we don't like to think very hard. Because of our love for both 
tasty food and for mindless shopping, we don't approach grocery 
shopping like a nutrition assignment. We just do it and move on to the 
next fifty-seven items on our to-do list. With this mindless mindset, 
when we're shopping at 5:45 on a Friday evening, we're not about to be 
fazed by there being a few more calories in pizza crust than in pita 
bread.
---------------------------------------------------------------------------
    \10\ This is controversial for me to admit since I'm the immediate 
past president of the Society for Nutrition Education and Behavior and 
because I was the White House-appointed person (2007-2009) in charge of 
promoting the [D]ietary [G]uidelines for the USDA.


    Maybe the best way we can change grocery shopping habits is to make 
them more mindlessly healthy--make it more convenient, attractive, and 
normal to pick up and buy a healthier food.\11\ So here's what we did 
in Bornholm. Based on our ``Kleenex Cam'' recordings,\12\ notes, 
stopwatch times, and data from thousands of similar shoppers, we 
focused on design changes in five areas of the store: carts, layouts, 
aisles, signs, and checkout lines. We had two criteria: (1) all the 
changes had to make the store more money in a month than they cost to 
implement, and (2) they all had to help make people slim by design. 
Let's start with a shopping cart.
---------------------------------------------------------------------------
    \11\ This was one focus of my book Mindless Eating. The basic idea 
is that making small changes around you that you don't even really 
notice has a tremendous long-term impact on changing behavior and 
weight.
    \12\ We no longer use the Kleenex Cam but we still call it that. We 
now use our bottles, hats, and iPhones.
---------------------------------------------------------------------------
Half-Cart Solutions
    Here's a Ten-Word Description of how most people shop for 
groceries: They throw things in their cart and they check out. What's 
the right amount of fruits and vegetables to put in a cart? We don't 
really know because we don't really care. Yet imagine what would happen 
if every time we put something in our cart we had to ask ourselves 
whether it was healthy or not. It would be irritating--for sure--but 
after a while we'd think twice about what we casually threw in. Just 
stopping and thinking for a split second would be enough to snap us out 
of our mindlessly habitual zombie shopping trance.13-14
---------------------------------------------------------------------------
    \13\ A number of years ago we gave secretaries dishes of chocolate 
Kisses that we either placed on their desk or 6 from their desk. We 
found that those who had to walk only 6 ate \1/2\ as much candy (100 
calories less; four each day instead of nine). Yet when we asked them 
if it was because the 6 walk was too far or too much of a hassle, 
their answer surprised us. They said instead that the 6 distance gave 
them a chance to pause and ask themselves if they were really that 
hungry. Half the time they'd answer ``no.'' The key was that 
something--that distance--caused them to pause and interrupt their 
mindlessness: Brian Wansink, James E. Painter, and Yeon-Kyung Lee, 
``The Office Candy Dish: Proximity's Influence on Estimated and Actual 
Candy Consumption,'' International Journal of Obesity 30, no. 5 (May 
2006): 871-75.
    \14\ Anything that stops and makes a person pause--even for a split 
second--might be enough to knock them out of their mindless trance and 
rethink.

    Back to the cart. When most of us shop, fruits and vegetables take 
up only 24 percent of our cart.\15\ But suppose your grocery store 
sectioned a cart in \1/2\ by taping a piece of yellow duct tape across 
the middle interior. And suppose they put a sign in the front of the 
cart that recommended that you put all the fruits and vegetables in the 
front and all the other foods in the back. This dividing line in the 
cart doesn't moralize or lecture. It just encourages shoppers to ask 
themselves whether the food in their hand goes in the front or back of 
the cart. There's nothing to resist or rage against--they're simply 
sorting their food . . . if they want to.
---------------------------------------------------------------------------
    \15\ The average grocery shopper buys only 24 percent of fruits and 
vegetables. Simone French, Melanie Wall, Nathan R. Mitchell, Scott T. 
Shimotsu, and Ericka Welsh, ``Annotated Receipts Capture Household Food 
Purchases from a Broad Range of Sources,'' International Journal of 
Behavioral Nutrition and Physical Activity 6, no. 37 (2009).
---------------------------------------------------------------------------
    When you use duct tape at home, you become MacGyver. When it's used 
to divide your grocery cart, you become healthier.\16\
---------------------------------------------------------------------------
    \16\ Brian Wansink, C.R. Payne, K.C. Herbst, and D. Soman, ``Part 
Carts: Assortment Allocation Cues That Increase Fruit and Vegetable 
Purchases,'' Journal of Nutrition Education and Behavior 45 (2013): 4S, 
42.
---------------------------------------------------------------------------
    We made a few dozen of these divided carts to test at supermarkets 
in Williamsburg, Virginia, and Toronto, Canada.\17\ When people 
finished shopping and returned their souped-up, tricked-out carts, we 
gave them a gift card to a local coffee shop if they would answer some 
questions and give us their shopping receipt.
---------------------------------------------------------------------------
    \17\ Brian Wansink, Dilip Soman, Kenneth C. Herbst, and Collin R. 
Payne, ``Partitioned Shopping Carts: Assortment Allocation Cues that 
Increase Fruit and Vegetable Purchases,'' under review.
---------------------------------------------------------------------------
    Shoppers with these divided carts spent twice as much on fruits and 
vegetables. They also spent more at the store--about 25 percent more. 
Not only did this fruit and vegetable divider make them think twice 
about what they bought; it also made them believe that buying more 
fruits and vegetables was normal. Who knows how much healthy stuff your 
neighbor buys? It must be about \1/2\, people think as they throw in 
some pears and three more red peppers.

------------------------------------------------------------------------
                   How Your Grocer Can Help You . . .
-------------------------------------------------------------------------
                        Test the Half-Cart Waters
------------------------------------------------------------------------
    Will a divided, half-cart approach be profitable? It can if it can
 sell more perishable produce--like fruits and vegetables. All that's
 needed is a visual divider in a few of your carts and a sign in the
 front that says, ``Put your fruits and vegetables in the front of your
 cart.''
    If your grocery store doesn't want to bust out the duct tape, they
 can use printable mats for the bottom of the cart that make the same
 suggestion--fruits and vegetables in the front \1/2\ and everything
 else in back (download at SlimByDesign.org).
------------------------------------------------------------------------

The Miracle of Duct Tape
A Half-Cart Solution


[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Do it yourself. Divide your cart with your coat, your purse, 
        or your briefcase. Or bring your own duct tape.

------------------------------------------------------------------------
                          What You Can Do . . .
-------------------------------------------------------------------------
                      Hints for Half-Cart Shopping
------------------------------------------------------------------------
    Your local supermarket might not have divided carts yet, and you
 probably don't travel with your own. Here's what you can do . . .
 
   Decide what you want to buy more of. For instance, a shopper
   with children might want to be nudged to buy more fruits and
   vegetables, and a shopper with high blood pressure might want to buy
   more low-sodium foods. A dieter might want to be nudged to buy more
   low-carb foods, and a diabetic might want to buy more foods with a
   low glycemic index.
 
   Physically divide your cart by putting something across the
   middle. This could be a purse, backpack, scarf, briefcase, coat, or a
   sleeping child you want to keep an eye on. You can then claim the
   front half of . . . our cart for whatever you want to purchase more
   of. If that target space isn't full, you'll naturally tend to buy
   more to balance things out.
------------------------------------------------------------------------

          You're 11 percent more likely to take the first vegetable you 
        see than the third.
          When opening your cupboard, you're three times as likely to 
        take the first cereal you see as you are the fifth.
Healthy First and Green Line Guides
    When You Walk Up To A Buffet, you're 11 percent more likely to take 
the first vegetable you see than the third.\18\ When opening your 
cupboard, you're three times as likely to take the first cereal you see 
as you are the fifth.\19\ The same is true in grocery stores. When you 
start shopping, you can't wait to start piling things in your cart. But 
after it starts filling up, you become more selective. If stores could 
get you to walk by more of the healthy--and profitable--foods first, 
they might be able to get you to fill up the cart on the good stuff, 
and squeeze out any room for the Ben & Jerry's variety pack.
---------------------------------------------------------------------------
    \18\ A really robust finding. A great reason why you should also 
pass around the salad and green beans to your kids at dinnertime before 
you bring out the lasagna. Brian Wansink and David Just, ``Healthy 
Foods First: Students Take the First Lunchroom Food 11% More Often than 
the Third,'' Journal of Nutrition Education and Behavior 43 (2011): 
4S1, S9.
    \19\ You can just believe me, or you can read ponderous evidence of 
why this happens: Pierre Chandon and Brian Wansink, ``When Are 
Stockpiled Products Consumed Faster? A Convenience-Salience Framework 
of Postpurchase Consumption Incidence and Quantity,'' Journal of 
Marketing Research 39, no. 3 (2002): 321-35.

          We spend less than 6 minutes in the fruit and vegetable 
---------------------------------------------------------------------------
        section.

    Most grocery stores in the United States place the fruit and 
vegetable section on the far right of the store. It's the first thing 
we see and wander over to. The bad news is that many of us spend less 
than 6 minutes there.\20\ We pick up some apples and lettuce and then 
wander over to the next aisle. But if stores could get us to linger 
there a little longer, we'd buy a little bit more.
---------------------------------------------------------------------------
    \20\ This is a really neat finding, but it seems like it will take 
a miracle to get it published. In the meantime, you can find it on 
SSRN: Brian Wansink and Kate Stein, ``Eyes in the Aisle: Eye Scanning 
and Choice in Grocery Stores,'' 2013.
---------------------------------------------------------------------------
    The secret might lie in the fact that we're wanderers--we're not 
always very deliberate. What if they put a dashed green line that 
zigzagged through the produce section, and what if they put floor 
decals in front of food shelves that offer healthy meal ideas? Just 
like that dashed yellow line on the highway that keeps you mindlessly 
on the road and the billboards that keep you mindlessly amused, maybe 
putting a dashed green line and floor decals would also have us 
wandering the produce section a bit longer.
    To test this, we proposed Operation: Green Highway on our mad 
scientist island in Denmark. Supermarkets could put a 2" wide dashed 
green line through the produce section--around the apples and oranges, 
over to the lettuce, past the onions and herbs, and back around to the 
berries and kumquats. They could even include some kid-friendly visuals 
or floor graphics. If a shopper followed this green highway, he or she 
might be tempted to buy more fruits and vegetables.
    To test this, we had people initially trace their way through 
grocery stores that either did or did not have Health Highway lines. 
Did people stay on the line? Of course not, but they would have spent 
an average equivalent of 3 more minutes in the produce section. At 
about $1/minute, this would mean they could spend as much as $3 more on 
fruits and vegetables than they otherwise would have.21-22
---------------------------------------------------------------------------
    \21\ Would this dashed green line work through the rest of the 
store? It could go down some of the healthier aisles--say canned fruits 
and vegetables or foods with whole grains--and around much of the 
perimeter of the store. Yet to use the quotation from Spinal Tap again, 
``It's a fine line between clever and stupid.'' This line might work 
well in the produce section, but don't take it overboard. It might be 
irritating or too strange in the rest of the store--particularly 
because these long aisles might make it look like a highway divider.
    \22\ My good colleagues Collin Payne and David Just have early 
evidence that this works well when it's first laid out. See Collin R. 
Payne and David R. Just, ``Using Floor Decals and Way Finding to 
Increase the Sales of Fruits and Vegetables,'' under review.
---------------------------------------------------------------------------
    But what about the other store aisles? Let's say that you have two 
favorite grocery stores: Tops and Hannaford. At Tops, the aisle after 
the produce section--let's call it Aisle 2--is the potato chips, 
cookies, and soft drinks aisle. At Hannaford, the potato chips, 
cookies, and soft drinks are in Aisle 15--the second-to-last aisle in 
the store. If you're on a diet, which store should you choose?
    We followed 259 shoppers in Washington, D.C., grocery stores to see 
if a person shops differently depending on which aisle they're in.\23\ 
We discovered that most people with shopping carts behave the same way: 
They walk through the produce section, then turn and go down Aisle 2 
(which leads back toward the front of the store). It almost doesn't 
matter what's in the aisle--health food, dog food, or mops. At this 
point, shopping's still a fun adventure. But after Aisle 2, shoppers 
get mission-oriented and start skipping aisles as they look for only 
what they think they need. So, Aisle 2 gets the most love and attention 
from the most shoppers.
---------------------------------------------------------------------------
    \23\ Wansink and Stein, ``Eyes in the Aisle.''
---------------------------------------------------------------------------
    So, what's in Aisle 2 at your favorite grocery store? It's often 
soft drinks, chips, or cookies as in the Tops store. To make a grocery 
store more slim by design, managers could easily load up this aisle 
with whatever healthier food is most profitable for them. This might be 
store-brand canned vegetables, whole-grain foods, or high-margin lower-
calorie foods. First in sight is first in cart.

------------------------------------------------------------------------
                   How Your Grocer Can Help You . . .
-------------------------------------------------------------------------
                    Guiding Angles, Aisles, and Lines
------------------------------------------------------------------------
    One way to help shoppers fill up their carts with healthy foods is
 to make sure those are the aisles they visit first and stay in longest.
 People cherry-pick their favorite fruits and vegetables and quickly
 move to the center of the store, but you can keep them in the produce
 area longer by angling displays so they guide shoppers through the
 store--think of the 30 and 45 angles you used to see in those old-
 school pinball games. Also, green lines--Green Highways--seem to nudge
 most of us, at least occasionally, to turn in a direction we otherwise
 wouldn't have turned in.
    Since shoppers are more likely to buy healthy foods when their carts
 are empty, stores should load up Aisles 1, 2, and 3 with whatever's
 healthiest and most profitable.
------------------------------------------------------------------------


------------------------------------------------------------------------
                          What You Can Do . . .
-------------------------------------------------------------------------
                     Wander the Healthy Aisles First
------------------------------------------------------------------------
    Following the green line works well if there is a green line. But if
 there isn't one, you can always make your own.
 
   Make a point of wheeling through as many of the produce
   aisles as possible. Even if it's fast and furious, simply seeing more
   fruits and vegetables while your cart is empty makes them more
   tempting.
 
   Hit the other healthier aisles--like those with canned and
   frozen fruits and vegetables--before you head for the Crunch & Munch
   section.
------------------------------------------------------------------------

Wide Aisles and High Products \24\
---------------------------------------------------------------------------
    \24\ If you want a beleaguered researcher's view of how this works, 
here's an op-ed: Kate Stein, ``Shop Faster,'' New York Times, April 15, 
2009, p. A29.
---------------------------------------------------------------------------
    The More Time You Spend in a store, the more you buy. Similarly, 
the more time you spend in an aisle, the more you buy.25 In 
order for us to buy a healthy food, we need to (1) see it and (2) have 
the time to pick it off the shelf.
---------------------------------------------------------------------------
    \25\ One source for this is Brian Wansink and Aner Tal, 
``Correlates of Purchase Quantities in Grocery Stores,'' under review.

    But not all shelves are the same. Food placed at eye level is 
easier to spot and buy. For instance, kids' foods are placed at their 
eye level, so that they can irritate us into buying them (``I want it! 
I want it! I want it!'').
    This works for Count Chocula and our kids, but would it for kale 
chips and us? We returned to our ``I-Spy'' habits and observed 422 
people purchasing thousands of products in the Washington, D.C., area. 
First we estimated the height of each shopper using a series of pre-
marked shelves they walked by (picture those height-marker decals on 
the doors of convenience stores).\26\ We then measured the height of 
each product they looked at. Based on where they looked, we could 
figure out what percent of the foods they bought were at eye level.\27\
---------------------------------------------------------------------------
    \26\ Of course this is less accurate than measuring people barefoot 
with a German-made stadeometer, but knowing someone's relative height 
is probably sufficient. Being able to document that a 6 male is taller 
than a 5 5" female is close enough for this calibration. This issue of 
precision does raise to mind the comedian Ron White's quote ``I'm a 
pretty big guy--between 6 and 6 6"--depending on what convenience 
store I'm coming out of.''
    \27\ In this study with Kate Stein, we tracked what people put in 
their carts but we didn't track them to the cash register. Still, 
unless someone changes their mind when in the National Enquirer 
checkout line, we assume that what they took, they probably bought.
---------------------------------------------------------------------------
    If you're shopping in a narrow aisle, 61 percent of everything 
you'll buy is within 1 of your eye level--either 1 above or 1 
below.\28\ This is useful to know if you're a grocery-store owner who 
wants to sell us healthier foods. Smart store managers can put these 
profitable healthy foods at eyeball level. If the product is one that's 
typically bought by males, it can be placed even 5" higher, since the 
average male is that much taller than the average female.
---------------------------------------------------------------------------
    \28\ And 12" is even a stretch. Most purchased products were within 
a 6 range--higher or lower--of eye level for a particular shopper. 
This includes 37 percent of what women put in their cart and 44 percent 
for men. To stretch the range of products purchased even further, widen 
the shopping aisles. If an aisle is narrow--6 or less--61 percent of 
the products you buy will be within 12" of eye level. But if you're in 
a wider aisle, you look higher and lower. If it's only 2 wider, \1/2\ 
of what you buy will be outside this eye zone. But wide aisles also 
have something else going for them.
---------------------------------------------------------------------------
    One well-known finding among people watchers is that nothing causes 
a person to scoot out of an aisle faster than when someone accidentally 
brushes against their behind. In his book Why We Buy, Paco Underhill 
refers to this as the ``butt brush.'' \29\ Think of the last time this 
happened to you--five seconds later you had pretty much teleported 
yourself to another spot in the store. Since brushing against people 
probably happens much more in narrow grocery store aisles than wide 
ones, people might spend less time and buy fewer items there. Many 
grocery store aisles range from 6 to 8 wide. In the Washington, D.C., 
grocery stores mentioned earlier, we measured the width of all the 
aisles and timed how long the average shopper spent in them. Indeed, 
the wider the aisle, the more they bought. It didn't matter what was 
there--canned Brussels sprouts, twenty-pound bags of cat food, 
dishwashing liquid--the more time they spent in the aisles, the more 
items they bought.\30\
---------------------------------------------------------------------------
    \29\ Paco Underhill, Why We Buy: The Science of Shopping (New York: 
Simon & Shuster, 2000).
    \30\ There's also an irritation factor with narrow aisles. If a 
person can't see a clear way through an aisle, they might be less 
likely to go down it. And if you keep getting interrupted by people as 
you're trying to shop because they're scooting by you, you're less 
likely to linger.
---------------------------------------------------------------------------
    Your grocer could put more healthy, high-margin food in wider 
aisles and less healthy food in narrower ones. Identifying or creating 
healthy food aisles that are wider would be one solution. Another 
solution--make sure the healthier foods are at eye level.\31\
---------------------------------------------------------------------------
    \31\ Kate Stein and Brian Wansink, ``Eye Height and Purchase 
Probability,'' under review.
---------------------------------------------------------------------------
Eye-Level Shopping Bull's-Eye


[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          * 60 percent of what shoppers buy is within 12" of their eye 
        height.
Slim-By-Design Grocery Shopping

[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

Groceries and Gum
    Most of Us Know that it's a bad personal policy to go shopping on 
an empty stomach. We think it's because we buy more food when we're 
hungry--but we don't. In our studies of starving shoppers, they buy the 
exact same amount of food as stuffed shoppers. They don't buy more, but 
they buy worse.\32\ When we're hungry, we buy foods that are convenient 
enough to eat right away and will stop our cravings.\33\ We don't go 
for broccoli and tilapia; we go for carbs in a box or bag. We go for 
one of the ``Four C's'': crackers, chips, cereal, or candy. We want 
packages we can open and eat with our right hand while we drive home 
with our left.
---------------------------------------------------------------------------
    \32\ Here's the best proof of why you shouldn't shop when you're 
hungry: Brian Wansink, Aner Tal, and Mitsuru Shimizu, ``First Foods 
Most: After 18-Hour Fast, People Drawn to Starches First and Vegetables 
Last,'' Archives of Internal Medicine 172, no. 12 (June 2012): 961-63.
    \33\ This is a current working paper by Brian Wansink and Drew 
Hanks, ``Timing, Hunger, and Increased Sales of Convenience Foods.'' 
Hopefully it will be published in time for our retirement.

    When it comes to cravings, our imagination is the problem. The 
cravings hit us super-hard when we're hungry because our hunger leads 
us to imagine what a food would feel like in our mouth if we were 
eating it. If your Girl Scout neighbor asked you to buy Girl Scout 
cookies, you'd buy one or two boxes. But if she were to instead ask you 
to describe what it's like to eat your favorite Girl Scout cookie, you 
would start imagining the texture, taste, and chewing sensation, and 
wind up ordering every life-giving box of Samoas she could carry. (Keep 
this in mind the next time your daughter wants to win the gold medal in 
---------------------------------------------------------------------------
cookie sales.)

          Starving shoppers don't buy more, but they buy worse.

    Most food cravings--including those that occur when we shop--are 
largely mental. As with the Girl Scout cookies, they seem to be caused 
when we imagine the sensory details of eating a food we love--we start 
imagining the texture, taste, and chewing sensation. But if we could 
interrupt our imagination, it might be easier to walk on by.
    One way we can interrupt these cravings is by simply chewing gum. 
Chewing gum short-circuits our cravings. It makes it too hard to 
imagine the sensory details of crunchy chips or creamy ice cream. My 
colleague Aner Tal and I discovered this when we gave gum to shoppers 
at the start of their shopping trip. When we reconnected with them at 
the end of their trip, they rated themselves as less hungry and less 
tempted by food--and in another study we found they also bought seven 
percent less junk food than those who weren't chewing gum.\34\ If you 
shop for groceries just before dinner, make sure the first thing you 
buy is gum--and our early findings show that sugarless bubble gum or 
mint-flavor might work best.
---------------------------------------------------------------------------
    \34\ One of the ways we've tested this is by intercepting grocery 
shoppers in the parking lot on their way into a store. We ask them to 
answer a couple of questions about the store and if we can talk to them 
after they shop. If they say yes, we tag their cart so we can catch 
them as they check out. At that time, we ask them a few questions about 
their experience and if we can have a copy of their shopping receipt. A 
second group of people get the exact same treatment, except that 
they're also given a piece of sugarless gum as a thank-you. We tag 
their cart with a different color tag, and again catch them as they 
check out.

          Most food cravings--including those that occur when we shop--
        are largely mental.
          Chewing gum short-circuits our cravings. It makes it too hard 
        to imagine the sensory details of crunchy chips or creamy ice 
        cream.
Lights, Stars, Numerology!
    Supermarkets Could Make Us slim by design if they only told us what 
foods were the healthiest, right? Not really. Supermarkets and food 
companies have endlessly experimented with little stickers and icons 
that they hoped would help us to eat better. They'd say things like 
``Good for You,'' ``Better for You,'' ``Don't Have a Stroke,'' and so 
on. The United Kingdom even uses a traffic light--each food has a green 
(go), yellow (slow), or red (no) icon on it.

    Do you remember these icons? Of course you don't. Most of us 
ignored them because they were too confusing, self-serving, or 
unconvincing. Oh, and even when people did pay attention to them, they 
often backfired. Some people believed the green and yellow foods were a 
lot healthier than they actually were and gorged out on them. Then food 
companies got tricky and took advantage of this by producing foods that 
barely met the minimum requirements for a green or yellow icon. Getting 
the healthy icon then became more important than actually coming up 
with a healthier product.

          Most labeling systems seem to backfire because we ignore them 
        or we game them.

    One exception seems to be the Guiding Stars program. Back in 2005, 
an innovative, brilliant, high-end grocery store in New England--
Hannaford Brothers--boldly stuck its neck out by putting bright yellow 
stars next to the healthiest foods on their shelves--super-healthy 
foods even got three stars. So, did people buy better food? Well, 
according to one study, they didn't initially seem to buy any more of 
the starred food. But they initially did buy less of the unstarred 
foods. They didn't buy more tofu, though this led them to think twice 
about the Doritos.\35\
---------------------------------------------------------------------------
    \35\ This is a great study that shows surprisingly that either 
taxing bad foods or subsidizing good foods seems to backfire. When you 
subsidize healthy foods, people buy more of both healthy and unhealthy 
foods. When you tax unhealthy foods, shoppers by less of both unhealthy 
and healthy foods. John Cawley et al., ``How Nutrition Rating Systems 
in Supermarkets Impact the Purchases of Healthy and Less Healthy 
Foods,'' under review.
---------------------------------------------------------------------------
    But here's why most of these labeling systems seem to backfire: (1) 
We don't believe them, or (2) we game them. We know an apple gets a 
green light, an A+, or a 100 percent rating. And we know a Twinkie gets 
a red light, a D^, and a two percent rating. It's the stuff in the 
middle that turns us into nonbelievers. If a food gets a rating that 
doesn't line up with our intuition, it totally loses credibility. When 
the magic formula is too complicated or too secret, we dismiss these 
ratings as ridiculous and ignore them.
    But worse than our ignoring them is when we game the system. We're 
experts at getting around something we don't want to do or believe. If 
one type of cracker is rated five points higher than another type of 
cracker, we choose it instead of an orange.\36\ Then we end up 
rewarding ourselves by eating more of them.\37\
---------------------------------------------------------------------------
    \36\ This is an award-winning article that opened a lot of eyes 
with the health halo concept: Pierre Chandon and Brian Wansink, ``The 
Biasing Health Halos of Fast Food Restaurant Health Claims: Lower 
Calorie Estimates and Higher Side-Dish Consumption Intentions,'' 
Journal of Consumer Research 34, no. 3 (October 2007): 301-14.
    \37\ There's a ton of evidence here that's compelling, but way too 
detailed to talk about in the text. It happens with both low-fat foods 
and with foods with healthy names. Knock yourself out reading these two 
detailed (but award-winning papers): One's mentioned in the prior note 
and the other one is Brian Wansink and Pierre Chandon, ``Can Low-Fat 
Nutrition Labels Lead to Obesity?,'' Obesity 14 (September 2006): A49-
50.

------------------------------------------------------------------------
                          What You Can Do . . .
-------------------------------------------------------------------------
            Use Your Intuition First and Their Labels Second
------------------------------------------------------------------------
    Relying too much on ratings is confusing and can backfire. Even if
 your grocery store is using them, rely first on your common sense and
 only use the ratings to break ties between brands--Count Chocula beats
 Cap'n Crunch.
    But don't celebrate your slightly smarter choice with a double-wide
 candy bar. That's the compensation danger in a health halo world.
------------------------------------------------------------------------

Using the Half-Plate Rule
    Each Spring, Wegmans, a popular grocery chain in the Northeast, 
does a big health promotion push called ``Eat well. Live well.'' From 
time to time, we've helped develop new ideas for their stores. In 2009, 
they visited our Lab to see if we could help develop a program that 
would encourage their own employees to eat more fruit and vegetables. 
They were thinking of providing some sort of education or promotion 
program. Instead, we were thinking of giving them a simple, visual rule 
of thumb. What we told Wegmans worked great for them, and it can work 
great for you in the store and even when you get home.

    In the good old days when we were kids, eating was easy. Your 
grandmother piled dishes of food on the table, you'd take a little of 
each, and--ta-da--that was nutrition! Today, the 273-page United States 
Dietary Guidelines tips the scale at almost 3 pounds. But there's an 
easier way for most people. When I was the executive director in charge 
of the Dietary Guidelines and people asked me how they should eat, 
although not the official USDA-sanctioned answer, my shortcut answer 
was to simply encourage them to use my Lab's Half-Plate Rule.\38\ Half 
of their plate had to be filled with fruit, vegetables, or salad, and 
the other \1/2\ could be anything they wanted. It could be lamb, a 
blueberry muffin, a handful of cheese . . . anything. They could also 
take as many plates of food as they wanted. It's just that every time 
they went back for seconds or thirds, \1/2\ their plate still had to be 
filled with fruit, vegetables, or salad.
---------------------------------------------------------------------------
    \38\ Wansink, Mindless Eating, pp. 178-9+.
---------------------------------------------------------------------------
Half-Plate Healthy



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          * Follow the Half-Plate Rule.

    Could a person load up \1/2\ of their plate with Slim Jims and pork 
bellies? Sure, but they don't. Giving people freedom--a license to eat 
with only one simple guideline--seems to keep them in check. There's 
nothing to rebel against, resist, or work around. As a result, they 
don't even try. They also don't seem to overeat.\39\ They may want more 
pasta and meatballs or another piece of pizza, but if they also have to 
balance this with a \1/2\ plate of fruit, vegetables, or salad, many 
people decide they don't want it bad enough.\40\
---------------------------------------------------------------------------
    \39\ Check out the article Brian Wansink and Kathryn Hoy,``Half-
plate Versus MyPlate: The Simpler the System, the Better the 
Nutrition,'' forthcoming, and Brian Wansink and Alyssa Niman, ``The 
Half-Plate Rule vs. MyPlate vs. Their Plate: The Effect on the Caloric 
Intake and Enjoyment of Dinner,'' Journal of Nutrition Education and 
Behavior 44, no. 4 (July-August 2012): S33.
    \40\ The more latitude we give, the more likely they'll follow our 
advice. When rules become just a little too complicated or vague, we 
find reasons to stop following them. This was an early problem with 
MyPlate. When somebody starts questioning ``Where does my dessert go?'' 
or ``How am I supposed to eat fruit with dinner,'' the more likely they 
are to simply say ``Whatever'' and ignore it.

          Using our Half-Plate Rule works amazingly well at home, but 
---------------------------------------------------------------------------
        only if you also use it when you shop.

    Using our Half-Plate Rule works amazingly well at home, but only if 
you also use it when you shop.\41\ To use it, you need to have enough 
fruits, vegetables, and salad around in the first place. If as you shop 
you think about you and your family being half-plate healthy, you'll 
buy healthier and you'll also spend more. The first is good for you; 
the second is good for the store.\42\
---------------------------------------------------------------------------
    \41\ A recap of this done by Jane Andrews, Wegmans dietitian, can 
be found at http://rochester.kidsoutandabout.com/node/1901.
    \42\ See more at Wansink and Niman, ``The Half-Plate Rule vs. 
MyPlate vs. Their Plate.''
---------------------------------------------------------------------------
    Wegmans jumped on our idea. Within 2 years, it was rolled out to 
all their stores, and you can now get Half-Plate place mats, magnets, 
posters. (They renamed it the trademarkable Half-Plate Healthy.) You 
can see it in action in any of their stores, and the only place it 
works better than in a grocery store is in your home.
    Supermarkets don't have to talk about servings of fruits and 
vegetables to get the point across. All they need to do is to reinforce 
the idea that \1/2\ a plate could hold whatever fruit, vegetables, or 
salad a person wanted. They can do this on signs, specials, recipes, or 
in-store promotions--and subtly encourage people to fill their cart 
with slightly more fruits and vegetables than they typically do.\43\
---------------------------------------------------------------------------
    \43\ Learn more about how Wegmans implemented our idea at http://
www.wegmans.com/webapp/wcs/stores/servlet/
ProductDisplay?storeId=10052&partNumber=UNIVERSAL_20235.

------------------------------------------------------------------------
                          What You Can Do . . .
-------------------------------------------------------------------------
                       The Half-Plate Rule at Home
------------------------------------------------------------------------
    ``Fill \1/2\ your plate with fruit, vegetables, or salad, and fill
 the other \1/2\ with whatever you want.'' We've given this simple rule
 to tens of thousands of people because it works. People often report
 back to us that they eat fewer calories and they eat a lot more
 ``balanced'' diet than they did before. They also say they eat until
 they're full but not stuffed.\44\
\44\ Wansink and Hoy, ``Half-plate Versus MyPlate.''
    Nobody likes to be told they can't do something. With the Half-Plate
 Rule there's nothing you can't eat. You just have to eat an equal
 amount of fruit, vegetables, or salad. At some point, getting that
 fourth piece of pizza just isn't worth having to eat another \1/2\
 plate of salad. But, most important, you're the one who made that
 decision.
------------------------------------------------------------------------

          After forty-five minutes of seeing food, guess what we want?
          It's not a snack-size can of lima beans.
The Three Checkouts
    Grocery Shopping Isn't Exactly a trip to Fantasy Island, but the 
checkout line can be an exception. It's filled with guilty-pleasure 
rewards at the end of the ho-hum errand of shopping. There are bizarre 
new gum flavors like mango chutney mint, meal-size candy bars, and 
irresistibly tacky tabloids with headlines like ``Cellulite of the 
Stars.'' These aisles are entertaining, but if you're with kids, you're 
doomed. Kids in grocery checkout lines are like kids in toy stores. 
They grab, bug, beg, pout, and scream. And if we cave in to buying pink 
marshmallow puff candy shaped like Hello Kitty, we also cave in to 
buying something with lots of chocolate--for us. There's usually 
nothing in the aisle that we actually need, but after forty-five 
minutes of seeing food, guess what we want? It's not a snack-size can 
of lima beans. So we buy the Heath bar we swore we'd never buy again, 
finish it by the time we leave the parking lot, and shake our head on 
the way home . . . just as we did last week.

          Mothers shopping with children wanted more foodfree cashier 
        lines. Fathers shopping with children didn't exist.

    One supermarket solution is to set up at least one checkout line so 
it's totally candy-free.\45\ Just as large supermarkets have different 
lines for ``10 items or less'' or ``cash only,'' some lines could have 
candy, others could have healthy snacks, and some could totally be free 
of food. The stores could still sell magazines and other crazy things--
like eyeglass repair kits and superglue--but one or two aisles wouldn't 
have any food at all.
---------------------------------------------------------------------------
    \45\ See Ulla M. Toft, Lise L. Winkler, Charlotte Glumer, and Brian 
Wansink (2014), ``Candy Free Checkout Aisles: Decreasing Candy Sales in 
Bornholm Island Supermarkets,'' under review.
---------------------------------------------------------------------------
    To see what tired shoppers in grocery store parking lots thought of 
this idea, we asked, ``If your favorite supermarket had ten checkout 
lines, how many should be candy lines, healthy lines, or food-free 
lines?'' Here's what we found:

   Men shopping alone wanted all candy lines.

   Women shopping alone wanted more of the healthy food lines.

   Mothers shopping with children wanted more food-free lines.

   Fathers shopping with children didn't exist.

    An easier first step would be to help convince your local 
supermarket manager to start by simply adding a healthy line--perhaps 
selling fresh fruit, granola bars, and so on. It might be the one 
longer line shoppers wouldn't mind waiting in. When the manager sees 
those lines getting longer, he'll quickly make the bigger steps. If he 
doesn't, there are other places you can shop.

------------------------------------------------------------------------
                   How Your Grocer Can Help You . . .
-------------------------------------------------------------------------
                What If All the Aisles Were Candy Aisles?
------------------------------------------------------------------------
    If you want that food-free checkout experience but all the aisles
 are loaded up with Skittles and SweeTarts, here's what you do:
 
    1.  Tell the manager that you want to avoid impulse-buying candy
     while you're in the checkout line. Ask him or her which of the open
     checkouts would be least tempting for a dieter or a shopper with
     children.
 
    2.  While the manager is thinking, ask if they would consider
     putting in a candy-free aisle. You can mention that other stores
     (such as Hy-Vee, Wegmans, and HEB) have at least one candy-free
     checkout aisle, and you've heard they're popular with both dieters
     and parents shopping with kids. If one of those stores you mention
     happens to be a nearby competitor, it might not be too many more
     trips before you have your candy-free aisle. That will be a good
     time to say ``thank you.'' \46\
\46\ More at Ulla M. Toft, Charlotte Glumer, Lise L. Winkler, and Brian
 Wansink (2015), ``Food Free Checkout Aisles: A Danish Field Study of
 Becoming Slim by Design,'' under review.
------------------------------------------------------------------------

Which of These Would You Like To See at Your Grocery Store?



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

Back to Bornholm
    After Watching, Coding, and Analyzing Shoppers on the Danish island 
of Bornholm, we generated a small list of changes--baby steps--these 
grocers could make to profitably help shoppers become slim by design. 
We were scheduled to present these ideas to all nine grocery store 
managers at the Bornholm Island Hall after they got off work a couple 
of days later at seven thirty.

------------------------------------------------------------------------
                   How Your Grocer Can Help You . . .
-------------------------------------------------------------------------
             The Original Slim-By-Design Supermarket Pledge
------------------------------------------------------------------------
    When the Danish Government said they'd be willing to try almost
 anything we recommended, here's what we first suggested, and here's
 what paved the way for the full 100-point Supermarket Scorecard at the
 end of this chapter. We asked them to try the three changes that would
 be easiest and most profitable for them.
 
      1.  Provide divided \1/2\ carts that encourage people to put their
     fruits and vegetables in front. The dividers can be made from
     paint, duct tape, mats, etc.
 
    2.  Angle produce displays and use floor decals (such as green
     lines) to guide and keep people shopping longer in the produce
     section.
 
    3.  Place the healthiest foods in Aisles 1 through 3.
 
    4.  Make the healthiest aisles the widest and put healthy products
     at eye level or on end-of-aisle displays (endcaps).
 
    5.  Use the ``Half-Plate Rule'' promotion.
 
    6.  On end-of-aisle displays, combine the regular promotion with a
     healthy food complement.
 
    7.  Have two or three types of checkout lines: standard, food-free,
     and healthy foods only.
------------------------------------------------------------------------

    Unfortunately, 2 days later at seven thirty my five-person 
delegation of researchers almost equaled the six grocery managers who 
actually showed up. Strike one. After starting the presentation with 
the only Danish word I knew--``Velkommen'' (welcome)--I told them the 
night was all about ``new ways you can sell more of your healthier 
foods and make more money.'' We then went on to give a punchy 
presentation on seven easy changes that we knew would work well. We had 
photos, video clips of shoppers, cool study results, numbers, and funny 
stories. It was great . . . except that nobody laughed, asked a 
question, moved, or even seemed to blink. It was like Q&A hour in a wax 
museum. Strike two.

          We generated a small list of changes these grocers could make 
        to profitably help shoppers become slim by design.

    Because there were no signs of life, I idled down my enthusiasm and 
wrapped up our presentation a half hour early so my Danish colleagues 
could try to salvage the evening. Once they started talking in Danish, 
some sort of switch flipped in the managers. They started talking 
louder, started to un-Danishly interrupt each other, and then started 
arguing. Thinking things were getting out of control, I suggested we 
call it a night before they started to break furniture. My Danish 
colleagues waved me off and the melee continued. An hour later, things 
had slowed down, and the managers thanked us and cleared out. Before we 
started cleaning up, I asked my Danish colleagues why they were so 
irate. They said, ``Oh, no. They like the changes and they'll make most 
of them. The rest of the time they were talking about the other changes 
they wanted to make, like having more produce tastings, more pre-
prepared salads, and bundling meat and vegetable specials together.''
    After all our supermarket makeovers, does every Bornholmian look 
like a sleek, slim, Danish version of Mad Men? As I mentioned earlier, 
it's still too soon to say (we're posting updates at 
www.SlimByDesign.org/Bornholm), but with every trip I make, all signs 
point in the right direction.
    One way to tell how well a new idea is working is by how many 
people want to jump in and be a part of it. The more changes we made to 
the grocery stores in Bornholm, the more other groups got involved. 
Before long, a public health advertising campaign was being rolled out, 
petitions were launched, and local ordinances were proposed. After the 
kitchen smoke clears, it will be difficult to see which of these moved 
the dial the most--but the people on the island are buying in to 
becoming slim by design.
    There's a humbling expression: ``Success has a thousand fathers, 
but failure has only one.'' If there are dramatic changes in the foods 
these Danes buy, the public health people will say it was because of 
their ads, the activists will say it was because of their tireless 
petition drives, and charismatic politicians will say it was because of 
their bold regulations. But if nothing happens and the whole plan ends 
up being a failure, which father will take the blame? It won't be the 
public health adviser or the politician. They'll abandon the program in 
a heartbeat. Unsuccessful public health campaigns cost lots of money. 
Unsuccessful ordinances can cost political careers.

          We projected each change would turn a profit within a month 
        if not immediately.

    Yet these supermarket makeovers were cheap and easy to make. Many 
were done over a weekend, and we projected each of them would turn a 
profit within a month if not immediately. Still, if even one works, 
stores will be further ahead than before. On my most recent trip, they 
asked me to help expand it to the mainland, so some hidden sales 
numbers must be looking pretty good. It's the beauty of being slim by 
design.
How Your Grocery Store Can Make You Slim
    There Are Dozens of Ways your favorite grocery store could 
profitably help you shop a little healthier. In April 2014, I shared 
the Bornholm story with some of the innovative American grocery stores 
that sponsored some of the studies you've read about throughout this 
chapter. They all had clever ideas they were trying out in their stores 
to help their customers shop a little healthier, but they were all 
doing something different--and often repeating each other's mistakes. 
If we could pool together all of my Lab's slim-by-design research 
findings with some of the ideas they were successfully experimenting 
with, we could make a supermarket scorecard that could help guide all 
of them to make profitable healthy changes.

          This supermarket scorecard tells shoppers what they should 
        look for or ask their local grocery manager to do.

    Grocery chains are competitive--and not just for shoppers. Even 
though a grocery chain in Texas doesn't compete for the same shoppers 
as a grocery chain in Chicago, they all want to win awards for Most 
Popular, Prettiest, Smartest, or Most Likely to Succeed at their annual 
Grocery Store-a-Palooza Award Conference. Because having a scorecard 
means there might be yet another new award they could compete on, most 
were eager to help develop one. But more important than enabling 
grocery chains to compete with each other, this supermarket scorecard 
will transparently show them exactly how to compete. Also, it will tell 
shoppers what they should look for or ask their local grocery store 
manager to do. If all these changes help grocery stores make a little 
more money, grocers will want to make the changes. If all these changes 
help shoppers shop a little healthier, shoppers will want to hassle 
their favorite grocer until he or she makes changes.

         Slim-by-Design Grocery Store Self-Assessment Scorecard
 
 
------------------------------------------------------------------------
    Okay, so your favorite grocery store has great prices, selection,
 and convenience, but it might still be making you fat and happy instead
 of happy and slim. This scorecard tells you what your store is doing to
 help you eat better. Our Lab has been working with top grocery chains
 around the nation to help them make you slim by design. You can use a
 scorecard like this to compare your favorite grocery stores, but it
 will also tell you what you can ask them to do to make you and your
 family more slim--and more loyal to their store. Some items on this
 scorecard might initially seem to have nothing to do with food--like
 having restrooms and a drinking fountain in the front of the store--but
 together they will make you less anxious or more comfortable, and
 others will slow you down and relax you. In the end, even some of these
 nonfood changes can lead you away from impulsively buying Chunky Monkey
 ice cream and more toward intelligently buying bananas. This is a
 start--every year this scorecard is updated with the best practices and
 the best research that helps us shop better (and helps stores make
 money). The newest can be found at SlimByDesign.org.
------------------------------------------------------------------------
                                Entrance
------------------------------------------------------------------------
 Assign designated parking spots      The first area entered by most
 (similar to handicapped spots) for   shoppers is the produce section.
 pregnant women and mothers with      Free healthy samples are near the
 infants.                             entrance.
 Offer preprinted shopping lists of   There's a small ``grab and go''
 basic staples near the entrance.     area in the front of the store
 Provide information sheets near      with a small selection of milk and
 the entrance on healthy ways to      bread for the in- and-out, or
 shop.                                ``fill-in'' shopper.
 Offer healthier foods near the       There's a small ``grab and go''
 entrance to prime healthy            area in the front of the store
 shopping.                            with a small selection of milk and
 Two sizes of shopping carts are      bread for the in- and-out, or
 available.                           ``fill-in'' shopper.
 Handbaskets are available.
 Divided shopping carts with a
 ``place fruits and vegetables
 here'' section are provided.
------------------------------------------------------------------------
                          Services and Signage
------------------------------------------------------------------------
 Signs promote seasonal               Signs provide ``Did you know?''
 combinations of fruits and           facts about the health benefits of
 vegetables.                          specific foods.
 Educational posters are located      There are specific perimeter
 around the stores to educate         promotions for lean dairy.
 people about healthy eating (for     There are specific promotions for
 example, the Half-Plate Rule).       whole-grain products, such as
 Local and seasonal foods are         bread and pasta.
 clearly promoted.                    Calorie information is available
 There is a special section for       in the meat section.
 organic fruits and/or vegetables.    Healthy food apps such as
 The organic section is boldly and    Fooducate and QR codes are
 clearly labeled.                     promoted.
 At least one produce-tasting         A kiosk with tear-off recipes is
 station is near the entrance.        available in the produce section.
 A wide range of precut fruits and    Combo packs are available that co-
 vegetables are available.            promote healthy foods (such as
                                      tomatoes and mozzarella).
 There are separate in-aisle          A guidance system such as Guiding
 promotions for canned fruits.        Stars or a stoplight approach is
                                      used.
 There are separate in-aisle          A dietitian is available and
 promotions for canned vegetables.    visible in the store a couple of
                                      days each week.
 There are separate in-aisle          Unit pricing ($/oz) is available
 promotions for frozen vegetables.    where relevant.
 There are specific perimeter
 promotions for lean meat.
------------------------------------------------------------------------
                          Layout and Atmosphere
------------------------------------------------------------------------
 Relaxing music is played in the      Lighting varies throughout the
 produce section.                     store, but is always brightest on
 Show price per unit along with       the healthier foods.
 price per weight for healthy food,   Healthy tear-off recipe cards are
 for ease of calculation.             provided near the fruits and
 Floor decals are used for way-       vegetables.
 finding to healthy sections.         Recipe ingredients for the recipe
                                      cards are located next to the
                                      cards.
------------------------------------------------------------------------
                           Aisles and Shelves
------------------------------------------------------------------------
 Some fruits are bundled into         Ingredients are organized by
 family-size packs.                   preparation type (stir-fry versus
 Some vegetables are bundled into     salad)--for example, put
 family-size packs.                   mushrooms, eggplants, and peppers
                                      in a ``stir-fry'' section.
 A complementary fresh produce        Expiration dates are visible (at
 display is available in the meat     front of package or on signs).
 section (such as one containing      Aisles with healthy foods are the
 broccoli, peas, cauliflower, and     widest.
 peppers).                            Less healthy foods are
 A complementary fresh produce        inconveniently placed very low or
 display is available in the          very high on the shelves.
 seafood section (such as lemons,     Healthier foods are conveniently
 tomatoes, beans, and asparagus).     placed at eye level.
 A complementary fresh produce        Aisles with healthy food are
 display is available in the frozen   brighter than aisles with
 food section.                        unhealthy food.
 Displays of single fruits (such as   Hard-to-decide-upon foods (``long-
 oranges, apples, pears,              buy'' items), such as soups,
 nectarines, and apricots) are next   dressings, and baby foods are
 to desserts.                         located in less busy aisles so
 Ready-to-eat fruits and vegetables   people are relaxed enough to
 are available in variety packs.      comparison shop.
------------------------------------------------------------------------
                           Prepared Food Area
------------------------------------------------------------------------
 Fruit is available in all            The healthy daily targeted entrees
 foodservice areas.                   have creative or descriptive
 Vegetables are available in all      names.
 food-service areas.                  Posters displaying healthy foods
 A mix of whole fruit options is      or a guidance system (such as the
 displayed in an attractive bowl or   Half-Plate Rule) are visible in
 basket.                              the dining area.
 The ``pick me up'' or prepared       The cafeteria tracks the
 food section has healthy default     popularity and frequency of
 foods.                               healthy-option orders to see what
 A daily fruit or vegetable option    promotions work most effectively.
 is bundled into all grab-and-go      All promotional signs and posters
 meals.                               are rotated, updated, or changed
 A salad bar is available.            at least monthly.
 All beverage coolers have both       Half portions are available for
 water and white milk available.      all entrees.
 Alternative healthy entree options   Half portions are available for
 (salad bar, yogurt parfaits, and     all desserts.
 the like) are highlighted on         Takeout boxes are available for
 posters or signs within all dining   leftovers not eaten in the
 areas.                               cafeteria.
 The healthy daily targeted entree
 is placed as the first one seen in
 all dining areas.
------------------------------------------------------------------------
                       Shopper Comfort and Service
------------------------------------------------------------------------
 Restrooms are easily accessible in   Health and nutrition games
 the front of the store.              dominate the playroom.
 A drinking fountain is located in    A local fitness club is co-
 the front of the store.              promoted.
 There is an area for shoppers to     A small discount to a local
 sit and relax.                       fitness club is given to loyalty
 There is an area for shoppers to     club shoppers.
 eat.                                 There is a drive-through where you
                                      can pick up your groceries, if you
                                      call ahead.
 There is a supervised playroom for   Home delivery is available (for an
 children.                            extra charge).
------------------------------------------------------------------------
                 Engagement: Employees and Social Media
------------------------------------------------------------------------
 The produce-department manager and   All employees are trained to
 staff are specifically trained to    suggest healthy complementary
 suggest healthy answers to shopper   products when asked about a
 questions.                           particular item.
 The meat-department manager and      There are plentiful staff in the
 staff are trained to suggest         meat and produce sections who are
 healthy answers to shopper           trained to suggest healthy upsells
 questions.                           or substitutes.
 The dairy-department manager and     Store or chain has an eng aging
 staff are trained to suggest         website that has a health-related
 healthy answers to shopper           blog featuring local or seasonal
 questions.                           products.
 The bakery-department manager and    The website has shopper loyalty
 staff are trained to suggest         specials.
 healthy answers to shopper           Tips, features, or videos
 questions.                           involving better shopping and
                                      better living (such as ``Shopping
                                      with Kids'') are available.
------------------------------------------------------------------------
                                Checkout
------------------------------------------------------------------------
 Loyalty programs specifically        Receipt provides an indication of
 reward fruit and vegetable           what percentage of purchases were
 consumption.                         fruits and vegetables, low-fat
 Receipts are itemized in             meat, and low-fat dairy.
 categories or otherwise coded to     A default shopping ``starter''
 indicate how healthy you're          list is made available to each
 shopping.                            shopper at the front of the store
 The back of receipts feature         with a number of the major staples
 coupons for healthy foods.           preprinted on it.
 There is at least one food-free      The same healthy shopping-tips
 checkout aisle.                      brochure available at the
 A discount is offered if a certain   beginning of the shopping trip is
 percentage of purchases are fruits   also available at the checkout
 and vegetables.                      register.
 Individual containers of precut      ``Don't Forget'' signs are placed
 fresh fruit are available next to    at the register to remind
 at least one cashier.                customers about certain healthy
 Healthy snack options are offered    foods.
 next to the cashiers.                A ``fruits and vegetables only''
 Receipt uses loyalty card            self-checkout station is provided
 information to show how much was     for quick purchases of produce.
 spent on fruits and vegetables
 compared to past trips.
------------------------------------------------------------------------
                            Scoring Brackets
------------------------------------------------------------------------
     70-100--Slim-by-Design Grocery Store--Gold
 
     50-69--Slim-by-Design Grocery Store--Silver
 
     30-49--Slim-by-Design Grocery Store--Bronze
------------------------------------------------------------------------

                              Attachment 2
Healthy Profits: An Interdisciplinary Retail Framework that Increases 
        the Sales of Healthy Foods
Brian Wansink a-b, *
---------------------------------------------------------------------------
    \a\ Dyson School of Applied Economics and Management, Cornell 
University, United States.
    \b\ Cornell Food and Brand Lab, Cornell University, United States.
    * Correspondence to: 475 H Warren Hall, Cornell University, Ithaca, 
NY 14853, United States. Fax: +1 607 255 9984.
    E-mail addresses: [email protected], [email protected].

  http://dx.doi.org/10.1016/j.jretai.2016.12.007**
---------------------------------------------------------------------------
    ** Please cite this article in press as: Wansink, Brian, Healthy 
Profits: An Interdisciplinary Retail Framework that Increases the Sales 
of Healthy Foods, Journal of Retailing (xxx, 2017), http://dx.doi.org/
10.1016/j.jretai.2016.12.007.
---------------------------------------------------------------------------
  0022-4359/' 2017 New York University. Published by 
    Elsevier Inc. All rights reserved.
Abstract
    Disruptive layouts, smart carts, suggestive signage, GPS alerts, 
and touch-screen preordering all foreshadow an evolution in how healthy 
foods will be sold in grocery stores. Although seemingly unrelated, 
they will all influence sales by altering either how convenient, 
attractive, or normal (CAN) it is to purchase a healthy target food. A 
Retail Intervention Matrix shows how a retailer's actions in these 
three areas can be redirected to target shoppers based on whether the 
shoppers are Health Vigilant, Health Predisposed, or Health 
Disinterested. For researchers, this review offers an organizing 
framework that integrates marketing, nutrition, psychology, public 
health, and behavioral economics to identify next generation research. 
For managers, this framework underscores how dozens of small, low cost, 
in-store changes are available to each that can surprisingly increase 
sales of entire categories of healthy food.

          2017 New York University. Published by Elsevier Inc. All 
        rights reserved.
Introduction
---------------------------------------------------------------------------
     Editor's note: The article is in press, consequently, the 
endnotes are unnumbered. In the submitted article pdf the referenced 
works have the author'(s) name(s) highlighted for hyperlinking, but 
they are not linked; therefore, the endnotes are in order as printed 
and not in order as referenced.
---------------------------------------------------------------------------
    Our best and worst eating habits start in the grocery store. 
Although critics claim that retailers are primarily motivated to sell 
unhealthy processed food--Froot Loops instead of fruit or fish sticks 
instead of fish--the opposite is true for the savvy ones. If the fruit 
turns mushy and the fish begins to smell, retailers may lose more money 
in sunk inventory costs then they would otherwise gain by selling the 
processed versions. Grocers are motivated to sell healthy, profitable 
foods. Unfortunately, they do not know how to effectively do so 
(Chandon and Wansink 2012; Guthrie 2017; Inman and Nikolova 2016), so 
retail fruit and vegetable sales continue to drop (Haywood 2016; 
Produce for Better Health 2015).
    Each issue of Supermarket News and Progressive Grocer highlights 
clever twists on how retailers can increase sales: novel POP displays, 
creative cross-promotions, compelling incentive programs, colorful 
floor decals, and trendy planogram arrangements. Most of these tactics 
are driven by manufacturers of branded, less-than-healthy packaged 
goods. In contrast, most of the newest and most creative solutions for 
selling unbranded healthy products--such as fish, poultry, fruits, and 
vegetables--have been discovered in academia (Johnson, et al., 2012).
    Regretfully, however, many of these discoveries are not widely 
adopted or used beyond one or two field test stores (Inman 2012). 
First, these discoveries appear disorganized or disjoint because 
together they use a wide range of interventions to investigate a wide 
range of outcomes (such as sales, satisfaction, loyalty, repatronage, 
eye-tracking, and so on). This combination is overwhelming to a manager 
who is looking for a single solution, such as how to simply sell more 
fish. Instead of giving managers a useful toolbox of organized 
solutions, what we give them is more like a shoebox full of tax-time 
receipts.
    The second reason our work is infrequently translated into practice 
is because its conclusions are either uncompelling or inconsistent 
(Vermeir and Van Kenhove 2005).We tend to focus on interactions or 
boundary conditions where an intervention might work with some 
customers and with some food categories, but not with others (List, 
Samek, and Zhu 2015). For instance, a Traffic Light rating system may 
be useful to some shoppers (Dzhogleva, Inman, and Maurer 2013; Grunert, 
Bolton, and Raats 2011; Trudel, et al., 2015), but to others it might 
be a glaring warning sign that the food will taste bad (Werle, et al., 
2011). Academia thrives on interactions and exceptions, but the rest of 
the world runs on main effects.
    The future of healthy retailing will be guided by the future of new 
research. All of the research in this review has been published or 
conducted after 2011 and \1/2\ are still working papers.
    They comprise a framework that integrates the newest discoveries in 
marketing, health psychology, public health, consumer research, 
nutrition, and behavioral economics to identify what might be the most 
actionable and compelling new research to influence practice and 
theory. First, the framework collapses the myriad of individual 
differences among shoppers into a three-segment hierarchy which 
summarizes their healthy shopping disposition. Second, it offers a 
useful way to organize the receipt box full of findings in a way that 
shows how various interventions work (improving convenience, 
attractiveness, and norms) and where they can work within grocery 
stores (by altering the signage, structure, service mix). Fig. 1 
foreshadows how these pieces will combine to eventually create a Retail 
Intervention Matrix framework that can organize existing findings and 
stimulate useful new insights.
Fig. 1. How and Where Retail Interventions Can Influence Shoppers



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

The Hierarchy of Health Predispostion
    Not all shoppers shop alike. Health food enthusiasts shop 
differently than mothers shopping with kids; a ``hot'' fast-thinker 
shops differently than a ``cold'' slow-thinker; and variety-seekers 
shop differently than budget-constrained shoppers (Hui, Huang, et al., 
2013; Verhoef and van Doorn 2016). There will always be an exception or 
an untested segment. This sometimes leads our results to appear 
frustratingly inconclusive when we have to admit that we do not know 
whether our new intervention works the same way with elderly shoppers 
as it does with shoppers using SNAP benefits (Guthrie 2017).
    One solution is to only view shoppers based on how predisposed they 
are to making a healthier shopping decision. We can view them as 
belonging to one of three fluid groups that belong to a Hierarchy of 
Health Predisposition. The top segment of this hierarchy are Health 
Vigilant shoppers (Fig. 2). They are highly informed, conscious of 
calories, and are influenced by nutrition information. At the bottom 
extreme, Health Disinterested shoppers have little interest in changing 
their eating choices because of either the effort, sacrifice, or 
perceived futility. The segment in the middle are the Health 
Predisposed shoppers. They would prefer to make healthier food choices, 
but they have difficulty consistently doing so unless it involves very 
little sacrifice. This Predisposed segment is the one that buys the 
100-calorie packages of snacks and the sugar-free yogurt. This segment 
is larger on New Year's Day than it was in December; it was larger this 
past Monday morning than it was during the prior Friday night's 
shopping trip.
    One reason nutrition guidance systems (such traffic lights or 
Guiding Stars) have had only modest influences on the sales of healthy 
food (Cawley, et al., 2015; Nikolova and Inman 2015) may be because 
they mainly resonate with only the top of the Hierarchy. Health 
Disinterested shoppers ignore these programs, and heath predisposed 
shoppers inconsistently follow them. If the only segment they reach are 
the vigilant shoppers, interventions like this will have hardly any 
sizable impact on health since this segment is already shopping in a 
healthy way. Even if the same intervention is perfectly targeted at the 
bottom portion of the Hierarchy, it would have hardly any impact 
because the bottom segment does not care.
Fig. 2. The Hierarchy of Health Predisposition



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

The CAN Approach to Improving Healthy Shopping
    Changing widespread eating behavior does not happen by convincing 
shoppers that an apple is healthier than a Snickers nor does it happen 
by coaching them to improve their imperfect willpower. While these may 
be reminders to Health Vigilant shoppers, they will not reliably work 
with Health Predisposed shoppers, and almost certainly will not work 
with Health Disinterested shoppers. Instead, a more sensible and cost-
effective solution would be to simply make sure that the apple is much 
more convenient, attractive, and normal to choose than the Snickers. 
Offering an apple sample at the front of the store primes more fruit 
sales (Tal and Wansink 2015) and offering an apple display at the 
checkout helps pre-empt Snickers sales (Winkler, et al., 2017). Such 
changes are effective because they influence passive shoppers and not 
just the vigilant ones.
    In 2011, Denmark started a public health initiative to reduce 
obesity--partly by trying to increase the sales of fish, fruits, and 
vegetables (fresh, frozen, and canned) in grocery stores (thereby 
hopefully decreasing the sales of less healthy foods). Starting with a 
list of dozens of retail changes that were believed to be revenue 
positive (see Appendix A), six were selected to be implemented over a 2 
year period on the isolated Danish island of Bornholm (population 
42,000). The six interventions selected were ones that retailers 
believed would both be profitable and easy to implement and maintain:

  1.  Fruit displays within 10 of the entrance

  2.  At least one candy-free check-out line

  3.  Traffic interrupters (displays of healthy foods in the 
            wideraisles)

  4.  End-aisle displays of fish

  5.  Traffic Light (``Green Key'') labeling

  6.  In-Store Promotions = \1/2\ Plate Rule Guidance System

    In combination, these retail interventions were successful because 
they made it more convenient, attractive, and normal to purchase fish, 
fruits, and vegetables. For instance, putting fruit in an attractive 
display made it appear more normal (typical, or reasonable) to take 
fruit--partly because it was now also more convenient and looked more 
attractive. It was the CAN approach to changing behavior (Wansink 
2015). Looking toward the future of retailing, the key to doing this 
successfully is to not handicap our imagination by too narrowly 
defining what is meant by convenient, attractive, and normal (Bommelaer 
and Wansink, 2017).
More Convenient to Select
    As Fig. 3 illustrates, a manager can help make healthy foods more 
convenient to see, to consider, and to purchase (Desai and Trivedi 
2014; Gilbride, Inman, and Stilley 2015). For instance, one of the 
biggest barriers to purchasing fish is that many shoppers are not 
confident about how to prepare and serve it. With these shoppers, no 
nutrition scale or promotion would lead a person to buy more fish until 
they understood that it could be integrated into cooking routines that 
were familiar and convenient for them. This was similar with tofu and 
to counter this, the largest tofu manufacturer in the U.S. launched an 
in-store campaign that clearly illustrated that tofu is convenient to 
buy and to cook (``Fridge to pan in 10 minutes'' and ``Cooks like 
chicken'') which helped increase both shopper confidence and retail 
sales (Hsu 2014).
    Even when shopping for familiar foods in familiar aisles, small 
changes can conveniently guide shoppers to make healthier choices. 
Vegetables placed near the front entrances are selected eight percent 
more than those that are not (Wilson, et al., 2016), floor decals that 
guide people to other vegetable displays increased sales by nine 
percent (Payne and Niculeseu 2012), and center-of-aisle ``traffic 
interrupter'' displays repeatedly increased 1 day sales of overlooked 
vegetables by 400% in Denmark. Convenience also helps explain why about 
43% of interior aisle grocery sales are within 12" of eye level (Stein 
2018). This ``you buy what you see'' continues all the way to the 
checkout where fruit displays can increase short-term sales by 35% (van 
Kleef, Often, and van Tripj 2012).
Fig. 3. The CAN Approach To Influencing Shopping Decisions


    Along with saving physical effort, convenience can also refer to 
saving cognitive effort. This ranges from using easier-to-understand 
product category layouts (de Wijk, et al., 2016; van Herpen 2016) to 
leveraging technology in the form of GPS alerts or personal shopping 
profiles (Sciandra and Inman 2014). Such reminders can guide shoppers 
to healthier choices by making it both more cognitively convenient to 
select and more convenient to visualize this food being prepared and 
eaten at a home meal (Hui, Inman, et al., 2013; Lowe, Souza-Monteiro, 
and Fraser 2013).
More Attractive to Select
    The second principle of the CAN approach is that the healthy choice 
needs to be made more attractive relative to less healthy (but usually 
more tastier) options. It could be more attractively named, more 
attractive in appearance, more attractively priced (Hampson and 
McGoldrick 2013), or it could evoke more attractive taste expectations 
than it usually does (Trivedi, Sridhar, and Kumar 2016; Vega Zamora, et 
al., 2014). Fruit that is haphazardly piled onto a flat table is less 
attractive than fruit that is angled on a display with a colored frame 
around it (Stein 2018). Even simply giving a fruit or vegetable a 
descriptive name--crisp carrots or Michigan cherries--makes them more 
attractive and increases a person's taste expectations (Spence and 
Piqueras-Fiszman, 2014) and selection by sixteen percent or more 
(Wansink, et al., 2012).
    Attractive packaging, descriptive names, color, labels, and 
appearance have all been shown to bias evaluations of taste. Food can 
also be more attractive simply by being novel (curried pumpkin), 
attention-getting (heirloom Indian corn), or even more ethically 
attractive (meat-free turkey). Both the sustainability movement and the 
``ugly vegetable'' movement have capitalized on ethically-motivated 
shoppers who find sustainable products to be more attractive.
    Making a food more attractive by altering its price is a popular 
tool of behavioral economists, and it takes the standard form of taxes, 
subsidies, rebates, coupons, and bundling (Carroll, Samek, and Zepeda 
2016). Unfortunately, when price rebates have been offered on fruits 
and vegetables, they can sometimes backfire by increasing both the 
sales of healthy produce in addition to the sales of unhealthy foods--
especially in low-income households (Cawley, et al., 2016). That is, 
the money saved on fruit is then spent on Froot Loops (Cawley, et al., 
2016).
More Normal to Select
    Last, many shoppers often prefer to buy the foods they believe are 
normal or popular to purchase, serve, and eat. For instance, signs that 
told people that chick peas were the favorite bean in that area 
(Harlem) shifted 21% of all bean selections over to chick peas (Bhana 
2017). This also works with quantities. Shopping cart signs that stated 
that the average shopper purchased at least five fruits and vegetables 
increased produce sales by ten percent (Payne, et al., 2014). Moreover, 
even the size of the store might subtly suggest to a customer how much 
is normal to purchase during a shopping trip (Ailawadi, Ma, and Grewal 
2016).
    Benchmarks provide visual purchase norms. Consider two benchmarks 
that increase fruit and vegetable sales. One is the Half-Plate rule 
which was originally designed to help consumers operationalize the 
spirit of USDA's MyPlate guidance system (Wansink and Tran 2017). The 
Half-Plate rule simply states that in order to eat more balanced meals, 
\1/2\ of your plate needs to be fruits, vegetables, or salad and the 
other \1/2\ can be whatever you wanted. You can have a second or third 
helping if you want, but \1/2\ of your plate always has to be fruits, 
vegetables, or salad. This was successfully implemented in the leading 
grocery chain in the United States (Kell 2016) as ``Half-Plate 
Healthy'' because it had been shown to encourage shoppers to buy 
``considerably more'' produce (Wansink 2014). After all, if consumers 
were going to eat half-plate healthy, they needed to shop half-plate 
healthy (see Fig. 4).
Fig. 4. The Half-Plate Rule and the Half-Cart Both Suggest Larger 
        Portion Size Norms for Fruits and Vegetables
        
        
        
        
        
        
        
        
        [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
        
    One of the reasons the half-plate healthy approach was effective 
for this leading retailer was because it offered a simple visual 
benchmark about how much fruit and vegetables are the right amount to 
eat--half the plate. Similarly, when consumers shop, little thought may 
be given as to whether a food is healthy or not. Yet if asked to 
categorize and separate each food they buy according to whether it is 
either a fruit or a vegetable (versus neither), it forces more mindful 
shopping. One set of studies involved shopping carts that had been 
physically divided across the middle and were accompanied with a sign 
in the front that instructed people to place their fruits and 
vegetables (fresh, frozen, or canned) in the front \1/2\ of the cart 
and everything else in the back \1/2\. Using this Half-Cart approach 
increased the sales of fruits and vegetables by eighteen percent 
(Wansink, Payne, and Herbst 2017). In a second set of studies, when the 
proportion of the cart allocated to fruits and vegetables was either at 
the 35% level or the 65% level, the amount that shoppers spent 
increased from $14.97 to $17.54 (Wansink, Soman, and Herbst 2017). When 
the same type of dividing lines were added to online shopper order 
forms for grocery delivery, the same results were found. The size of 
partitions indeed matters to shoppers.
    Nearly all healthy interventions in retailing influence shoppers by 
increasing how convenient, attractive, or normal it is to purchase one 
food instead of another--an apple or a fish instead of crackers and 
beef (Bommelaer and Wansink, 2017). By organizing how our discoveries 
work, we open up new possibilities of influence. The CAN approach 
enables us to organize how our interventions influence shoppers. As 
Table 1 foreshadows, the next section shows where they will work best 
in a store.
The Signage, Structure, Service Mix: Where Retailers Can Best Change 
        Behavior
    Although nearly all shopping interventions influence shoppers by 
altering how convenient, attractive, or normal it is to buy a product, 
there are endless ways they can do so. There are also three different 
areas where retailers can influence shoppers by using these tools. 
Shoppers can be influenced through signage (inside and outside the 
store), by the structure of the store (layout and product positioning), 
and by the service the store provides (on-line, in-person, or on-site). 
This signage, structure, service mix influences different shoppers in 
different ways. Improving service might work best for Health Vigilant 
shoppers (because they are most likely to seek out the extra 
information or assistance). Improving signage might work best for 
Health Predisposed shoppers (as well as those who are and Vigilant). 
Changing the store's structure might work well for all three segments.
Signage
    Signage overlaps with the traditional ``Promotion P'' of the 4-P's 
framework. It involves all out-of-store, in-store, and online efforts 
that are directed toward influencing what a shopper buys (Kovacheva and 
Inman 2014). Outside the store it includes fliers, circulars, 
commercials, outdoor advertising, and coupons. Inside the store it 
includes posters, signs, shelf-hangers, floor decals, and kiosks as 
well as take-home media such as recipes, brochures, and magazines, and 
more stylized or person-based media, such as tailored ads, feedback or 
messages on shopping receipts (Otterbring, et al., 2014), and GPS 
alerts for promotions. On-line it includes the website, on-line tools, 
social media, e-mail alerts, sponsored apps, and GPS alerts for 
promotions that can be triggered both in and out of the store.

  Table 1. How Sample Findings Fit Into the Retail Intervention Matrix
------------------------------------------------------------------------
                     More convenient    More attractive   More normal to
                       to  purchase       to  purchase       purchase
------------------------------------------------------------------------
Signage              Floor      New        Signa
                     decal arrow        recipe ideas, co-  ge stating
                     stickers asking    promotions, and    that garbonzo
                     people to follow   end-of-aisle       beans were
                     the arrows to      displays           the most
                     eat more           increased canned   popular
                     nutritiously       fish sales by      beans,
                     lead to a nine     eighteen percent   increased
                     percent increase   (Toft, et al.,     selection by
                     in produce sales   in preparation)    fourteen
                     (Payne, et al.,    Starring   percent
                     2014)              items as more      (Bhana 2017)
                     Joint      healthy            Shopp
                     efforts to         decreased the      ing cart
                     provide fish       purchase of        signs stating
                     dinner recipe      unstarred (less    that the
                     cards and          healthy foods)     average
                     grilling           by two percent     shopper
                     instruction        (Cawley, et al.,   purchased at
                     brochures were     2015)              least five
                     part of a larger                      fruits and
                     campaign that                         vegetables
                     increased fish                        increased
                     sales by 28%                          produce sales
                     (Karevold, Tran,                      by ten
                     and Wansink                           percent
                     2017)                                 (Payne, et
                                                           al., 2014)
Structure            A fruit    Fruit      Visua
                     display near       samples provided   lly diving a
                     cash register      to consumers       shopping cart
                     increased sales    upon entering      in \1/2\ and
                     35%, even when     the store          suggesting
                     product was not    increased sales    that \1/2\
                     discounted (van    fruit sales by     should be
                     Kleef, Often,      seven percent      used for
                     and van Tripj      (Tal and Wansink   fruits and
                     2012)              2015)              vegetables,
                     Items      People     increased
                     (including         were sixteen       their sales
                     produce) that      percent more       by fourteen
                     was within 12"     likely to          percent
                     of a shopper's     purchase a         (Wansink,
                     eye-level          product from the   Payne, and
                     comprised over     first full aisle   Herbst 2017;
                     43% of all sales   they entered       Wansink,
                     (Stein 2018)       than any           Soman, and
                                        subsequent aisle   Herbst 2017;
                                        (Stein 2017)       Wansink,
                                                           Tran, and
                                                           Karevold
                                                           2017)
                                                           Using
                                                           more islands
                                                           than aisles
                                                           in produce
                                                           aisles
                                                           increased
                                                           shopping time
                                                           and items
                                                           purchased
                                                           (Mukund,
                                                           Atakan, and
                                                           Wansink 2018)
Service              Healthy    In-store   ``Hal
                     ``Grab and Go''    suggestions by     f-Plate
                     lines in store     staff              Healthy'' on-
                     cafeterias led     contributed to     line planner,
                     to a 82%           increased fish     led to higher
                     increase in        sales (Karevold,   produce sales
                     healthy food       Tran, and          and more
                     sales (Hanks, et   Wansink 2017)      balanced
                     al., 2012)         One        meals a
                     Mobil      loyalty program    Shopp
                     apps that          rewarded fruit     ing receipt
                     indicated what     and vegetable      ``scorecards'
                     percent of your    purchases by       ' showed
                     food is healthy    providing a        consumers how
                     and which were     scaled discount    the
                     missing, was       based on how       percentage of
                     rating as being    much was           fruits and
                     most attractive    purchased a        vegetables
                     to in-store                           purchased in
                     consumers (Mao                        this trip
                     and Atakan 2017)                      compared with
                                                           past trips
                                                           (based on
                                                           loyalty card
                                                           data) a
------------------------------------------------------------------------
a Unpublished findings based on proprietary studies.

    Signage builds awareness, offers reminders, changes attitudes, 
encourages comparisons, and so on. It can change the perceived 
convenience of purchasing healthy foods by making it more convenient or 
easy to consider (``Having turkey for dinner sounds good''), by 
changing perceptions of how attractive it would be to add organic 
parsnips into a routine meal, or changing how normal it would be to 
have a full fruit bowl sitting out when the kids return home from 
school (see Fig. 5).
Fig. 5. The Signage-Structure-Service Mix




[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

Structure
    The structure of a store includes its layout and where and how 
foods are positioned, such as whether the healthier foods are nearest 
the door, at eye level, co-promoted with other displayed products, and 
whether they are located in the first two aisles where a consumer 
shops. But structure also influences people before they even enter the 
store. Starting in the entryway, the size and shape of the shopping 
carts structurally influences how much is purchased (bigger carts lead 
to bigger shopping trips) and what is purchased (divided carts lead to 
more fruit and vegetable sales). Any changes related to shopping carts 
and hand baskets continue to influence shoppers throughout their entire 
shopping trip, but shopping carts have their biggest impact before it 
fills up because this makes a shopper's budget constraints more salient 
(van Ittersum, et al., 2013).
    A store's structure can be changed by using traffic interrupters 
and islands (instead of aisles) in the produce section. A recent 
analysis of 1,242 shoppers in four different sections of various 
grocery stores shows that while purchases in many sections of a grocery 
store (such as meat and cereal) begin to level off after 2 minutes of 
shopping, the total number of dollars spent in the produce section 
continues rising for about 12 min. at a rate of $1.84/min. One 
objective for a store, therefore, is to determine how to keep people 
shopping in the produce section for up to 12 min. Islands (instead of 
aisles) may help. They appear to slow shoppers down which relates to 
them spending more money on produce (Mukund, Atakan, and Wansink 2018).
Service
    Most obviously, service includes the sunny appearance, helpfulness, 
and friendliness of greeters, butchers, and cashiers (Huneke, et al., 
2015; Keeling, McGoldrick, and Sadhu 2013), the cleanliness of the 
store, and the restocking and upkeep of shelves (Robinson, et al., 
2016). Yet much of the service that really guides shoppers to healthier 
choices is surprisingly less face-to-face. It starts with how 
technology can influence the goals and expectations customers have 
before they enter the store (Gustafsson, et al., 2016; Hunneman, 
Verhoef, and Sloot 2015; Lee 2015), such as when a Health Vigilant 
shopper reads a store blog on healthy food substitutes and prints off 
the related coupons. Once in the store, service can be efficiently 
boosted by new technologies, such as kiosks that give tailored recipes 
or a GPS cart-mounted tablet that gives real-time shopping advice 
(Block and Platt 2014). Last, service can influence a shopper's comfort 
and mood (Atalay and Meloy 2011; Chen, Lee, and Yap 2011). While the 
location of the restrooms and drinking fountains or the availability of 
near-the-entrance parking for new mothers appears to have little to do 
with sales, it increases a person's shopping time and store 
satisfaction, and it may indirectly trigger healthier sales (Atakan and 
Finch 2018).
    Signage, structure, and service are the areas of the store where 
the CAN approach can be much more creatively leveraged to sell 
healthier foods. Still, aggressively pressuring shoppers to fill their 
shopping carts with healthy foods has diminishing returns, especially 
as their shopping trip progresses (Biswas, Szocs, and Inman 2016; 
Sheehan and van Ittersum 2016; Van der Heide, van Ittersum, and van 
Doorn 2016). There is a limit to how much more produce shoppers can be 
nudged to take (Toft, et al., in preparation; Trivedi, Gauri, and Ma 
2016). Unless total shopping volume rises, a short intervention study 
might heroically claim 30% increases in fruit and vegetable purchases, 
but a sustained long-term sales increase of three percent would be more 
realistic.
    Although a long-term increase in sales of three percent for one 
intervention is much less exciting than 30%, there is an entire 
shopping experience or journey that needs to be taken into account 
(Beatty, et al., 2015; Lemon and Verhoef 2016). This gradual healthy 
shift in the entire shopping experience could form the habits (Cleeran, 
et al., 2016) that can nurture healthier store loyalty and healthier 
bodies.
Shaping Future Healthy Shopping
    Organizing our findings into a Retail Intervention Matrix helps us 
make them more useful to retailers. If we can better see how one of our 
new discoveries influences choice (through the CAN Approach), and then 
better imagine where it will work best (the signage, structure, service 
mix of a store), we can help retailers far more than if we give them a 
nuanced, isolated finding. Moreover, knowing that there are three 
segments of shoppers with different degrees of health disposition 
(Vigilant, Predisposed, and Disinterested), helps us more realistically 
point to who we will have an impact on and who we will not.
Thinking Deeper
    Within the signage, structure, service mix, much of the 
interdisciplinary retailing research focuses on using signage to make a 
healthy food more attractive through the way it is positioned or priced 
(Shah, et al., 2013). As the upper right corner of Fig. 6 indicates, 
what is less known is how signage can be used to establish new purchase 
norms or consumption norms (Van Doorn and Verhoef 2015). For instance, 
over the past 40 years, foods like yogurt and granola have gone from 
being foreign oddities to favorite staples. Knowing what created these 
new norms could help engineer sustainable healthy food trends of the 
future--regardless of whether they involve tofu or lab-grown meat 
(Purdy 2016).
Fig. 6. Where Research Is Most Needed



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

    In contrast to signage, changes in ``structure'' have generally 
focused only on making a healthy food more convenient: Move the fruit 
to front of the store, over to the cash register, to eye level, to an 
end-aisle display, and so on. Now it is time for bigger questions such 
as how structure can make a healthy food more attractive or more normal 
or popular to buy. Again, consider healthy, high-margin, 
environmentally sustainable tofu (Groening, Inman, and Ross 2014). 
Using a store's structure to make tofu become more popular and trendy 
could be surprisingly transforming for retailers, manufacturers, and 
consumers.
    Service is sometimes too narrowly defined as face-to-face or voice-
to-voice encounters. New technologies both inside and outside the store 
give service the most unrealized potential by leveraging eye-tracking, 
smart shopping carts, video-tracking, and GPS technology (Hue, et al., 
2013; Nikolova, et al., 2014). Whereas most interventions cannot easily 
show which of the three Hierarchy of Health predisposition segments 
they impact most, new technologies could show the results of these 
interventions by either directly linking them to sales or indirectly 
doing so through shopper loyalty cards.
Applying Wider
    Some of what we know about improving healthy shopping in grocery 
stores has already been systematically adopted into the growing 24-h 
lifestyle of convenience stores, corner stores, and mini-stores (Lenard 
and Schnare 2016). In 2016, the National Association of Convenience 
Stores launched a new toolkit titled, ``Ideas That Work to Grow Better-
for-You Sales,'' and they include evidence-based tactics including (1) 
grab them immediately, (2) variety sells produce, (3) use creative 
adjectives, (4) remember the convenience factor, (5) have multiple 
displays, (6) let your store ``talk,'' (7) direct their feet, and (8) 
remind them (Lenard and Schnare 2016). Given this success in C-Stores 
(note the fruit baskets that are now near most cash registers), there 
are three other retailing frontiers that are deserving of our 
attention.
Concessions and Kiosks
    Entrenched managers in food concessions and kiosks have long 
justified their unhealthy food portfolio mix my reactively claiming 
they simply ``sell what people buy.'' Yet they say this without really 
having given healthier food much of a chance. Indeed, when a healthier 
range of snacks (fruit, chicken sandwiches, granola bars, low-fat 
string cheese, trail mix, and so on) were offered alongside existing 
concession foods during one Iowa football season, sales of healthy 
snacks rose with each high school game until they comprised nine 
percent of sales in less than 2 months because of both switching and 
new sales (Laroche, et al., 2015). When Disney World followed by 
changing the defaults on kids' meals at their kiosks and offering fruit 
instead of french fries, it too generated more praise than pushback 
(Peters, et al., 2016). Discovering simple, evidence-based steps that 
help retail concessions profitably move from selling snack foods to 
selling meal substitutes could be game changing (Laroche, et al., 
2017).
On-line Shopping and Delivery
    After its initial growing pains, on-line shopping and delivery has 
been consistently growing across both North America and Europe. Yet the 
new adopters of this service are often families with children who 
steadily use the service once a week for a month; use it less 
consistently for the next 2 months; and often become inactive after 
that. Other than focusing on price promotions or loyalty programs 
(Bodur, Klein, and Arora 2015), a better solution would be to determine 
how to increase retention in a way that transforms how they eat in the 
same way it transformed how they order (Marinova, et al., 2016). The 
opportunity to help people transform the way they view themselves (and 
their health) because of how they order food could sustain both this 
industry and their families (Lund and Marinova 2014).
Food Pantries
    Helping food pantry shoppers make healthier decisions has typically 
involved research replicated from other contexts (Bhana and Contento 
2017; Wilson 2016). There are limited numbers of products in food 
pantries and there are binding constraints (such as how much one can 
carry, or how much a person is allowed to take from a category such as 
pastries). Yet these limitations are precisely why a food pantry is a 
rich context for discovery. Without economic considerations, how do 
food shoppers behave? If they still take no fruits and vegetables, this 
might suggest that subsidizing cucumbers and taxing cupcakes may not 
have the intended policy impact that public health policy makers 
believe it would have (Bhana 2017; Cawley, et al., 2015). Aside from 
being a rich context for research, applying useful insights to food 
pantries provides a world of value far from the office.
Why Healthy Field Study Interventions Appear to Fail
    Applying this Retail Intervention Matrix framework is enticing. Yet 
one frustration when applying our theories deeper and wider is that 
health-focused interventions often fail when we move from the lab to 
the field (e.g., van Herpen, et al., 2016). We usually believe it was 
because of poor implementation by our retail partner, or it was because 
of a noisy measurement problem. Instead, there are two reanalyses we 
could make ex post to more precisely determine if an intervention was 
more effective than it initially appears. We need to analyze the right 
people, and we need to analyze the right days of the week.
We Do Not Analyze the Right Consumer Segment
    Not all interventions work with all people (recall Fig. 2). An 
expensive, digital, in-store calorie education program with a hip 
spokesperson and viral social media support will still have no impact 
on the top or bottom segments of this hierarchy. This is because the 
Health Vigilant Shoppers already know it, and the Health Disinterested 
Shoppers do not care. Yet most retail field studies show 
disappointingly modest results because they do not try to disaggregate 
the data and focus their analysis on the segment it was most intended 
to influence. A more targeted analysis could be done by segmenting 
shoppers into the Vigilant, Predisposed, or Disinterested segments 
based on their purchase history (which is linked to their loyalty 
cards) and then reanalyzing each segment.
    Different interventions influence different segments (Table 2). 
Setting up a study when and where it is most likely to influence a 
targeted segment will better help sift out which interventions are 
actually working in the way they intended. Aside from segmenting 
shoppers based on their loyalty card purchase records, shoppers could 
also be segmented or targeted by where they shop (e.g., Whole Foods, 
Target, Wal-Mart, the Co-op, and so on). If neither is possible, 
shoppers could be targeted by the time of the day or the day of the 
week when they shop.

   Table 2. A Retail Intervention Matrix of How Scandinavian Retailers
                    Doubled the Sales of Frozen Fish
------------------------------------------------------------------------
                 More convenient to  More attractive to   More normal to
  Mix element         purchase            purchase           purchase
------------------------------------------------------------------------
Signage           Created     Co-         Create
                  recipe cards        promoted the fish   d ``Native
                  titled ``Fish in    with vegetables     Norway'' logos
                  15'' (min)          (suck as leeks      to promote
                  Offered a   and broccoli)       fish as local
                  ``Grill Tips''      Named       Used
                  flier for the       select fish and     ``Local
                  grilling salmon     included a map      Favorite'' and
                                      showing the part    ``Managers
                                      of the world        Special''
                                      where it was        stickers
                                      caught
Structure         Utilized    Moved       Placed
                  vertical display    fish displays       the single
                  cases; moved fish   immediately after   servings of
                  to eye level and    vegetables          fish and some
                  processed foods     Included    of the lower
                  to the bottom       a buffer of         priced ``sales
                                      frozen vegetables   specials''
                                      between the fish    near the
                                      and the beef so     highest
                                      people would not    traffic edges
                                      make an unfair      of the
                                      sensory             displays
                                      comparison with
                                      beef
Service           Offered     Offered     Employ
                  frozen freezer      smaller, one-       ees were
                  packages to keep    portion servings    instructed to
                  fish frozen until   Put         suggest the
                  home                markings on the     two best
                  Offered     wrapper to show     selling types
                  plastic bags to     how much to         of fish and
                  put shrink-         prepare for one,    the two most
                  wrapped fish in     two, three, or      common items
                  for extra           four persons        with which
                  separation          E-mail      they were
                  protection from     promotions were     prepared
                  other foods in      send to loyalty     (e.g., rice
                  the basket          card holders,       pilaf and
                                      with recipe ideas   broccoli)
                                      and web-links to    Employ
                                      downloadable        ees were
                                      coupons             trained to
                                                          suggest
                                                          additional
                                                          items commonly
                                                          bought along
                                                          with specific
                                                          types of fish
------------------------------------------------------------------------

We Do Not Analyze the Right Days of the Week
    It is not surprising that people shop much less healthy at the end 
of the year--October through December--than they do after January 1st. 
The dollar amount of the healthy food we purchase increases 29.4% right 
after the first of the year (Pope, et al., 2014). This is not 
surprising but it would suggest that if an intervention has any chance 
of working, it would be better to test it in mid-January than in mid-
December or even mid-June. In general, a healthy intervention's 
effectiveness might continually decline throughout the year. That is, 
healthy shopping-focused interventions may be most effective in the 
first quarter, moderately effective in the second quarter and third 
quarter, and least effective in the fourth quarter.
    Yet if shoppers are on their best healthy shopping behavior during 
January, something similar may happen the beginning of each week in a 
smaller way. After a weekend of indulging, some people might have an 
unstated resolution to try and shop better, which makes them more 
susceptible to in-store nudges on a Monday than they would have been 
the prior Friday night. This Monday Morning Effect has been recently 
shown in both in cafeterias and grocery stores (Wansink, Tran, and 
Karevold 2017). In a 3 month study of over 15,000 diners, putting fish 
first (and beef last) on a buffet line increased fish selections on 
Mondays to Wednesdays but had no influence after Wednesday. Analogous 
results were found in grocery stores. Among people who made larger 
purchases (over $50 USD), interventions were most effective early in 
the week (Monday-Wednesday) than on Thursday-Sunday. If a field study 
intervention does not seem to have worked, reanalyze the sales results 
for only Mondays, Tuesdays, and Wednesdays. It may give a more accurate 
assessment of whether the intervention is worth dropping, reporting, or 
improving.
Using the Retail Intervention Matrix to Sell More Fish
    Until now, the Retail Intervention Matrix has been presented as a 
way to organize research findings based on how they work (making 
healthier foods more convenient, attractive, or normal) and where they 
are implemented in the store (within the signage, structure, service 
mix). This framework can be used to organize key findings into a 
sensible pattern that is also useful in practice.
    For example, a large Scandinavian grocer had the marketing 
objective of growing their market share by repositioning itself as the 
most environmentally sustainable retailer in Norway. One way they 
planned to accomplish this was by increasing their sales of fresh and 
frozen fish, which are much more environmentally sustainable than beef, 
pork, and lamb. They planned to first increase the variety of fish they 
offered (types, sizes, packaging, and so on) and to more actively 
promote this fish though advertising campaigns and price promotions. In 
addition to these traditional 4-P marketing mix methods of growing this 
category, the Retail Intervention Matrix was then used to create a 
broader set of interventions that could be used to further push the 
sales of fish by focusing on changes in the signage, structure, and 
service mix.
    All 457 stores in the chain used the traditional marketing mix 
approach of altering the variety, packaging, advertising, and price 
promotions of fish. Over a 2 year period, these marketing efforts 
consistently increased sales by nine percent. Following this, 239 
stores selected various additional changes to make (see the Retail 
Intervention Matrix for increasing fish sales in Table 2). Because of 
these changes, the average store generated 28% more fresh fish sales 
per transaction than those stores that had initially changed only the 
marketing mix (Karevold, Tran, and Wansink 2017).
    This brief example involving Norwegian fish shows one way research 
findings can be extrapolated, organized, and presented in a way that is 
compelling for mangers who have little time or tolerance for ambiguity 
and nuance. Showing how an intervention might work (the CAN approach) 
and where it can be implemented (through the signage, structure, 
service mix) enabled this retailer to provide a menu of actions or 
changes that each of its stores could pick and choose from. Similar 
adoptions of retail-based findings are also being explored by an 
American consortium of grocers (Borstein 2015) who are assembling an 
industry-wide Grocery Retail Scorecard that will show retailers how 
they can profitably help their customers shop healthier 
(Convergencepolicy.org/scorecard/).
Conclusion
    Retailing research in the future will be different than that of the 
past. It will be partly judged on whether it delivers fresh, useful 
solutions. A common view in the past was that an academic's role was to 
generate insights, and the role of managers was to determine how to use 
them. In the future, determining and discovering which insights have 
the biggest impact will be broadly rewarded. Using the Retail 
Intervention Matrix--including the CAN approach and the signage, 
structure, service mix--can help determine what is known and what needs 
to be discovered. Last, the Hierarchy of Health Predisposition can show 
where an intervention can be most effective, most immediately.

  Appendix A. An Abbreviated Scorecard To Help Retailers By Organizing
         Sample Findings Into the Retail Intervention Matrix a	c
------------------------------------------------------------------------
                     More convenient    More attractive   More normal to
                       to purchase        to purchase        purchase
------------------------------------------------------------------------
Signage              Use        Use a      Displ
                     display signs to   guidance system,   ay
                     draw attention     such as Guiding    educational
                     to and promote     Stars or a         posters
                     the store's        stoplight          around the
                     selection          approach, at the   store that
                     seasonal fruits    shelf edge         encourage
                     and vegetables     Use        healthy
                     with display       display signs to   eating, such
                     signs              draw attention     as the Half-
                     Provide    to and promote     Plate Rule
                     information        seasonal fruits    Co-
                     sheets on          and vegetables     promote
                     healthier ways     with display       healthier
                     to shop near all   signs              options
                     entrances          Use        together in
                     Directs    signs which        snack aisles
                     traffic entering   provide ``Did      Highl
                     the store such     You Know?''        ight healthy
                     that most          health benefit     alternative
                     shoppers begin     facts, positive    entree
                     in the produce     messages about     options such
                     section            specific           as the salad
                     Provide    healthful foods    bar on
                     a circular/ad      throughout the     posters or
                     publication        store, or both     signs within
                     featuring and      Bundle     all dining
                     promoting          recipe             areas
                     healthier value    ingredients for    Place
                     options at least   family meals       posters
                     once per week      next to recipe     displaying
                                        cards for a        healthier
                                        healthy meal       foods or a
                                        Make       guidance
                                        sure that soda     system such
                                        and low-nutrient   as the Half-
                                        snacks (i.e.,      Plate Rule in
                                        chips) are not     visible areas
                                        displayed or       in the dining
                                        merchandised in    area
                                        the produce
                                        section
Structure            Offer a    Assign     Offer
                     ``grab and go''    designated         at least
                     area in the        parking spots      three
                     front of the       near at least      healthier
                     store with a       one entrance for   foods for
                     small selection    pregnant women     sale at all
                     of low fat milk,   and mothers with   entrances to
                     eggs, 100%         infants (similar   prime
                     juice, low-fat     to handicapped     healthier
                     yogurt, and        spots) d           shopping
                     whole grain        Create a   Offer
                     bread for the in-  fresh produce      pre-printed
                     and-out shopper    display in the     shopping
                     Organize   seafood section    lists of
                     ingredients for    including items    basic staples
                     a healthy meal     such as lemons,    near all
                     by preparation     tomatoes, beans,   entrances
                     method, such as    and asparagus      Offer
                     a stir-fry         Display    healthier
                     section that       whole fruits       food samples
                     includes           such as oranges,   or
                     mushrooms,         apples, pears,     demonstration
                     eggplants,         nectarines, and    s near at
                     peppers, and so    apricots next to   least one
                     forth              prepared           entrance and
                     Place      desserts           at least once
                     healthier foods    Make       per week
                     conveniently at    sure that there    Offer
                     eye level          is at least one    \1/2\
                     Make       checkout aisle     portions for
                     available one      in which the       all entrees
                     percent or fat     only food for      and desserts
                     free milk, 100%    sale qualifies     that are
                     juice, and water   as healthier (no   served or pre-
                     in all mini        candy aisle)       packaged,
                     fridges in                            smaller
                     checkout aisles                       containers
                     Make                          for self-
                     sure there is at                      service
                     lest one                              entrees and
                     checkout aisle                        desserts, or
                     [i]n which the                        both
                     only food for                         Make
                     sale qualifies                        sure that
                     as healthier (no                      takeout boxes
                     candy aisle)                          are available
                     Make                          for leftovers
                     sure that all                         not eaten in
                     beverage coolers                      the dining
                     have both water                       area
                     and low-fat non-                      Offer
                     flavored milk                         divided
                     stocked and                           shopping
                     available                             carts with a
                                                           ``place
                                                           fruits and
                                                           vegetables
                                                           here''
                                                           section
Service              Supply     Provide    Suppl
                     simple five-       calorie            y useful tips
                     ingredient         information on     related to
                     recipes as tear-   different types    preparation,
                     off cards next     and cuts of meat   storage, and
                     to specific        in the form of     food safety
                     produce in-        posters,           in produce
                     store, on the      brochures, or      section, via
                     store's website,   labels             mobile phone
                     mobile phone       Make       app, or both
                     app, or both       sure that the      Use a
                     Make pre-  store's website,   receipt
                     cut vegetables     mobile app, or     program which
                     available in the   both (if they      can create an
                     meat section       have one) has      itemized list
                     Provide    Shopper Loyalty    indicating
                     an area in the     specials that      what
                     store for          include deals on   percentage of
                     shoppers to sit    healthier items    purchases
                     and relax d        Provide    were fruits
                     Provide    a loyalty card     and
                     an area in the     program which      vegetables,
                     store for          rewards            low-fat meat,
                     shoppers to eat    customers with     and low-fat
                     d                  incentives such    dairy
                     Offer a    as bonus points    Use a
                     salad bar that     or coupons for     receipt
                     includes lower     purchasing         program that
                     calorie            fruits and         uses loyalty
                     dressings          vegetables,        card
                     options such as    making healthier   information
                     oil and vinegar    choices, or both   to show how
                     Promote    Offer a    much was
                     mobile phone       discount for       spent on
                     apps that          customers if a     fruits and
                     encourage          certain            vegetables,
                     healthful eating   percentage of      and compares
                     such as            purchases are      this amount
                     Fooducate,         fruits and         to past trips
                     MyFitnessPal or    vegetables
                     other Barcode/QR   Offer at
                     code scanners      least two daily
                     Offer      healthier grab &
                     tips, features,    go breakfast,
                     or videos          lunch, and
                     involving better   dinner options
                     shopping and
                     better living on
                     the store's
                     website or
                     social media
                     outlets
------------------------------------------------------------------------
a  Reprinted, with permission, Slim by Design, Wansink (2014).
b Findings are from published papers, working papers, and unpublished
  pilot studies (Wansink 2014).
c Comfort measures reduce stress. People make better food decisions when
  they are under lower stress conditions.
d Editor's note: No footnote in submitted article.


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    The Chairman. I thank our panel, terrific. I want to remind 
our Members that I am going to be relatively strict with the 5 
minute clock in order to try to get everybody through the 
system. So if you want to use most of your 5 minutes to make 
editorial comments and ask a question with a second left on the 
clock, I will ask our witnesses to submit the answers for the 
record. I am just trying to be fair to everybody.
    So with that, I will recognize the Chairman of the 
Subcommittee on Nutrition for his 5 minutes. G.T.?
    Mr. Thompson. Thank you, Mr. Chairman. Thank you, members 
of the panel, for everything that you do, supporting the 
nutritional needs of American families. It is greatly 
appreciated.
    This is such a great topic, obviously one that I am 
passionate about. We are looking at how Americans find 
themselves, and American families, individuals, a lot of 
children find themselves in some pretty challenging financial 
circumstances, get access to nutrition. Certainly in addition 
to personal resources and family support, community programs, 
and obviously our TEFAP program and other ways that this 
Committee supports those community programs, and then we have 
SNAP, the Supplemental Nutritional Assistance Program.
    And this is an appropriate place to have this discussion. 
Quite frankly, this is the appropriate jurisdiction when you 
look, because there are two basic principles. First, nutrition 
matters in so many different ways; and second, it is farmers' 
feed.
    And so my first question is to the gentleman from the 
Keystone State, Mr. Weidman. It is good to see you. Thank you 
for being here today, and congratulations on The Food Trust's 
25th anniversary. We appreciate all that, sir, your 
organization does to improve access for those in need to 
affordable and nutritious food.
    Your testimony mentions that in Pennsylvania, nutrition 
education programming is in both urban and rural environments. 
I represent the Pennsylvania 5th district. Obviously, on this 
topic I am concerned with all Americans, but in the 5th 
district, which is very rural by definition, 24 percent of the 
land mass of Pennsylvania, how does SNAP-Education reach into 
those rural areas?
    Mr. Weidman. Thank you, Congressman Thompson.
    In Pennsylvania, we have a great SNAP-Ed program. There is 
a little variability from state to state in how the program is 
operated. In Pennsylvania, it is led by Penn State, and they do 
a great job. Because of the extension program, they have a lot 
of breadth to cover rural areas. We have stuff happening in 
almost every county in Pennsylvania. And it is similar to the 
work that we are doing in Pennsylvania, working with children, 
working with adults to get them to learn more about where food 
comes from, sometimes nutrition science can be confusing to all 
of us, so helping them, kind of guide them to make good choices 
of the food around them.
    One of the programs we work with is the Share Our Strength 
Program called Cooking Matters in the supermarkets. It is 
really taking seniors and other adults on tours of a grocery 
store literally and teaching them about how to shop healthy, 
how to shop on a budget. And this kind of work is happening all 
around the country. There is a great rural example of SNAP-Ed 
happening in New Mexico, the CHILE (Child Health Initiative for 
Lifelong Eating and Exercise) Plus Program, and that is doing 
work in Head Start centers as well as pre-K, working with kids 
and their families, basically, to help them, again, guide them 
on making healthier choices, teaching them how to cook healthy 
recipes, taste tests, and that is happening on Tribal lands as 
well in New Mexico, in addition to other sites. It is at about 
80 sites in all in rural areas of New Mexico. And I am sure 
there are plenty of other examples.
    SNAP-Ed is a great way to get at both this problem of 
improving health in urban and rural communities.
    Mr. Thompson. It seems like from the testimony and past 
discussions I have had with key stakeholders and folks making 
sure that nutritional needs are met is really strengthened by a 
collaborative process, and obviously with programs like SNAP-
Ed, food insecurity, nutrition incentives, Healthy Food 
Financing Initiative, all those, can you expand just in the 
short time we have on other types of collaboratives, other 
folks who have sat at the table. You mentioned my alma mater, 
the great land-grant university of Penn State. Are there other 
examples of collaboratives?
    Mr. Weidman. Sure.
    Mr. Thompson. It seems like a model we should continue to 
strengthen.
    Mr. Weidman. Yes, There are great examples of 
collaboratives, a lot with the grocers. We work with a great 
local grocery chain in Pennsylvania called The Fresh Grocer, 
and The Fresh Grocer is partnering with us to provide us space 
for doing nutrition education, SNAP-Ed programming in their 
stores. As Brian said, these stores are a great place to meet 
customers where they shop and help guide them to make healthier 
choices. That same grocer is also helping us with SNAP 
incentives, doing our Philly Food Bucks inside The Fresh 
Grocer. Every time a customer spends $5, the grocer is the one 
that created the whole technology to put out a coupon, an 
electronic coupon for $2 in free fruits and vegetables at that 
store. And, again, this is something that we are seeing 
nationally, great partners with grocers, with farmers certainly 
at all of our farmers' markets in Pennsylvania and around the 
country have been great partners.
    I also just quickly would mention that the U.S. Chamber of 
Commerce today in D.C. is having a conference called the Health 
Means Business conference, and they are recognizing 
partnerships between nonprofits and the corporate sector aimed 
at improving health. GSK has funded a citywide initiative 
called Get Hype Philly, working to get youth to be leaders in 
making healthy changes in their community. So we are working 
with nine other nonprofits and 50,000 kids in Philadelphia with 
GSK, and then Campbell Soup Foundation in Camden, New Jersey is 
midway through a 10 year initiative working with a number of 
groups to improve health and childhood obesity.
    Mr. Thompson. That is great, Mr. Weidman. Thank you.
    I see my time has expired.
    Mr. Weidman. Okay, thank you.
    The Chairman. The gentleman's time has expired.
    Mr. Scott, 5 minutes.
    Mr. David Scott of Georgia. Thank you, Mr. Chairman.
    This whole issue, to me, strikes right at the nerve of the 
foundation of our great country, which is founded on the 
principles of life, liberty, and the pursuit of happiness. And 
there is no other area of human endeavor that best manifests 
our foundation of life, of liberty, and happiness than our 
choice of food.
    Think of what makes you happy. I know there are many things 
out there individually that make us happy, but none greater 
than food. And what bothers me with this is that we want to 
make subjections here that are just absolutely not true. Sodas, 
candy, sweet things, that is not what makes us obese. It is the 
lack of our children exercising. Look at the history of this 
country. Look at us 30 years ago, 20 years ago. What has 
happened? Our children and us, we don't go and exercise. We 
don't have physical education in the schools anymore. But what 
we have is this Blackberry, this Facebook, this going on the 
Internet. And instead of children going and saying let's go 
play basketball or let's hook up a game here, they go in the 
basement or they go in their room and they stay hour after hour 
on that.
    My whole point is this. Food surveillance violates the 
basic principles of this great country, and first of all, you 
are going to discriminate between a low-income person simply 
because for 6 months on average that is all they stay on food 
stamps. They are gone. Look at the complexity you are going to 
put into the grocery store. Who is going to pick up that extra 
cost to have the food police there monitoring, and why?
    Now I think that a better way of going about solving many 
of these things is to look at how we educate people. You can't 
force them. You can't deny them their freedoms to be able to 
make choices without violating their pursuit of happiness.
    Think about it. When Thomas Jefferson wrote those words, he 
said to himself, and he wrote in one particular pamphlet, and 
he wrote this to his arch competitor, Alexander Hamilton. And 
what he said was, in this way, he said, ``What I have declared 
here, my dear Mr. Hamilton, is has come to me these words, 
life, liberty, and the pursuit of happiness.'' He said by some 
divine providence intervention. In other words, what he was 
saying was those words, life, liberty, and the pursuit of 
happiness, he came and he wrote that Declaration of 
Independence under the inspiration of God Almighty. Let us not 
go against that.
    Thank you, Mr. Chairman.
    The Chairman. The gentleman yields back.
    Mr. Crawford, 5 minutes.
    Mr. Crawford. Thank you, Mr. Chairman. That is a tough act 
to follow, Mr. Scott. I appreciate that.
    I represent a part of the country, the Delta region, 
probably better than \1/2\ of my district is, and as you can 
imagine, working with a high degree of poverty. So many of my 
constituents are heavily dependent on SNAP benefits, and the 
problem they confront is that over the years, we have seen a 
decline in the number of supermarkets. So what we are dealing 
with ultimately here, ironically, is one of the most productive 
agricultural regions in the country is effectively a food 
desert. We have limited access to the healthy foods, so they 
rely on convenience stores and things like that. To restrict 
SNAP purchases to healthier food products, my question is would 
the compliance costs outweigh the benefits of accepting SNAP 
benefits at retail locations, or would it encourage SNAP 
retailers to offer a wider variety of healthy food products? 
And I will just leave that to any or all that want to make a 
comment on that.
    Ms. Sarasin. It depends, frankly, on how any changes to the 
program were structured. Obviously, retailers want very much to 
be in areas where they can meet customer needs, and if the 
customer base is there and they can be profitable and 
successfully meet the needs locally, they will, and they want 
to.
    The kinds of proposals that we are talking about here will 
definitely have an impact on how these companies can function. 
The potential increase in the administrative costs for a 
program that limits certain products, whatever they are, 
whatever kind of products we are talking about, is going to be 
oppressive, as I indicated in my testimony, given the sheer 
volume of products that are available in supermarkets today, 
and the number of new products that are introduced every year. 
The creation of a structure to monitor that and determine which 
products are in and which ones are out, is going to necessarily 
create pressure on the system, and also create pressure at the 
retail level for stores that are in existence, for stores that 
are being contemplated to be created, and the result could be 
that stores can't function profitably any longer in some areas. 
It could also be that some stores will have to determine that 
the administrative costs are so great that they would have to 
leave the SNAP program entirely.
    Dr. Schanzenbach. Thank you.
    I would echo that. I would be particularly concerned that 
these increased regulatory burdens would drive out some of the 
smaller retailers, especially in rural areas.
    The other thing that I would like to add is that, as an 
economist, all of this comes down to supply and demand, and I 
have heard a lot of conversation about how do we increase the 
demand for healthy foods, whether that is through education, 
whether that is through pricing incentives. If people demand 
more healthy foods in those areas, those grocery stores are 
going to respond by supplying more of them. So that is why I 
would like to see the market work in this, and not restrict.
    Mr. Weidman. And I would just agree with you of the need 
for more grocery stores in the Delta. We are working with the 
Michael and Susan Dell Foundation and Hope Enterprises located 
in Jackson, Mississippi, to incentivize more grocery stores to 
come to the Delta region. I also think the USDA through the 
farm bill, the Healthy Food Financing Initiative offers real 
opportunities to bring more grocery stores to the region.
    Mr. Crawford. Dr. Rachidi, do you want to weigh in on that?
    Dr. Rachidi. Sure, just real quickly. If you placed 
restrictions on a very narrowly defined product such as 
sweetened beverages, it would not be overly burdensome for 
retailers, and I agree that it is really a supply and demand 
issue. So if you did a restriction on sweetened beverages, for 
example, which drove up demand for healthier products because 
that is all people could use their SNAP benefits for, you would 
hope that the retailers would then respond by providing more 
healthy options.
    Dr. Schanzenbach. And just respectfully, we think based on 
economic theory that that is not what will happen. So many 
people are using both SNAP benefits and their own cash, it 
won't actually change behavior.
    Ms. Sarasin. And if I could also respond to that.
    I think we end up on a slippery slope when we start talking 
about sweet beverages, because I don't know what that means, 
and like most things, the devil is in the details. Because when 
we start talking about sweetened beverages, are we talking, I 
don't know exactly we are talking about. I mean, there are 
juices that bring lots of nutrition that are sweetened 
beverages. There are yogurt drinks that bring all kinds of 
nutrients to the consumers of them that also have sugar in 
them. We need to be careful about how we are discussing these, 
because we are talking about a category of products as if we 
all understand what that means.
    Mr. Crawford. Thank you. My time has expired.
    The Chairman. The gentleman's time has expired.
    Mr. McGovern, 5 minutes.
    Mr. McGovern. Well thank you.
    It is safe to say that we all can make better choices and 
healthier choices, SNAP recipients and non-SNAP recipients. The 
avoidable health care costs that taxpayers pay for non-SNAP 
recipients, they get diabetes, heart disease. We all need to do 
better. But I don't think by limiting the choices of SNAP 
recipients you get there.
    In fact, Ms. Rachidi said that we have a new President. 
Maybe this is a time to try a pilot project. So when you say 
that, I Googled Donald Trump's eating habits, and it is not a 
pretty picture. Domino's Pizza, Kentucky Fried Chicken, 
McDonald's, Diet Cokes. I mean, maybe we ought to begin with a 
pilot project that limits access to unhealthy foods at the 
White House, because we all pay for that. The taxpayers pay for 
that.
    If we are serious about it, this ought to be a bigger 
discussion. And one of the things we ought not to do, and this 
is out of this Committee's purview, is cut back on the 
nutritional standards of the school feeding programs, which 
some have suggested. We ought to figure out the things that 
have worked. I visited a place in Dorchester, Massachusetts, 
called Daily Table. They provide access to nutritional foods at 
a lower cost. A lot of these vegetables and foods would 
otherwise be discarded by other grocery stores, but people go 
there and they can afford to be able to make healthier choices.
    I personally think that one of the things that we could do 
is increase the SNAP benefit. It is about $1.40 per person per 
meal. You can't make a lot of choices in general with that kind 
of benefit. Research from the Center on Budget and Policy 
Priorities found that increasing SNAP benefits by a mere $30 
per month would lower food insecurity, decrease fast food 
consumption, and increase vegetable consumption. We have seen 
the Healthy Incentives Pilot which found that an ongoing 
investment of less than 15 per person per day may result in 25 
percent increase in fresh fruit and vegetable consumption. And 
out of this pilot came the FINI grants, which are working 
across the country to incentivize healthy eating. All very 
positive stuff.
    I have been to SNAP-Education programs, and I will be 
honest with you, the critique I get from some who attend these 
programs is that the ability to buy the stuff to have a 
healthier diet is difficult, because in their neighborhoods; 
they don't have supermarkets. They have to rely on convenience 
stores, and there are a lot of issues here that we need to talk 
about.
    In our school programs, we ought to stress nutrition 
education at an earlier age. It is a lot easier to get people 
on a healthy pathway when they are younger.
    But let me ask, Dr. Schanzenbach, do you support increasing 
SNAP benefits? Do you think that would promote healthy eating?
    Dr. Schanzenbach. There is good evidence that an increase 
in SNAP benefits would increase consumption of healthy foods. 
Just like was testified earlier, when people have really tight 
budgets, they concentrate on getting the lowest cost calories; 
and then, if we expand purchasing power over time, then people 
will increase both the quantity and the quality of foods that 
they are eating.
    We have really good evidence from the Summer Feeding 
Program, the Summer EBT Program that says, additional resources 
improve nutrition outcomes, and similar, this work that you 
cited from the Center on Budget and Policy Priorities suggests 
that additional $30 per month would change how people eat and 
make them consume more healthy foods.
    Mr. McGovern. And I agree with what Ms. Sarasin said about 
how do you define a sweetened beverage. Does cranberry juice 
fall into that category? There are lots of nutritional benefits 
to cranberry juice, but it is a sweetened beverage. And would 
you take that off the list?
    And again, from my experience talking to people on SNAP, a 
lot of times it comes down to the affordability as well as the 
access. We have lots of pilot programs going on all across the 
country. You mentioned one going on in Pennsylvania, all very, 
very positive stuff. We ought to understand that is how you do 
it, not by going and telling somebody that we are going to 
restrict your choices. I think that is something that we ought 
not to be doing here in Washington. But if you want to do a 
pilot program, I am happy to cosponsor one at the White House, 
because I am worried about our President's eating habits right 
now.
    So thank you.
    The Chairman. The gentleman's time has expired.
    Mr. LaMalfa, for 5 minutes. Mr. LaMalfa, for 5 minutes? You 
pass? Mr. Davis, 5 minutes.
    Mr. Davis. Thank you, Mr. Chairman, and thank you, Mr. 
LaMalfa.
    Mr. LaMalfa. You are very welcome.
    Mr. Davis. I appreciate that. It is always actually great 
to follow my colleague, Mr. McGovern, and outside of the 
comments about the President's eating habits, I actually agree 
with him on some of these issues that maybe we ought to look at 
incentives. Having this debate is great for all of us, because 
this is isn't a partisan issue. I would challenge my colleague, 
Mr. McGovern, to go to some of those restaurants that he named 
and I believe he is going to be able to find that he can make 
healthy choices at every single one of those restaurants, and 
that is what is great about what we have seen in our country, 
in our access to healthy foods. The marketplace is demanding 
healthier choices, and all of those restaurants that he 
mentioned have so many more today at a very much more 
affordable cost than what they had even 5, 10 years ago.
    So the marketplace is actually helping to supply that 
demand for healthier choices, and I agree with Mr. McGovern. I 
don't think that we have a role here in being the food police. 
And he mentioned some critics of the School Nutrition Program. 
Yes, I am one of those, and it is because the lunch ladies tell 
me stories about how kids are throwing food away that they are 
not eating. We don't have an adequate supply of healthy food to 
serve in our school lunches that tastes good. Kids are throwing 
it away, so how do we fix that? We do it by actually offering 
more healthier choice, but in a way that is less of a top down 
approach. Maybe incentivize it.
    It is great to see so much testimony about expanding 
purchasing options. I was a big supporter of the Double Bucks 
Program in the last farm bill, and Dr. Wansink, I was actually 
leaving to go to another hearing, but listening to your 
testimony, and you talked about how do we have more incentives? 
What can we do to incentivize rather than punish? Because I 
don't drink cranberry juice. Sorry. It is probably good for me, 
Jim.
    Mr. McGovern. It is.
    Mr. Davis. I don't drink it. It tastes like syrup to me. I 
can't handle the sugar content in it. But if I was a SNAP 
beneficiary, would I be able to buy cranberry juice and not 
what I live off of, Diet Coke or Diet Pepsi? Who is going to 
make that choice? It has zero calories. Actually, cranberry 
juice has a lot more sugar and a lot more calories. So I don't 
know who is going to make those choices, and frankly, I haven't 
seen the Federal Government be a good barometer of making 
choices like that for the constituents that I serve.
    But Dr. Wansink, can you tell us what type of incentive 
program would you recommend?
    Dr. Wansink. Thank you very much.
    Well if we can use schools as a parallel, as was brought 
up. One of the ways that we found that it is best to guide kids 
to eat healthier in schools is not necessarily nutrition 
education programs, because they are costly and they are tough 
to get into schools, but instead simply making the healthier 
products more convenient, more attractive, more normal. Having 
a basket of apples next to the checkout line, making foods 
taste better, reducing waste and it also increases how much 
people eat. And there are 29,000 schools who are now on that 
program.
    Now a similar thing can be done in the stores, and you are 
right spot on when you say anybody goes in these restaurants 
can eat healthy, because there are the options that are now 
cheaper than they used to be. Making simple changes in grocery 
stores that are incentive compatible with the grocery stores 
that are either profit neutral or profitable for them.
    Mr. Davis. Haven't they already been doing that?
    Dr. Wansink. Not as widespread. I took last year off and 
went on sabbatical to implement this in Norway to show that it 
could be done as a tested concept, and even making small 
changes in these grocery stores, simply having things such as 
having fruits and vegetables within 10 of the doorway 
increases how much people take by three percent. Making these 
changes are things that grocery stores find profitable, but 
then it also benefits all of us, not just SNAP beneficiaries.
    Mr. Davis. But you wouldn't make the government force the 
stores to change?
    Dr. Wansink. Absolutely not.
    Mr. Davis. Okay.
    Dr. Wansink. No, we would make the profit argument to them 
that they can make more money making people healthier.
    Mr. Davis. Okay, because I know some stores would have to 
actually move their Starbucks out of the way to be within that 
10 of the door.
    Does anybody else on the panel want to address the 
incentivization?
    Ms. Sarasin. If I could just say that, apart from the 
incentive part of it, the thing that retailers are doing is a 
lot of the stuff is happening on their own without incentives. 
Our most recent data shows that something in the neighborhood 
of 95 percent of our member companies have nutritionists and 
dieticians onsite in their stores or at corporate headquarters 
helping direct what is going on with their customers and 
education. So there is a lot of this stuff that is happening 
even without the incentives.
    Mr. Davis. Thank you. My time has expired.
    The Chairman. The gentleman's time has expired.
    Ms. Lujan Grisham, 5 minutes.
    Ms. Lujan Grisham. Thank you, Mr. Chairman, and I want to 
thank my colleagues, Mr. McGovern and Mr. Davis. The focus of 
all of our conversations ought to be on the incentives, and I 
don't want to lose momentum. And we do really want very 
specific ideas. In my state, we have incentives and initiatives 
that are both authorized and supported by the farm bill, and 
many of those that are solely state or corporate private-public 
partnership initiatives. We have programs at WIC, we have 
programs at Head Start that are uniquely focused on SNAP-
Education. We have a program called CHILE Plus. For those of 
you not from New Mexico, we are the leaders and have the best-
tasting New Mexico chile anywhere. In fact, our state question 
is whether it is red or green? But it is the Child Health 
Initiative for Lifelong Eating and Exercise, and it really is 
focused to integrate both purchasing and education and cooking 
and eating healthy that we pushed out into the rural areas.
    The core issue is that we want the flexibility for states 
and rural communities and communities to really figure out how 
to do it, but we need the farm bill to be really clear that 
there is not only those incentives in terms of authorizations, 
but there is funding and incentives for those funding vehicles. 
I did the SNAP challenge, for $30, so I just had a protein 
shake. I really think, as nearly a 60 year old woman with a 
fairly sedentary public policy lifestyle I am really proud of, 
I try to be cognizant of my calorie intakes. I work very hard 
at it. Well during my SNAP challenge, I wasn't so good at it, 
all right? I ate ramen noodles. I am trying to think of the 
other high carbohydrate kinds of foods. I tried to get peanut 
butter, high fat, and I couldn't get any organics. I bought one 
banana and one apple for my weekly benefit if I was going to 
have enough food and $1.50 left over.
    Now if I am dealing with average benefits for my whole 
family, and God forbid somebody in your family is sick and they 
say we want high iron, high protein, you have a teenager who is 
playing football. With that SNAP benefit, you can try all you 
want to do healthy foods. It is impossible, because unhealthy, 
cheaper foods are all you can buy. And I ate it. I stayed true 
to doing what I was supposed to do, but it wasn't good.
    So if we don't deal with that, in my state, seniors are 
about to get their SNAP benefits cut: $33 a month with the 
state portion that they are going to cut. I don't know about 
you. I am a caregiver for my mom. If I go to the grocery store 
for $33, I can't get anything that she ought to be eating. 
Anything. So if we don't increase SNAP-Education funding and we 
don't really put resources to allow folks to do these 
incentives, we can talk about how great they are all the time, 
and they are. I agree with that, my colleagues on the other 
side of the aisle, we really shouldn't be the food police. We 
ought to do incentives. We ought to do something about obesity. 
You do something about obesity, you have hundreds of millions 
of dollars to put back into economic incentives and farm bill 
incentives to grow better food and to do more in the areas that 
we all care about on this Committee. How can you get us, one of 
the most bipartisan committees, to really think long and hard 
about putting the resources where they need to be and seeing 
the evidence-based outcomes that we have the research, the 
Chairman teases me about research all the time. We have the 
research that shows us that you have to educate people.
    Do you have ideas to help us get to that agreement about 
making sure that there are the resources that allow us to do 
the things that you know would make a difference?
    Dr. Wansink. I believe if we want to change things really 
quick, it is probably not going to be education. It is a nice 
long-term solution that is going to take a long time, and it is 
not going to be the payoff. Initially educating, in this case, 
retailers as to what they could do to guide people to these 
healthier options, which are also high margin foods, because 
they have to throw them away. If a banana goes bad, a retailer 
loses money on it. What they can do to guide people to these 
and get people to buy more of them. It is not just going to 
benefit SNAP recipients, but it is going to benefit all of us.
    Ms. Lujan Grisham. Anybody else? I have 10 seconds. Let's 
go.
    Dr. Rachidi. Just real quickly, there is really little 
evidence that, and I am in favor of incentive programs, but 
there is little evidence that incentive programs reduce 
consumption of unhealthy foods. And so I advocate for both, and 
so if you look at the integrity of the program, you could gain 
support for increasing incentive programs and education if you 
eliminate some of these other issues like allowing unhealthy 
foods to be purchased from the program.
    Ms. Lujan Grisham. My time is definitely up, Mr. Chairman.
    The Chairman. Thank you.
    Mr. Comer, 5 minutes. Mr. Comer, 5 minutes.
    Mr. Comer. I was Commissioner of Agriculture in Kentucky 
for 4 years, and one of the things that worked really well for 
us with being able to provide healthy options to people with 
EBT cards was when I first got elected, we only had 21 farmers' 
markets that took EBT cards. When I went out of office, all 225 
farmers' markets took EBT cards, and a lot of people said well, 
that will never be a factor in sales. In a lot of those 
farmers' markets, it was over 25 percent of the sales were from 
EBT cards because of food deserts, and access to healthy food.
    The farmers' markets are a great way, a great option for 
people on SNAP because there are no bad foods at a farmers' 
market, or I have never seen candy or soft drinks sold at any 
Kentucky farmers' market, so I just wanted to share that story. 
That was a pretty successful way to get healthy food options to 
people that need it because of the obesity problem that we 
clearly have.
    Shifting gears here, what percentage of people use their 
entire monthly SNAP benefits during the first week of the 
month? Does anybody know the answer to that?
    Ms. Sarasin. I don't know the percentage, but I can tell 
you that the data that we have seen shows that a tremendous 
amount of it is spent in the first week, and that those 
purchases tend to be the largest of the month.
    Mr. Comer. Right.
    Ms. Sarasin. And the ones that have the most protein and 
the things that we would tend to expect that they would buy 
first.
    Mr. Comer. In talking with retailers across the state about 
this issue, several have come up with this suggestion, and they 
use this example. The majority of the people that they deal 
with use their entire benefit, monthly benefit, the first week 
of the month. So if you want to provide milk and things like 
that, meat for low-income people to eat healthy, if this is 
their only source of revenue for their food, the milk expires 
or it is gone. They don't have access to milk or a lot of 
proteins that expire. I wonder how feasible it would be to have 
a bi-monthly benefit to encourage more people to try to manage 
their budgets to where they can have milk for the first half of 
the month and the second half of the month, because it is a big 
problem. I represent a very poor district and that is something 
that just about every retailer that I have talked to has 
mentioned that as a suggestion to be more efficient and to help 
the people. Because a lot of the people unfortunately don't 
have a high level of financial literacy, and that is an issue. 
So I just wanted to get your thoughts on that, Ms. Sarasin.
    Ms. Sarasin. As a Kentuckian myself, and from the next 
county over from you, I can totally understand the discussions 
that you have had. And what we find in many states is that they 
have gone to not having single dates of the month when the 
benefits are available. There are multiple points in the month 
when recipients have access to their benefits. And so in the 
states where that has happened, it has been very beneficial, 
certainly from the retail perspective because it allows us, 
instead of having to have such pressure on both our labor pool 
on a certain day or in a certain week of the month, but also on 
the supply chain issues so that we have enough milk in 
different quantities and different styles and different sizes, 
for example. Being able to move these things out over the 
course of a month would certainly, from a retail perspective, 
be a better situation for us.
    Mr. Comer. Yes, I am for less government, and I don't like 
the nanny state and all that, but is it clearly a problem, and 
the obesity issue, it is almost at epidemic levels. The poorer 
the county, the higher the obesity rate. And you can see that 
when you go into public schools and, unfortunately for the 
students in the poorer schools. You can just tell there is a 
higher obesity rate in those schools.
    Ms. Sarasin. A couple of things. One is the data seems to 
indicate that everybody is getting fat, rich kids, poor kids 
alike. But to give my perspective on your question about the 
twice a month. Something that people raise as a concern there, 
especially for people with limited access to places to shop, 
breaking this benefit up into twice a month might make it 
harder for them to get to the store, because now instead of one 
big shopping trip, they have to do multiple. So it is just 
something to consider.
    Mr. Comer. Thank you, Mr. Chairman.
    The Chairman. The gentleman's time has expired.
    Ms. Adams, 5 minutes.
    Ms. Adams. Thank you, and thank you, Mr. Chairman and 
Ranking Member Peterson, for hosting the hearing, and thank you 
to the witnesses for being here today.
    The SNAP program is very important to those in the 12th 
District of North Carolina. I represent that district, and the 
folks struggle with food insecurity a lot. We have a lot of 
food deserts. But as someone who lives with diabetes, I know 
that there will be times when someone that participates in the 
SNAP program and has diabetes will need to buy a candy bar to 
quickly raise their blood sugar, and they should be able to buy 
that candy bar with their SNAP benefits.
    Dr. Schanzenbach, could you provide a brief summary of the 
findings of your research on the long-term health impacts on 
individuals who participated in SNAP as infants and toddlers?
    Dr. Schanzenbach. Thank you. So my recent research study 
looked at the introduction of the Food Stamp Program, which was 
done over the 1960s and 1970s. Congress in its great wisdom 
decided to roll it out slowly, and so that gives us an 
opportunity to study, if you lived in this county when you were 
5 years old versus that county, you had different access to the 
Food Stamp Program, as it was then called. And so then we can 
tease out well, what happens if people are given access to the 
Food Stamp Program.
    What we found was a couple of things. First is children are 
born healthier if their moms have access to food stamps while 
she is pregnant. But then because this happened so long ago, we 
were able to follow the children who grew up in these areas 
over time. So now they are 40 and 50 years old. What we found 
was that we should really be thinking about food stamps as an 
investment in children. So we found that access to food stamps 
during childhood increased the likelihood that they graduated 
from high school by 18 percentage points. Furthermore, we were 
able to look at their adult outcomes. We found that they are 
healthier in adulthood. We looked at this thing called 
metabolic syndrome, which is a clustered association between 
obesity, diabetes, high blood pressure, et cetera. What we 
found there was more access to food in early life sets up 
systems in your body to actually make you less obese in later 
life.
    Then finally we found that, and this was particularly the 
case for women, that people who had access to food stamps in 
childhood grew up to be more economically self sufficient. They 
are more likely to be employed. They had higher earnings, and 
they themselves as adults were less likely to be reliant on 
food stamps or welfare programs.
    And of course, as an economist, what I think is going on 
here is that the children were better able to make investments, 
right? They weren't going to school hungry so they could pay 
attention in school better and learn more. And so this is very 
important evidence, evidence I certainly want the Committee to 
know about, to think about this program as an investment.
    Ms. Adams. Okay. So would you support a higher SNAP 
benefit?
    Dr. Schanzenbach. Certainly, it is very important to 
preserve the program as it is, so that is sort of always my 
first worry. But then I do think with separate evidence that 
there is good evidence that increasing the benefit levels will 
increase the amount of healthy foods purchased, will reduce 
food insecurity, and of course, one out of every five children 
in this nation lives in a food-insecure household right now, 
and in nine states, it is one out of four children live in a 
food-insecure household. I think that is too high for this 
great nation of ours.
    Ms. Adams. Okay. So why would SNAP restrictions on soft 
drinks, for example, be unlikely to change consumption patterns 
shared by all Americans?
    Dr. Schanzenbach. Sure. So of course, remember that food 
stamps benefits are relatively modest, $4.50 per person per 
day, and if we think about an average household, which gets 
about $250 in food stamp benefits, and then they have to 
supplement their food purchases by additional cash resources. 
So it is $100, $150 additional. Then on average, households 
spend about $12 to $14 a month on soda, right? So $250 SNAP, 
$100 in cash, $12 on soda. Be very straightforward that even if 
we go through all this red tape and debate what is in a soda 
and what is out of a soda and is this sugar sweetened or not, 
if we did that, when they get to the checkout line, they would 
be able to say, ``Okay, I still want to purchase my soda, my 
sugar sweetened beverage. I just need to do it out of this pot 
of money instead of that pot of money.'' That is a lot of red 
tape to go through to not change behavior.
    Ms. Adams. Thank you very much, Mr. Chairman. I yield back.
    The Chairman. The gentlelady yields back.
    Mr. Yoho, 5 minutes.
    Mr. Yoho. Thank you, Mr. Chairman, I appreciate it, and I 
appreciate you all being here. This is such an important topic 
that we look to reform and make it right, both for the 
recipient and for the taxpayers.
    Ms. Sarasin, one of the common arguments against 
restricting SNAP purchases has been the operational challenges 
of implementing restrictions, and if you have gone over that, I 
apologize, and if you haven't, with regard to the tech needed 
to track the restricted items, what do you see as a hold up on 
that, or is there anything that we can do better legislatively, 
or leave you guys alone?
    Ms. Sarasin. Well as I mentioned in testimony, one of the 
things that is challenging is that our cashiers end up being, 
to some degree, the food police at checkout time. And as you 
are probably aware, that holds up a line.
    Mr. Yoho. Yes.
    Ms. Sarasin. And if you have ever been in line behind 
somebody who is having a challenge like that, it is difficult. 
And sometimes, it ends up being a difficulty with some of our 
most vulnerable populations, and so it becomes also a stigma 
and a problem in that regard.
    But when you are operating a business that in general is on 
a one to two percent profit margin a year, every second that is 
delayed at the checkout line is a problem. Our companies 
measure it because they want to keep things moving.
    Mr. Yoho. Right.
    Ms. Sarasin. It creates a lot of issues for us at checkout, 
and just the administrative function of trying to figure out 
what is in, what is out, as if we went into the role of trying 
to determine that certain things shouldn't be allowed and 
certain things should be allowed, it would create real havoc in 
our stores.
    Mr. Yoho. Let me ask you this, because this has been 
brought up to me multiple times, in the big retailers' aisles 
that were restricted just to those things so people could go 
right there. It would expedite them going in there, buying 
those products, bringing them up and checking out with no 
confusion. Your thoughts on that, and then the other one is the 
financial impact. We hear people saying that on the retail side 
that this brings in `X' amount of dollars for us, and we can't 
change it because we are dependent upon that. What is the 
pushback that you have experienced in your industry?
    Ms. Sarasin. Well the real pushback is the administrative 
costs of trying to actually facilitate the program. One of the 
things that I hear regularly from our companies is that these 
programs are some of the most difficult regulatory programs for 
them to implement in their stores. And when you are talking 
about companies that have to deal with things like the Food 
Safety Modernization Act and all of the regulations that go 
along with that, if this is a more difficult challenge for 
them, that says a lot for what they are dealing with.
    The costs associated in the store with doing this on such a 
low margin business is significant, and not that there 
shouldn't be changes to the program if they are desirable and 
if they achieve a policy goal, but just to unilaterally 
identify that certain types of products should or should not be 
in without a real basis for making the decision is problematic 
for us.
    Mr. Yoho. Well, you can see how important it is, as many 
meetings as we have had on it, and I commend Chairman Conaway 
and the Chairwoman of the Nutrition Subcommittee last year, 
Jackie Walorski.
    Let me ask one other question, and this goes to Mr. 
Weidman. How is SNAP-Ed reached in the rural area? And I know 
in the State of Florida with the University of Florida, which 
is a land-grant, they have an extension office in every county, 
67 counties in Florida. And they seem to do a good job of doing 
it. The nutritional educational programs, are they different 
based on regions? Like we are in Florida. We have a hot, humid 
climate. How is it in your area, and then can you do a one size 
fits all for nutritional program for the whole nation, or 
should it be more regionalized?
    Mr. Weidman. Yes, that is a great question, and SNAP-Ed 
does great work in rural and urban areas all around the 
country. I mentioned earlier a rural program in New Mexico, 
CHILE Plus, which is doing great work in pre-K and Head Start 
programs. But yet, to your point, the great thing about the 
SNAP-Ed program is it does have kind of oversight and guidance 
to all of the programs that the different states are doing, but 
it allows for local on the ground sort of innovation so that 
the right type of nutrition education is happening, based on 
region and based on the population that you are serving.
    Mr. Yoho. Okay, I appreciate your time. I am out of time, 
and thank you. Mr. Chairman, I thank you.
    The Chairman. The gentleman yields back.
    Mr. Lawson, from Florida, 5 minutes.
    Mr. Lawson. Thank you, Mr. Chairman. I would like to thank 
all of you all who are here. I was just thinking, I am a 
country boy and so I couldn't think of anything more important 
on a Friday than RC Cola and a moon pie. And the other day, I 
was in the airport in Atlanta and I wanted to have a healthy 
choice, and I saw a long line at Subway, but there wasn't a 
line at Bojangles', so I tried to make the right decision, but 
Bojangles' won out. So I understand.
    What I really want to say is that it appears that when they 
did this survey, and anyone can answer, the FNS did a survey, 
and they said that in order to change the program, put 
restriction on the program, that it could cost as much as $400 
million or $600 million to administer the program. And I know 
that would be dollars well spent if you put that into the 
program, and people are going to do different things. And I 
have seen people go into these convenience stores, and even 
standing in line when they were making purchases, and saw that 
it was very difficult and they didn't really want to be there. 
But what I would say to you, and this question will go to 
anyone, is that in my state, we have an organization like Farm 
Share and Frenchtown Farmers Market that carry a similar 
initiative to alleviate hunger. From your success with Food 
Bucks programs and with nonprofit, how can I as a Congressman 
assist other food banks and various organizations to help be 
successful in this way and get this message out? Because you 
talk about the educational aspects of it, rural and urban. What 
can we do, because, you want to see this program continue, and 
I don't know whether the young people know about RC and a moon 
pie, but I want to make sure that it happens to all of us. But 
what can we do as legislators to help in those areas? Anyone 
can answer that.
    Mr. Weidman. I will. As I said in my testimony, I really 
think what is working is this comprehensive approach that 
includes nutrition education, and the SNAP-Ed program is doing 
a great job at that. Through incentives like the new FINI 
Program, and I really appreciate Congress for launching the 
FINI Program. We, for years, have been hearing that you get the 
farmers' market in the neighborhood or if you get a grocery 
store in the neighborhood, what about price, and that can be an 
issue. And we have heard that today. The FINI Program does a 
great job of both, making healthy foods more affordable, and 
also allowing for innovation, again, at the local level in 
places all around the country. And then last, actually getting 
the stores located in areas so that people don't have to take 
three buses to get to the grocery store. And I really 
appreciate, again, the leadership of Congresswoman Fudge and 
many others on this Committee for their support of the Healthy 
Food Financing Initiative, which is a proven model that was 
launched in Pennsylvania, working in partnership with the 
grocers and other food retailers, to locate in under-served 
urban and rural areas, create jobs, and provide access to 
healthy food.
    Mr. Lawson. Okay, and I have one more question for, is it 
Raskins?
    Ms. Sarasin. Sarasin.
    Mr. Lawson. Ms. Sarasin, okay. I'm seeing things--dyslexic. 
But why in the grocery stores are all the candies and stuff 
right up by the cash registers? It feels good to look at all of 
it, but I just ask that question, you know what I mean? Once 
you missed it you got it again. Once you miss it down in the 
candy aisle, it is back up there at the cash register.
    Ms. Sarasin. What you will find is that increasingly in our 
stores, while there are still aisles with candy right up front, 
increasingly there are stores that have lots of other things 
right up front as well. Mr. Wansink referred earlier to the 
increasing incidents of bowls of fruit and other healthy 
products that are available at checkout for consumers who are 
interested in having them.
    So from a retail perspective, our role is to provide the 
best service and create the best experience with the product 
lines that our customers seek, and at a price that they can 
afford, and hopefully as conveniently as possible. So that is 
what we strive to do for all of our customers, whether they be 
SNAP beneficiaries or others. And so we have this constant 
balance going on of trying to make sure that we are meeting all 
of these needs, and for some people, having a sweet treat as 
they walk out of the store is important. For others, it is 
other kinds of products. They would rather have a piece of 
fruit or they would rather have a yogurt as they walk out the 
door.
    So our goal is to try to provide a balance of products for 
all of our customers, depending on what they are looking for.
    The Chairman. The gentleman's time has expired.
    Mr. LaMalfa, 5 minutes.
    Mr. LaMalfa. Thank you, Mr. Chairman.
    So today we are talking about the SNAP program, 
Supplemental Nutrition Assistance Program. Supplemental meaning 
in addition to what might be someone's personal income, or 
other forms of aid a family might be receiving. Nutrition, 
generally thought of as something good for the body, making you 
healthier, stronger. Assistance, the idea that someone else is 
probably paying for this to help people.
    Ms. Sarasin, you talked repeatedly about how what basically 
a hassle this will be for stores to have the system in place to 
differentiate between more of these food products, so do people 
that come through the checkout line that are SNAP users not 
have other products that are ineligible for SNAP very 
frequently, such as house cleaning items, toiletries, other 
things that they are paying for that are not eligible? Is there 
anything that is not eligible for SNAP, I guess, that would 
have to cause a second transaction at the checkout counter?
    Ms. Sarasin. Yes. Yes, there are many types of products 
that are not----
    Mr. LaMalfa. Tobacco, alcohol, like that?
    Ms. Sarasin. Alcohol and tobacco are not SNAP eligible.
    Mr. LaMalfa. Okay.
    Ms. Sarasin. SNAP is applicable to food products.
    Mr. LaMalfa. Yes. So if you have someone in line that is 
making one trip to the store, they are buying all the needs for 
their household for the next week or 2. They are buying 
multiple items. Some are eligible, some are not.
    Ms. Sarasin. Correct.
    Mr. LaMalfa. So if we were to have this discussion about 
things that are nutritional and we have items on the list that 
maybe are now eligible for SNAP but determined somehow to not 
be nutritional, is it really that much tougher to differentiate 
between soda pop and tobacco?
    Ms. Sarasin. The challenge is in how you are defining soda 
pop or how you are defining nutrition or how you are defining a 
healthy product. We have had a lot----
    Mr. LaMalfa. Well shouldn't we try, because we are having 
all this effort made in recent years over fighting obesity and 
kind of differentiating between what things are contributing to 
obesity and what are not?
    Ms. Sarasin. We have had testimony this morning that has 
provided the evidence that doing so is going to be at great 
cost, and that the ultimate benefit----
    Mr. LaMalfa. It is great cost to the people that are the 
assistance part of this program, and it is also of great cost 
to the people, for lack of maybe knowledge or the idea that the 
government is incentivizing it, sending them home with candy 
bars and soda pop. So maybe it is worth the trouble.
    Let me shift to Dr. Rachidi here. I thank you for appearing 
as well. When we talk about the SNAP program's intention to 
alleviate hunger and malnutrition, and permit low-income 
households to obtain a more nutritious diet through normal 
sources, that is in statute, so with these aims and the idea 
that we are approaching nearly ten percent of beverages are 
accounting for expenditure, as was mentioned, we don't have 
data to determine how the restriction should impact the 
program, but we should at least try.
    The recent USDA study was troubling, and I think kind of a 
red flag for a lot of folks. A couple thoughts for you on that 
is you discussed a study also that evaluated the impact of a 
hybrid pilot of incentives and restrictions. So do you think 
this could be a feasible demonstration we could take more 
widely for entire states, and with some more cooperation from 
USDA, which seems to want to shut down states from making their 
own determination? Please expound upon that.
    Dr. Rachidi. Yes, I definitely think it is something that 
should be tested, and at the state level or the local level. 
Like I mentioned, we tried to do it in 2011 in New York City. 
The USDA at the time denied it, as they denied a few other 
states that had----
    Mr. LaMalfa. What do you think the USDA's incentive is to 
deny these possible studies and the learning we can get from 
that at state level or New York City level?
    Dr. Rachidi. I think there is a general aversion to 
restrictions, as we have heard today, and that is part of it. 
An additional reason that was given to us was also that it is, 
they felt that our evaluation was not going to be rigorous 
enough, which we did not----
    Mr. LaMalfa. Do you think we have rigor now in separating 
these----
    Dr. Rachidi. Meaning that the evaluation design was not 
rigorous enough that in the end, even with an evaluation, we 
still wouldn't have been able to tell if it was effective or 
not. Which we didn't necessarily agree with, but that was one 
of the reasons. And the other reason was what we have also 
heard today about the difficulties in defining what is a 
sweetened beverage or not. We actually came up with what we 
thought was a pretty clear definition, which is it excludes 
juice, 100 percent juice, and any other beverage that has 10 
calories per 8 ounces is a sweetened beverage, with a few 
exclusions like Pedialyte, for example. But it was a pretty 
straightforward definition.
    Mr. LaMalfa. So we have super computers that could probably 
program this in at the register and not make it that tough, 
right?
    Dr. Rachidi. Exactly, and we talked to retailers in New 
York City, and there have been other retailers that we have 
talked to through other efforts that have said exactly what you 
said. They already restrict alcoholic beverages, for example, 
non-food products, and this would just be one more thing to add 
to the list.
    Mr. LaMalfa. Thank you.
    The Chairman. The gentleman's time has expired.
    Mr. O'Halleran?
    Mr. O'Halleran. Thank you, Mr. Chairman. I just have a 
couple of brief statements. I will have plenty of questions for 
the record.
    But one of the statements I heard today was this pot 
instead of that pot, and another one was three buses. And my 
district is kind of a little bit different. It is a district 
the size of Pennsylvania. It has 12 Native American 
reservations on it, and some of the kids go to school on a bus 
2 hours one way. Some of them have anywhere from a 50 percent 
to an 80 percent unemployment rate. And sometimes, people can't 
get out of their homes after a big storm because of the 
condition of the roads to get to the store. So we have the 
urban setting, the rural setting, and then we have these very 
rural settings. And I am just trying caution us that as we look 
at this whole problem, the cost of stores is an important 
aspect to me, because in my area, stores are very far apart, 
obviously, and the food that is in those stores is much more 
limited in scope than other stores in urban areas. We also have 
the concern that the education level on nutrition is very low, 
and I appreciate the cooking classes and everything else, but 
it is kind of hard to get to a cooking class if you are 2 hours 
away from the nearest class.
    And so between the quality of the merchandise, the concern 
I have for the distances traveled, the unacceptable 
unemployment rates, I just want to just caution everybody when 
we start to think about this a little more that the entire 
process, and I don't think there is anybody here that doesn't 
care about nutrition for our families and our children, but we 
also have to understand the realities of life in some areas of 
America.
    Thank you. I yield back.
    The Chairman. The gentleman yields back.
    Mr. Marshall, 5 minutes.
    Mr. Marshall. Thank you, Mr. Chairman. My first question is 
for Dr. Rachidi.
    As you may know, I am an obstetrician and very familiar 
with WIC programs. Of all the things that my patients and 
nurses seem to think is a good thing, is WIC. What can we learn 
from WIC that we could apply to SNAP? What makes it successful? 
Tell me what we are doing differently between the two programs 
briefly, if you could?
    Dr. Rachidi. Well sure. Real briefly, I mean, WIC has a set 
of products that are eligible products to be purchased, and so 
there is a list that is put together and it is intended to be 
healthy products, and also they cater towards infants and new 
mothers and pregnant women. SNAP, on the other hand, does not 
have that. There are a few restrictions as we have heard today, 
alcoholic beverages, non-food items, hot prepared foods, but in 
general, there are no restrictions on what can be purchased 
with SNAP benefits.
    Mr. Marshall. Tell us a little bit about that education, 
what is going on with those pregnant women and breastfeeding 
moms that WIC is doing that seems to me to be so beneficial?
    Dr. Rachidi. Yes, so WIC also has a large education 
component, and again, it is a little bit of a different program 
because it is focused on new mothers and infants primarily, and 
young children. The education efforts are very much geared 
towards that, but also very much geared towards nutrition.
    On the SNAP side, as we have also heard today, there is a 
nutrition and education program, and it is very different 
across the states. States can choose how to implement it. Some 
choose to have very robust programs. Some choose to have maybe 
not so robust, but reach a lot of people, and so it is just a 
little bit different program than WIC.
    Mr. Marshall. Okay. Dr. Wansink, I guess my next question 
is for you.
    Certainly, I am concerned about health and diabetes and 
obesity and these things, but my question for you is: have any 
of the current educational or in city-based efforts resulted in 
large scale changes, in your opinion, large scale changes in 
dietary habits? Is it working?
    Dr. Wansink. There is some of this going on that is very 
good that has been effective, and back when I was Executive 
Director for the Center for Nutrition Policy and Promotion, I 
kind of said, this is too big of a thing for the government to 
figure out, because government can't be where everybody 
purchases and prepares food everywhere they work and they play, 
but all of the things around us can, the companies and things 
like this. So we started a program called Partnering with 
MyPyramid. It's now called Partnering with MyPlate. And the 
idea was to give credit and incentives to any company or any 
nonprofit that would help make it easier for people to move 
toward eating following the Dietary Guidelines. It was 
tremendously successful under the last year of President Bush's 
term, and it still is in place but it is not being encouraged 
as much as it could be. And that would be great, because it 
would enlist everybody to help more people eating toward the 
Dietary Guidelines.
    Mr. Marshall. Okay. I am going to stick with this theme of 
lifestyle changes a little bit, and this is probably your 
questioning, Dr. Wansink.
    In my lifetime experiences, as a physician, trying to 
change people's lifestyles, when they are pregnant seems to be 
their most willing to do it. I have given up trying to convince 
people to stop smoking unless they are pregnant or they ask me 
about it. Trying to help a newly developed diabetic pregnant 
woman to talk to them about diet modifications, they are very 
motivated. They start wearing seatbelts. There are reasons that 
this woman is motivated for lifestyle changes.
    Why are they so motivated, and how can we apply that to 
SNAP as well? I just think that pregnant women, by the time 
they are 45, it is too late, but when they are 21, there are 
opportunities here. So help me with what the next step is for 
SNAP to take?
    Dr. Wansink. I think that is an outstanding question, 
because you are looking at, there is somebody who is doing 
something for a bigger cause than themselves, and we see this 
with people making changes in their diet, too. They will do it 
for a bigger cause and become a vegetarian for a bigger cause, 
but not for their health. And in trying to apply some of these 
things to SNAP benefits, maybe what we need to do is we need to 
start focusing on the impact this has on a person's family or 
on their children, and start talking about SNAP benefits not in 
terms of, oh, he was going to buy some groceries, but on the 
implication this has on their family. And I love the stats that 
you had about what happens that graduation rates go up by 18 
percent for kids on SNAP benefits----
    Mr. Marshall. I am sorry to cut you off, but I appreciate 
the answer. My biggest concern is lack of activity as opposed 
to calories in. I think that is the biggest problem with 
obesity. Do any of you--can you--are we doing anything with 
SNAP related to encouraging activity as opposed to playing 
video games all day? My time is out. Sorry. I yield back.
    The Chairman. The gentleman yields back.
    Mr. Panetta, 5 minutes.
    Mr. Panetta. Thank you, Mr. Chairman. I appreciate it, and 
thanks to all of the witnesses who are here. I appreciate your 
testimony, your preparation. I know it took quite a bit of 
time, I am sure, to put together your statements today, so 
thank you very much. I appreciate that.
    My question kind of stems around education. As many Members 
are starting to know, and as many people do know, I come from 
the salad bowl of the world there on the central coast of 
California. But we are looking to change that name actually. We 
are going to call it the salad bar of the world. No, I am 
serious. The reason they are doing that is because a lot of the 
growers and the shippers, what they realized is the people who 
work for them weren't eating the same foods that they are 
picking. And they realized how to get to them is by getting to 
their kids. And so what a lot of our ag companies have done is 
donated salad bars, over 100, to the local schools to start 
getting our children, including my two daughters, to start 
eating more healthy foods, having that salad bar option. And 
they are doing that. And what they are seeing is that when 
their children start to eat more at schools, those trends go 
home and their parents start to develop those same trends, and 
that is actually working to a certain extent.
    And so my question is how do we continue, besides ag 
companies donating salad bars to our schools, how do we 
continue to educate our children when it comes to getting them 
to eat healthier in our schools? How do we do that?
    Ms. Sarasin. A couple of things that the food retailers are 
working on, one is a very high percentage of our companies do 
in-store tours. I mentioned earlier that about 95 percent of 
them have on staff nutritionists and dieticians, and what they 
are doing is actually bringing school groups into the stores, 
and the nutritionists and the dieticians take the children 
through the store, and help them understand about nutrition, 
help them understand the kinds of nutrients and vitamins they 
get from various products, and the balance that they need to be 
trying to achieve in their lives. So that is one thing that has 
worked well and will continue to work well.
    Another thing that we have done at FMI through our FMI 
Foundation is we just had our second annual National Family 
Meals Month in September. And the notion of National Family 
Meals Month is sort of multi-fold. One is that some of the 
societal challenges that we have are improved by having more 
frequent family meals, and I am talking now about school 
truancy, underage drinking, drug abuse, et cetera. The research 
shows that more family meals tends to bring down the incidences 
with young children and teenagers. But in addition to that, 
what we find is that children who engage with their families at 
mealtime, both by cooking, by purchasing the food, by being 
involved in preparation and serving, they tend to have a better 
understanding of nutrition and diet and health than those that 
don't. So we are promoting national family meals within our 
organization, but also at store level. And we have had, as I 
mentioned, our second annual in September of 2016, so this is 
something that we are doing on an annual basis so that our 
retailers can actually be engaged with their customers in 
helping children engage more with the preparation of food in 
their homes.
    Mr. Panetta. I appreciate that.
    With the FINI Program and the SNAP-Ed program, what do 
those entail?
    Mr. Weidman. Yes, I was just going to say we work in 100 
schools in Pennsylvania, doing SNAP-Ed, nutrition education 
work. So teaching kids to try new foods, a lot of it is also 
peer-to-peer marketing, so getting kids to be leaders in 
changing their school environment, youth-led wellness councils, 
and you really find that when the students are kind of 
marketing to their peers around healthier eating, that has a 
big impact. We also do, to the Congressman's point, our Get 
Hype Philly program is about healthy eating and exercise, so 
the combination of both of those is really important.
    Mr. Panetta. Great. In regards to you, Dr. Wansink, you 
talked about middle of the road consumers. You mentioned 
signage, service, and structure, is there anything else we can 
do to target them? What else can we do?
    Dr. Wansink. Well what can be done at a retail level is to 
make sure that the foods we want to guide them to are the 
healthier foods, and they are being the ones that are most 
convenient to purchase, they are most attractive to purchase, 
not just by price, but attractively looking, attractively 
named, attractively positioned, and then also that are more 
normal, because right now it is just not normal to buy a lot of 
healthy things at the grocery store, because you feel like you 
are kind of a strange person. Simply a lot of placement changes 
can make a big difference. Thank you very much for your 
questions.
    Mr. Panetta. Thank you. Thank you, Mr. Chairman.
    The Chairman. The gentleman yields back.
    Mr. Faso, 5 minutes.
    Mr. Faso. Thank you, Mr. Chairman. I am intrigued, we had a 
table here that came from USDA that suggests in 2011 that there 
were approximately six billion purchases of sweetened beverages 
in 2011. I don't know, do any of the witnesses have an idea of 
how much of that six billion would be what we call soda in the 
East and my colleagues like Mrs. Hartzler call pop in the West. 
Although in western New York, they do call soda pop.
    Dr. Rachidi. I believe it is a little more than \1/2\.
    Mr. Faso. A little more than \1/2\. And would any of the 
witnesses contend to me that soda, sweetened soda has 
nutritional value?
    This would be for Dr. Schanzenbach, and maybe Dr. Rachidi 
as well. I take it by no answer from any of the witnesses that 
no one believes soda has nutritional value. What would be the 
problem with our, especially if we are looking at more than $3 
billion of taxpayer money going to buy something that no one, 
as far as I can tell, believes has nutritional value? What 
would be the issue in your mind of a carefully designed study 
by the USDA to actually analyze this question as to whether if 
we had a restriction on certain sugared beverages that it could 
result in altered buying habits and dietary consequences and 
nutritional consequences for the families, particularly the 
children who live in those households where that $3 billion of 
taxpayer money is spent to buy soda?
    Dr. Schanzenbach. You are asking a researcher if we should 
have more research and that is the first thing they teach you 
in grad school is yes, I would welcome any sort of a 
demonstration program, but I would be quick to add that it 
needs to be high quality, and so in particular that includes it 
needs to be real randomized controlled trial, and that it also 
needs to do a couple of other things. One, it needs to measure 
consumption, not just compliance, but how does this change what 
people consume, because some of the research out there that 
maybe looks at the impact of soda taxes and other things like 
that show that yes, people substitute away from soda sometimes, 
but what they replace it with isn't necessarily much better.
    Mr. Faso. Right, and so how many people do you think would 
be appropriate in such a study?
    Dr. Schanzenbach. Oh boy. I can't do power calculations on 
the fly. I would be happy to submit something.
    Mr. Faso. Perhaps you could submit that for the record.
    Dr. Schanzenbach. I would be happy to.
    Mr. Faso. Ms. Sarasin, at the risk of getting my friends in 
the food merchants, and my friend, Mike Rosen, in Albany upset, 
the fact is that now that SNAP benefits are in EBT form by and 
large for the vast majority of those purchases, the merchants 
are able to differentiate among taxable items and non-taxable 
items. We had an issue in New York State for years where 
certain marshmallows that were used if you put them on a stick 
and you roasted them over the fire, those were tax exempt, but 
if you bought the small marshmallows, those were taxable. I 
realize the administrative complexity argument, but it does 
seem to me that we are now at a point where we could be able to 
more readily differentiate, just as we do with tobacco and 
beer. You can't buy that with food stamps.
    Ms. Sarasin. Well as I said in my testimony, could it be 
done, yes, probably so. The question is at what cost, and is 
the cost of trying to put together a means through which to 
define the products that are in clearly, define the products 
that are out clearly, such that electronically they could be 
contained in a system and therefore would be able 
electronically to be able to segregate? Absolutely, that would 
certainly help, but again, we are talking about many tens of 
thousands of products that would have to be done every year, 
and the infrastructure to be able to make those determinations.
    Mr. Faso. My point would be that we have these wonderful 
academic researchers and experts. Perhaps we could design a 
study that was statistically valid and which would consider the 
difficulty that the food merchants have, but also get to the 
core of the fact that when we were kids, the only time we ever 
had soda or pop was when it was someone's birthday. And when I 
see $6 billion, perhaps $3 billion of taxpayer dollars being 
spent on soda, which has no nutritional value, in a program 
that is called Supplemental Nutrition Assistance, something is 
wrong.
    Thank you, Mr. Chairman.
    The Chairman. The gentleman's time has expired.
    Mr. Soto, 5 minutes.
    Mr. Soto. Thank you, Mr. Chairman.
    In Florida, we have our Fresh From Florida Program, which 
has tried to cue in local farmers with our schools, which has 
had some pretty good success. In listening to your testimony, 
it appears that most of you are encouraging us to have 
incentives, to have a carrot rather than a stick, pun intended 
on that--and to have greater access to folks in food deserts 
rather than desserts. And I agree with both those things.
    I did, however, read a Washington Post article this morning 
that went right into this issue, and they had a conclusion that 
a SNAP purged of sodas or candy or both could be less 
vulnerable to cuts, and supporters can seek full funding. That 
every dollar for SNAP would help nurse the poor, just as 
Congress intended. And it got me thinking, first, how many of 
you by a show of hands would support a ban on soda and candy? 
Go ahead, how many? Okay, we have one. How many of you believe 
that it would save money if we banned these two products? Raise 
your hand. Okay.
    And so I think that is what my main quandary is now is 
whether or not the real goal is to have these sorts of bans to 
get people to eat healthier, whether the real goal would be to 
try to save money to expand a lot of the pilot programs that 
you all have discussed. And I am one who doesn't want food 
police or a big brother society or any of these other things 
that we are all so worried about. And so it would be great in 
the time I have remaining for you all to either support or not 
the concept of whether this would save money, and why? And I 
would like to hear from all of you on it.
    Dr. Rachidi. Well I guess I will start.
    In terms of saving money, just the opportunity or the 
potential to save medical-related expenses, especially on the 
public health side, Medicaid/Medicare, I think that there is 
potential there. And then----
    Mr. Soto. Excuse me, I didn't mean to interrupt. Just with 
regard to the SNAP program, whether we would save money in SNAP 
funds.
    Dr. Rachidi. Right. Well, I don't know if this is exactly 
what you are getting at, but in terms of the article this 
morning, again, I look at it as a program integrity issue. It 
is difficult to talk about expanding SNAP benefits, for 
example, when that ten percent of SNAP benefits are spent on 
sweetened beverages which have no nutritional value and do 
nothing to further the goals of the program.
    Dr. Schanzenbach. I think that this won't save SNAP 
dollars. In fact, as I testified earlier, it will increase the 
administrative cost of the program to no benefit. My 
professional opinion as an economist, I don't think it is going 
to change behavior.
    Ms. Sarasin. And as I have said before, I don't think it is 
going to save money either. The administrative costs associated 
with making these determinations in the context of USDA would 
be astronomical.
    Mr. Weidman. We recommend an access to healthy food 
incentives and nutrition education, and we think that approach 
is the best way to create jobs, lift people out of poverty so 
they don't need SNAP, and reduce healthcare costs.
    Dr. Wansink. There are easier ways to get at that 
objective, and I don't think just cutting that is going to have 
the benefits we want.
    Mr. Soto. Now my next question is what would be the 
administrative costs, knowing that we already ban alcohol, and 
that seems to be something that hasn't mushroomed costs.
    Dr. Rachidi. When I hear the discussion about how the cost 
would be astronomical, I don't quite understand how that could 
be with items, for example, like sweetened beverages that are 
very straightforward. I understand moving more towards a WIC 
model, how that could potentially increase administrative 
costs, but the things that I am talking about I don't see how 
that would increase administrative costs.
    Mr. Soto. And this is a reference just to a ban on candy 
and soda, no other items.
    Dr. Schanzenbach. So I guess I would add to that that 
restricting alcoholic beverages, that is sort of a different 
product category and it is real easy for the person who is 
checking you out to know oh, this is a bottle of wine and not 
something else. But when it comes to something like sugar 
sweetened beverages, what we saw in the New York pilot proposal 
was it is really hard to decide how to define this. For 
example, two what I would call similar beverages, V8 you could 
still purchase, but V8 Splash, which is the same sort of thing 
but it has a little kiwi fruit in it, was not eligible. I think 
that it gets to something that is very complicated at the 
store, and it is going to cause confusion. Do we have great 
estimates of how much it will cost? We have some evidence from 
the Healthy Incentives Pilot that maybe $5 billion a year, 
something like that.
    The Chairman. The gentleman's time has expired.
    Mr. Arrington, 5 minutes.
    Mr. Arrington. Thank you, Mr. Chairman. I admittedly come 
to the table to discuss as with tension between the consumers' 
freedom to choose what they purchase to eat, and our 
responsibility as stewards of taxpayer money to guide in the 
most responsible way. And I must say, I am undecided, quite 
frankly, and I am sorry I couldn't get all your testimonies and 
be a part of the discussion. I had another hearing.
    Dr. Rachidi, I understand that you ran the SNAP program for 
New York City and that you requested a waiver so that you could 
apply restrictions to people on SNAP and their purchases. Why 
were you denied that flexibility?
    Dr. Rachidi. And just to be clear, I didn't run the 
program, but I was the director for policy, and so we proposed 
the restriction.
    But ultimately, what we were told in terms of being denied 
was related to the evaluation design and that it wasn't 
rigorous enough to be able to conclude whether a restriction 
would be effective or not. And that was the main reason that 
was given, and then given that other states in the past had 
also proposed similar things, we suspected it was just a 
general aversion to wanting to do any type of restrictions.
    Mr. Arrington. Have they granted--go ahead.
    Ms. Sarasin. If I could, just one comment that I don't 
think has been mentioned today and it is worth mentioning in 
the context of waivers for various reasons. This Committee 
several years ago under the leadership of Mr. Goodlatte spent 
an awful lot of time and energy working toward a state by state 
interoperability type of process with SNAP. In this mobile 
society that we are in right now, there has been the need for 
SNAP recipients to be able to use their benefits where they 
find themselves, and so with EBT cards, et cetera, that has 
been facilitated, so these waivers have created a tension 
within USDA as well, because once you start doing waivers 
piecemeal around the country, the interoperability that this 
Committee spent so much time trying to achieve is compromised.
    Mr. Arrington. When is the last time the USDA has granted a 
waiver for such restrictions?
    Dr. Rachidi. They have not.
    Mr. Arrington. Ever, okay. Yes?
    Dr. Schanzenbach. But, if you wanted to do a real 
demonstration project, we would just really need to make sure 
that it is set up so that we can learn something from it. Not 
only studying the impact on consumption, which I will let you 
know I have a prediction what that will be, but also the impact 
on retailers and others. It is going to cost you if you elect 
to do it.
    Mr. Arrington. Yes, that is a good idea and it is fair to 
include all stakeholders, with states bearing much of the cost 
in healthcare, or let's just say significant costs for 
healthcare of their citizens, why not enter another freedom to 
choose? Why not block grant SNAP, let states choose if they 
want to go higher with support and supplemental support and 
work any reforms they want in on work requirements and other 
requirements and other reforms that have been discussed, not 
for this hearing? And then let them decide if they find it 
useful and meaningful to restrict purchases based on the 
nutritional value? Let states do that. Has that been discussed, 
and what are your thoughts about that?
    Dr. Schanzenbach. So my grave concern around a potential 
block grant is that one of the things that makes SNAP most 
successful, especially to the broader economy, is that it is 
designed to respond quickly to changing economic conditions and 
to times of need. So the program, as you saw during the great 
recession, expanded in response to the greater need that we 
saw. It is starting to come back down as the economy is 
starting to get a foothold.
    You may be aware that the dollars that we spend in SNAP 
also they are very promptly spent and they are spent in the 
local communities, and so they provide an economic stimulus to 
the whole area. For every dollar that we spend, at the height 
of the great recession we got $1.74 in local economic activity 
because of this. A block grant takes that important aspect of 
this program off the table. I think it would be a mistake.
    Mr. Arrington. So it seems to me that in terms of who is 
more nimble, the Federal Government, Federal program or a state 
and local government and program, I am going to put my money on 
the state and local program in terms of nimbleness. I don't 
think we have anything to compare it to with respect to this 
specific program, but I bet there are other ways to compare it.
    I am running out of time.
    The Chairman. The gentleman's time has expired.
    Mr. Evans. Mr. Evans, 5 minutes.
    Mr. Evans. Thank you, Mr. Chairman.
    One question that I have, and maybe all of you can deal 
with this, my inquiry is what is the impact a reduction in SNAP 
would mean for retailers from a job perspective? Can someone 
shed light on the impact of jobs and a reduction of SNAP would 
create?
    Mr. Weidman. One of the things that we have been doing 
around the country since we started in Pennsylvania with the 
Fresh Food Financing Initiative is convening groups that 
include grocers, but other stakeholders around the issue of 
access to healthy food and grocery store access. That is one 
thing that we heard loud and clear is that in order to have a 
successful enterprise in low-income communities, SNAP has 
become a very critical component there. So in our view, 
reductions to SNAP is not only going to result in more hunger 
and less food on the table for American families who are 
struggling with hard times, but it is going to have an economic 
effect. Oftentimes grocery stores are the anchor in a 
community, so if the grocery store closes down, that can have a 
domino effect, affecting other retail in the community. This 
happens in rural small towns and urban neighborhoods.
    Mr. Evans. Is anybody as, with the national retailer, able 
to quantify it in some way what you think it means in terms of 
numbers?
    Dr. Schanzenbach. Sure. During normal economic times, every 
dollar that we spend on SNAP returns about $1.25 to the local 
area, so I would think the way to think about it during normal 
economic times, although this would be worse during downturns, 
but during normal economic times if we took $1 away from SNAP, 
we would expect to see a reduction of $1.25 in local economic 
activity.
    Mr. Evans. Can each of you shed light from your perspective 
on what a SNAP benefit impact would be on recipients?
    Dr. Schanzenbach. Sure. We have strong predictions that if 
benefits were reduced, I would predict that we would see an 
increase in food insecurity. Currently one out of every five 
children in this great nation lives in a food-insecure 
household. I also think that, just the opposite of what I 
talked about before, having fewer dollars to spend at the 
grocery store means that people are going to substitute towards 
cheaper forms of calories, and that is exactly the opposite of 
the direction that we like to see people go. We like to see 
people eat healthier foods, which tend to be more expensive per 
calorie.
    Mr. Evans. Thank you, Mr. Chairman.
    The Chairman. The gentleman yields back.
    Mr. Allen, 5 minutes.
    Mr. Allen. Thank you, Mr. Chairman, and the reason I an the 
last one to ask questions is because I was in a conference 
meeting this morning talking about spiraling cost of healthcare 
in this country. And as I look at, statistically, at the growth 
of this program from 17 million people in 2000 to over 40 
million people today, and the fact that this program was 
initially started during World War II, because I am military, 
our generals felt like they didn't have the nourishment that 
they needed to battle the enemy. So we have seen tremendous 
growth in this program, and then we see tremendous growth in 
the cost of healthcare.
    We are talking about nutrition, and then what is that doing 
to healthcare? Do we have any studies that tell us, okay, are 
they related, and if they are related, how do we fix this?
    Dr. Schanzenbach. To be sure, obesity rates have 
skyrocketed, not just among the poor, but all across the 
distribution. And there are studies, we could nitpick them, but 
common sense dictates that this increase in obesity that we 
have seen across the income distribution has real ramifications 
for the cost of healthcare.
    Mr. Allen. Obviously, the retailers have a stake in this, 
the producers, our farmers obviously have a stake in this. We 
have talked about some options here available to us, but it 
sounds like to me we better fix this problem because when you 
look, for example, at Medicaid costs, I mean, it is 
skyrocketing and the number of people on Medicaid is 
skyrocketing. And it is because folks are having health 
problems because of, it may be other factors, but a large part 
of it is nutrition.
    Doctor, would you like to comment on what your thoughts 
are? I mean, how do we fix this?
    Dr. Wansink. Yes, absolutely. We have all the health 
concerns that we face, diet-related disease and obesity are the 
only ones that we can deal with and change immediately. Now you 
bring up a great point that most grocery stores, maybe they 
don't really care that much about the shoppers who are there, 
and to use a health motivation to try to encourage them to get 
people to buy more fruits and vegetables wouldn't be the right 
way to do it. But instead, it is aligned in their interest to 
get more people to buy fresh fruits and vegetables, lean meat 
and dairy, things like this because when that stuff goes bad, 
they actually lose money. The margin on it might be thin at the 
register, but the loss is huge compared to Fruity Pebbles if 
they don't sell it. Being able to show them that these are easy 
ways that we can help you get that stuff moving through your 
store is going to be a win/win situation, just like it was with 
convenience stores when the Association of Convenience Stores 
started giving their members ways that they could accelerate 
sales of healthy foods.
    Mr. Allen. I am sure you would like to respond to that.
    Ms. Sarasin. Yes, I would like to respond to that. Thank 
you.
    I think the notion that food retailers don't care about the 
health of their customers is just incorrect.
    Dr. Wansink. We will----
    Ms. Sarasin. It is incorrect. Just not factually correct. 
Of course we care about the health of our customers, and of 
course we are doing things to try to enhance the health of our 
customers. And we do that every single day, and in my longer 
testimony, there are multiple examples of the things that we do 
in store, in our communities, and across the board to try to 
make sure that we are doing everything we can to meet the needs 
of our customers.
    So while the convenience stores are relatively new to this 
process and apparently are doing some good things, that is 
wonderful, but your broad line grocers have been engaged in 
this process for decades in trying to assist their customers in 
meeting their dietary needs, and they do it by bringing in 
nutritionists and dieticians and other professionals in the 
store to work with their customers on a daily basis to meet 
those needs, and will continue to do so.
    Mr. Allen. And of course, we have the food deserts that we 
have to deal with now. We had testimony here with Amazon, which 
is becoming a big player in the grocery market. Obviously, we 
have to come up with a solution to this issue, and so thank you 
for your help here today, and hopefully we can get our arms 
around this and solve this problem.
    The Chairman. The gentleman's time has expired.
    I want to thank our witnesses. The great news about this 
Committee, and today's hearing is a terrific example of it, is 
that if you took the names off the questions and the comments 
made, you would be hard pressed to determine which were 
Republicans and which were Democrats. You all have given us 
great information. The panel has given us terrific information 
to chew on. This is not the last conversation we will have on 
SNAP restrictions. I have some folks who feel really strongly 
about both sides, and the Committee will work its will when we 
get to this point and place, but this is an important 
conversation to have had today. You have been incredibly 
respectful and I appreciate everyone's participation, and I 
wish more of our work here in the House was as nonpartisan as 
this is. Not a person here doesn't care about nutrition. Not a 
person here doesn't care that people eat healthy and that they 
exercise, and that they make good decisions.
    I was particularly informed by the triangle from Dr. 
Wansink. I wish it was reversed. I wish the health vigilant was 
the big piece and that the health-disinterested, or the ones 
who don't care, was the smaller piece of that triangle, but 
that is correct. There are far more people in America who 
really don't care. And then there is that group that we can 
hit, that can change their habits. It is a convenience issue. 
It is an opportunity to have their kids tell them to do it.
    So this program is important, and what they spend their 
benefit on is important. I am not convinced that the more 
decisions we make on people's behalf doesn't make them less 
capable of making good decisions on their own, so it takes 
education. Somebody said in their testimony there is no silver 
bullet to fixing this issue. Sugar drinks have a clear impact 
on people's health, but if we eliminated them off the face of 
the Earth, I don't know that obesity rates would be any 
different than they are right now. There are some other 
systemic changes that have to go on in people's choices and the 
way they conduct their lives to make this happen.
    Under the Rules of the Committee, the record of today's 
hearing will remain open for 10 calendar days to receive 
additional material and supplementary written responses from 
the witnesses to any question posed by a Member.
    This hearing of the Committee on Agriculture is adjourned. 
Thank you.
    [Whereupon, at 12:20 p.m., the Committee was adjourned.]
    [Material submitted for inclusion in the record follows:]
   Submitted Report by Hon. K. Michael Conaway, a Representative in 
                          Congress from Texas
Foods Typically Purchased by Supplemental Nutrition Assistance Program 
        (SNAP) Households
November 2016
Nutrition Assistance Program Report
Food and Nutrition Service, Office of Policy Support

 
 
 
Authors:                             Submitted to:
  Steven Garasky                       Office of Policy Support,
  Kassim Mbwana                        Food and Nutrition Service,
  Andres Romualdo                      3101 Park Center Drive,
  Alex Tenaglio                        Alexandria, VA 22302-1500
  Manan Roy                          Project Officer:
Submitted by:                          Sarah Zapolsky
  IMPAQ International, LLC,
  10420 Little Patuxent Parkway,
   Suite 300,
  Columbia, MD 21044
Project Director:
  Steven Garasky
 

    This study was conducted under Contract number GS-10-F-0240U with 
the Food and Nutrition Service, United States Department of 
Agriculture.
    This report is available on the Food and Nutrition website: http://
www.fns.usda.gov/research-and-analysis.

    Suggested Citation:

    Garasky, Steven, Kassim Mbwana, Andres Romualdo, Alex Tenaglio and 
Manan Roy. Foods Typically Purchased by SNAP Households. Prepared by 
IMPAQ International, LLC for USDA, Food and Nutrition Service, November 
2016.
Table of Contents
    Executive Summary

          Purpose and Overview
          Methodology

                  Data Overview
                  Identifying SNAP Households and Creating Analysis 
                Categories
                  Data Caveats and Limitations

          Key Findings

                  Food Items Purchased by SNAP Households

    Chapter 1. Introduction and Background

          1.1  Introduction

          1.2  Background
          1.3  Research Questions
          1.4  Challenges of Collecting Point-of-Sale Data

    Chapter 2. Methodology

          2.1  Data Overview
          2.2  Identification of SNAP Households and Creation of 
        Analysis Categories
          2.3  Data Caveats and Limitations

    Chapter 3. Findings: Top Expenditures by SNAP and Non-SNAP 
Households

          3.1  Distribution of Expenditures by Summary Categories
          3.2  Distribution of Expenditures by Commodities
          3.3  Distribution of Expenditures by Subcommodities
          3.4  Distribution of Expenditures by Household Demographics, 
        Store Characteristics, Type of Resource Used, and Month of 
        Purchase

    Chapter 4. Findings: Top Expenditures by USDA Food Pattern 
Categories

          4.1  Top Expenditures for Dairy
          4.2  Top Expenditures for Fruits
          4.3  Top Expenditures for Grains
          4.4  Top Expenditures for Oils
          4.5  Top Expenditures for Protein Foods
          4.6  Top Expenditures for Solid Fats and Added Sugars (SoFAS)
          4.7  Top Expenditures for Vegetables
          4.8  Top Expenditures for Composite Foods
          4.9  Top Expenditures for Other Subcommodities

    Chapter 5. Conclusion
    Appendix A. Top Purchases by Expenditure for SNAP and Non-SNAP 
Households *
---------------------------------------------------------------------------
    * Editor's note: the report entitled, Foods Typically Purchased By 
Supplemental Nutrition Assistance Program (SNAP) Households and Foods 
Typically Purchased By Supplemental Nutrition Assistance Program (SNAP) 
Households--Appendices are two different documents. For purposes of 
publication in this hearing they are treated as one document.
---------------------------------------------------------------------------
    Appendix B. Crosswalk of Top 1000 Subcommodities to Summary 
Categories
    Appendix C. Crosswalk of Subcommodities to USDA Food Pattern 
Categories
    Appendix D. Top 100 Subcommodities for SNAP Households by 
Expenditure for Each USDA Food Pattern Category
    Appendix E. Top 100 Subcommodities for SNAP Households by 
Expenditure by Demographic and Store Characteristics
Table of Exhibits
    Exhibit 1: SNAP and Non-SNAP Household Food Expenditure Patterns
    Exhibit 2: Conceptual Map for Identification of SNAP Households in 
the POS Data
    Exhibit 3: Summary of SNAP and Non-SNAP Household Food Expenditures 
in the Dataset by Subcommodity
    Exhibit 4: Aggregating Food Items
    Exhibit 5: Summary Categories by Expenditure
    Exhibit 6: Top 100 Commodities for SNAP Households by Expenditure
    Exhibit 7: Top 100 Subcommodities for SNAP Households by 
Expenditure
    Exhibit 8: Top 25 SNAP Household Dairy Subcommodity Expenditures
    Exhibit 9: Top 25 SNAP Household Fruit Subcommodity Expenditures
    Exhibit 10: Top 25 SNAP Household Grains Subcommodity Expenditures
    Exhibit 11: Oils Subcommodity Expenditures
    Exhibit 12: Top 25 SNAP Household Protein Foods Subcommodity 
Expenditures
    Exhibit 13: Top 25 SNAP Household Solid Fats and Added Sugars 
(SoFAS) Subcommodity Expenditures
    Exhibit 14: Solid Fats and Added Sugars (SoFAS) Expenditures by 
Subcategory
    Exhibit 15: Top 25 SNAP Household Vegetables Subcommodity 
Expenditures
    Exhibit 16: Top 25 SNAP Household Composite Subcommodity 
Expenditures
    Exhibit 17: Composite Expenditures by Subcategory
    Exhibit 18: Top 25 SNAP Household Other Subcommodity Expenditures
    Exhibit 19: Other Expenditures by Subcategory
    Exhibit 20: SNAP and Non-SNAP Household Food Expenditure Patterns
Executive Summary
Purpose and Overview
    The Food and Nutrition Service (FNS) awarded a contract to IMPAQ 
International, LLC, to determine what foods are typically purchased by 
households receiving Supplemental Nutrition Assistance Program (SNAP) 
benefits. This study examined point-of-sale (POS) food purchase data to 
determine for what foods SNAP households have the largest expenditures, 
including both SNAP benefits and other resources, and how their 
expenditures compare to those made by non-SNAP households.
    SNAP, administered by FNS, is the nation's largest nutrition 
assistance program. In 2011, SNAP participants redeemed over $71 
billion in SNAP benefits in more than 230,000 SNAP-authorized 
stores.\1\ Given the magnitude of SNAP, FNS has a sustained interest in 
understanding the effects of the program. To date, FNS has studied SNAP 
household food consumption and expenditures using national surveys that 
generally rely on consumers to recall what they ate or to report or 
scan every purchase. This previous research has shown that the 
similarities in food purchases, consumption patterns, and dietary 
outcomes among low-income families and higher-income households are 
more striking than the differences.\2\
---------------------------------------------------------------------------
    \1\ USDA FNS. (2011). Supplemental Nutrition Assistance Program 
2011 Annual Report. Benefit Redemption Division. Available at http://
www.fns.usda.gov/snap/retailers/pdfs/2011-annual-report-revised.pdf.
    \2\ See, for example, Office of Research and Analysis (2012). 
Building a Healthy America: A Profile of the Supplemental Nutrition 
Assistance Program. Food and Nutrition Service, USDA (available on line 
at www.fns.usda.gov/ora/MENU/Published/snap/FILES/Other/BuildingHealthy
America.pdf).
---------------------------------------------------------------------------
    By using POS data to compare the purchases of SNAP households to 
those of non-SNAP households, the current study provides more detail on 
food expenditure patterns than previous studies. This study examines 
two major questions:

   What food items are purchased by SNAP households?

   How do foods purchased by SNAP households compare to food 
        purchased by non-SNAP households?
Methodology
Data Overview
    POS transaction data from January 1, 2011 through December 31, 2011 
from a leading grocery retailer were examined for this study.\3\ The 
majority of stores from which the data came would be classified as 
grocery stores, supermarkets, and combination food and drug stores per 
FNS Retailer Policy and Management Division food retailer 
definitions.\4\ On average, each of the 12 monthly data files contained 
over one billion records of food items purchased by 26.5 million 
households, reflecting 127 million unique transactions. Each monthly 
data file included an average of 3.2 million SNAP households, 
identified using the methodology described below. Total expenditures on 
all SNAP-eligible food items in the dataset by SNAP and non-SNAP 
households over the 12 months were $39.0 billion, or approximately $3.3 
billion per month. SNAP households spent approximately $555 million on 
SNAP-eligible items each month in this dataset, using both SNAP 
benefits and other resources such as cash or credit cards.\5\
---------------------------------------------------------------------------
    \3\ Per the data sharing agreement between the data provider and 
IMPAQ, a description of the source of these data must be limited to the 
following: ``From a leading U.S. grocery retailer data examining POS 
transactions from January 1, 2011 through December 31, 2011 across 
approximately 11 million SNAP households. The majority of stores would 
be classified as grocery stores, supermarkets, and combination food and 
drug stores per USDA/FNS food retailer definitions.''
    \4\ Stores that opened or closed during 2011 were not included in 
these analyses.
    \5\ By way of comparison, in FY 2011, 21.1 million households 
participated in SNAP in an average month (http://www.fns.usda.gov/ora/
MENU/Published/snap/FILES/Participation/2011Characteristics.pdf) and 
redeemed $6.0 billion in benefits in an average month (http://
www.fns.usda.gov/snap/retailers/pdfs/2011-annual-report-revised.pdf).
---------------------------------------------------------------------------
Identifying SNAP Households and Creating Analysis Categories
    SNAP households were identified in the data for each month. This 
identification was performed monthly because, in any given month, some 
households enter or leave the program. The analysis identified SNAP 
households each month by first identifying any transaction in which 
SNAP electronic benefit transfer (EBT) was used to pay for at least \1/
2\ of the value of the purchase and designating the household that made 
that transaction as a SNAP household.\6\ It then linked all other 
transactions made by that household during that month to estimate total 
monthly spending by SNAP households. All other transactions in these 
stores were designated as non-SNAP household purchases.\7\
---------------------------------------------------------------------------
    \6\ SNAP transactions in which SNAP EBT was not the majority tender 
were not identifiable in the data.
    \7\ Some of these transactions may, in fact, have included SNAP 
purchases. Some SNAP households may never have presented EBT as the 
majority tender in any transaction, for example.
---------------------------------------------------------------------------
    IMPAQ analyzed SNAP-eligible food items given the focus of the 
study. Per the Food and Nutrition Act of 2008 (the Act), eligible food 
includes any food or food product for home consumption, as well as 
seeds and plants which produce food for consumption. The Act precludes 
alcoholic beverages, tobacco products, hot food and any food sold for 
on-premises consumption from being purchased with SNAP benefits.\8\ The 
unit of analysis for the study was a food-related subcommodity, with 
subcommodities and commodities defined by the data provider. Each 
subcommodity typically consisted of multiple food items, often 
distinguished by brand or package size, identified by a Universal 
Product Code (UPC) or a Price Look Up (PLU) code. Each commodity was an 
aggregation of similar subcommodities. The ``apples'' commodity group, 
for example, combined different varieties (Gala, Fuji, Honeycrisp) and 
forms (bagged, bulk) that were presented separately as subcommodities.
---------------------------------------------------------------------------
    \8\ See http://www.fns.usda.gov/snap/retailers/eligible.htm for 
more details.
---------------------------------------------------------------------------
    Although subcommodities and commodities provide adequate comparison 
reference points, these groupings were designed to help retailers 
classify purchases for their own needs (e.g., marketing purposes). 
Therefore, this study analyzed purchases at two higher levels of 
aggregation. Thirty summary categories were created--for example, meat/
poultry/seafood, fruits, vegetables, and frozen prepared foods--to be 
roughly analogous to the major sections or departments in a typical 
grocery store. These categories were constructed to enhance discussion 
of similarities and differences between purchasing patterns of SNAP and 
non-SNAP households. Appendix B provides a crosswalk of subcommodities 
to summary categories.
    IMPAQ also mapped food subcommodities to USDA Food Pattern 
categories (dairy, fruits, grains, oils, protein foods, solid fats and 
added sugars (SoFAS), and vegetables). Not all subcommodities could be 
classified into a single Food Pattern category. Subcommodities 
incorporating multiple food categories, such as foods packaged as 
complete meals, were classified as composite foods. In addition, some 
subcommodities did not contain any Food Pattern categories, or the 
labels were not descriptive enough to permit categorization even with 
the addition of the composite category. A ninth category, other, was 
created to capture such subcommodities. ``Other'' captured all items 
that could not be classified using USDA Food Patterns, such as water, 
isotonic drinks, and baby food.
Data Caveats and Limitations
    Although POS data provide a wealth of information on the food 
purchase patterns of SNAP households, some limitations existed in the 
data analyzed for this study. The data used for this study captured 
only transactions completed at a specific set of retail outlets. As 
stated before, the majority of stores from which the data came would be 
classified as grocery stores, supermarkets, and combination food and 
drug stores per FNS Retailer Policy and Management Division food 
retailer definitions.\9\ Purchases made at other SNAP-authorized 
retailers or other venues (e.g., farmers['] markets) were not included 
in these data. On average, SNAP households in the data spent 
approximately $229 per month on SNAP-eligible foods using a combination 
of SNAP benefits, cash and other forms of payment.\10\ In contrast, the 
national average monthly SNAP benefit per household was $284 in FY 
2011.\11\ Therefore, although these data account for a significant 
proportion of SNAP-eligible food expenditures by SNAP households, they 
do not include all SNAP benefit expenditures.
---------------------------------------------------------------------------
    \9\ Stores that opened or closed during 2011 were not included in 
these analyses.
    \10\ On average, SNAP households in the data made 8.5 transactions 
per month. The average total expenditure on SNAP-eligible foods per 
transaction was $26.99.
    \11\ http://www.fns.usda.gov/pd/19SNAPavg$HH.htm.
---------------------------------------------------------------------------
    SNAP transactions were identified as those for which a SNAP EBT 
card was the majority tender. Because some transactions included both 
SNAP and cash or credit tenders, these data could not differentiate 
between items purchased with SNAP benefits and those purchased with 
other funds. These data, therefore, represent food purchases made by 
SNAP households, rather than the foods purchased with SNAP EBT 
specifically.
    Rankings of expenditure categories depend in part on the level of 
food item aggregation (whether at the Food Pattern, summary, commodity 
or subcommodity levels). As discussed above, the data provider 
aggregated food items into subcommodities and commodities, considering 
other factors outside of the needs of this particular analysis. These 
classifications at times presented analytic challenges that may have 
affected the rank ordering of purchases. For example, subcommodity 
groups categorized as ``composite'' or ``other'' for these analyses 
likely included food items that would more appropriately be included in 
one of the Food Pattern categories had more information been available. 
Similarly, some distinctions of potential nutritional importance were 
not available in these data. For example, it was not possible to 
distinguish between fat-free or low-fat varieties of some dairy 
products, such as fluid milk or yogurt, from whole milk varieties.
Key Findings
Food Items Purchased by SNAP Households
    Overall, the findings from this study indicate that SNAP households 
and non-SNAP households purchased similar foods in the retail outlets 
in these data. Exhibits 1 and 2 summarize the findings.

   There were no major differences in the expenditure patterns 
        of SNAP and non-SNAP households, no matter how the data were 
        categorized. Similar to most American households:

     About 40 of every dollar of food expenditures by SNAP 
            households was spent on basic items such as meat, fruits, 
            vegetables, milk, eggs, and bread.

     Another 20 out of every dollar was spent on sweetened 
            beverages, desserts, salty snacks, candy and sugar.

     The remaining 40 were spent on a variety of items 
            such as cereal, prepared foods, dairy products, rice, and 
            beans.

   The top ten summary categories and the top seven commodities 
        by expenditure were the same for SNAP and non-SNAP households, 
        although ranked in slightly different orders.

   Expenditure shares for each of the USDA Food Pattern 
        categories (dairy, fruits, grains, oils, protein foods, solid 
        fats and added sugars (SoFAS), and vegetables) varied by no 
        more than 3 per dollar when comparing SNAP and non-SNAP 
        households. Protein foods represented the largest expenditure 
        share for both household types, while proportionally more was 
        spent on fruits and vegetables than on SoFAS, grains, or dairy.

   Less healthy food items were common purchases for both SNAP 
        and non-SNAP households. Sweetened beverages, prepared desserts 
        and salty snacks were among the top ten summary categories for 
        both groups. Expenditures were greater for sweetened beverages 
        compared to all milk for both groups, as well.

   Expenditures were concentrated in a relatively small number 
        of similar food-item categories. The top five summary groups 
        totaled \1/2\ (50%) of the expenditures for SNAP households and 
        nearly \1/2\ (47%) for non-SNAP households. Twenty-five 
        commodities accounted for over forty percent of the food 
        expenditures in these data with SNAP and non-SNAP households 
        having 20 of them in common. The top 25 subcommodities for SNAP 
        households and non-SNAP households, respectively, accounted for 
        between \1/5\ to \1/4\ of total food expenditures for each 
        group with 16 subcommodities in common for the two groups.

    Exhibit 1: SNAP and Non-SNAP Household Food Expenditure Patterns
------------------------------------------------------------------------
        Finding             SNAP Households        Non-SNAP  Households
------------------------------------------------------------------------
Total annual            $6.7 billion             $32.3 billion
 expenditures on SNAP-
 eligible foods in
 dataset
Percentage of all       12%                      88%
 transactions by all
 households
Percentage of total     17%                      83%
 annual expenditures
 by all households
Top 1,000 subcommodity  99%                      98%
 (of 1,792)
 expenditures as a
 percentage of all
 expenditures
Top 100 subcommodity    51%                      46%
 expenditures as a
 percentage of all
 expenditures
Top 25 subcommodity     25%                      21%
 expenditures as a
 percentage of all
 expenditures
Top 25 commodity (of    45%                      41%
 238) expenditures as
 a percentage of all
 expenditures
Top 10 summary          Meat/Poultry/Seafood     Meat/Poultry/Seafood
 categories (of 30) by
 expenditure
                        Sweetened Beverages      Vegetables
                        Vegetables               High-fat Dairy/Cheese
                        Frozen Prepared Foods    Fruits
                        Prepared Desserts        Sweetened Beverages
                        High-fat Dairy/Cheese    Prepared Desserts
                        Bread and Crackers       Bread and Crackers
                        Fruits                   Frozen Prepared Foods
                        Milk                     Milk
                        Salty Snacks             Salty Snacks
Top 10 commodities (of  Soft Drinks              Fluid Milk Products
 238) by expenditure
                        Fluid Milk Products      Soft Drinks
                        Beef Grinds              Cheese
                        Bag Snacks               Baked Breads
                        Cheese                   Bag Snacks
                        Baked Breads             Beef Grinds
                        Cold Cereal              Cold Cereal
                        Chicken Fresh            Candy--Packaged
                        Frozen Handhelds and     Coffee and Creamers
                         Snacks
                        Lunchmeat                Ice Cream, Ice Milk,
                                                  and Sherbets
Top 10 subcommodities   Fluid Milk/White Only    Fluid Milk/White Only
 (of 1,792) by
 expenditure
                        Soft Drinks 12-18 pack   Soft Drinks 12-18 pack
                        Lean Beef                Shredded Cheese
                        Kids' Cereal             Chicken Breast--
                                                  Boneless
                        Shredded Cheese          Frozen Premium
                                                  Nutritional Meals
                        2-Liter Soft Drink       Pure Orange Juice--
                                                  Dairy Case
                        Potato Chips             Lean Beef
                        Primal Beef              Potato Chips
                        Lunchmeat--Deli fresh    Large Eggs
                        Infant Formula/Starter   Bananas
                         Solution
USDA Food Pattern
 categories, by
 expenditure:
 
   Dairy        9%                       10%
   Fruits       6%                       9%
   Grains       12%                      13%
   Oils         2%                       2%
   Protein      23%                      20%
   Foods
   Solid Fats   13%                      12%
   and Added Sugars
   Vegetables   8%                       10%
   Composite    19%                      16%
   Other        8%                       8%
------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ
  International, LLC, 2016.

Chapter 1. Introduction and Background
1.1  Introduction
    The Food and Nutrition Service (FNS) awarded a contract to IMPAQ 
International, LLC, to determine what foods are typically purchased by 
households receiving Supplemental Nutrition Assistance Program (SNAP) 
benefits. More specifically, this study examined POS food purchase data 
to determine for what foods SNAP households have the largest 
expenditures, including both SNAP benefits and other resources, and how 
these expenditures compare to those made by non-SNAP households.
1.2  Background
    The mission of FNS is to provide children and needy families with 
improved access to food and a more healthful diet through a range of 
nutrition assistance programs and comprehensive nutrition education 
efforts. SNAP, administered by FNS, is the nation's largest nutrition 
assistance program, providing benefits to more than 15% of the U.S. 
population. In 2011, SNAP participants redeemed over $71 billion in 
SNAP benefits in more than 230,000 SNAP-authorized stores.\12\ Total 
program costs in FY 2011 were nearly $76 billion.\13\ Given the 
magnitude of SNAP, FNS has a sustained interest in understanding the 
effects of the program.
---------------------------------------------------------------------------
    \12\ USDA FNS. (2011). Supplemental Nutrition Assistance Program 
2011 Annual Report. Benefit Redemption Division. Available at http://
www.fns.usda.gov/snap/retailers/pdfs/2011-annual-report-revised.pdf.
    \13\ http://www.fns.usda.gov/pd/SNAPsummary.htm.
---------------------------------------------------------------------------
    SNAP aims to alleviate hunger and improve the nutritional status of 
participants by increasing the resources available to households to 
purchase food. Paradoxically, one-in-six people in the U.S. experiences 
food insecurity,\14\ while \2/3\ of adults and \1/3\ of children are 
overweight or obese.\15\ These public health problems 
disproportionately affect low-income populations.\16\ While no evidence 
exists that SNAP participation causes obesity, the high rates of 
obesity and food insecurity among low-income Americans underscore the 
importance of exploring ways to continue to employ SNAP strategically 
as a tool to promote healthier nutrition, as well as to reduce obesity 
rates among program participants of whom nearly 50% are children.
---------------------------------------------------------------------------
    \14\ Coleman-Jensen, A., Nord, M., Andrews, M., & Carlson, S. 
(2011). Household food security in the United States in 2010. Economic 
Research Report, No. ERR-125. Available at http://www.ers.usda.gov/
media/884525/err141.pdf.
    \15\ Flegal, K.M., Carroll, M.D., Ogden, C.L., & Curtin, L.R. 
(2010). ``Prevalence and trends in obesity among U.S. adults, 1999-
2008,'' Journal of the American Medical Association, 303, 235-241; 
Burgstahler, R., Gundersen, C., & Garasky, S. (forthcoming). ``The 
Supplemental Nutrition Assistance Program, financial stress, and 
childhood obesity.'' Agricultural and Resource Economics Review; 
Eisenmann, J.C., Gundersen, C., Lohman, B.J., Garasky, S., & Stewart, 
S.D. (2011). ``Is food insecurity related to overweight and obesity in 
children and adolescents? A summary of studies, 1995-2009.'' Obesity 
Reviews, 12, e73-e83; Lohman, B.J., Stewart, S., Gundersen, C., 
Garasky, S., & Eisenmann, J.C. (2009). ``Adolescent overweight and 
obesity: Links to food insecurity and individual, maternal, and family 
stressors.'' Journal of Adolescent Health, 45, 230-237; Gundersen, C., 
Garasky, S., & Lohman, B.J. (2009) ``Food insecurity is not associated 
with childhood obesity as assessed using multiple measures of 
obesity.'' Journal of Nutrition, 139, 1173-1178.
    \16\ Trust for America's Health. (2011). F as in fat: How obesity 
threatens America's future. Available at http://healthyamericans.org/
reports/obesity2010/Obesity2010Report.pdf.
---------------------------------------------------------------------------
1.3  Research Questions
    The project addressed two key research questions.
    Research Question 1: What food items are purchased by SNAP 
households? Specifically, the study examined SNAP household food 
expenditure data by four categorizations: U.S. Department of 
Agriculture (USDA) Food Pattern categories, ``summary categories,'' 
commodities, and subcommodities.
    Research Question 2: How do foods purchased by SNAP households 
compare to purchases made by non-SNAP households? Analyses paralleled 
those for Research Question 1, but for non-SNAP households. Comparisons 
were then drawn between the food expenditures of SNAP and non-SNAP 
households.
1.4  Challenges of Collecting Point-of-Sale Data
    Understanding the food choices and purchasing patterns of SNAP 
participants is an important part of promoting healthy choices. FNS 
analyzes various extant data that describe the diets and food 
purchasing patterns of SNAP households. For example, The National 
Health and Nutrition Examination Survey is an annual nationally 
representative survey of approximately 5,000 respondents that collects, 
among other data, dietary behavior and 24-hour dietary recall data.\17\ 
The Nielsen Homescan data include a panel of households that records 
grocery purchases using a scanning device.\18\ Panelists scan the 
barcodes of the products they purchase, recording information such as 
price and quantity. The Consumer Expenditure Survey gathers expenditure 
information from participants every 3 months over a 15 month period 
through interviews and a diary survey.\19\ The interview is designed to 
gather expenditure data on items that are easy to recall, while the 
diary survey records purchases made each day during a 2 week period.
---------------------------------------------------------------------------
    \17\ http://www.cdc.gov/nchs/tutorials/Dietary/SurveyOrientation/
intro.htm.
    \18\ http://www.ncppanel.com.
    \19\ http://www.bls.gov/cex.
---------------------------------------------------------------------------
    An outstanding question is whether food purchase data collected at 
the point-of-sale offers a different or more detailed perspective on 
the food choices of SNAP and other households. Ideally, retail data on 
SNAP electronic benefit transfer (EBT) purchases would be collected in 
a timely manner--preferably at the point of sale--and with sufficient 
sample size to be nationally representative. To date, there have been 
numerous challenges to collecting such retail data:

   The immense volume of SNAP retail data--in FY 2011, over $71 
        billion in SNAP benefits were redeemed at over 230,000 
        participating stores, farmers['] markets and other venues 
        authorized to accept SNAP benefits.\20\ These transactions 
        represent billions of food items purchased each month via an 
        estimated 250 million or more unique transactions.
---------------------------------------------------------------------------
    \20\ Supplemental Nutrition Assistance Program, USDA FNS Benefit 
Redemption Division 2011 Annual Report. Available from http://
www.fns.usda.gov/snap/retailers/pdfs/2011-annual-report-revised.pdf.

   The wide variety of food products and package sizes sold by 
        the over 230,000 SNAP-authorized retailers--roughly 40,000 
        items in larger stores \21\--and the diverse ways retailers 
        identify and track these items.
---------------------------------------------------------------------------
    \21\ http://www.fmi.org/facts_figs/?fuseaction=superfact.

   Industry reluctance to share detailed sales data, a key 
---------------------------------------------------------------------------
        competitive tool for food marketers.

   Equipment and system changes needed to capture item-level 
        data at SNAP-approved stores. The numerous cash register 
        technologies currently in use vary in their sophistication and 
        their ability to collect item-level data. Data transmission and 
        storage are also important issues.

   Distinguishing between SNAP and non-SNAP transactions and 
        purchases, given that SNAP households at times combine SNAP 
        benefits and their own funds when making purchases.

    The current study provides a snapshot of food purchasing patterns 
using POS data from a set of retailers to compare expenditures on SNAP-
eligible food items made by SNAP and non-SNAP households.
Chapter 2. Methodology
2.1  Data Overview
    POS transaction data from January 1, 2011 through December 31, 2011 
from a leading grocery retailer were examined in this study.\22\ The 
majority of stores from which the data came would be classified as 
grocery stores, supermarkets, and combination food and drug stores per 
FNS Retailer Policy and Management Division food retailer 
definitions.\23\ On average, each of the 12 monthly data files 
contained over one billion records of food items purchased by 26.5 
million households, reflecting 127 million unique transactions. Each 
monthly data file included an average of 3.2 million SNAP households, 
identified using the methodology described below. Total expenditures on 
all SNAP-eligible food items in the dataset by SNAP and non-SNAP 
households over the 12 months were $39.0 billion, or approximately $3.3 
billion per month. SNAP households expended approximately $555 million 
on SNAP-eligible food items each month in this dataset, using both SNAP 
benefits and other resources such as cash or credit cards.\24\
---------------------------------------------------------------------------
    \22\ Per the data sharing agreement between the data provider and 
IMPAQ, a description of the source of these data must be limited to the 
following: ``From a leading U.S. grocery retailer data examining POS 
transactions from January 1, 2011 through December 31, 2011 across 
approximately 11 million SNAP households. The majority of stores would 
be classified as grocery stores, supermarkets, and combination food and 
drug stores per USDA/FNS food retailer definitions.''
    \23\ Stores that opened or closed during 2011 were not included in 
these analyses.
    \24\ By way of comparison, in FY 2011, 21.1 million households 
participated in SNAP in an average month (http://www.fns.usda.gov/ora/
MENU/Published/snap/FILES/Participation/2011Characteristics.pdf) and 
redeemed $6.0 billion in benefits in an average month (http://
www.fns.usda.gov/snap/retailers/pdfs/2011-annual-report-revised.pdf).
---------------------------------------------------------------------------
2.2  Identification of SNAP Households and Creation of Analysis 
        Categories
    SNAP households were identified in the data for each month. This 
identification was performed monthly because, in any given month, some 
households enter or leave the program. The analysis identified SNAP 
households each month by first identifying any transaction in which 
SNAP EBT was used to pay for at least \1/2\ of the value of the 
purchase and designating the household that made that transaction as a 
SNAP household.\25\ It then linked all other transactions made by that 
household during that month to estimate total monthly spending by SNAP 
households. All other transactions in these stores were designated as 
non-SNAP household purchases.\26\ Exhibit 2 illustrates the 
identification of SNAP households.
---------------------------------------------------------------------------
    \25\ SNAP transactions in which SNAP EBT was not the majority 
tender were not identifiable in the data.
    \26\ Some of these transactions may, in fact, have included SNAP 
purchases. Some SNAP households may never have presented EBT as the 
majority tender in any transaction, for example.
---------------------------------------------------------------------------
Exhibit 2: Conceptual Map for Identification of SNAP Households in the 
        POS Data 
        
        
    IMPAQ analyzed SNAP-eligible food items given the focus of the 
study. Per the Food and Nutrition Act of 2008 (the Act), eligible food 
include any food or food product for home consumption, as well as seeds 
and plants which produce food for consumption. The Act precludes 
alcoholic beverages, tobacco products, hot food and any food sold for 
on-premises consumption from being purchased with SNAP benefits.\27\ 
The unit of analysis for the study was a food-related subcommodity, 
with subcommodities and commodities defined by the data provider. Each 
subcommodity typically consisted of multiple food items, often 
distinguished by brand or package size, identified by a Universal 
Product Code (UPC) or a Price Look Up (PLU) code. Each commodity was an 
aggregation of similar subcommodities. The ``apples'' commodity group, 
for example, combined different varieties (Gala, Fuji, Honeycrisp) and 
forms (bagged, bulk) that were presented separately as subcommodities. 
The decision to rely on subcommodity groupings follows procedures 
established in published studies.\28\ These studies prefer 
subcommodity-level analyses over item-level analyses because UPCs and 
PLUs assigned by manufacturers and retailers can change over time. 
Additionally, the same food item may be sold in multiple forms with 
different brands and labels, each with its own unique UPC.\29\
---------------------------------------------------------------------------
    \27\ See http://www.fns.usda.gov/snap/retailers/eligible.htm for 
more details.
    \28\ For examples, see Hamilton, S., et al. (2007). ``Food and 
nutrient availability in New Zealand: An analysis of supermarket sales 
data.'' Public Health Nutrition, 10(12): 1448-1455; Van Wave, T.W., & 
Decker, M. (2003). ``Secondary analysis of a marketing research 
database reveals patterns in dairy product purchases over time.'' 
Journal of American Dietetic Association, 103(4), 445-453.
    \29\ Baxter, J., et al. (1996). Experiences in using computerized 
sales data to evaluate a nutrition intervention program. Journal of 
Nutrition Education, 28, 443-445.
---------------------------------------------------------------------------
    Exhibit 3 details expenditures on SNAP-eligible food items in the 
dataset. As can be seen, expenditures on all 1,792 subcommodities in 
the dataset sum up to $6.7 billion and $32.3 billion for SNAP and non-
SNAP households, respectively. Notably, expenditures on the top 1,000 
subcommodities account for 99% of expenditures for SNAP households and 
98% for non-SNAP households. For this reason, all subsequent analyses 
and tables in the report are generated using the top 1,000 
subcommodities.

 Exhibit 3: Summary of SNAP and Non-SNAP Household Food Expenditures in
                       the Dataset by Subcommodity
------------------------------------------------------------------------
                                                            Non-SNAP
              Finding                SNAP Households       Households
------------------------------------------------------------------------
Total annual expenditures on SNAP-       $6.7 billion      $32.3 billion
 eligible foods in dataset
Percentage of all transactions by                 12%                88%
 all households
Percentage of total annual                        17%                83%
 expenditures by all households
Top 1,000 (of 1,792) subcommodity                 99%                98%
 expenditures as a percentage of
 all expenditures
Top 100 (of 1,792) subcommodity                   51%                46%
 expenditures as a percentage of
 all expenditures
Top 25 (of 1,792) subcommodity                    25%                21%
 expenditures as a percentage of
 all expenditures
Top 25 commodity (of 238)                         45%                41%
 expenditures as a percentage of
 all expenditures
                                   -------------------------------------
  Total annual expenditures on top    $6.5805 billion   $31.5138 billion
   1,000 subcommodities
------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ
  International, LLC, 2016.

    The data provider aggregated the subcommodities to commodities. The 
top 1,000 subcommodities represented 238 commodities. Although 
subcommodities and commodities provide adequate comparison reference 
points, these groupings were designed to help retailers classify 
purchases for their own needs (e.g., marketing purposes). Therefore, 
this study analyzed purchases at two higher levels of aggregation. 
Thirty summary categories were created--for example, meat/poultry/
seafood, fruits, vegetables, cereal, candy, and frozen prepared foods--
to be roughly analogous to the major sections or departments in a 
typical grocery store. These categories were constructed to enhance 
discussion of similarities and differences between the purchasing 
patterns of SNAP and non-SNAP households. Appendix B provides a 
crosswalk of subcommodities to summary categories.
    IMPAQ also mapped food subcommodities to USDA Food Pattern 
categories (dairy, fruits, grains, oils, protein foods, solid fats and 
added sugars (SoFAS), and vegetables).\30\ A crosswalk of 
subcommodities to USDA Food Pattern categories can be found in Appendix 
C. Relative to the 30 summary categories, there are only seven USDA 
Food Pattern categories. As a result, more subcommodities were included 
in each Food Pattern category, on average, relative to the summary 
categories which at times lead to differing results for categories with 
the same name. For example, for the USDA Food Patterns analysis, 100% 
pure orange juice was classified as a fruit. Juice, however, is a 
specific category among the summary categories. Therefore, expenditures 
on 100% orange juice were not included as fruit expenditures for the 
summary categories analysis as they were for the Food Patterns 
analysis. Readers should keep this in mind when comparing results for 
categories such as fruits or vegetables across analyses.
---------------------------------------------------------------------------
    \30\ USDA Center for Nutrition Policy and Promotion Food Patterns 
(http://www.cnpp.usda.gov/USDAFoodPatterns.htm).
---------------------------------------------------------------------------
    Not all subcommodities could be classified into single Food Pattern 
categories. Subcommodities incorporating multiple food categories, such 
as foods packaged as complete meals, were classified as composite 
foods. In addition, some subcommodities did not fit any Food Pattern 
categories, or the labels were not descriptive enough to permit 
categorization even with the addition of the composite category. A 
ninth category, other, was created to capture such subcommodities. 
``Other'' captured all items that could not be classified using USDA 
Food Patterns, such as water, isotonic drinks, and baby food. Exhibit 4 
describes the aggregations of food items used for these analyses, using 
fluid milk products as an example.
Exhibit 4: Aggregating Food Items 


          Note: The vast majority of commodities included 
        subcommodities that could be mapped to a single summary 
        category as shown above. However, a small number of commodities 
        included subcommodities that did not map to the same summary 
        category. For example, the commodity group Authentic Hispanic 
        Foods and Products included authentic vegetables and foods, 
        Hispanic carbonated beverages, and authentic pasta/rice/beans 
        subcommodities which mapped to the vegetables, sweetened 
        beverages, and rice summary categories, respectively. The top 
        1,000 subcommodities accounted for 99% of all expenditures on 
        SNAP-eligible food items in the dataset for SNAP households and 
        98% of all expenditures on SNAP-eligible food items by non-SNAP 
        households.
2.3  Data Caveats and Limitations
    Although POS data provide a wealth of information on the food 
purchase patterns of SNAP households, some limitations existed in the 
data analyzed for this study. The data used for this study captured 
only transactions completed at a specific set of retail outlets. As 
stated before, the majority of stores from which the data came would be 
classified as grocery stores, supermarkets, and combination food and 
drug stores per FNS Retailer Policy and Management Division food 
retailer definitions.\31\ Purchases made at other SNAP-authorized 
retailers or other venues (e.g., farmers['] markets) were not included 
in these data. On average, SNAP households in the data spent 
approximately $229 per month on SNAP-eligible foods using a combination 
of SNAP benefits, cash and other forms of payment.\32\ In contrast, the 
national average monthly SNAP benefit per household was $284 in FY 
2011.\33\ Therefore, although these data account for a significant 
proportion of SNAP-eligible food expenditures by SNAP households, they 
do not include all SNAP benefit expenditures.
---------------------------------------------------------------------------
    \31\ Stores that opened or closed during 2011 were not included in 
these analyses.
    \32\ On average, SNAP households in the data made 8.5 transactions 
per month. The average total expenditure on SNAP-eligible foods per 
transaction was $26.99.
    \33\ http://www.fns.usda.gov/pd/19SNAPavg$HH.htm.
---------------------------------------------------------------------------
    SNAP transactions were identified as those for which a SNAP EBT 
card was the majority tender. Because some transactions included both 
SNAP and cash or credit tenders, these data could not differentiate 
between items purchased with SNAP benefits and those purchased with 
other funds. These data, therefore, represent food purchases made by 
SNAP households rather than the foods purchased with SNAP EBT.
    Rankings of expenditure categories depend in part on the level of 
food item aggregation (whether at the Food Pattern category, summary 
category, commodity or subcommodity levels). As discussed above, the 
data provider aggregated food items into subcommodities and commodities 
considering other factors outside of the needs of this particular 
analysis. These classifications at times presented analytic challenges 
that may have affected the rank ordering of expenditures. For example, 
subcommodity groups categorized as ``composite'' or ``other'' for these 
analyses likely included food items that would more appropriately be 
included in one of the Food Pattern categories had more information 
been available. Similarly, some distinctions of potential nutritional 
importance were not available in these data. For example, it was not 
possible to distinguish between fat-free or low-fat varieties of some 
dairy products, such as fluid milk or yogurt, from whole milk 
varieties.
Chapter 3. Findings: Top Expenditures by SNAP and Non-SNAP Households

------------------------------------------------------------------------
 
-------------------------------------------------------------------------
Key Findings
 
     There were no major differences in the expenditure patterns
     of SNAP and non-SNAP households, no matter how the data were
     categorized. Similar to most American households:
 
         About 40 of every dollar of food expenditures by SNAP
         households was spent on basic items such as meat, fruits,
         vegetables, milk, eggs, and bread.
 
         Another 20 out of every dollar was spent on sweetened
         beverages, desserts, salty snacks, candy and sugar.
 
         The remaining 40 were spent on a variety of items such as
         cereal, prepared foods, dairy products, rice, and beans.
 
     The top ten summary categories and the top seven
     commodities by expenditure were the same for SNAP and non-SNAP
     households, although ranked in slightly different orders.
 
     Less healthy food items were common purchases for both SNAP
     and non-SNAP households. Sweetened beverages, prepared desserts and
     salty snacks were among the top ten summary categories for both
     groups. Expenditures were greater for sweetened beverages compared
     to all milk for both groups, as well.
 
     Expenditures were concentrated in a relatively small number
     of similar food-item categories. The top five summary groups
     totaled \1/2\ (50%) of the expenditures for SNAP households and
     nearly \1/2\ (47%) for non-SNAP households. Twenty-five commodities
     accounted for nearly \1/2\ of the food expenditures in these data
     with SNAP and non-SNAP households having 20 of them in common. The
     top 25 subcommodities for SNAP households and non-SNAP households,
     respectively, accounted for over \1/5\ of food expenditures for
     each group with 16 subcommodities in common for the two groups.
------------------------------------------------------------------------

3.1  Distribution of Expenditures by Summary Categories
    Exhibit 5 provides an overview of expenditures by the summary 
categories described in Chapter 2. In general, SNAP and non-SNAP 
household expenditure rankings and proportions were similar. 
Expenditures on basic or staple foods (meat/poultry/seafood, fruits, 
vegetables, milk, eggs and bread/crackers) comprised over 40 of every 
food purchase dollar for both SNAP and non-SNAP households (41 and 
44/dollar, respectively). Another 20 per dollar was spent on less 
healthy foods such as sweetened beverages, prepared desserts, salty 
snacks, candy and sugars by both household groups (SNAP households--
23; non-SNAP households--20).
    Expenditures were generally concentrated in a small number of 
summary groups for both SNAP and non-SNAP households. The top five 
groups total \1/2\ (50%) of the expenditures for SNAP households and 
nearly \1/2\ (47%) for non-SNAP households. The top three categories by 
expenditures for SNAP households were meat/poultry/seafood, sweetened 
beverages, and vegetables. The top three categories for non-SNAP 
households were meat/poultry/seafood, vegetables, and high fat dairy/
cheese; sweetened beverages ranked fifth. Both SNAP and non-SNAP 
households spent a greater proportion of total expenditures on meat, 
poultry and seafood than any other category. Both household groups 
spent more on fruits and vegetables than on prepared foods, and more on 
sweetened beverages than on milk.

                                  Exhibit 5: Summary Categories by Expenditure
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
          Summary Category                         $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Meat, Poultry and Seafood                    1    $1,262.9          19.19%         1    $5,016.3          15.92%
Sweetened Beverages                          2      $608.7           9.25%         5    $2,238.8           7.10%
Vegetables                                   3      $473.4           7.19%         2    $2,873.9           9.12%
Frozen Prepared Foods                        4      $455.2           6.92%         8    $1,592.3           5.05%
Prepared Desserts                            5      $453.8           6.90%         6    $2,021.2           6.41%
High Fat Dairy/Cheese                        6      $427.8           6.50%         3    $2,483.2           7.88%
Bread and Crackers                           7      $354.9           5.39%         7    $1,978.2           6.28%
Fruits                                       8      $308.2           4.68%         4    $2,271.2           7.21%
Milk                                         9      $232.7           3.54%         9    $1,211.0           3.84%
Salty Snacks                                10      $225.6           3.43%        10      $969.7           3.08%
Prepared Foods                              11      $202.2           3.07%        14      $707.0           2.24%
Cereal                                      12      $186.9           2.84%        11      $933.9           2.96%
Condiments and Seasoning                    13      $174.6           2.65%        12      $878.9           2.79%
Fats and Oils                               14      $155.1           2.36%        13      $766.9           2.43%
Candy                                       15      $138.2           2.10%        15      $701.4           2.23%
Baby Food                                   16      $126.8           1.93%        27      $198.2           0.63%
Juices                                      17      $110.4           1.68%        16      $605.4           1.92%
Coffee and Tea                              18       $83.4           1.27%        17      $568.8           1.80%
Bottled Water                               19       $78.1           1.19%        22      $377.4           1.20%
Eggs                                        20       $73.8           1.12%        21      $388.2           1.23%
Other Dairy Products                        21       $69.8           1.06%        18      $549.5           1.74%
Pasta, Cornmeal, Other Cereal               22       $66.4           1.01%        23      $281.5           0.89%
 Products
Soups                                       23       $62.7           0.95%        20      $414.1           1.31%
Sugars                                      24       $60.9           0.93%        24      $260.3           0.83%
Nuts and Seeds                              25       $53.2           0.81%        19      $445.9           1.41%
Beans                                       26       $38.3           0.58%        25      $234.5           0.74%
Rice                                        27       $30.1           0.46%        28      $131.0           0.42%
Jams, Jellies, Preserves and Other          28       $29.1           0.44%        29      $117.5           0.37%
 Sweets
Flour and Prepared Flour Mixes              29       $18.7           0.28%        30       $94.9           0.30%
Miscellaneous                               30       $18.6           0.28%        26      $202.6           0.64%
                                               ----------------------------          ---------------------------
  Total Summary Category                          $6,580.5            100%             $31,513.8            100%
   Expenditures (Top 1,000
   subcommodities)
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.

3.2  Distribution of Expenditures by Commodities
    Exhibit 6 examines expenditures at the commodity level, listing the 
top 100 commodities by expenditure for SNAP households while providing 
corresponding rankings of these commodities for non-SNAP households. 
The top 100 commodities accounted for nearly all expenditures for both 
SNAP (87%) and non-SNAP (82%) households. The top 25 SNAP household 
commodities accounted for nearly \1/2\ (46%) of the food expenditures 
for SNAP households; the top 25 commodities for non-SNAP households 
accounted for 42%. Among the top 25 commodities, the two households 
groups had 20 in common.
    The top two commodities were the same for SNAP and non-SNAP 
households, namely soft drinks and fluid milk products, although the 
order was reversed with soft drinks ranked first for SNAP households 
compared to fluid milk products for non-SNAP households. However, while 
expenditure proportions were similar for fluid milk products across the 
two household types (4 per dollar), expenditure proportions on soft 
drinks were slightly higher for SNAP households compared to non-SNAP 
households (5 versus 4 per dollar). Overall, the expenditure rankings 
and patterns should be assessed with caution as a small difference in 
the expenditure share of a commodity can lead to a major difference in 
the ranking of the commodity. For example, among SNAP households, the 
difference in expenditure shares between lunchmeat, ranked tenth, and 
aseptic juice, ranked sixty-ninth, is approximately 1 per dollar.

                        Exhibit 6: Top 100 Commodities for SNAP Households by Expenditure
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
              Commodity                            $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Soft drinks                                  1      $357.7           5.44%         2    $1,263.3           4.01%
Fluid milk products                          2      $253.7           3.85%         1    $1,270.3           4.03%
Beef grinds                                  3      $201.0           3.05%         6      $621.1           1.97%
Bag snacks                                   4      $199.3           3.03%         5      $793.9           2.52%
Cheese                                       5      $186.4           2.83%         3      $948.9           3.01%
Baked breads                                 6      $163.7           2.49%         4      $874.8           2.78%
Cold cereal                                  7      $139.2           2.12%         7      $583.9           1.85%
Chicken fresh                                8      $121.4           1.85%        11      $477.8           1.52%
Frozen handhelds and snacks                  9      $101.5           1.54%        47      $214.6           0.68%
Lunchmeat                                   10       $99.4           1.51%        17      $386.1           1.23%
Candy--packaged                             11       $96.2           1.46%         8      $527.7           1.67%
Infant formula                              12       $95.7           1.45%        80      $124.8           0.40%
Frozen pizza                                13       $90.2           1.37%        23      $305.7           0.97%
Refrigerated juices/drinks                  14       $88.5           1.35%        14      $412.8           1.31%
Ice cream, ice milk, sherbets               15       $86.0           1.31%        10      $481.8           1.53%
Coffee and creamers                         16       $82.3           1.25%         9      $519.4           1.65%
Cookies                                     17       $78.2           1.19%        16      $408.3           1.30%
Water--(sparkling and still)                18       $77.0           1.17%        18      $379.2           1.20%
Shelf stable juice                          19       $73.1           1.11%        28      $282.2           0.90%
Eggs/muffins/potatoes                       20       $72.0           1.09%        20      $358.7           1.14%
Frozen single serving premium meals         21       $68.6           1.04%        12      $447.1           1.42%
Cakes                                       22       $68.2           1.04%        38      $240.9           0.76%
Bacon                                       23       $66.1           1.00%        27      $283.2           0.90%
Traditional Mexican foods                   24       $62.6           0.95%        25      $286.9           0.91%
Yogurt                                      25       $59.9           0.91%        13      $442.3           1.40%
Salad dressing and sandwich spreads         26       $59.7           0.91%        30      $280.9           0.89%
Dinner sausage                              27       $59.3           0.90%        46      $222.6           0.71%
Frozen prepared chicken                     28       $58.6           0.89%        74      $136.4           0.43%
Baked sweet goods                           29       $57.5           0.87%        62      $159.6           0.51%
Beef loins                                  30       $56.3           0.86%        31      $280.3           0.89%
Chicken frozen                              31       $54.8           0.83%        85      $123.0           0.39%
Deli meat: bulk                             32       $54.6           0.83%        15      $411.0           1.30%
Frozen multi-serve meals                    33       $53.0           0.81%        54      $183.5           0.58%
Dinner mixes-dry                            34       $51.8           0.79%        72      $140.3           0.45%
Frozen breakfast foods                      35       $51.3           0.78%        55      $180.9           0.57%
Crackers and misc baked food                36       $50.9           0.77%        21      $323.7           1.03%
Frozen novelties-water ice                  37       $50.7           0.77%        43      $229.7           0.73%
Margarines                                  38       $50.3           0.76%        24      $303.0           0.96%
Condiments and sauces                       39       $49.8           0.76%        52      $187.2           0.59%
Potatoes                                    40       $48.8           0.74%        34      $265.2           0.84%
Frozen vegetable and veg dish               41       $48.2           0.73%        33      $266.9           0.85%
Hot dogs                                    42       $45.5           0.69%        63      $158.4           0.50%
Can vegetables--shelf stable                43       $45.3           0.69%        50      $191.7           0.61%
Shortening and oil                          44       $44.6           0.68%        57      $174.2           0.55%
Sugars and sweeteners                       45       $43.3           0.66%        60      $162.4           0.52%
Isotonic drinks                             46       $42.8           0.65%        53      $185.3           0.59%
Salad mix                                   47       $42.8           0.65%        22      $319.4           1.01%
Milk by-products                            48       $42.5           0.65%        32      $268.9           0.85%
Pork boneless loin/rib                      49       $41.5           0.63%        58      $168.0           0.53%
Convenience breakfasts and wholesome        50       $41.1           0.62%        45      $226.1           0.72%
 snacks
Frozen single serve economy meals           51       $40.9           0.62%       109       $80.7           0.26%
Refrigerated dough products                 52       $40.5           0.62%        56      $176.6           0.56%
Beef round                                  53       $40.4           0.61%        75      $134.2           0.43%
Dry bean vegetables and rice                54       $39.9           0.61%        59      $166.1           0.53%
Convenient meals                            55       $38.7           0.59%       108       $81.0           0.26%
Tomatoes                                    56       $38.3           0.58%        35      $261.7           0.83%
Candy--checklane                            57       $37.9           0.58%        64      $154.0           0.49%
Berries                                     58       $37.4           0.57%        19      $373.5           1.19%
Grapes                                      59       $36.1           0.55%        39      $235.7           0.75%
Bananas                                     60       $36.1           0.55%        36      $261.4           0.83%
Peanut                                      61       $36.0           0.55%        42      $231.0           0.73%
Pork thin meats                             62       $35.0           0.53%        93      $106.8           0.34%
Citrus                                      63       $34.3           0.52%        37      $251.7           0.80%
Breakfast sausage                           64       $34.2           0.52%        79      $126.7           0.40%
Dry sauce, gravy, potatoes, stuffing        65       $34.0           0.52%        87      $119.2           0.38%
Salad and dips                              66       $33.9           0.52%        40      $235.3           0.75%
Apples                                      67       $33.7           0.51%        29      $281.7           0.89%
Meat--shelf stable                          68       $33.3           0.51%        91      $109.2           0.35%
Aseptic juice                               69       $33.1           0.50%       112       $78.9           0.25%
Sweet goods                                 70       $32.5           0.49%        66      $152.9           0.49%
Frozen potatoes                             71       $32.2           0.49%        95      $104.5           0.33%
Meat frozen                                 72       $31.9           0.48%       120       $69.9           0.22%
Baby foods                                  73       $30.6           0.46%       121       $67.8           0.22%
Vegetables salad                            74       $30.0           0.46%        44      $228.6           0.73%
Beef: thin meats                            75       $30.0           0.46%        78      $127.7           0.41%
Seafood--shrimp                             76       $29.8           0.45%        84      $123.1           0.39%
Canned soups                                77       $29.7           0.45%        65      $153.6           0.49%
Baking mixes                                78       $28.3           0.43%        69      $148.1           0.47%
Pasta and pizza sauce                       79       $27.6           0.42%        99       $96.7           0.31%
Dry noodles and pasta                       80       $27.5           0.42%        71      $141.5           0.45%
Can seafood--shelf stable                   81       $26.5           0.40%        77      $132.3           0.42%
Rts/micro soup/broth                        82       $26.0           0.40%        48      $200.8           0.64%
Canned pasta and microwave food             83       $25.9           0.39%       135       $56.7           0.18%
Smoked hams                                 84       $25.7           0.39%        92      $108.8           0.35%
Nuts                                        85       $25.6           0.39%        41      $234.2           0.74%
Value-added fruit                           86       $25.3           0.38%        70      $146.6           0.47%
Can beans                                   87       $24.0           0.36%        82      $123.3           0.39%
Dry/ramen bouillon                          88       $21.7           0.33%       133       $61.0           0.19%
Powder and crystal drink mix                89       $21.6           0.33%       119       $75.2           0.24%
Rtd tea/new age juice                       90       $21.5           0.33%       103       $93.8           0.30%
Baking needs                                91       $21.3           0.32%        51      $188.9           0.60%
Can fruit/jar applesauce                    92       $20.9           0.32%        96      $104.0           0.33%
Spices and extracts                         93       $20.4           0.31%        86      $121.9           0.39%
Energy drinks                               94       $20.1           0.30%       102       $94.1           0.30%
Onions                                      95       $20.0           0.30%        81      $123.5           0.39%
Tropical fruit                              96       $19.8           0.30%        61      $160.1           0.51%
Bagels and cream cheese                     97       $19.8           0.30%        83      $123.2           0.39%
Frozen bread/dough                          98       $19.7           0.30%       114       $77.7           0.25%
Rolls                                       99       $18.9           0.29%        88      $113.9           0.36%
Hot cereal                                 100       $18.9           0.29%       100       $96.1           0.30%
                                               ----------------------------          ---------------------------
  Expenditures on Listed Commodities              $5,700.3          86.62%             $25,800.4          81.93%
                                               ============================          ===========================
    Expenditures on Top 1,000                     $6,580.5            100%             $31,513.8            100%
     Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 100 commodities for SNAP households and the corresponding rankings of these
  commodities for non-SNAP households. Columns may not sum to total shown due to rounding.

3.3  Distribution of Expenditures by Subcommodities
    Exhibit 7 presents the top 100 subcommodities purchased by SNAP 
households, along with corresponding expenditures and ranks of these 
subcommodities for non-SNAP households.\34\ These 100 subcommodities 
accounted for over \1/2\ (51%) of the food expenditures in these data 
for SNAP households. Comparatively, the food purchases of non-SNAP 
households on these 100 subcommodities represented only 43% of their 
total expenditures. As expected, the level of detail provided by the 
subcommodity classifications resulted in relatively small proportions 
of total expenditures being spent on any single subcommodity. 
Individually, only six subcommodities represented more than 1% of the 
expenditures of SNAP households. As with the commodity rankings, a 
small difference in the expenditure share of a subcommodity translated 
into a substantial difference in its ranking. For example, among SNAP 
households, the difference in shares of expenditures between potato 
chips, ranked seventh, and bananas, ranked thirty-fifth, is less than 
\1/2\ of one percentage point.
---------------------------------------------------------------------------
    \34\ See Appendix A for the commodity that corresponds to each 
subcommodity for the top 1,000 subcommodities.
---------------------------------------------------------------------------
    The top two subcommodities purchased by SNAP households, fluid 
milk/white only and carbonated soft drinks in 12-18 can packages, were 
the top subcommodities for non-SNAP households as well. An interesting 
difference in rankings of subcommodities between SNAP households and 
non-SNAP households was for infant formula/starter solution. This 
subcommodity ranked tenth among SNAP households. The majority of these 
formula purchases were made when SNAP EBT was not the majority tender 
(results not presented here), perhaps because WIC (Special Supplemental 
Nutrition Program for Women, Infants, and Children) benefits were used. 
Infant formula/starter solution purchases ranked well out of the top 
100 for non-SNAP households, at 190.

                      Exhibit 7: Top 100 Subcommodities for SNAP Households by Expenditure
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
            Subcommodity                           $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/White Only                        1      $191.1           2.90%         1      $853.8           2.71%
Soft Drinks 12/18 &15pk Can Car              2      $164.6           2.50%         2      $601.2           1.91%
Lean [Beef]                                  3      $112.4           1.71%         7      $257.9           0.82%
Kids' Cereal                                 4       $78.1           1.19%        20      $186.4           0.59%
Shredded Cheese                              5       $74.7           1.14%         3      $342.0           1.09%
Soft Drink 2 Liter Btl Carb Incl             6       $70.9           1.08%        12      $230.1           0.73%
Potato Chips                                 7       $64.4           0.98%         8      $253.2           0.80%
Primal [Beef]                                8       $62.4           0.95%        14      $219.8           0.70%
Lunchmeat--Deli Fresh                        9       $55.8           0.85%        11      $242.6           0.77%
Infant Formula Starter/Solution             10       $54.2           0.82%       190       $45.3           0.14%
Eggs--Large                                 11       $52.1           0.79%         9      $251.6           0.80%
Chicken Breast Boneless                     12       $49.6           0.75%         4      $292.9           0.93%
Still Water Drinking/Mineral Water          13       $48.8           0.74%        19      $187.7           0.60%
Mainstream White Bread                      14       $48.0           0.73%        39      $136.8           0.43%
Tortilla/Nacho Chips                        15       $47.4           0.72%        17      $209.0           0.66%
Snacks/Appetizers                           16       $44.6           0.68%        65      $100.5           0.32%
American Single Cheese                      17       $44.1           0.67%        41      $136.6           0.43%
Frozen Single Serve Premium                 18       $43.8           0.67%        24      $175.4           0.56%
 Traditional Meals
Dairy Case 100% Pure Juice--Orange          19       $43.5           0.66%         6      $269.0           0.85%
Snack Cake--Multi-Pack                      20       $41.6           0.63%        63      $101.7           0.32%
Enhanced [Pork Boneless Loin/Rib]           21       $41.5           0.63%        27      $168.0           0.53%
Unflavored Can Coffee                       22       $41.3           0.63%        18      $198.0           0.63%
Frozen Single Serve Economy Meals           23       $40.9           0.62%        81       $80.7           0.26%
 All
Bacon--Trad 16oz Or Less                    24       $40.7           0.62%        29      $157.6           0.50%
Soft Drinks 20pk & 24pk Can Carb            25       $39.7           0.60%        60      $106.4           0.34%
Pizza/Premium                               26       $39.7           0.60%        32      $153.3           0.49%
Mainstream Variety Breads                   27       $38.4           0.58%        26      $173.2           0.55%
Sugar                                       28       $36.9           0.56%        55      $112.7           0.36%
All Family Cereal                           29       $36.2           0.55%        16      $214.9           0.68%
Sandwiches and Handhelds                    30       $35.9           0.54%        91       $73.6           0.23%
Potatoes Russet (Bulk & Bag)                31       $35.8           0.54%        30      $154.5           0.49%
Natural Cheese Chunks                       32       $35.3           0.54%        15      $216.1           0.69%
Ribs [Pork]                                 33       $35.0           0.53%        59      $106.8           0.34%
Convenient Meals--Kids Meal                 34       $34.2           0.52%        96       $69.7           0.22%
Bananas                                     35       $34.2           0.52%        10      $242.7           0.77%
Soft Drink Mlt-Pk Btl Carb                  36       $34.0           0.52%        25      $173.6           0.55%
Premium [Ice Cream & Sherbert]              37       $31.2           0.47%        13      $226.0           0.72%
Isotonic Drinks Single Serve                38       $30.5           0.46%        47      $119.5           0.38%
Frozen Chicken--White Meat                  39       $30.0           0.46%        66       $99.8           0.32%
Condensed Soup                              40       $29.7           0.45%        31      $153.6           0.49%
Pourable Salad Dressings                    41       $29.0           0.44%        37      $139.4           0.44%
Choice Beef                                 42       $28.4           0.43%        40      $136.6           0.43%
Select Beef                                 43       $27.9           0.42%        36      $143.7           0.46%
Soft Drink Single Srv Btl Carb              44       $27.8           0.42%        94       $71.4           0.23%
Frozen Family Style Entrees                 45       $27.6           0.42%        77       $83.5           0.26%
Mayonnaise & Whipped Dressing               46       $27.3           0.41%        48      $119.1           0.38%
Frozen Bag Vegetables--Plain                47       $25.7           0.39%        42      $131.9           0.42%
Traditional [Ice Cream and Sherbert]        48       $25.6           0.39%        49      $118.7           0.38%
Hot Dogs--Base Meat                         49       $25.1           0.38%       138       $56.8           0.18%
Adult Cereal                                50       $24.9           0.38%        21      $182.6           0.58%
Frozen Single Serve Premium                 51       $24.7           0.38%         5      $271.6           0.86%
 Nutritional Meals
Macaroni and Cheese Dinners                 52       $24.3           0.37%       125       $59.7           0.19%
Aseptic Pack Juice and Drinks               53       $24.2           0.37%       134       $57.1           0.18%
Refrigerated Coffee Creamers                54       $24.1           0.37%        34      $147.2           0.47%
Choice Beef                                 55       $24.0           0.37%        92       $72.5           0.23%
Mexican Soft Tortillas and Wraps            56       $23.7           0.36%        54      $113.1           0.36%
Strawberries                                57       $23.5           0.36%        22      $178.4           0.57%
Margarine: Tubs and Bowls                   58       $23.4           0.36%        64      $100.9           0.32%
Mainstream [Pasta & Pizza]                  59       $23.0           0.35%        80       $81.0           0.26%
Chicken Wings                               60       $22.2           0.34%       300       $28.6           0.09%
Can Pasta                                   61       $22.2           0.34%       179       $47.7           0.15%
Frozen Chicken--Wings                       62       $22.2           0.34%       452       $17.4           0.06%
Lunchmeat--Bologna/Sausage                  63       $21.8           0.33%       121       $60.9           0.19%
Multi-Pack Bag Snacks                       64       $21.6           0.33%       199       $43.4           0.14%
Candy Bags-Chocolate                        65       $21.5           0.33%        33      $147.5           0.47%
Sweet Goods: Donuts                         66       $21.3           0.32%        78       $82.3           0.26%
Tuna                                        67       $21.1           0.32%        57      $109.9           0.35%
Vegetable Oil                               68       $20.5           0.31%       246       $35.4           0.11%
Frozen French Fries                         69       $20.5           0.31%       163       $50.3           0.16%
Peanut Butter                               70       $20.4           0.31%        43      $127.8           0.41%
Pizza/Economy                               71       $19.8           0.30%       192       $45.1           0.14%
Butter                                      72       $19.6           0.30%        23      $175.6           0.56%
Meat: Turkey Bulk                           73       $19.3           0.29%        28      $159.6           0.51%
Frozen Breakfast Sandwiches                 74       $19.1           0.29%       142       $55.7           0.18%
Frozen Meat--Beef                           75       $19.0           0.29%       185       $46.3           0.15%
Frozen Skillet Meals                        76       $18.8           0.29%        83       $79.3           0.25%
Value Forms/18oz and Larger                 77       $18.6           0.28%       209       $42.6           0.14%
 [Chicken]
Cakes: Birthday/Celebration                 78       $18.6           0.28%       164       $50.3           0.16%
Sandwich Cookies                            79       $18.0           0.27%        93       $71.8           0.23%
Pizza/Traditional                           80       $17.9           0.27%       111       $64.1           0.20%
Fruit Snacks                                81       $17.6           0.27%       202       $43.2           0.14%
Rts Soup: Chunky/Homestyle                  82       $17.6           0.27%        46      $119.9           0.38%
Sour Creams                                 83       $17.5           0.27%        70       $95.2           0.30%
Waffles/Pancakes/French Toast               84       $17.3           0.26%        90       $77.4           0.25%
Chicken Drums                               85       $17.3           0.26%       270       $31.5           0.10%
Cream Cheese                                86       $17.2           0.26%        51      $115.5           0.37%
Angus [Beef]                                87       $17.1           0.26%        61      $103.8           0.33%
Bagged Cheese Snacks                        88       $17.1           0.26%       157       $52.0           0.16%
Salsa and Dips                              89       $17.1           0.26%       135       $57.0           0.18%
Sandwiches--(Cold)                          90       $16.9           0.26%       106       $67.7           0.21%
Ramen Noodles/Ramen Cups                    91       $16.7           0.25%       304       $28.1           0.09%
Cheese Crackers                             92       $16.5           0.25%        72       $90.2           0.29%
Dinner Sausage--Links Pork                  93       $16.4           0.25%       233       $37.6           0.12%
Candy Bars (Singles)                        94       $16.3           0.25%       146       $54.9           0.17%
Hamburger Buns                              95       $16.2           0.25%        95       $70.2           0.22%
Hot Dog Buns                                96       $16.2           0.25%       117       $62.2           0.20%
Spring Water                                97       $16.2           0.25%        69       $95.6           0.30%
Dairy Case Juice Drink Under 10oz           98       $16.0           0.24%       177       $48.0           0.15%
Flavored Milk                               99       $16.0           0.24%       128       $59.4           0.19%
Sweet Goods--Full Size                     100       $15.8           0.24%       133       $57.9           0.18%
                                               ----------------------------          ---------------------------
  Expenditures on Listed                          $3,372.2          51.01%             $13,390.0          42.14%
   Subcommodities
                                               ============================          ===========================
    Expenditures on Top 1,000                     $6,580.5            100%             $31,513.8            100%
     subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 100 subcommodities for SNAP households and the corresponding rankings of these
  subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

3.4  Distribution of Expenditures by Household Demographics, Store 
        Characteristics, Type of Resource Used, and Month of Purchase
    In addition to analyzing purchase patterns as a whole, IMPAQ also 
analyzed the POS purchase data by household demographic and store 
characteristic subgroups based on information from the data provider. 
Appendix E provides these analyses. More transactions in these data 
were made by households without children than by households with 
children. In addition, a larger proportion of transactions were made at 
retail outlets in metropolitan areas than in rural or suburban areas; 
\35\ at larger stores rather than smaller ones; \36\ and in counties 
with 10-20% poverty rates, the median of the three poverty rate 
categories into which the counties in which the stores were located 
were classified.\37\ Compared to non-SNAP household transactions, SNAP 
household transactions were more likely to be made by households headed 
by adults 19-44 years of age, in stores located in the Midwest, and in 
medium-sized grocery stores. A larger proportion of SNAP household 
transactions than of non-SNAP household transactions took place in the 
most impoverished counties (counties with poverty rates greater than 
20%). Notably, the distribution of transactions by household 
demographic and store characteristics was relatively consistent whether 
SNAP households used SNAP benefits or other resources.
---------------------------------------------------------------------------
    \35\ USDA Economic Research Service Urban Influence Codes (http://
www.ers.usda.gov/data-products/urban-influence-codes.aspx).
    \36\ Following Food Marketing Institute conventions from http://
www.fmi.org/about/ and http://www.fmi.org/facts--figs/
?fuseaction=superfact and FNS Retailer Policy and Management Division 
food retailer definitions from http://www.fns.usda.gov/snap/retailers/
pdfs/2012-annual-report.pdf.
    \37\ Census Bureau data from http://www.census.gov/did/www/saipe/
county.html.
---------------------------------------------------------------------------
    In addition to analyzing the POS data for the full year, analyses 
were completed at the monthly level to investigate monthly or seasonal 
patterns in purchases. There was little month-to-month variation in 
expenditure patterns for either SNAP or non-SNAP households. A notable 
exception was that for both household types expenditure shares for 
vegetables were 2-3 percentage points lower during the summer months, 
while expenditure shares for fruits were 2-3 percentage points higher 
(data not shown).
Chapter 4. Findings: Top Expenditures by USDA Food Pattern Categories

------------------------------------------------------------------------
 
-------------------------------------------------------------------------
Key Findings
 
     Overall, there were few differences between SNAP and non-
     SNAP household expenditures by USDA Food Pattern categories.
     Expenditure shares for each of the USDA Food Pattern categories
     (dairy, fruits, grains, oils, protein foods, solid fats and added
     sugars (SoFAS), and vegetables) varied by no more than 3 per
     dollar when comparing SNAP and non-SNAP households.
 
     Protein foods represented the largest expenditure share for
     both household types, while proportionally more was spent on fruits
     and vegetables than on solid fats and added sugars, grains or
     dairy.
------------------------------------------------------------------------

SNAP and Non-SNAP Household Expenditures by USDA Food Pattern 
        Categories
        
        
        
        [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
        

 
 
 
          SNAP Households                    Non-SNAP Households
 

          Source: Foods Typically Purchased by SNAP Households, IMPAQ 
        International, LLC, 2016.
4.1  Top Expenditures for Dairy
    There are few differences in dairy expenditure patterns between 
SNAP households and non-SNAP households. Shown in Exhibit 8, the top 
four dairy subcommodities for both household groups were identical--
fluid milk/white only, shredded cheese, American single cheese, and 
natural cheese chunks. These top four accounted for 60% of all dairy 
expenditures for SNAP households and 47% for non-SNAP households. The 
biggest driver of the proportional difference was the purchase of fluid 
milk/white only. Fluid white milk was the top subcommodity representing 
33% of all dairy expenditures by SNAP households. In comparison, this 
subcommodity accounted for 26% of non-SNAP household dairy 
expenditures. Overall, 23 dairy subcommodities in the top 25 for SNAP 
households were also among the top 25 for non-SNAP households. The top 
25 dairy subcommodities for SNAP households represented almost all 
dairy expenditures, 93%, while these 25 subcommodities represented 85% 
of dairy expenditures for non-SNAP households.

                        Exhibit 8: Top 25 SNAP Household Dairy Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
         Dairy Subcommodity                        $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/White Only                        1      $191.1          33.25%         1      $853.8          25.69%
Shredded Cheese                              2       $74.7          13.00%         2      $342.0          10.29%
American Single Cheese                       3       $44.1           7.67%         4      $136.6           4.11%
Natural Cheese Chunks                        4       $35.3           6.14%         3      $216.1           6.50%
Bagged Cheese Snacks                         5       $17.1           2.98%        16       $52.0           1.56%
Flavored Fluid Milk                          6       $16.0           2.78%        14       $59.4           1.79%
String Cheese                                7       $15.1           2.63%         9       $99.0           2.98%
Yogurt/Kids                                  8       $14.0           2.44%        20       $42.4           1.28%
Cottage Cheese                               9       $13.9           2.42%         7      $108.8           3.27%
Natural Cheese Slices                       10       $13.4           2.33%         6      $113.2           3.41%
Yogurt/Single Serving Regular               11       $11.0           1.91%        11       $69.0           2.07%
Loaf Cheese                                 12       $10.9           1.90%        23       $38.1           1.15%
Yogurt/Single Serve Light                   13       $10.2           1.78%         8      $103.1           3.10%
Yogurt/Pro Active Health                    14        $7.4           1.29%        13       $63.5           1.91%
Yogurt/Adult Multi-Packs                    15        $7.2           1.25%        19       $42.5           1.28%
Specialty/Lactose Free Milk                 16        $6.7           1.17%        17       $48.4           1.46%
Grated Cheese                               17        $6.2           1.08%        25       $33.6           1.01%
Bulk Semi-Hard (Cheese)                     18        $6.1           1.05%        18       $44.0           1.32%
Fluid Milk                                  19        $5.9           1.02%         5      $113.3           3.41%
Canned Milk                                 20        $5.5           0.96%        27       $27.9           0.84%
Yogurt/Specialty Greek                      21        $5.0           0.86%        10       $77.4           2.33%
Half & Half                                 22        $4.4           0.77%        15       $54.6           1.64%
Yogurt/Large Size (16oz or More)            23        $4.4           0.76%        22       $40.4           1.22%
Miscellaneous Cheese                        24        $3.8           0.67%        21       $42.1           1.27%
Bulk Processed (Cheese)                     25        $3.4           0.59%        29       $19.8           0.60%
                                               ----------------------------          ---------------------------
  Sum of Listed Dairy Expenditures                  $532.9          92.70%              $2,841.0          85.49%
                                               ============================          ===========================
    Total Dairy Expenditures Among                  $571.2            100%              $3,257.4            100%
     Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 dairy subcommodities for SNAP households and the corresponding ranking of these
  subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

4.2  Top Expenditures for Fruits
    The top 25 fruit subcommodities by expenditure for SNAP households 
included whole fruits as well as 100% fruit juices, as shown in Exhibit 
9 below. The top fruit subcommodity for both SNAP and non-SNAP 
households was 100% orange juice. This top fruit subcommodity 
represented 10% of all SNAP household fruit expenditures, 9% for non-
SNAP households. Bananas and strawberries rank second and third, 
respectively, for both household groups. Together, the top three fruit 
subcommodities account for about \1/4\ (24%) of the fruit expenditures 
for both SNAP and non-SNAP households. The top 25 SNAP household fruit 
subcommodities accounted for 71% of all SNAP household fruit 
expenditures. These 25 subcommodities accounted for 66% of fruit 
expenditures for non-SNAP households. Twenty-one of the top 25 fruit 
subcommodities for SNAP households were also in the top 25 for non-SNAP 
households.

                        Exhibit 9: Top 25 SNAP Household Fruit Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
         Fruit Subcommodity                        $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
100% Pure Juice--Orange; Dairy Case          1       $43.5          10.18%         1      $269.0           9.35%
Bananas                                      2       $34.2           8.00%         2      $242.7           8.43%
Strawberries                                 3       $23.5           5.48%         3      $178.4           6.20%
Fruit Snacks                                 4       $17.6           4.13%        17       $43.2           1.50%
Grapes Red                                   5       $15.8           3.70%         4      $121.7           4.23%
Grapes White                                 6       $15.5           3.61%         6       $84.9           2.95%
Apple Juice & Cider (Over 50% Pure           7       $13.3           3.11%        14       $45.8           1.59%
 Juice)
Instore Cut Fruit                            8       $13.2           3.09%         5       $85.8           2.98%
Oranges Navels                               9       $12.6           2.94%         8       $79.3           2.75%
Fruit Cup                                   10       $10.6           2.47%        19       $42.7           1.49%
Blended Juice & Combinations                11        $9.3           2.17%        29       $29.6           1.03%
Clementines                                 12        $8.8           2.06%         9       $78.6           2.73%
Melons Instore Cut                          13        $8.2           1.93%        18       $42.8           1.49%
Watermelon Seedless Whole                   14        $7.9           1.84%        16       $43.9           1.53%
Cherries Red                                15        $6.9           1.61%        11       $56.7           1.97%
Apples Gala (Bulk & Bag)                    16        $6.6           1.54%        10       $69.3           2.41%
Cranapple/Cran Grape Juice                  17        $6.1           1.43%        31       $27.3           0.95%
Apples Red Delicious (Bulk & Bag)           18        $5.8           1.35%        23       $35.2           1.22%
100% Pure Juice--Other; Dairy Case          19        $5.4           1.26%        25       $32.3           1.12%
Cantaloupe Whole                            20        $5.3           1.24%        15       $44.4           1.54%
Blueberries                                 21        $5.1           1.19%         7       $79.4           2.76%
Pineapple                                   22        $4.9           1.15%        33       $24.0           0.83%
Peaches Yellow Flesh                        23        $4.8           1.13%        22       $35.6           1.24%
Grape Juice (Over 50% Juice)                24        $4.8           1.12%        44       $17.1           0.60%
Lemons                                      25        $4.6           1.08%        24       $33.6           1.17%
                                               ----------------------------          ---------------------------
  Sum of Listed Fruit Expenditures                  $294.3          68.81%              $1,843.4          64.06%
                                               ============================          ===========================
    Total Fruit Expenditures Among                  $416.8            100%              $2,772.4            100%
     Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 fruit subcommodities for SNAP households and the corresponding rankings of
  these subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

4.3  Top Expenditures for Grains
    Exhibit 10 details the top 25 grain subcommodities purchased by 
SNAP households. Cereals are a popular purchase among grain 
subcommodities for both SNAP and non-SNAP households. The top grain 
subcommodity for SNAP households was kids cereal, representing almost 
10% of all grain expenditures. Kids cereal, ranked third for non-SNAP 
households. All family cereal was ranked first for non-SNAP households 
and fifth for SNAP households. Adult cereals were also common purchases 
ranking sixth for SNAP households and fourth for non-SNAP households. 
The top 25 grain subcommodities purchased by SNAP households made up 
67% of their grain expenditures. Comparatively, these 25 subcommodities 
comprised 57% of expenditures on grains subcommodities for non-SNAP 
households. Ninteen subcommodities in the top 25 for SNAP households 
were also among the top 25 for non-SNAP households.

                       Exhibit 10: Top 25 SNAP Household Grains Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
         Grains Subcommodity                       $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Kids Cereal                                  1       $78.1           9.88%         3      $186.4           4.51%
Mainstream White Bread                       2       $48.0           6.07%         7      $136.8           3.31%
Tortilla/Nacho Chips                         3       $47.4           5.99%         2      $209.0           5.05%
Mainstream Variety Breads                    4       $38.4           4.86%         5      $173.2           4.19%
All Family Cereal                            5       $36.2           4.58%         1      $214.9           5.20%
Adult Cereal                                 6       $24.9           3.15%         4      $182.6           4.42%
Mexican Soft Tortillas and Wraps             7       $23.7           3.00%         8      $113.1           2.74%
Waffles/Pancakes/French Toast                8       $17.3           2.19%        13       $77.4           1.87%
Ramen Noodles/Ramen Cups                     9       $16.7           2.12%        43       $28.1           0.68%
Cheese Crackers                             10       $16.5           2.08%        10       $90.2           2.18%
Hamburger Buns                              11       $16.2           2.05%        14       $70.2           1.70%
Hot Dog Buns                                12       $16.2           2.05%        18       $62.2           1.50%
Refrigerated Biscuits                       13       $14.7           1.86%        30       $45.2           1.09%
Butter Spray Crackers                       14       $14.6           1.85%        15       $68.7           1.66%
Toaster Pastries                            15       $14.0           1.77%        27       $47.6           1.15%
Rice Side Dish Mixes Dry                    16       $14.0           1.76%        28       $46.7           1.13%
Popcorn--Microwave                          17       $13.1           1.65%        17       $63.4           1.53%
Long Cut Pasta                              18       $13.0           1.64%        19       $60.4           1.46%
Granola Bars                                19       $12.8           1.61%        11       $88.9            .15%
Premium Bread                               20       $12.3           1.55%         6      $144.7           3.50%
Cereal Bars                                 21       $10.9           1.38%        12       $78.4           1.90%
Short Cut Pasta                             22        $9.9           1.25%        21       $56.2           1.36%
Rolls: Dinner                               23        $9.5           1.21%        23       $50.5           1.22%
Frozen Garlic Toast                         24        $9.1           1.16%        44       $27.8           0.67%
Corn Chips                                  25        $9.1           1.15%        29       $45.6           1.10%
                                               ----------------------------          ---------------------------
  Sum of Listed Grain Expenditures                  $536.6          67.86%              $2,368.4          57.27%
                                               ============================          ===========================
    Total Grain Expenditures Among                  $783.8            100%              $4,049.9            100%
     Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 grain subcommodities for SNAP households and the corresponding ranking of these
  subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

4.4  Top Expenditures for Oils
    The top oils subcommodity expenditures are shown in Exhibit 11. 
Pourable salad dressings was the top oils subcommodity by expenditure 
for both SNAP and non-SNAP households, accounting for nearly \1/4\ of 
their total expenditures on oils. The second and third ranked oils 
subcommodities, mayonnaise/whipped dressing and margarine in tubs and 
bowls, were the same for both household groups, as well.

                                   Exhibit 11: Oils Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
          Oils Subcommodity                        $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Pourable Salad Dressings                     1       $29.0          22.71%         1      $139.4          24.28%
Mayonnaise and Whipped Dressing              2       $27.3          21.34%         2      $119.1          20.73%
Margarine: Tubs and Bowls                    3       $23.4          18.37%         3      $100.9          17.56%
Vegetable Oils                               4       $20.5          16.07%         5       $35.4           6.16%
Canola Oils                                  5        $8.3           6.49%         6       $29.3           5.10%
Olive Oils                                   6        $7.3           5.69%         4       $63.8          11.11%
Cooking Sprays                               7        $3.2           2.49%         7       $21.0           3.65%
Dressing Creamy                              8        $1.6           1.23%         8       $14.5           2.53%
Sandwich/Horseradish and Tartar              9        $1.4           1.14%        10        $7.2           1.26%
 Sauce
Corn Oils                                   10        $1.3           1.01%        14        $4.1           0.71%
Cooking Oils: Peanut/Safflower              11        $1.1           0.89%        11        $6.7           1.17%
Dressing Blue Cheese                        12        $0.9           0.71%         9        $9.5           1.65%
Margarine: Squeeze                          13        $0.6           0.44%        13        $4.2           0.74%
                                               ----------------------------          ---------------------------
  Sum of Listed Oils Expenditures                   $125.9          98.58%                $555.0          96.65%
                                               ============================          ===========================
    Total Oils Expenditures Among                   $125.9            100%                $555.0            100%
     the Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The data included only 13 oils subcommodities in the top 1,000 subcommodities. Columns may not sum to
  total shown due to rounding.

4.5  Top Expenditures for Protein Foods
    The top 25 protein foods subcommodities based on expenditures of 
SNAP households are shown in Exhibit 12. For SNAP households, the top 
25 represented over \1/2\ (54%) of all protein foods expenditures. 
These same 25 subcommodities comprised 48% of the protein foods 
expenditures for non-SNAP households. The top five subcommodities were 
the same for both household groups, although in slightly different 
order and accounted for \1/5\ of all protein expenditures for both 
households. The protein foods included in the top five were beef, 
lunchmeat, eggs and chicken. Lean ground beef was the top protein foods 
subcommodity by expenditure for SNAP households, totaling just over 7% 
of all protein foods expenditures. The top protein foods subcommodity 
for non-SNAP households was boneless chicken breasts at 5% of their 
expenditures. Eighteen of the SNAP household top 25 subcommodities were 
also ranked in the top 25 for non-SNAP households.

                    Exhibit 12: Top 25 SNAP Household Protein Foods Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
     Protein Foods Subcommodity                    $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Lean Ground Beef                             1      $112.4           7.38%         2      $257.9           4.03%
Primal Ground Beef                           2       $62.4           4.10%         5      $219.8           3.43%
Lunchmeat--Deli Fresh                        3       $55.8           3.67%         4      $242.6           3.79%
Eggs--Large                                  4       $52.1           3.43%         3      $251.6            .93%
Chicken Breast Boneless                      5       $49.6           3.26%         1      $292.9           4.57%
Enhanced Pork Boneless Loin/Rib              6       $41.5           2.73%         6      $168.0           2.62%
Bacon--Trad 16oz Or Less                     7       $40.7           2.68%         8      $157.6           2.46%
Ribs (Pork)                                  8       $35.0           2.30%        15      $106.8           1.67%
Frozen Chicken--White Meat                   9       $30.0           1.97%        17       $99.8           1.56%
Choice Beef (Loins)                         10       $28.4           1.87%        11      $136.6           2.13%
Select Beef                                 11       $27.9           1.83%         9      $143.7           2.24%
Hot Dogs--Base Meat                         12       $25.1           1.65%        27       $56.8           0.89%
Choice Beef (Rounds)                        13       $24.0           1.58%        20       $72.5           1.13%
Chicken Wings                               14       $22.2           1.46%        58       $28.6           0.45%
Frozen Chicken--Wings                       15       $22.2           1.46%        97       $17.4           0.27%
Lunchmeat--Bologna/Sausage                  16       $21.8           1.43%        24       $60.9           0.95%
Tuna                                        17       $21.1           1.39%        14      $109.9           1.72%
Peanut Butter                               18       $20.4           1.34%        12      $127.8           1.99%
Meat: Turkey Bulk                           19       $19.3           1.27%         7      $159.6           2.49%
Frozen Meat--Beef                           20       $19.0           1.25%        34       $46.3           0.72%
Value Forms/18oz & Larger                   21       $18.6           1.22%        41       $42.6           0.67%
Chicken Drumsticks                          22       $17.3           1.14%        49       $31.5           0.49%
Angus Beef                                  23       $17.1           1.13%        16      $103.8           1.62%
Dinner Sausage--Links Pork Ckd              24       $16.4           1.08%        45       $37.6           0.59%
Meat: Ham Bulk                              25       $15.3           1.00%        13      $115.9           1.81%
                                               ----------------------------          ---------------------------
  Sum of Listed Protein Foods                       $815.7          53.62%              $3,088.3          48.22%
   Expenditures
                                               ============================          ===========================
    Total Protein Foods Expenditures              $1,512.2            100%              $6,288.8            100%
     Among Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 protein foods subcommodities for SNAP households and the corresponding ranking
  of these subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

4.6  Top Expenditures for Solid Fats and Added Sugars (SoFAS)
    The top 25 SoFAS subcommodities by expenditure for SNAP households 
are shown in Exhibit 13. Twenty two subcommodities in the top 25 for 
SNAP households were also among the top 25 for non-SNAP households. In 
addition, the top two subcommodities were the same. They were 
carbonated soft drinks packaged as 12-18 pack cans and 2-liter bottles. 
These two subcommodities represented approximately \1/4\ of the SoFAS 
expenditures for both types of households. Sugar, ranked fourth, was 
the highest ranked non-beverage SoFAS subcommodity for SNAP households. 
It was eighth ranked for non-SNAP households. Butter ranked higher 
(third) for non-SNAP households compared to tenth for SNAP households. 
Overall, the top 25 SNAP household SoFAS subcommodities in Exhibit 13 
totaled 75% of SNAP household SoFAS expenditures. These 25 
subcommodities totaled 71% of the SoFAS expenditures for non-SNAP 
households.

         Exhibit 13: Top 25 SNAP Household Solid Fats and Added Sugars (SoFAS) Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
 Solid Fats and Added Sugars (SoFAS) ---------------------------------------------------------------------------
            Subcommodity                           $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Soft Drinks 12/18 & 15pk Can Car             1      $164.6          18.86%         1      $601.2          16.11%
Soft Drinks 2 Liter Btl Carb Incl            2       $70.9           8.12%         2      $230.1           6.17%
Soft Drinks 20pk & 24pk Can Carb             3       $39.7           4.55%         9      $106.4           2.85%
Sugar                                        4       $36.9           4.23%         8      $112.7           3.02%
Soft Drink Mlt-Pk Btl Carb                   5       $34.0           3.90%         4      $173.6           4.65%
Soft Drink Single Serve Btl Carb             6       $27.8           3.18%        11       $71.4           1.91%
Aseptic Pack Juice And Drinks                7       $24.2           2.78%        16       $57.1           1.53%
Refrigerated Coffee Creamers                 8       $24.1           2.76%         6      $147.2           3.95%
Candy Bags-Chocolate                         9       $21.5           2.46%         5      $147.5           3.95%
Butter                                      10       $19.6           2.24%         3      $175.6           4.71%
Sour Creams                                 11       $17.5           2.00%        10       $95.2           2.55%
Cream Cheese                                12       $17.2           1.97%         7      $115.5           3.10%
Candy Bars (Singles)                        13       $16.3           1.87%        18       $54.9           1.47%
Dairy Case Juice Drink Under 10 Oz          14       $16.0           1.83%        22       $48.0           1.29%
Candy Bars (Multi Pack)                     15       $15.6           1.79%        12       $69.6           1.86%
Tea Sweetened                               16       $13.9           1.59%        13       $68.7           1.84%
Chewing Gum                                 17       $13.2           1.51%        14       $68.3           1.83%
Candy Bags-Non Chocolate                    18       $12.6           1.44%        19       $54.9           1.47%
Molasses and Syrups                         19       $11.7           1.34%        15       $58.7           1.57%
Dairy Case Citrus Punch/OJ Subs             20       $11.0           1.26%        27       $34.4           0.92%
Fruit Drinks: Canned & Glass                21       $10.6           1.21%        60       $10.9           0.29%
Non Dairy Creamer                           22       $10.5           1.20%        25       $35.4           0.95%
Seasonal Miscellaneous                      23        $9.2           1.05%        23       $46.9           1.26%
Dairy Case Tea With Sugar                   24        $8.4           0.96%        36       $23.1           0.62%
Seasonal Candy Bags-Chocolate               25        $7.9           0.90%        20       $54.8           1.47%
                                               ----------------------------          ---------------------------
  Sum of Listed SoFAS Expenditures                  $655.0          75.00%              $2,662.3          71.34%
                                               ============================          ===========================
    Total SoFAS Expenditures Among                  $864.1            100%              $3,673.1            100%
     Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 SoFAS subcommodities for SNAP households and the corresponding ranking of these
  subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

    SoFAS were divided into three broad subcategories to inform the 
analyses: butter/cream/solid fats, candy/sweets, and sweetened 
beverages.\38\ The distribution of these subcategories for both 
household types is shown in Exhibit 14. As a share of total SoFAS 
expenditures, sweetened beverage expenditures were more than ten 
percentage points higher in SNAP households than non-SNAP households. 
In contrast, non-SNAP households spent a larger share of their SoFAS 
expenditures on the butter/cream/solid fats and candy/sweets 
subcategories.
---------------------------------------------------------------------------
    \38\ Fruit drinks that are over 50% juice are categorized as 
fruits. All other fruit drinks are categorized as SoFAS. In our 
discussion, fruit drinks that are less than 50% juice are grouped into 
``sweetened beverages.''
---------------------------------------------------------------------------
Exhibit 14: Solid Fats and Added Sugars (SoFAS) Expenditures by 
        Subcategory
        
        
        
        
        [GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
        

 
 
 
          SNAP Households                    Non-SNAP Households
 

          Source: Foods Typically Purchased by SNAP Households, IMPAQ 
        International, LLC, 2016.
4.7  Top Expenditures for Vegetables
    As shown in Exhibit 15, russet potatoes and plain frozen bag 
vegetables were the top two vegetable subcommodities by expenditure 
purchased by SNAP and non-SNAP households. Overall, 18 of the top 25 
vegetable subcommodities for SNAP households were among the top 25 for 
non-SNAP households. The top 25 SNAP household subcommodities comprised 
56% of total vegetable expenditures for SNAP households. These same 25 
subcommodities comprised 47% of total vegetable expenditures for non-
SNAP households. The top 25 subcommodities for both SNAP and non-SNAP 
households for this Food Pattern category included a range of 
vegetables such as potatoes, avocados, green beans, corn, lettuce and 
cucumbers to name a few.

                     Exhibit 15: Top 25 SNAP Household Vegetables Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
       Vegetables Subcommodity                     $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Potatoes Russet (Bulk & Bag)                 1       $35.8           6.74%         1      $154.5           4.60%
Frozen Bag Vegetables--Plain                 2       $25.7           4.85%         2      $131.9           3.93%
Mainstream Pasta & Pizza Sauce               3       $23.0           4.33%         6       $81.0           2.41%
Frozen French Fries                          4       $20.5           3.86%        19       $50.3           1.50%
Avocado                                      5       $13.4           2.52%         4      $112.6           3.35%
Blends Salad Mix                             6       $13.1           2.47%         3      $124.0           3.69%
Green Beans: Fs/Whl/Cut                      7       $12.8           2.41%        15       $53.1           1.58%
Potatoes: Dry                                8       $12.3           2.31%        33       $32.3           0.96%
Corn                                         9       $12.1           2.28%        22       $44.0           1.31%
Head Lettuce                                10       $11.6           2.18%        13       $55.5           1.65%
Frozen Steamable Vegetables                 11       $10.5           1.98%         5       $81.4           2.42%
Mexican Sauces and Picante Sauce            12       $10.2           1.93%         9       $62.3           1.85%
Tomatoes Diced                              13        $9.5           1.79%        11       $59.9           1.78%
Tomatoes Hothouse On The Vine               14        $9.2           1.74%         7       $77.7           2.31%
Onions Yellow (Bulk & Bag)                  15        $8.7           1.65%        27       $39.3           1.17%
Cucumbers                                   16        $8.2           1.55%        12       $58.9           1.75%
Vegetable Salads--Prepack                   17        $7.8           1.48%        29       $36.6           1.09%
Peppers Green Bell                          18        $7.8           1.47%        25       $41.5           1.24%
Regular Garden                              19        $7.8           1.46%        35       $31.9           0.95%
Roma Tomatoes (Bulk/Pkg)                    20        $7.5           1.41%        26       $39.6           1.18%
Carrots Mini Peeled                         21        $7.0           1.32%        10       $61.4           1.83%
Onions Sweet (Bulk & Bag)                   22        $6.2           1.16%        20       $47.4           1.41%
Celery                                      23        $5.9           1.11%        17       $51.2           1.52%
Tomatoes Vine Ripe Bulk                     24        $5.7           1.07%        51       $22.5           0.67%
Garden Plus Salad Mix                       25        $5.5           1.03%        36       $31.8           0.95%
                                               ----------------------------          ---------------------------
  Sum of Listed Vegetable                           $297.7          56.10%              $1,582.6          47.10%
   Expenditures
                                               ============================          ===========================
    Total Vegetable Expenditures                    $520.5            100%              $3,251.8            100%
     Among Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 vegetable subcommodities for SNAP households and the corresponding ranking of
  these subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

4.8  Top Expenditures for Composite Foods
    Composite foods include those subcommodities that contain more than 
one USDA Food Pattern category. As a result, they could not be assigned 
specifically to a single category. For example, composite foods include 
both dairy and grains (macaroni and cheese), dairy and SoFAS (ice 
cream), vegetables and oils (potato chips), or protein foods, 
vegetables and grains (frozen meals). The top 25 composite foods 
subcommodities based on the expenditures of SNAP households are 
presented in Exhibit 16. Potato chips were the top composite 
subcommodity by expenditure for SNAP households, representing 5% of 
their overall expenditures on composite items. Potato chips were ranked 
second for non-SNAP households. Overall, expenditures on composite 
subcommodities were similar for SNAP and non-SNAP households with 19 
subcommodities in the top 25 for both groups. The top 25 SNAP household 
subcommodities shown in Exhibit 16 represented 58% of all SNAP 
household composite foods expenditures, while expenditures on these 25 
subcommodities by non-SNAP households accounted for 51% of their total 
composite foods expenditures.

                      Exhibit 16: Top 25 SNAP Household Composite Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
       Composite Subcommodity                      $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Potato Chips                                 1       $64.4           5.19%         2      $253.2           4.88%
Snacks/Appetizers                            2       $44.6           3.59%        10      $100.5           1.94%
Frozen Single Serve Premium                  3       $43.8           3.53%         4      $175.4           3.38%
 Traditional Meals
Snack Cake--Multi Pack                       4       $41.6           3.36%         9      $101.7           1.96%
Frozen Single Serve Economy Meals            5       $40.9           3.30%        15       $80.7           1.56%
Pizza/Premium                                6       $39.7           3.20%         6      $153.3           2.95%
Sandwiches and Handhelds                     7       $35.9           2.89%        17       $73.6           1.42%
Convenient Meals--Kids Meal                  8       $34.2           2.76%        19       $69.7           1.34%
Premium (Ice Cream & Sherbert)               9       $31.2           2.52%         3      $226.0           4.35%
Condensed Soup                              10       $29.7           2.39%         5      $153.6           2.96%
Frozen Family Style Entrees                 11       $27.6           2.23%        13       $83.5           1.61%
Traditional                                 12       $25.6           2.07%         8      $118.7           2.29%
Frozen Single Serve Premium                 13       $24.7           1.99%         1      $271.6           5.23%
 Nutritional Meals
Macaroni and Cheese Dinners                 14       $24.3           1.96%        24       $59.7           1.15%
Can Pasta                                   15       $22.2           1.79%        36       $47.7           0.92%
Multi-Pack Bag Snacks                       16       $21.6           1.74%        38       $43.4           0.84%
Sweet Goods: Donuts                         17       $21.3           1.72%        14       $82.3           1.58%
Pizza/Economy                               18       $19.8           1.60%        37       $45.1           0.87%
Frozen Breakfast Sandwiches                 19       $19.1           1.54%        29       $55.7           1.07%
Frozen Skillet Meals                        20       $18.8           1.51%        16       $79.3           1.53%
Cakes: Birthday/Celebration                 21       $18.6           1.50%        33       $50.3           0.97%
Sandwich Cookies                            22       $18.0           1.45%        18       $71.8           1.38%
Pizza/Traditional                           23       $17.9           1.44%        22       $64.1           1.24%
Rts Soup: Chunky/Homestyle                  24       $17.6           1.42%         7      $119.9           2.31%
Salsa and Dips                              25       $17.1           1.38%        28       $57.0           1.10%
                                               ----------------------------          ---------------------------
  Sum of Listed Composite                           $720.5          58.07%              $2,637.7          50.83%
   Expenditures
                                               ============================          ===========================
    Total Composite Expenditures                  $1,235.4            100%              $5,132.0            100%
     Among Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 composite subcommodities for SNAP households and the corresponding ranking of
  these subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

    The composite subcommodities were further categorized as snacks, 
soups, desserts, and entree/meal items to inform the analyses. Exhibit 
17 suggests some differences in SNAP and non-SNAP household expenditure 
distributions on these subgroups. SNAP households spent a larger share 
of their composite expenditures on entree/meal subcommodities, while 
non-SNAP households spent larger shares on desserts and soup. 
Expenditures on snacks were not very different across the two groups.
Exhibit 17: Composite Expenditures by Subcategory



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]


 
 
 
          SNAP Households                    Non-SNAP Households
 

          Source: Foods Typically Purchased by SNAP Households, IMPAQ 
        International, LLC, 2016.
4.9  Top Expenditures for Other Subcommodities
    Some subcommodities did not contain any USDA Food Pattern 
categories, or the subcommodity labels were not descriptive enough to 
permit categorization even with the addition of the composite category. 
As a result, a ninth category, other, was created to capture such 
subcommodities. ``Other'' included subcommodities such as water, 
isotonic drinks, and baby food. The top 25 other subcommodities based 
on the expenditures of SNAP households are shown in Exhibit 18 and 
accounted for 66% of their overall other subcommodity expenditures. 
These subcommodities accounted for 54% of all other expenditures for 
non-SNAP households. Overall, expenditures on other subcommodities were 
similar for SNAP and non-SNAP households with 19 subcommodities in 
common in the top 25 for both groups. The top other subcommodity 
purchased by SNAP households was infant formula/starter solution, 
accounting for almost 10% of the total SNAP household expenditures on 
these items. Subcommodities reflecting drinking water and coffee were 
ranked second and third, respectively. Coffee subcommodities were 
ranked first and third for non-SNAP households with the same water 
subcommodity that was ranked second for SNAP households ranked second 
for non-SNAP households, as well. Interestingly, infant formula/starter 
solution that was ranked first for SNAP households was ranked 14th for 
non-SNAP households.

                        Exhibit 18: Top 25 SNAP Household Other Subcommodity Expenditures
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
         Other Subcommodity                        $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Infant Formula/Starter Solution              1       $54.2           9.60%        14       $45.3           1.70%
Still Water Drinking/Mineral Water           2       $48.8           8.64%         2      $187.7           7.03%
Unflavored Can Coffee                        3       $41.3           7.32%         1      $198.0           7.41%
Isotonic Drinks Single Serve                 4       $30.5           5.40%         4      $119.5           4.47%
Spring Water                                 5       $16.2           2.87%         5       $95.6           3.58%
Traditional Spices                           6       $14.1           2.49%         8       $61.2           2.29%
Bbq Sauce                                    7       $12.3           2.17%        16       $38.6           1.45%
Baby Food--Beginner                          8       $11.7           2.07%        21       $28.1           1.05%
Non-Carb Water Flavor--Drink/Mnr             9       $11.6           2.05%         7       $63.4           2.37%
Catsup                                      10       $11.5           2.03%        15       $41.5           1.55%
Sauce Mixes/Gravy Mixes Dry                 11       $11.5           2.03%        13       $46.7           1.75%
Baby Food Junior/All Brands                 12       $11.2           1.98%        22       $27.5           1.03%
Isotonic Drinks Multi-Pack                  13       $10.8           1.92%         9       $58.1           2.17%
Ice--Crushed/Cubed                          14        $9.3           1.65%        11       $49.9           1.87%
Unflavored Bag Coffee                       15        $8.5           1.50%         3      $137.3           5.14%
Infant Formula Specialty                    16        $8.4           1.49%        71        $9.1           0.34%
Infant Formula Starter Large                17        $8.3           1.46%        30       $22.8           0.85%
Steak & Worchester Sauce                    18        $8.2           1.44%        25       $26.7           1.00%
Unflavored Instant Coffee                   19        $7.6           1.34%        23       $27.3           1.02%
Non-Dairy Milk                              20        $7.1           1.25%         6       $67.7           2.53%
Unsweetened Envelope (Powder Drink          21        $7.0           1.25%        88        $6.2           0.23%
 Mix)
Malted Milk/Syrup/Powders/Eggnog            22        $6.9           1.23%        28       $25.3           0.95%
Still Water Flavored Drink/Mineral          23        $6.3           1.11%        17       $38.1           1.43%
 Water
Infant Formula Toddler                      24        $6.0           1.06%        55       $12.4           0.46%
Mexican Seasoning Mixes                     25        $5.9           1.05%        33       $20.6           0.77%
                                               ----------------------------          ---------------------------
  Sum of Listed Other Expenditures                  $374.8          66.40%              $1,454.7          54.44%
                                               ============================          ===========================
    Total Other Expenditures Among                  $550.7            100%              $2,533.2            100%
     Top 1,000 Subcommodities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: The table lists the top 25 ``other'' subcommodities for SNAP households and the corresponding ranking of
  these subcommodities for non-SNAP households. Columns may not sum to total shown due to rounding.

    All other subcommodities were divided into the following six 
subcategories for additional analysis: condiments; infant formula/baby 
food; seasoning/baking needs; supplements/meal replacements/energy 
drinks; unsweetened beverages; and miscellaneous. Exhibit 19 shows that 
SNAP households spent a notably larger share--about 15 percentage 
points more than non-SNAP households--on infant formulas and baby foods 
in these data. Non-SNAP households spent a larger share on unsweetened 
beverages.
Exhibit 19: Other Expenditures by Subcategory




[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]


 
 
 
          SNAP Households                    Non-SNAP Households
 

          Source: Foods Typically Purchased by SNAP Households, IMPAQ 
        International, LLC, 2016.
Chapter 5. Conclusion
    IMPAQ analyzed point-of-sale transaction data from January 1, 2011 
through December 31, 2011 from a leading grocery retailer to understand 
what food items are typically purchased by SNAP households and how 
these purchases compare to those made by non-SNAP households. The 
majority of stores from which the data came would be classified as 
grocery stores, supermarkets, and combination food and drug stores per 
FNS Retailer Policy and Management Division food retailer 
definitions.\39\ Expenditures on SNAP-eligible food items were examined 
at four levels: by USDA Food Pattern categories, summary categories, 
commodities, and subcommodities, as shown in Exhibit 20.
---------------------------------------------------------------------------
    \39\ Stores that opened or closed during 2011 were not included in 
these analyses.
---------------------------------------------------------------------------
    Overall, the findings from this study indicate that SNAP households 
and non-SNAP households purchased similar foods in the retail outlets 
in these data. The findings hold true after assessing food expenditure 
patterns of SNAP and non-SNAP households using multiple categorization 
methods. Both groups of households spent about 40 of every dollar of 
food expenditures on basic items such as meat, fruits, vegetables, 
milk, eggs, and bread. Another 20 out of every dollar was spent on 
sweetened beverages, desserts, salty snacks, candy and sugar. The 
remaining 40 were spent on a variety of items such as cereal, prepared 
foods, dairy products, rice, and beans.

    Exhibit 20: SNAP and Non-SNAP Household Food Expenditure Patterns
------------------------------------------------------------------------
        Finding             SNAP Households        Non-SNAP  Households
------------------------------------------------------------------------
Total annual            $6.7 billion             $32.3 billion
 expenditures on SNAP-
 eligible foods in
 dataset
Percentage of all       12%                      88%
 transactions by all
 households
Percentage of total     17%                      83%
 annual expenditures
 by all households
Top 1,000 (of 1,792)    99%                      98%
 subcommodity
 expenditures as a
 percentage of all
 expenditures
Top 100 subcommodity    51%                      46%
 expenditures as a
 percentage of all
 expenditures
Top 25 subcommodity     25%                      21%
 expenditures as a
 percentage of all
 expenditures
Top 25 commodity (of    45%                      41%
 238) expenditures as
 a percentage of all
 expenditures
Top 10 summary          Meat, Poultry and        Meat, Poultry and
 categories (of 30) by   Seafood                  Seafood
 expenditure
                        Sweetened Beverages      Vegetables
                        Vegetables               High-fat Dairy/Cheese
                        Frozen Prepared Foods    Fruits
                        Prepared Desserts        Sweetened Beverages
                        High-fat Dairy/Cheese    Prepared Desserts
                        Bread and Crackers       Bread and Crackers
                        Fruits                   Frozen Prepared Foods
                        Milk                     Milk
                        Salty Snacks             Salty Snacks
Top 10 commodities (of  Soft Drinks              Fluid Milk Products
 238) by expenditure
                        Fluid Milk Products      Soft Drinks
                        Beef Grinds              Cheese
                        Bag Snacks               Baked Breads
                        Cheese                   Bag Snacks
                        Baked Breads             Beef Grinds
                        Cold Cereal              Cold Cereal
                        Chicken Fresh            Candy--Packaged
                        Frozen Handhelds and     Coffee and Creamers
                         Snacks
                        Lunchmeat                Ice Cream, Ice Milk,
                                                  and Sherbets
Top 10 subcommodities   Fluid Milk/White Only    Fluid Milk/White Only
 (of 1,792) by
 expenditure
                        Soft Drinks 12-18 pack   Soft Drinks 12-18 pack
                        Lean Beef                Shredded Cheese
                        Kids' Cereal             Chicken Breast--
                                                  Boneless
                        Shredded Cheese          Frozen Premium
                                                  Nutritional Meals
                        2-Liter Soft Drink       Pure Orange Juice--
                                                  Dairy Case
                        Potato Chips             Lean Beef
                        Primal Beef              Potato Chips
                        Lunchmeat--Deli fresh    Large Eggs
                        Infant Formula/Starter   Bananas
                         Solution
------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ
  International, LLC, 2016.
* All SNAP totals represent purchases by SNAP households in the dataset,
  not SNAP dollars.
In summary, after assessing food expenditure patterns of SNAP households
  and non-SNAP households using multiple categorization methods, both
  household types made similar food expenditures in 2011 from the retail
  outlets included in these data.

Appendix A: Top Purchases by Expenditure for SNAP and Non-SNAP 
        Households

                                          Exhibit A-1: All Commodities
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
              Commodity                            $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Soft drinks                                  1      $357.7           5.44%         2    $1,263.3           4.01%
Fluid milk products                          2      $253.7           3.85%         1    $1,270.3           4.03%
Beef: grinds                                 3      $201.0           3.05%         6      $621.1           1.97%
Bag snacks                                   4      $199.3           3.03%         5      $793.9           2.52%
Cheese                                       5      $186.4           2.83%         3      $948.9           3.01%
Baked breads                                 6      $163.7           2.49%         4      $874.8           2.78%
Cold cereal                                  7      $139.2           2.12%         7      $583.9           1.85%
Chicken fresh                                8      $121.4           1.85%        11      $477.8           1.52%
Frozen handhelds & snacks                    9      $101.5           1.54%        47      $214.6           0.68%
Lunchmeat                                   10       $99.4           1.51%        17      $386.1           1.23%
Candy--packaged                             11       $96.2           1.46%         8      $527.7           1.67%
Infant formula                              12       $95.7           1.45%        80      $124.8           0.40%
Frozen pizza                                13       $90.2           1.37%        23      $305.7           0.97%
Refrigerated juices/drinks                  14       $88.5           1.35%        14      $412.8           1.31%
Ice cream ice milk & sherbets               15       $86.0           1.31%        10      $481.8           1.53%
Coffee & creamers                           16       $82.3           1.25%         9      $519.4           1.65%
Cookies                                     17       $78.2           1.19%        16      $408.3           1.30%
Water--(sparkling & still)                  18       $77.0           1.17%        18      $379.2           1.20%
Shelf stable juice                          19       $73.1           1.11%        28      $282.2           0.90%
Eggs/muffins/potatoes                       20       $72.0           1.09%        20      $358.7           1.14%
Frozen ss premium meals                     21       $68.6           1.04%        12      $447.1           1.42%
Cakes                                       22       $68.2           1.04%        38      $240.9           0.76%
Bacon                                       23       $66.1           1.00%        27      $283.2           0.90%
Traditional Mexican foods                   24       $62.6           0.95%        25      $286.9           0.91%
Yogurt                                      25       $59.9           0.91%        13      $442.3           1.40%
Salad dressing & sandwich spreads           26       $59.7           0.91%        30      $280.9           0.89%
Dinner sausage                              27       $59.3           0.90%        46      $222.6           0.71%
Frozen prepared chicken                     28       $58.6           0.89%        74      $136.4           0.43%
Baked sweet goods                           29       $57.5           0.87%        62      $159.6           0.51%
Beef loins                                  30       $56.3           0.86%        31      $280.3           0.89%
Chicken frozen                              31       $54.8           0.83%        85      $123.0           0.39%
Deli meat: bulk                             32       $54.6           0.83%        15      $411.0           1.30%
Frozen multi serve                          33       $53.0           0.81%        54      $183.5           0.58%
Dinner mixes--dry                           34       $51.8           0.79%        72      $140.3           0.45%
Frozen breakfast foods                      35       $51.3           0.78%        55      $180.9           0.57%
Crackers & misc baked food                  36       $50.9           0.77%        21      $323.7           1.03%
Frozen novelties--water ice                 37       $50.7           0.77%        43      $229.7           0.73%
Margarines                                  38       $50.3           0.76%        24      $303.0           0.96%
Condiments & sauces                         39       $49.8           0.76%        52      $187.2           0.59%
Potatoes                                    40       $48.8           0.74%        34      $265.2           0.84%
Frozen vegetable & veg dish                 41       $48.2           0.73%        33      $266.9           0.85%
Hot dogs                                    42       $45.5           0.69%        63      $158.4           0.50%
Can vegetables--shelf stable                43       $45.3           0.69%        50      $191.7           0.61%
Shortening & oil                            44       $44.6           0.68%        57      $174.2           0.55%
Sugars & sweeteners                         45       $43.3           0.66%        60      $162.4           0.52%
Isotonic drinks                             46       $42.8           0.65%        53      $185.3           0.59%
Salad mix                                   47       $42.8           0.65%        22      $319.4           1.01%
Milk by-products                            48       $42.5           0.65%        32      $268.9           0.85%
Pork boneless loin/rib                      49       $41.5           0.63%        58      $168.0           0.53%
Cnv breakfast & wholesome snacks            50       $41.1           0.62%        45      $226.1           0.72%
Frozen ss economy meals                     51       $40.9           0.62%       109       $80.7           0.26%
Refrigerated dough products                 52       $40.5           0.62%        56      $176.6           0.56%
Beef: round                                 53       $40.4           0.61%        75      $134.2           0.43%
Dry bean veg & rice                         54       $39.9           0.61%        59      $166.1           0.53%
Convenient meals                            55       $38.7           0.59%       108       $81.0           0.26%
Tomatoes                                    56       $38.3           0.58%        35      $261.7           0.83%
Candy--checklane                            57       $37.9           0.58%        64      $154.0           0.49%
Berries                                     58       $37.4           0.57%        19      $373.5           1.19%
Grapes                                      59       $36.1           0.55%        39      $235.7           0.75%
Bananas                                     60       $36.1           0.55%        36      $261.4           0.83%
Peanut butter/jelly/jams & honey            61       $36.0           0.55%        42      $231.0           0.73%
Pork thin meats                             62       $35.0           0.53%        93      $106.8           0.34%
Citrus                                      63       $34.3           0.52%        37      $251.7           0.80%
Breakfast sausage                           64       $34.2           0.52%        79      $126.7           0.40%
Dry sauce/gravy/potatoes/stuffing           65       $34.0           0.52%        87      $119.2           0.38%
Salad & dips                                66       $33.9           0.52%        40      $235.3           0.75%
Apples                                      67       $33.7           0.51%        29      $281.7           0.89%
Meat--shelf stable                          68       $33.3           0.51%        91      $109.2           0.35%
Aseptic juice                               69       $33.1           0.50%       112       $78.9           0.25%
Sweet goods                                 70       $32.5           0.49%        66      $152.9           0.49%
Frozen potatoes                             71       $32.2           0.49%        95      $104.5           0.33%
Meat frozen                                 72       $31.9           0.48%       120       $69.9           0.22%
Baby foods                                  73       $30.6           0.46%       121       $67.8           0.22%
Vegetables salad                            74       $30.0           0.46%        44      $228.6           0.73%
Beef: thin meats                            75       $30.0           0.46%        78      $127.7           0.41%
Seafood--shrimp                             76       $29.8           0.45%        84      $123.1           0.39%
Canned soups                                77       $29.7           0.45%        65      $153.6           0.49%
Baking mixes                                78       $28.3           0.43%        69      $148.1           0.47%
Pasta & pizza sauce                         79       $27.6           0.42%        99       $96.7           0.31%
Dry noodles & pasta                         80       $27.5           0.42%        71      $141.5           0.45%
Can seafood--shelf stable                   81       $26.5           0.40%        77      $132.3           0.42%
Rts/micro soup/broth                        82       $26.0           0.40%        48      $200.8           0.64%
Canned pasta & mwv fd-shlf stbl             83       $25.9           0.39%       135       $56.7           0.18%
Smoked hams                                 84       $25.7           0.39%        92      $108.8           0.35%
Nuts                                        85       $25.6           0.39%        41      $234.2           0.74%
Value-added fruit                           86       $25.3           0.38%        70      $146.6           0.47%
Can beans                                   87       $24.0           0.36%        82      $123.3           0.39%
Dry/ramen bouillon                          88       $21.7           0.33%       133       $61.0           0.19%
Powder & crystal drink mix                  89       $21.6           0.33%       119       $75.2           0.24%
Rtd tea/new age juice                       90       $21.5           0.33%       103       $93.8           0.30%
Baking needs                                91       $21.3           0.32%        51      $188.9           0.60%
Can fruit/jar applesauce                    92       $20.9           0.32%        96      $104.0           0.33%
Spices & extracts                           93       $20.4           0.31%        86      $121.9           0.39%
Energy drinks                               94       $20.1           0.30%       102       $94.1           0.30%
Onions                                      95       $20.0           0.30%        81      $123.5           0.39%
Tropical fruit                              96       $19.8           0.30%        61      $160.1           0.51%
Bagels & cream cheese                       97       $19.8           0.30%        83      $123.2           0.39%
Frozen bread/dough                          98       $19.7           0.30%       114       $77.7           0.25%
Rolls                                       99       $18.9           0.29%        88      $113.9           0.36%
Hot cereal                                 100       $18.9           0.29%       100       $96.1           0.30%
Tomato products-shelf stable               101       $18.8           0.29%        90      $112.5           0.36%
Bread                                      102       $18.7           0.28%        49      $194.7           0.62%
Frozen desserts                            103       $18.7           0.28%       107       $82.9           0.26%
Chicken & poultry                          104       $18.7           0.28%       140       $50.3           0.16%
Refrigerated dairy case                    105       $18.6           0.28%        26      $284.7           0.90%
Dry cheese                                 106       $18.5           0.28%       111       $79.1           0.25%
Stone fruit                                107       $18.3           0.28%        73      $138.6           0.44%
Molasses/syrups/pancake mixes              108       $17.9           0.27%       110       $80.6           0.26%
Peppers                                    109       $17.7           0.27%        76      $133.4           0.42%
Fruit snacks                               110       $17.6           0.27%       152       $43.2           0.14%
Vegetables cooking bulk                    111       $17.3           0.26%        68      $150.6           0.48%
Sandwiches                                 112       $16.9           0.26%       124       $67.7           0.21%
Service case meat                          113       $16.8           0.26%        97      $101.4           0.32%
Melons                                     114       $16.7           0.25%        89      $113.2           0.36%
Popcorn                                    115       $15.3           0.23%       117       $76.6           0.24%
Warehouse snacks                           116       $14.7           0.22%       125       $67.1           0.21%
Dry mix desserts                           117       $14.7           0.22%       128       $65.0           0.21%
Single serve fruit/applesauce              118       $14.6           0.22%       127       $65.4           0.21%
Frozen seafood                             119       $13.8           0.21%       155       $41.0           0.13%
Flour & meals                              120       $13.8           0.21%       126       $65.7           0.21%
Pickle/relish/pckld veg & olives           121       $13.5           0.21%       106       $83.1           0.26%
Turkey grinds                              122       $13.1           0.20%       113       $78.0           0.25%
Bulk service case cheese                   123       $12.5           0.19%       104       $87.1           0.28%
Pies                                       124       $12.3           0.19%       123       $67.7           0.21%
Water                                      125       $12.3           0.19%       122       $67.8           0.22%
Sushi                                      126       $11.8           0.18%        94      $104.6           0.33%
Teas                                       127       $11.4           0.17%       116       $76.9           0.24%
Authentic Hispanic foods & products        128       $11.0           0.17%       165       $31.7           0.10%
Cookie/cracker multi-pks                   129       $10.9           0.16%       136       $52.7           0.17%
Carrots                                    130       $10.6           0.16%        98       $97.3           0.31%
Pork shoulder                              131       $10.5           0.16%       164       $32.1           0.10%
Cocoa mixes                                132       $10.4           0.16%       153       $43.0           0.14%
Juices super premium                       133       $10.3           0.16%       130       $63.2           0.20%
Snack meat                                 134       $10.3           0.16%       147       $47.9           0.15%
Seafood--catfish                           135        $9.8           0.15%       191       $17.6           0.06%
Turkey frozen                              136        $9.7           0.15%       138       $51.8           0.16%
Specialty cheese pre pack                  137        $9.6           0.15%        67      $152.4           0.48%
Smoked pork                                138        $9.4           0.14%       156       $39.2           0.12%
Frozen ice                                 139        $9.3           0.14%       142       $49.9           0.16%
Seafood--crab                              140        $9.2           0.14%       182       $24.5           0.08%
Mushrooms                                  141        $9.1           0.14%       105       $85.7           0.27%
Value-added vegetables                     142        $9.0           0.14%       115       $77.0           0.24%
Seafood--value-added seafood               143        $8.9           0.14%       178       $25.6           0.08%
Sweet goods & snacks                       144        $8.6           0.13%       146       $48.3           0.15%
Meat snacks                                145        $8.5           0.13%       170       $29.3           0.09%
Single serve/vending--salty snacks         146        $8.4           0.13%       197       $15.8           0.05%
Traditional Asian foods                    147        $8.3           0.13%       134       $59.8           0.19%
Frozen juice and smoothies                 148        $7.7           0.12%       150       $44.9           0.14%
Broccoli/cauliflower                       149        $7.4           0.11%       118       $76.5           0.24%
Beef: rib                                  150        $7.3           0.11%       151       $43.3           0.14%
Refrigerated desserts                      151        $7.0           0.11%       143       $49.5           0.16%
Croutons/bread stick & salad top           152        $6.9           0.11%       171       $29.1           0.09%
Dietary aid product/med liq nutr           153        $6.8           0.10%       132       $62.9           0.20%
Dressings/dips                             154        $6.6           0.10%       139       $51.7           0.16%
Party tray                                 155        $6.6           0.10%       154       $42.6           0.14%
Corn                                       156        $6.5           0.10%       149       $45.3           0.14%
Canned & dry milk                          157        $6.1           0.09%       163       $33.1           0.10%
Fitness & diet                             158        $5.8           0.09%       101       $95.8           0.30%
Juice                                      159        $5.8           0.09%       148       $46.2           0.15%
Single serve sweet goods                   160        $5.7           0.09%       196       $16.2           0.05%
Refrigerated hispanic grocery              161        $5.7           0.09%       177       $26.5           0.08%
Enhancements (Pickles/Spreads)             162        $5.6           0.08%       174       $27.3           0.09%
Convenience/snacking                       163        $5.5           0.08%       173       $28.5           0.09%
Dried fruit                                164        $5.4           0.08%       137       $52.6           0.17%
Seafood--salmon-farm raised                165        $5.0           0.08%       144       $48.8           0.15%
Frozen whipped topping                     166        $5.0           0.08%       167       $30.9           0.10%
Deli meat: presliced                       167        $4.9           0.07%       129       $63.8           0.20%
Herbs/garlic                               168        $4.8           0.07%       141       $50.0           0.16%
Seafood--party trays                       169        $4.8           0.07%       181       $24.8           0.08%
Salad bar                                  170        $4.5           0.07%       188       $18.2           0.06%
Seafood--salmon--wild caught               171        $4.5           0.07%       158       $36.7           0.12%
Frozen fruits                              172        $4.3           0.07%       145       $48.6           0.15%
Single serve/vending--cookie/cracker       173        $4.1           0.06%       211        $9.1           0.03%
Chicken specialty/natural                  174        $3.8           0.06%       166       $31.5           0.10%
Cereals                                    175        $3.8           0.06%       131       $63.0           0.20%
Pork offal                                 176        $3.5           0.05%       232        $4.2           0.01%
Pears                                      177        $3.5           0.05%       162       $33.6           0.11%
Frozen meatless                            178        $3.3           0.05%       169       $30.0           0.10%
Seafood--tilapia                           179        $3.2           0.05%       194       $16.4           0.05%
Non-dairy/dairy aseptic                    180        $3.1           0.05%       168       $30.5           0.10%
Refrigerated italian                       181        $2.9           0.04%       159       $36.6           0.12%
Rice cakes                                 182        $2.8           0.04%       184       $22.4           0.07%
Vinegar & cooking wines                    183        $2.8           0.04%       176       $27.2           0.09%
Seafood--salad/dip/sce/cond                184        $2.8           0.04%       223        $6.2           0.02%
Refrigerated vegetarian                    185        $2.8           0.04%       180       $24.8           0.08%
Cake decor                                 186        $2.7           0.04%       199       $15.4           0.05%
Frozen pasta                               187        $2.6           0.04%       193       $16.9           0.05%
Syrups toppings & cones                    188        $2.6           0.04%       202       $14.1           0.04%
Snacks                                     189        $2.6           0.04%       157       $37.6           0.12%
Trail mix & snacks                         190        $2.5           0.04%       189       $18.1           0.06%
Snack                                      191        $2.5           0.04%       160       $35.6           0.11%
Prepared/pdgd foods                        192        $2.3           0.04%       161       $34.1           0.11%
Turkey fresh                               193        $2.3           0.04%       192       $17.0           0.05%
Condiments                                 194        $2.3           0.03%       175       $27.2           0.09%
Seafood--fin fish other                    195        $2.2           0.03%       225        $5.8           0.02%
Seafood--lobster                           196        $2.2           0.03%       204       $13.0           0.04%
Pre-slice service case cheese              197        $2.1           0.03%       172       $28.6           0.09%
Spices/jarred garlic                       198        $2.1           0.03%       205       $12.4           0.04%
Vegetables cooking packaged                199        $2.0           0.03%       187       $18.3           0.06%
Mixers                                     200        $1.9           0.03%       195       $16.4           0.05%
Poultry other                              201        $1.8           0.03%       219        $6.7           0.02%
Pork bone in loin/rib                      202        $1.8           0.03%       214        $7.6           0.02%
Turkey offal                               203        $1.6           0.02%       235        $2.0           0.01%
Organics fruit & vegetables                204        $1.6           0.02%       185       $22.2           0.07%
Frozen ethnic                              205        $1.6           0.02%       218        $6.7           0.02%
Lamb                                       206        $1.6           0.02%       207       $11.4           0.04%
Seasonal                                   207        $1.5           0.02%       209       $10.3           0.03%
Chicken offal                              208        $1.5           0.02%       230        $4.3           0.01%
Turkey smoked                              209        $1.5           0.02%       234        $2.5           0.01%
Seafood--cod                               210        $1.5           0.02%       206       $12.0           0.04%
Frozen meat alternatives                   211        $1.5           0.02%       203       $13.6           0.04%
Soup                                       212        $1.4           0.02%       179       $25.4           0.08%
Authentic central american fds             213        $1.4           0.02%       227        $5.5           0.02%
Cereal bars                                214        $1.4           0.02%       183       $23.6           0.07%
Frozen entrees                             215        $1.4           0.02%       186       $21.5           0.07%
Authentic asian foods                      216        $1.4           0.02%       208       $11.3           0.04%
Bulk food                                  217        $1.3           0.02%       190       $18.0           0.06%
Baking                                     218        $1.2           0.02%       201       $14.6           0.05%
Random weight meat products                219        $1.1           0.02%       233        $4.0           0.01%
Processed (dry mixes/squeezed fruit)       220        $1.0           0.02%       222        $6.2           0.02%
Mediterranean bar                          221        $1.0           0.02%       198       $15.5           0.05%
Chicken grinds                             222        $0.9           0.01%       217        $6.9           0.02%
Chilled ready meals                        223        $0.9           0.01%       231        $4.2           0.01%
Dry tea/coffee/coco mixes                  224        $0.9           0.01%       210        $9.2           0.03%
Crackers                                   225        $0.8           0.01%       200       $14.6           0.05%
Seafood--trout                             226        $0.7           0.01%       224        $6.0           0.02%
Beverages                                  227        $0.7           0.01%       215        $7.6           0.02%
Seafood--scallops                          228        $0.6           0.01%       221        $6.4           0.02%
Baby food                                  229        $0.6           0.01%       226        $5.5           0.02%
Deli specialties (retail pk)               230        $0.6           0.01%       228        $5.3           0.02%
Buffalo                                    231        $0.5           0.01%       213        $8.3           0.03%
Seafood--smoked seafood                    232        $0.5           0.01%       212        $8.4           0.03%
Pork grinds                                233        $0.5           0.01%       229        $4.3           0.01%
Authentic italian foods                    234        $0.5           0.01%       216        $7.4           0.02%
Bakery party trays                         235        $0.4           0.01%       236        $1.9           0.01%
Candy                                      236        $0.4           0.01%       220        $6.5           0.02%
Authentic caribbean foods                  237        $0.4           0.01%       238        $1.1           0.00%
Seafood--shellfish other                   238        $0.4           0.01%       237        $1.3           0.00%
                                               ----------------------------          ---------------------------
  Totals                                          $6,580.5            100%             $31,513.8            100%
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.


                    Exhibit A-2: Top 1,000 Subcommodities by Expenditures of SNAP Households
----------------------------------------------------------------------------------------------------------------
                                          SNAP Household  Expenditures        Non-SNAP Household  Expenditures
                                     ---------------------------------------------------------------------------
    Commodity        Subcommodity                  $ in          % of                    $ in          % of
                                        Rank     Millions    Expenditures     Rank     Millions    Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk        Milk/White Only            1      $191.1           2.90%         1      $853.8           2.71%
 Products
Soft Drinks       Soft Drinks 12/18          2      $164.6           2.50%         2      $601.2           1.91%
                   & 15pk Can Car
Beef: Grinds      Lean [Beef]                3      $112.4           1.71%         7      $257.9           0.82%
Cold Cereal       Kids Cereal                4       $78.1           1.19%        20      $186.4           0.59%
Cheese            Shredded Cheese            5       $74.7           1.14%         3      $342.0           1.09%
Soft Drinks       Sft Drnk 2 Liter           6       $70.9           1.08%        12      $230.1           0.73%
                   Btl Carb Incl
Bag Snacks        Potato Chips               7       $64.4           0.98%         8      $253.2           0.80%
Beef: Grinds      Primal [Beef]              8       $62.4           0.95%        14      $219.8           0.70%
Lunchmeat         Lunchmeat--Deli            9       $55.8           0.85%        11      $242.6           0.77%
                   Fresh
Infant Formula    Infant Formula            10       $54.2           0.82%       190       $45.3           0.14%
                   Starter/Solution
Eggs/Muffins/     Eggs--Large               11       $52.1           0.79%         9      $251.6           0.80%
 Potatoes
Chicken Fresh     Chicken Breast            12       $49.6           0.75%         4      $292.9           0.93%
                   Boneless
Water--(Sparklin  Still Water               13       $48.8           0.74%        19      $187.7           0.60%
 g & Still)        Drnking/Mnrl
                   Water
Baked Breads      Mainstream White          14       $48.0           0.73%        39      $136.8           0.43%
                   Bread
Bag Snacks        Tortilla/Nacho            15       $47.4           0.72%        17      $209.0           0.66%
                   Chips
Frozen Handhelds  Snacks/Appetizers         16       $44.6           0.68%        65      $100.5           0.32%
 & Snacks
Cheese            American Single           17       $44.1           0.67%        41      $136.6           0.43%
                   Cheese
Frzn Ss Premium   Fz Ss Prem                18       $43.8           0.67%        24      $175.4           0.56%
 Meals             Traditional Meals
Refrgratd Juices/ Dairy Case 100%           19       $43.5           0.66%         6      $269.0           0.85%
 Drinks            Pure Juice--O
Baked Sweet       Snack Cake--Multi         20       $41.6           0.63%        63      $101.7           0.32%
 Goods             Pack
Pork Boneless     Enhanced [Pork            21       $41.5           0.63%        27      $168.0           0.53%
 Loin/Rib          Boneless Loin/
                   Rib]
Coffee &          Unflavored Can            22       $41.3           0.63%        18      $198.0           0.63%
 Creamers          Coffee
Frzn Ss Economy   Fz Ss Economy             23       $40.9           0.62%        81       $80.7           0.26%
 Meals             Meals All
Bacon             Bacon--Trad 16oz          24       $40.7           0.62%        29      $157.6           0.50%
                   Or Less
Soft Drinks       Soft Drinks 20pk &        25       $39.7           0.60%        60      $106.4           0.34%
                   24pk Can Carb
Frozen Pizza      Pizza/Premium             26       $39.7           0.60%        32      $153.3           0.49%
Baked Breads      Mainstream Variety        27       $38.4           0.58%        26      $173.2           0.55%
                   Breads
Sugars &          Sugar                     28       $36.9           0.56%        55      $112.7           0.36%
 Sweeteners
Cold Cereal       All Family Cereal         29       $36.2           0.55%        16      $214.9           0.68%
Frozen Handhelds  Sandwiches &              30       $35.9           0.54%        91       $73.6           0.23%
 & Snacks          Handhelds
Potatoes          Potatoes Russet           31       $35.8           0.54%        30      $154.5           0.49%
                   (Bulk & Bag)
Cheese            Natural Cheese            32       $35.3           0.54%        15      $216.1           0.69%
                   Chunks
Pork Thin Meats   Ribs [Pork]               33       $35.0           0.53%        59      $106.8           0.34%
Convenient Meals  Convenient Meals--        34       $34.2           0.52%        96       $69.7           0.22%
                   Kids Meal C
Bananas           Bananas                   35       $34.2           0.52%        10      $242.7           0.77%
Soft Drinks       Sft Drnk Mlt-Pk           36       $34.0           0.52%        25      $173.6           0.55%
                   Btl Carb (Excp)
Ice Cream Ice     Premium [Ice Cream        37       $31.2           0.47%        13      $226.0           0.72%
 Milk & Sherbets   & Sherbert]
Isotonic Drinks   Isotonic Drinks           38       $30.5           0.46%        47      $119.5           0.38%
                   Single Serve
Chicken Frozen    Frzn Chicken--Wht         39       $30.0           0.46%        66       $99.8           0.32%
                   Meat
Canned Soups      Condensed Soup            40       $29.7           0.45%        31      $153.6           0.49%
Salad Dresing &   Pourable Salad            41       $29.0           0.44%        37      $139.4           0.44%
 Sandwich          Dressings
 Spreads
Beef: Loins       Choice Beef               42       $28.4           0.43%        40      $136.6           0.43%
Beef: Loins       Select Beef               43       $27.9           0.42%        36      $143.7           0.46%
Soft Drinks       Sft Drnk Sngl Srv         44       $27.8           0.42%        94       $71.4           0.23%
                   Btl Carb (Ex)
Frzn Multi Serve  Fz Family Style           45       $27.6           0.42%        77       $83.5           0.26%
                   Entrees
Salad Dresing &   Mayonnaise &              46       $27.3           0.41%        48      $119.1           0.38%
 Sandwich          Whipped Dressing
 Spreads
Frozen Vegetable  Fz Bag Vegetables--       47       $25.7           0.39%        42      $131.9           0.42%
 & Veg Dish        Plain
Ice Cream Ice     Traditional [Ice          48       $25.6           0.39%        49      $118.7           0.38%
 Milk & Sherbets   Cream & Sherbert]
Hot Dogs          Hot Dogs--Base            49       $25.1           0.38%       138       $56.8           0.18%
                   Meat
Cold Cereal       Adult Cereal              50       $24.9           0.38%        21      $182.6           0.58%
Frzn Ss Premium   Fz Ss Prem                51       $24.7           0.38%         5      $271.6           0.86%
 Meals             Nutritional Meals
Dinner Mixes-Dry  Macaroni & Cheese         52       $24.3           0.37%       125       $59.7           0.19%
                   Dnrs
Aseptic Juice     Aseptic Pack Juice        53       $24.2           0.37%       134       $57.1           0.18%
                   And Drinks
Fluid Milk        Refrigerated              54       $24.1           0.37%        34      $147.2           0.47%
 Products          Coffee Creamers
Beef: Round       Choice Beef               55       $24.0           0.37%        92       $72.5           0.23%
Traditional       Mexican Soft              56       $23.7           0.36%        54      $113.1           0.36%
 Mexican Foods     Tortillas And
                   Wraps
Berries           Strawberries              57       $23.5           0.36%        22      $178.4           0.57%
Margarines        Margarine: Tubs           58       $23.4           0.36%        64      $100.9           0.32%
                   And Bowls
Pasta & Pizza     Mainstream [Pasta         59       $23.0           0.35%        80       $81.0           0.26%
 Sauce             & Pizza Sauce]
Chicken Fresh     Chicken Wings             60       $22.2           0.34%       300       $28.6           0.09%
Canned Pasta &    Can Pasta                 61       $22.2           0.34%       179       $47.7           0.15%
 Mwv Fd-Shlf
 Stbl
Chicken Frozen    Frzn Chicken--            62       $22.2           0.34%       452       $17.4           0.06%
                   Wings
Lunchmeat         Lunchmeat--Bologna/       63       $21.8           0.33%       121       $60.9           0.19%
                   Sausage
Bag Snacks        Mult Pk Bag Snacks        64       $21.6           0.33%       199       $43.4           0.14%
Candy--Packaged   Candy Bags-               65       $21.5           0.33%        33      $147.5           0.47%
                   Chocolate
Sweet Goods       Sw Gds: Donuts            66       $21.3           0.32%        78       $82.3           0.26%
Can Seafood--     Tuna                      67       $21.1           0.32%        57      $109.9           0.35%
 Shelf Stable
Shortening & Oil  Vegetable Oil             68       $20.5           0.31%       246       $35.4           0.11%
Frozen Potatoes   Frzn French Fries         69       $20.5           0.31%       163       $50.3           0.16%
Peanut Butter/    Peanut Butter             70       $20.4           0.31%        43      $127.8           0.41%
 Jelly/Jams &
 Honey
Frozen Pizza      Pizza/Economy             71       $19.8           0.30%       192       $45.1           0.14%
Margarines        Butter                    72       $19.6           0.30%        23      $175.6           0.56%
Deli Meat: Bulk   Meat: Turkey Bulk         73       $19.3           0.29%        28      $159.6           0.51%
Frozen Breakfast  Frzn Breakfast            74       $19.1           0.29%       142       $55.7           0.18%
 Foods             Sandwiches
Meat Frozen       Frzn Meat--Beef           75       $19.0           0.29%       185       $46.3           0.15%
Frzn Multi Serve  Fz Skillet Meals          76       $18.8           0.29%        83       $79.3           0.25%
Frzn Prepared     Value Forms/18oz          77       $18.6           0.28%       209       $42.6           0.14%
 Chicken           And Larger
                   [Chicken]
Cakes             Cakes: Birthday/          78       $18.6           0.28%       164       $50.3           0.16%
                   Celebration
Cookies           Sandwich Cookies          79       $18.0           0.27%        93       $71.8           0.23%
Frozen Pizza      Pizza/Traditional         80       $17.9           0.27%       111       $64.1           0.20%
Fruit Snacks      Fruit Snacks              81       $17.6           0.27%       202       $43.2           0.14%
Rts/Micro Soup/   Soup: Chunky/             82       $17.6           0.27%        46      $119.9           0.38%
 Broth Rts         Homestyle
Milk By-Products  Sour Creams               83       $17.5           0.27%        70       $95.2           0.30%
Frozen Breakfast  Waffles/Pancakes/         84       $17.3           0.26%        90       $77.4           0.25%
 Foods             French Toast
Chicken Fresh     Chicken Drums             85       $17.3           0.26%       270       $31.5           0.10%
Bagels & Cream    Cream Cheese              86       $17.2           0.26%        51      $115.5           0.37%
 Cheese
Beef: Grinds      Angus [Beef]              87       $17.1           0.26%        61      $103.8           0.33%
Bag Snacks        Bagged Cheese             88       $17.1           0.26%       157       $52.0           0.16%
                   Snacks
Bag Snacks        Salsa & Dips              89       $17.1           0.26%       135       $57.0           0.18%
Sandwiches        Sandwiches--(Cold)        90       $16.9           0.26%       106       $67.7           0.21%
Dry/Ramen         Ramen Noodles/            91       $16.7           0.25%       304       $28.1           0.09%
 Bouillon          Ramen Cups
Crackers & Misc   Cheese Crackers           92       $16.5           0.25%        72       $90.2           0.29%
 Baked Food
Dinner Sausage    Dnr Sausage--Links        93       $16.4           0.25%       233       $37.6           0.12%
                   Pork Ckd
Candy--Checklane  Candy Bars                94       $16.3           0.25%       146       $54.9           0.17%
                   (Singles)
Baked Breads      Hamburger Buns            95       $16.2           0.25%        95       $70.2           0.22%
Baked Breads      Hot Dog Buns              96       $16.2           0.25%       117       $62.2           0.20%
Water--(Sparklin  Spring Water              97       $16.2           0.25%        69       $95.6           0.30%
 g & Still)
Refrgratd Juices/ Dairy Case Juice          98       $16.0           0.24%       177       $48.0           0.15%
 Drinks            Drnk Under 10 oz
Fluid Milk        Flavored Milk             99       $16.0           0.24%       128       $59.4           0.19%
 Products
Baked Sweet       Sweet Goods--Full        100       $15.8           0.24%       133       $57.9           0.18%
 Goods             Size
Grapes            Grapes Red               101       $15.8           0.24%        45      $121.7           0.39%
Candy--Packaged   Candy Bars (Multi        102       $15.6           0.24%        97       $69.6           0.22%
                   Pack)
Grapes            Grapes White             103       $15.5           0.23%        76       $84.9           0.27%
Cookies           Tray Pack/Choc           104       $15.3           0.23%       153       $53.9           0.17%
                   Chip Cookies
Deli Meat: Bulk   Meat: Ham Bulk           105       $15.3           0.23%        50      $115.9           0.37%
Cheese            String Cheese            106       $15.1           0.23%        67       $99.0           0.31%
Breakfast         Bkfst Sausage--          107       $15.1           0.23%       119       $61.4           0.19%
 Sausage           Fresh Rolls
Seafood--Shrimp   Shrimp--Raw              108       $15.0           0.23%        99       $69.0           0.22%
Seafood--Shrimp   Shrimp--Cooked           109       $14.8           0.22%       152       $54.0           0.17%
Refrgrated Dough  Refrigerated             110       $14.7           0.22%       191       $45.2           0.14%
 Products          Biscuits
Crackers & Misc   Butter Spray             111       $14.6           0.22%       101       $68.7           0.22%
 Baked Food        Cracker
Frozen            Sticks/Enrobed           112       $14.2           0.22%       126       $59.7           0.19%
 Novelties--Wate   [Frozen
 r Ice             Novelties]
Spices &          Traditional Spices       113       $14.1           0.21%       120       $61.2           0.19%
 Extracts
Frozen            Water Ice [Frozen        114       $14.0           0.21%       160       $50.6           0.16%
 Novelties--Wate   Novelties]
 r Ice
Yogurt            Yogurt/Kids              115       $14.0           0.21%       212       $42.4           0.13%
Cnv Breakfast &   Toaster Pastries         116       $14.0           0.21%       180       $47.6           0.15%
 Wholesome Snks
Dry Bean Veg &    Rice Side Dish           117       $14.0           0.21%       184       $46.7           0.15%
 Rice              Mixes Dry
Ice Cream Ice     Pails [Ice Cream &       118       $13.9           0.21%       250       $35.1           0.11%
 Milk & Sherbets   Sherbert]
Milk By-Products  Cottage Cheese           119       $13.9           0.21%        58      $108.8           0.35%
Rtd Tea/New Age   Tea Sweetened            120       $13.9           0.21%       102       $68.7           0.22%
 Juice
Can Beans         Prepared Beans--         121       $13.4           0.20%       145       $55.3           0.18%
                   Baked W/Pork
Cheese            Natural Cheese           122       $13.4           0.20%        53      $113.2           0.36%
                   Slices
Tropical Fruit    Avocado                  123       $13.4           0.20%        56      $112.6           0.36%
Meat--Shelf       Chili: Canned            124       $13.3           0.20%       206       $42.8           0.14%
 Stable
Shelf Stable      Apple Juice &            125       $13.3           0.20%       187       $45.8           0.15%
 Juice             Cider (Over 50%)
Value-Added       Instore Cut Fruit        126       $13.2           0.20%        74       $85.8           0.27%
 Fruit
Candy--Checklane  Chewing Gum              127       $13.2           0.20%       103       $68.3           0.22%
Salad Mix         Blends [Salad Mix]       128       $13.1           0.20%        44      $124.0           0.39%
Popcorn           Popcorn--Microwave       129       $13.1           0.20%       114       $63.4           0.20%
Turkey Grinds     Ground Turkey            130       $13.1           0.20%        87       $78.0           0.25%
Dinner Sausage    Dnr Sausage--Links       131       $13.0           0.20%       132       $58.0           0.18%
                   Fresh
Dinner Mixes-Dry  Skillet Dinners          132       $13.0           0.20%       332       $25.8           0.08%
Dry Noodles &     Long Cut Pasta           133       $13.0           0.20%       122       $60.4           0.19%
 Pasta
Chicken Fresh     Whole Chicken            134       $12.9           0.20%       136       $56.9           0.18%
                   (Roasters/Fryer)
Frozen Pizza      Pizza/Single Serve/      135       $12.8           0.19%       203       $43.2           0.14%
                   Microwave
Can Vegetables--  Green Beans: Fs/         136       $12.8           0.19%       155       $53.1           0.17%
 Shelf Stable      Whl/Cut
Cnv Breakfast &   Granola Bars             137       $12.8           0.19%        73       $88.9           0.28%
 Wholesome Snks
Candy--Packaged   Candy Bags-Non           138       $12.6           0.19%       147       $54.9           0.17%
                   Chocolate
Citrus            Oranges Navels All       139       $12.6           0.19%        84       $79.3           0.25%
Baked Breads      Premium Bread            140       $12.3           0.19%        35      $144.7           0.46%
Dry Sce/Gravy/    Potatoes: Dry            141       $12.3           0.19%       262       $32.3           0.10%
 Potatoes/
 Stuffng
Condiments &      Bbq Sauce                142       $12.3           0.19%       226       $38.6           0.12%
 Sauces
Chicken Fresh     Chicken Thighs           143       $12.2           0.19%       165       $50.0           0.16%
Dinner Sausage    Dnr Sausage--Pork        144       $12.1           0.18%       227       $38.2           0.12%
                   Rope Ckd
Can Vegetables--  Corn                     145       $12.1           0.18%       197       $44.0           0.14%
 Shelf Stable
Bacon             Bacon--Trad              146       $12.0           0.18%       193       $44.6           0.14%
                   Greater Than 16oz
Ice Cream Ice     Super Premium            147       $11.8           0.18%        71       $91.1           0.29%
 Milk & Sherbets   Pints [Ice Cream
                   & Sherbert]
Baby Foods        Baby Food--              148       $11.7           0.18%       303       $28.1           0.09%
                   Beginner
Molasses/Syrups/  Molasses & Syrups        149       $11.7           0.18%       130       $58.7           0.19%
 Pancake Mixes
Water             Non-Carb Water           150       $11.6           0.18%       115       $63.4           0.20%
                   Flvr--Drnk/Mnr
Vegetables Salad  Head Lettuce             151       $11.6           0.18%       143       $55.5           0.18%
Condiments &      Catsup                   152       $11.5           0.17%       216       $41.5           0.13%
 Sauces
Dry Sce/Gravy/    Sauce Mixes/Gravy        153       $11.5           0.17%       183       $46.7           0.15%
 Potatoes/         Mixes Dry
 Stuffng
Beef: Thin Meats  Soup/Stew                154       $11.2           0.17%       195       $44.1           0.14%
Baby Foods        Baby Food Junior/        155       $11.2           0.17%       311       $27.5           0.09%
                   All Brands
Frzn Prepared     Whole Muscle             156       $11.1           0.17%       285       $29.9           0.09%
 Chicken           Breaded/18oz
Cakes             Cakes: Cupcakes          157       $11.1           0.17%       247       $35.3           0.11%
Refrgratd Juices/ Dairy Case Citrus        158       $11.0           0.17%       254       $34.4           0.11%
 Drinks            Pnch/Oj Subs
Yogurt            Yogurt/Ss Regular        159       $11.0           0.17%       100       $69.0           0.22%
Dry Cheese        Loaf Cheese              160       $10.9           0.17%       229       $38.1           0.12%
Frozen Handhelds  Corn Dogs                161       $10.9           0.17%       401       $20.6           0.07%
 & Snacks
Cnv Breakfast &   Cereal Bars              162       $10.9           0.17%        86       $78.4           0.25%
 Wholesome Snks
Isotonic Drinks   Isotonic Drinks          163       $10.8           0.16%       131       $58.1           0.18%
                   Multi-Pack
Cookies           Cookies: Regular         164       $10.8           0.16%       127       $59.6           0.19%
Shelf Stable      Fruit Drinks:            165       $10.6           0.16%       617       $10.9           0.03%
 Juice             Canned & Glass
Single Serve      Fruit Cup                166       $10.6           0.16%       207       $42.7           0.14%
 Fruit/
 Applesauce
Can Beans         Variety Beans--          167       $10.5           0.16%       104       $68.0           0.22%
                   Kidney/Pinto
Frozen Vegetable  Frzn Steamable           168       $10.5           0.16%        79       $81.4           0.26%
 & Veg Dish        Vegetables
Coffee &          Non Dairy Creamer        169       $10.5           0.16%       244       $35.4           0.11%
 Creamers
Beef: Thin Meats  Cubed Meats [Beef]       170       $10.5           0.16%       286       $29.8           0.09%
Hot Dogs          Hot Dogs--Base           171       $10.3           0.16%       171       $49.4           0.16%
                   Beef
Yogurt            Yogurt/Ss Light          172       $10.2           0.16%        62      $103.1           0.33%
Traditional       Mexican Sauces And       173       $10.2           0.16%       116       $62.3           0.20%
 Mexican Foods     Picante Sauce
Frozen Handhelds  Burritos                 174       $10.2           0.15%       406       $20.0           0.06%
 & Snacks
Eggs/Muffins/     Eggs--Medium             175       $10.1           0.15%       394       $21.0           0.07%
 Potatoes
Dry Noodles &     Short Cut Pasta          176        $9.9           0.15%       140       $56.2           0.18%
 Pasta
Dinner Mixes-Dry  Microwave Dinners        177        $9.8           0.15%       220       $39.9           0.13%
Cakes             Cakes: Layers            178        $9.8           0.15%       228       $38.2           0.12%
Pork Shoulder     Butts [Pork              179        $9.7           0.15%       292       $29.2           0.09%
                   Shoulder]
Frzn Prepared     Boneless Snack/          180        $9.6           0.15%       384       $21.5           0.07%
 Chicken           18oz And Larger
Rolls             Rolls: Dinner            181        $9.5           0.14%       161       $50.5           0.16%
Chicken &         Chix: Value-Added        182        $9.5           0.14%       323       $26.7           0.08%
 Poultry           (Cold)
Tomato Products-  Tomatoes Diced           183        $9.5           0.14%       123       $59.9           0.19%
 Shelf Stable
Frozen Ice        Ice--Crushed/Cubed       184        $9.3           0.14%       166       $49.9           0.16%
Beef: Round       Angus [Beef]             185        $9.3           0.14%       271       $31.4           0.10%
Shelf Stable      Blended Juice &          186        $9.3           0.14%       287       $29.6           0.09%
 Juice             Combinations
Sushi             Sushi--In Store          187        $9.2           0.14%        75       $85.4           0.27%
                   Prepared
Tomatoes          Tomatoes Hothouse        188        $9.2           0.14%        88       $77.7           0.25%
                   On The Vine
Candy--Packaged   Seasonal                 189        $9.2           0.14%       182       $46.9           0.15%
                   Miscellaneous
                   [Candy]
Frozen Bread/     Frzn Garlic Toast        190        $9.1           0.14%       307       $27.8           0.09%
 Dough
Warehouse Snacks  Canister Snacks          191        $9.1           0.14%       241       $36.4           0.12%
Beef: Grinds      Patties [Beef]           192        $9.1           0.14%       221       $39.7           0.13%
Bag Snacks        Corn Chips               193        $9.1           0.14%       188       $45.6           0.14%
Hot Cereal        Instant Oatmeal          194        $8.9           0.14%       218       $41.1           0.13%
Breakfast         Bkfst Sausage--          195        $8.9           0.14%       325       $26.3           0.08%
 Sausage           Fresh Links
Crackers & Misc   Snack Crackers           196        $8.9           0.14%        68       $98.6           0.31%
 Baked Food
Citrus            Clementines              197        $8.8           0.13%        85       $78.6           0.25%
Frzn Prepared     Bone-In Wings            198        $8.8           0.13%       586       $12.0           0.04%
 Chicken
Onions            Onions Yellow            199        $8.7           0.13%       225       $39.3           0.12%
                   (Bulk & Bag)
Dry Mix Desserts  Pudding & Gelatin        200        $8.7           0.13%       310       $27.6           0.09%
                   Cups/Cans
Coffee &          Unflavored Bag           201        $8.5           0.13%        38      $137.3           0.44%
 Creamers          Coffee
Refrgratd Juices/ Dairy Case Tea           202        $8.4           0.13%       364       $23.1           0.07%
 Drinks            With Sugar
Infant Formula    Infant Formula           203        $8.4           0.13%       687        $9.1           0.03%
                   Specialty
Ss/Vending--      Salty Snacks             204        $8.4           0.13%       480       $15.8           0.05%
 Salty Snacks      Vending
Shortening & Oil  Canola Oils              205        $8.3           0.13%       291       $29.3           0.09%
Infant Formula    Infant Formula           206        $8.3           0.13%       368       $22.8           0.07%
                   Starter Large
Value-Added       Melons Instore Cut       207        $8.2           0.13%       205       $42.8           0.14%
 Fruit
Vegetables Salad  Cucumbers                208        $8.2           0.13%       129       $58.9           0.19%
Smoked Hams       Hams--Half/Port          209        $8.2           0.12%       282       $30.0           0.10%
                   Bone-In
Crackers & Misc   Saltine/Oyster           210        $8.2           0.12%       204       $43.1           0.14%
 Baked Food
Condiments &      Steak & Worchester       211        $8.2           0.12%       321       $26.7           0.08%
 Sauces            Sauce
Cookie/Cracker    Multi-Pack               212        $8.0           0.12%       217       $41.3           0.13%
 Multi-Pks         Crackers
Frozen            Cones [Frozen            213        $7.9           0.12%       273       $31.2           0.10%
 Novelties--Wate   Novelties]
 r Ice
Deli Meat: Bulk   Meat: Beef Bulk          214        $7.9           0.12%       154       $53.4           0.17%
Melons            Watermelon               215        $7.9           0.12%       198       $43.9           0.14%
                   Seedless Whole
Candy--Packaged   Seasonal Candy           216        $7.9           0.12%       148       $54.8           0.17%
                   Bags--Chocolate
Salad & Dips      Vegetable Salads--       217        $7.8           0.12%       238       $36.6           0.12%
                   Prepack
Baked Breads      Bagels                   218        $7.8           0.12%       108       $66.9           0.21%
Peppers           Peppers Green Bell       219        $7.8           0.12%       215       $41.5           0.13%
Salad Mix         Regular Garden           220        $7.8           0.12%       265       $31.9           0.10%
                   Salad
Energy Drinks     Energy Drink--           221        $7.7           0.12%       327       $26.3           0.08%
                   Single Serve
Smoked Hams       Hams--Spiral             222        $7.6           0.12%       240       $36.5           0.12%
Coffee &          Unflavored Instant       223        $7.6           0.12%       316       $27.3           0.09%
 Creamers          Coffee
Tomatoes          Roma Tomatoes            224        $7.5           0.11%       222       $39.6           0.13%
                   (Bulk/Pkg)
Cookies           Vanilla Wafer/Kids       225        $7.5           0.11%       236       $36.7           0.12%
                   Cookies
Frozen            Ice Cream                226        $7.4           0.11%       354       $24.2           0.08%
 Novelties--Wate   Sandwiches
 r Ice
Hot Dogs          Hot Dogs--Premium        227        $7.4           0.11%       208       $42.7           0.14%
Yogurt            Yogurt/Pro Active        228        $7.4           0.11%       113       $63.5           0.20%
                   Health
Snack Meat        Snack Meat--             229        $7.4           0.11%       263       $32.1           0.10%
                   Pepperoni
Cakes             Cakes: Creme/            230        $7.4           0.11%       333       $25.8           0.08%
                   Pudding
Meat Frozen       Frzn Meat--              231        $7.3           0.11%       602       $11.3           0.04%
                   Breakfast Sausage
Beef: Rib         Angus [Beef]             232        $7.3           0.11%       200       $43.3           0.14%
Shortening & Oil  Olive Oil                233        $7.3           0.11%       112       $63.8           0.20%
Dry Bean Veg &    Noodle Side Dish         234        $7.3           0.11%       390       $21.1           0.07%
 Rice              Mixes
Yogurt            Yogurt/Adult Multi-      235        $7.2           0.11%       210       $42.5           0.14%
                   Packs
Dry Bean Veg &    Rice--Dry Bag And        236        $7.1           0.11%       255       $33.9           0.11%
 Rice              Box
Energy Drinks     Energy Drink--           237        $7.1           0.11%       224       $39.5           0.13%
                   Single Serve
Baked Breads      Sandwich Buns            238        $7.1           0.11%       137       $56.8           0.18%
Refrigerated      Non-Dairy Milks          239        $7.1           0.11%       105       $67.7           0.21%
 Dairy Case
Beef: Round       Select Beef              240        $7.1           0.11%       278       $30.4           0.10%
Powder & Crystal  Unsweetened              241        $7.0           0.11%       802        $6.2           0.02%
 Drink Mix         Envelope [Powder
                   Drink Mix]
Refrigerated      Refrigerated             242        $7.0           0.11%       170       $49.5           0.16%
 Desserts          Pudding
Carrots           Carrots Mini             243        $7.0           0.11%       118       $61.4           0.19%
                   Peeled
Baking Mixes      Layer Cake Mix           244        $7.0           0.11%       251       $35.1           0.11%
Cocoa Mixes       Malted Mlk/Syrup/        245        $6.9           0.11%       339       $25.3           0.08%
                   Pwdrs (Eggnog)
Stone Fruit       Cherries Red             246        $6.9           0.10%       139       $56.7           0.18%
Frzn Seafood      Frz Coated Fish          247        $6.9           0.10%       389       $21.1           0.07%
                   Fillets
Meat Snacks       Jerky/Nuggets/           248        $6.8           0.10%       334       $25.8           0.08%
                   Tenders
Dry Bean Veg &    Rice--Instant &          249        $6.8           0.10%       231       $38.0           0.12%
 Rice              Microwave
Seafood--Catfish  Catfish--Fillet          250        $6.8           0.10%       544       $13.1           0.04%
Refrgrated Dough  Refrigerated             251        $6.8           0.10%       296       $28.8           0.09%
 Products          Cookies-Brand
Fluid Milk        Specialty/Lactose        252        $6.7           0.10%       175       $48.4           0.15%
 Products          Free Milk
Peanut Butter/    Preserves/Jam/           253        $6.7           0.10%       141       $56.2           0.18%
 Jelly/Jams &      Marmalade
 Honey
Margarines        Margarine Stick          254        $6.7           0.10%       376       $22.3           0.07%
Rts/Micro Soup/   Broth                    255        $6.7           0.10%       109       $65.6           0.21%
 Broth
Rtd Tea/New Age   Juice (Under 10%         256        $6.7           0.10%       374       $22.4           0.07%
 Juice             Juice)
Apples            Apples Gala (Bulk        257        $6.6           0.10%        98       $69.3           0.22%
                   & Bag)
Chicken Fresh     Chicken Legs/            258        $6.6           0.10%       536       $13.5           0.04%
                   Quarters
Frozen Breakfast  Frzn Breakfast           259        $6.5           0.10%       420       $19.0           0.06%
 Foods             Pastry
Flour & Meals     Flour: White &           260        $6.4           0.10%       297       $28.8           0.09%
                   Self Rising
Seafood--Value-   Seafood Value-           261        $6.4           0.10%       459       $16.9           0.05%
 Added             Added Breaded
                   Shrimp
Sugars &          Sweeteners               262        $6.4           0.10%       168       $49.8           0.16%
 Sweeteners
Baking Mixes      Frosting                 263        $6.3           0.10%       318       $27.0           0.09%
Pies              Pies: Fruit/Nut          264        $6.3           0.10%       223       $39.6           0.13%
Molasses/Syrups/  Pancake Mixes            265        $6.3           0.10%       379       $21.9           0.07%
 Pancake Mixes
Water--(Sparklin  Still Water Flvrd        266        $6.3           0.10%       230       $38.1           0.12%
 g & Still)        Drnk/Mnrl Wtr
Bag Snacks        Pretzels                 267        $6.2           0.09%       144       $55.4           0.18%
Dry Cheese        Grated Cheese            268        $6.2           0.09%       256       $33.6           0.11%
Onions            Onions Sweet (Bulk       269        $6.2           0.09%       181       $47.4           0.15%
                   & Bag)
Shelf Stable      Cranapple/Cran           270        $6.1           0.09%       315       $27.3           0.09%
 Juice             Grape Juice
Frzn Seafood      Frz Fishsticks/          271        $6.1           0.09%       506       $14.7           0.05%
                   Tenders/Nuggets
Seafood--Crab     Crab--Snow               272        $6.1           0.09%       598       $11.4           0.04%
Bread             Bread:Italian/           273        $6.1           0.09%       172       $49.0           0.16%
                   French
Bulk Service      Bulk Semi-Hard           274        $6.1           0.09%       196       $44.0           0.14%
 Case Cheese       Cheese
Baking Mixes      Muffin & Corn            275        $6.0           0.09%       295       $28.9           0.09%
                   Bread Mix
Chicken &         Chix: Frd 8pc/Cut        276        $6.0           0.09%       558       $12.7           0.04%
 Poultry           Up (Cold)
Infant Formula    Infant Formula           277        $6.0           0.09%       570       $12.4           0.04%
                   Toddler
Vegetables        Celery                   278        $5.9           0.09%       158       $51.2           0.16%
 Cooking Bulk
Traditional       Mexican Seasoning        279        $5.9           0.09%       402       $20.6           0.07%
 Mexican Foods     Mixes
Refrigerated      Fluid Milk               280        $5.9           0.09%        52      $113.3           0.36%
 Dairy Case
Soft Drinks       Soft Drinks Can          281        $5.9           0.09%       592       $11.5           0.04%
                   Non-Carb
Condiments &      Hot Sauce                282        $5.8           0.09%       466       $16.4           0.05%
 Sauces
Apples            Apples Red               283        $5.8           0.09%       248       $35.2           0.11%
                   Delicious (Bulk &
                   Bag)
Single Serve      Snack Cake--Single       284        $5.7           0.09%       470       $16.2           0.05%
 Sweet Goods       Serve
Milk By-Products  Refrig Dips              285        $5.7           0.09%       350       $24.7           0.08%
Tomatoes          Tomatoes Vine Ripe       286        $5.7           0.09%       373       $22.5           0.07%
                   Bulk
Bag Snacks        Brand Snacks             287        $5.6           0.09%       176       $48.1           0.15%
Refrgrated Dough  Refrigerated             288        $5.5           0.08%       312       $27.5           0.09%
 Products          Specialty Rolls
Canned & Dry      Canned Milk              289        $5.5           0.08%       305       $27.9           0.09%
 Milk
Coffee &          Ready To Drink           290        $5.5           0.08%       403       $20.5           0.06%
 Creamers          Coffee
Salad Mix         Garden Plus [Salad       291        $5.5           0.08%       267       $31.8           0.10%
                   Mix]
Cookies           Cookies: Holiday/        292        $5.5           0.08%       320       $26.8           0.08%
                   Special Occas
Bag Snacks        Misc Bag Snacks          293        $5.5           0.08%       591       $11.5           0.04%
Refrgratd Juices/ 100% Pure Juice          294        $5.4           0.08%       261       $32.3           0.10%
 Drinks Dairy      Other
 Case
Refrgrated Dough  Refrigerated             295        $5.4           0.08%       274       $31.2           0.10%
 Products          Crescent Rolls
Teas              Tea Bags & Bulk          296        $5.4           0.08%       317       $27.2           0.09%
                   Tea
Aseptic Juice     Aseptic Pack Juice       297        $5.3           0.08%       449       $17.5           0.06%
                   And Drinks
Infant Formula    Infant Formula           298        $5.3           0.08%       497       $15.2           0.05%
                   Solutions Large
Vegetables        Cabbage                  299        $5.3           0.08%       340       $25.1           0.08%
 Cooking Bulk
Melons            Cantaloupe Whole         300        $5.3           0.08%       194       $44.4           0.14%
Dry Sce/Gravy/    Stuffing Mixes           301        $5.3           0.08%       378       $22.1           0.07%
 Potatoes/
 Stuffng
Frozen Desserts   Frozen Fruit Pies        302        $5.3           0.08%       359       $23.7           0.08%
                   & Cobblers
Frozen Potatoes   Frzn Tater Tots/         303        $5.2           0.08%       424       $18.8           0.06%
                   Other Extruded
Traditional       Mexican Taco/            304        $5.2           0.08%       417       $19.1           0.06%
 Mexican Foods     Tostado/Shells
Broccoli/         Broccoli Whole &         305        $5.2           0.08%       156       $52.0           0.16%
 Cauliflower       Crowns
Tomato Products-  Tomato Sauce             306        $5.1           0.08%       353       $24.2           0.08%
 Shelf Stable
Candy--Checklane  Candy Bars               307        $5.1           0.08%       476       $15.9           0.05%
                   (Singles)
Lunchmeat         Lunchmeat--Chop/         308        $5.1           0.08%       583       $12.1           0.04%
                   Form Pltry
Vegetables Salad  Variety Lettuce          309        $5.1           0.08%       110       $65.2           0.21%
Berries           Blueberries              310        $5.1           0.08%        82       $79.4           0.25%
Shelf Stable      Cranberry Juice          311        $5.0           0.08%       371       $22.6           0.07%
 Juice             (50% And Under)
Seafood--Salmon-  Salmon Fr--              312        $5.0           0.08%       173       $48.8           0.15%
 Farm Raised       Atlantic
Tomatoes          Tomatoes Hot House       313        $5.0           0.08%       280       $30.3           0.10%
                   Bulk
Yogurt            Yogurt/Specialty         314        $5.0           0.08%        89       $77.4           0.25%
                   Greek
Frozen Whipped    Frzn Whipped             315        $5.0           0.08%       276       $30.9           0.10%
 Topping           Topping
Can Fruit/Jar     Pineapple                316        $4.9           0.07%       357       $24.0           0.08%
 Applesauce
Frozen Desserts   Frozen Cream Pies        317        $4.9           0.07%       423       $18.9           0.06%
Infant Formula    Infant Formula           318        $4.9           0.07%       954        $3.9           0.01%
                   Concentrate
Stone Fruit       Peaches Yellow           319        $4.8           0.07%       243       $35.6           0.11%
                   Flesh
Sweet Goods       Sw Gds: Sw Rolls/        320        $4.8           0.07%       319       $26.9           0.09%
                   Dan
Potatoes          Potatoes Sweet &         321        $4.8           0.07%       234       $37.1           0.12%
                   Yams
Seafood--Party    Party Tray--Shrimp       322        $4.8           0.07%       347       $24.8           0.08%
 Trays
Shelf Stable      Blended Juice &          323        $4.8           0.07%       365       $22.9           0.07%
 Juice             Combinations
Baking Mixes      Brownie Mix              324        $4.8           0.07%       313       $27.5           0.09%
Shelf Stable      Grape Juice (Over        325        $4.8           0.07%       455       $17.1           0.05%
 Juice             50% Juice)
Frzn Prepared     Fz Meal Kits/            326        $4.8           0.07%       578       $12.2           0.04%
 Chicken           Stuffed/Other
Peanut Butter/    Jelly                    327        $4.7           0.07%       439       $18.1           0.06%
 Jelly/Jams &
 Honey
Smoked Pork       Ham Steaks/Cubes/        328        $4.7           0.07%       324       $26.3           0.08%
                   Slices
Tomatoes          Tomatoes Grape           329        $4.7           0.07%       150       $54.6           0.17%
Traditional       Mexican Beans/           330        $4.7           0.07%       393       $21.0           0.07%
 Mexican Foods     Refried
Citrus            Lemons                   331        $4.6           0.07%       257       $33.6           0.11%
Can Fruit/Jar     Peaches                  332        $4.6           0.07%       387       $21.3           0.07%
 Applesauce
Frozen Potatoes   Frzn Hashbrown           333        $4.6           0.07%       348       $24.8           0.08%
                   Potatoes
Dry Noodles &     Noodles Dry              334        $4.5           0.07%       344       $24.9           0.08%
 Pasta
Salad Bar         Salad Bar Other          335        $4.5           0.07%       438       $18.2           0.06%
Corn              Corn Bulk                336        $4.5           0.07%       260       $32.5           0.10%
Sweet Goods       Sw Gds: Muffins          337        $4.5           0.07%       266       $31.8           0.10%
Frozen Breakfast  Frzn Breakfast           338        $4.5           0.07%       473       $16.2           0.05%
 Foods             Entrees
Eggs/Muffins/     Eggs--X-Large            339        $4.5           0.07%       232       $37.9           0.12%
 Potatoes
Convenient Meals  Convenient Meals--       340        $4.5           0.07%       603       $11.2           0.04%
                   Adult Meal
Bacon             Bacon--Poultry           341        $4.5           0.07%       435       $18.4           0.06%
Smoked Hams       Hams--Whole              342        $4.5           0.07%       510       $14.6           0.05%
                   Boneless
Fluid Milk        Half & Half              343        $4.4           0.07%       149       $54.6           0.17%
 Products
Deli Meat: Bulk   Meat Bulk:               344        $4.4           0.07%       302       $28.3           0.09%
                   Specialty Dry
                   Meats
Frozen Vegetable  Fz Box Vegetables--      345        $4.4           0.07%       349       $24.7           0.08%
 & Veg Dish        Value-Added
Apples            Apples Granny            346        $4.4           0.07%       277       $30.9           0.10%
                   Smith (Bulk &
                   Bag)
Baking Needs      Bits & Morsels           347        $4.4           0.07%       162       $50.3           0.16%
                   [Baking Needs]
Meat--Shelf       Chunk Meats--Chix/       348        $4.4           0.07%       338       $25.3           0.08%
 Stable            Ham/Etc.
Yogurt            Yogurt/Large Size        349        $4.4           0.07%       219       $40.4           0.13%
                   (16oz Or Larger)
Energy Drinks     Energy Drink--           350        $4.3           0.07%       421       $19.0           0.06%
                   Multi-Pack
Frozen Fruits     Frozen Fruit             351        $4.3           0.07%       174       $48.6           0.15%
Turkey Frozen     Whole Toms (Over         352        $4.3           0.06%       407       $20.0           0.06%
                   16lbs) [Turkey]
Lunchmeat         Lunchmeat--Whole         353        $4.2           0.06%       413       $19.7           0.06%
                   Muscle Pltry
Dry Bean Veg &    Dry Beans/Peas/          354        $4.2           0.06%       425       $18.8           0.06%
 Rice              Barley: Bag &
                   Bulk
Frozen            Adult Premium            355        $4.2           0.06%       151       $54.5           0.17%
 Novelties--Wate   [Frozen
 r Ice             Novelties]
Traditional       Mexican Dinners          356        $4.2           0.06%       597       $11.4           0.04%
 Mexican Foods     And Foods
Salad Mix         Kits [Salad Mix]         357        $4.2           0.06%       258       $33.5           0.11%
Cookies           Premium Cookies          358        $4.2           0.06%       269       $31.5           0.10%
Peanut Butter/    Honey                    359        $4.1           0.06%       294       $28.9           0.09%
 Jelly/Jams &
 Honey
Pickle/Relish/    Ripe Olives              360        $4.1           0.06%       337       $25.3           0.08%
 Pckld Veg &
 Olives
Bacon             Bacon--Pre-Cooked        361        $4.1           0.06%       346       $24.8           0.08%
Rolls             Rolls: Sandwich          362        $4.1           0.06%       322       $26.7           0.08%
Potatoes          Potatoes Red (Bulk       363        $4.1           0.06%       264       $32.0           0.10%
                   & Bag)
Croutons/Bread    Salad Toppers            364        $4.1           0.06%       500       $15.1           0.05%
 Stick & Salad
 Top
Candy--Packaged   Gum (Packaged)           365        $4.1           0.06%       331       $25.9           0.08%
Baking Needs      Baking Nuts              366        $4.1           0.06%       201       $43.2           0.14%
Soft Drinks       Soft Drinks 6pk          367        $4.1           0.06%       308       $27.8           0.09%
                   Can Carb
Single Serve      Applesauce Cup           368        $4.1           0.06%       370       $22.6           0.07%
 Fruit/
 Applesauce
Dry Sce/Gravy/    Gravy Can/Glass          369        $4.0           0.06%       485       $15.7           0.05%
 Potatoes/
 Stuffng
Cookies           Graham Crackers          370        $4.0           0.06%       342       $24.9           0.08%
Candy--Packaged   Miscellaneous            371        $4.0           0.06%       418       $19.0           0.06%
                   Candy
Frozen Vegetable  Frzn Corn On The         372        $4.0           0.06%       708        $8.4           0.03%
 & Veg Dish        Cob
Cookies           Chocolate Covered        373        $4.0           0.06%       432       $18.5           0.06%
                   Cookies
Value-Added       Vegetable Party          374        $4.0           0.06%       341       $25.1           0.08%
 Vegetables        Tray
Value-Added       Cut Vegetables All       375        $4.0           0.06%       213       $42.2           0.13%
 Vegetables        Other
Deli Meat: Bulk   Bologna/Loaves/          376        $4.0           0.06%       415       $19.2           0.06%
                   Franks
Condiments &      Marinades                377        $3.9           0.06%       434       $18.4           0.06%
 Sauces
Nuts              Pistachios               378        $3.9           0.06%       293       $29.1           0.09%
Service Case      Seasoned Poultry         379        $3.9           0.06%       463       $16.5           0.05%
 Meat
Salad & Dips      Protein Salads--         380        $3.9           0.06%       326       $26.3           0.08%
                   Bulk
Hot Cereal        Standard Oatmeal         381        $3.9           0.06%       284       $29.9           0.09%
Cheese            Miscellaneous            382        $3.8           0.06%       214       $42.1           0.13%
                   Cheese
Salad & Dips      Vegetable Salads--       383        $3.8           0.06%       275       $31.0           0.10%
                   Bulk
Shelf Stable      Veg Juice (Except        384        $3.8           0.06%       279       $30.4           0.10%
 Juice             Tomato)
Juices Super      Juices Superfoods/       385        $3.8           0.06%       367       $22.8           0.07%
 Premium           Enhanced
Breakfast         Bkfst Sausage--          386        $3.8           0.06%       651        $9.8           0.03%
 Sausage           Fresh Patties
Vegetables        Asparagus                387        $3.8           0.06%       159       $50.7           0.16%
 Cooking Bulk
Baby Foods        Baby Food Cereals        388        $3.8           0.06%       756        $7.1           0.02%
Baked Breads      English Muffins/         389        $3.8           0.06%       169       $49.5           0.16%
                   Waffles
Baked Breads      Main Meal Bread          390        $3.8           0.06%       252       $34.9           0.11%
Juice             Non-Carb Jce (Over       391        $3.8           0.06%       268       $31.7           0.10%
                   50% Juice)
Deli Meat: Bulk   Meat: Chicken Bulk       392        $3.7           0.06%       253       $34.6           0.11%
Breakfast         Bkfst Sausage--          393        $3.7           0.06%       385       $21.4           0.07%
 Sausage           Precooked
Dietary Aid       Diet Cntrl Liqs          394        $3.7           0.06%       281       $30.3           0.10%
 Prdct/Med Liq     Nutritional
 Nutr
Refrgratd Juices/ Fruit Drinks             395        $3.7           0.06%     1,041        $2.8           0.01%
 Drinks Dairy
 Case
Dinner Sausage    Dnr Sausage--Beef        396        $3.7           0.06%       577       $12.2           0.04%
                   Rope Ckd
Canned Pasta &    Microwavable Cups        397        $3.7           0.06%       690        $9.0           0.03%
 Mwv Fd-Shlf
 Stbl
Turkey Frozen     Whole Hens (Under        398        $3.6           0.06%       419       $19.0           0.06%
                   16lbs) [Turkey]
Cakes             Cakes: Cheesecake        399        $3.6           0.06%       507       $14.7           0.05%
Enhancements      Enhancements--Pick       400        $3.6           0.06%       410       $19.8           0.06%
 (Pickles/         les/Kraut
 Spreads)
Tomatoes          Tomatoes Vine Ripe       401        $3.6           0.06%       743        $7.3           0.02%
                   Pkg
Peppers           Peppers Red Bell         402        $3.6           0.05%       211       $42.5           0.13%
Dinner Sausage    Dnr Sausage--Other       403        $3.6           0.05%       381       $21.6           0.07%
                   Forms
Pork Offal        External Fresh           404        $3.5           0.05%       937        $4.2           0.01%
Pasta & Pizza     Value [Pasta &           405        $3.5           0.05%       657        $9.7           0.03%
 Sauce             Pizza Sauce]
Aseptic Juice     Aseptic Pack Juice       406        $3.5           0.05%       934        $4.2           0.01%
                   And Drinks
Berries           Raspberries              407        $3.5           0.05%       186       $45.8           0.15%
Beef: Thin Meats  Corned Beef              408        $3.5           0.05%       461       $16.9           0.05%
Party Tray        Deli Tray: Meat          409        $3.5           0.05%       383       $21.5           0.07%
                   And Cheese
Can Vegetables--  Peas/Green               410        $3.5           0.05%       504       $14.7           0.05%
 Shelf Stable
Dry/Ramen         Dry Soup                 411        $3.5           0.05%       362       $23.3           0.07%
 Bouillon
Can Vegetables--  Spinach & Greens         412        $3.5           0.05%       765        $7.0           0.02%
 Shelf Stable
Frzn Multi Serve  Fz Meatballs             413        $3.5           0.05%       447       $17.7           0.06%
Milk By-Products  Aerosol Toppings         414        $3.5           0.05%       351       $24.5           0.08%
                   [Milk By-
                   Products]
Baked Breads      Dinner Rolls             415        $3.5           0.05%       513       $14.5           0.05%
Cocoa Mixes       Hot Chocolate/           416        $3.5           0.05%       445       $17.8           0.06%
                   Cocoa Mix
Infant Formula    Infant Formula           417        $3.5           0.05%       768        $6.9           0.02%
                   Ready To Use
Powder & Crystal  Sugar Free               418        $3.5           0.05%       391       $21.1           0.07%
 Drink Mix         Canister [Powder
                   Drink Mix]
Cnv Breakfast &   Treats [Breakfast]       419        $3.5           0.05%       605       $11.2           0.04%
 Wholesome Snks
Smoked Hams       Hams--Half/Port          420        $3.4           0.05%       392       $21.0           0.07%
                   Boneless
Fitness & Diet    Fitness & Diet--         421        $3.4           0.05%       124       $59.8           0.19%
                   Bars W/Flour
Refrgrated Dough  Refrigerated             422        $3.4           0.05%       551       $12.9           0.04%
 Products          Cookie Dough
Grapes            Grapes Black/Blue        423        $3.4           0.05%       380       $21.8           0.07%
Bulk Service      Bulk Processed           424        $3.4           0.05%       411       $19.8           0.06%
 Case Cheese       [Cheese]
Candy--Packaged   Seasonal Candy           425        $3.4           0.05%       462       $16.6           0.05%
                   Box--Chocolate
Coffee &          Coffee Pods/             426        $3.4           0.05%       167       $49.8           0.16%
 Creamers          Singles/Filter
                   Pack
Can Fruit/Jar     Fruit Cocktail/          427        $3.4           0.05%       569       $12.5           0.04%
 Applesauce        Fruit Salad
Peppers           Peppers Other Bell       428        $3.4           0.05%       301       $28.4           0.09%
Mushrooms         Mushrooms White          429        $3.3           0.05%       306       $27.8           0.09%
                   Sliced Pkg
Lunchmeat         Lunchmeat--Chip          430        $3.3           0.05%       653        $9.7           0.03%
                   Meat
Soft Drinks       Sft Drnk 1 Liter         431        $3.3           0.05%       716        $8.2           0.03%
                   Btl Carb
Cakes             Cakes: Fancy/            432        $3.3           0.05%       451       $17.4           0.06%
                   Service Case
Salad Mix         Shredded Lettuce         433        $3.3           0.05%       616       $10.9           0.03%
Powder & Crystal  Sugar Free Sticks        434        $3.3           0.05%       426       $18.8           0.06%
 Drink Mix         [Powder Drink
                   Mix]
Dinner Mixes-Dry  Package Dinners/         435        $3.3           0.05%       664        $9.5           0.03%
                   Pasta Salads
Cakes             Cakes: Layers/           436        $3.3           0.05%       565       $12.5           0.04%
                   Sheets Novelties
Flour & Meals     Breadings/Coatings/      437        $3.2           0.05%       474       $16.0           0.05%
                   Crumbs
Pies              Pies: Pumpkin/           438        $3.2           0.05%       545       $13.1           0.04%
                   Custard
Refrigerated      Yogurt                   439        $3.2           0.05%       107       $67.0           0.21%
 Dairy Case
Apples            Mixed Fruit Bags         440        $3.2           0.05%       829        $5.7           0.02%
Shelf Stable      Fruit Drinks:            441        $3.2           0.05%       870        $5.0           0.02%
 Juice             Canned & Glass
Dry Mix Desserts  Puddings Dry             442        $3.2           0.05%       400       $20.8           0.07%
Can Seafood--     Salmon                   443        $3.2           0.05%       534       $13.6           0.04%
 Shelf Stable
Shortening & Oil  Cooking Sprays           444        $3.2           0.05%       396       $21.0           0.07%
Meat--Shelf       Sandwich Sauce           445        $3.2           0.05%       733        $7.7           0.02%
 Stable            (Manwich)
Bread             Bread: Specialty         446        $3.2           0.05%       366       $22.9           0.07%
Seafood--Tilapia  Tilapia--Fillet          447        $3.2           0.05%       465       $16.4           0.05%
Frzn Multi Serve  Frzn Burgers             448        $3.2           0.05%     1,010        $3.1           0.01%
Convenience/      Jarred Fruit             449        $3.1           0.05%       511       $14.6           0.05%
 Snacking          Single Serve
Powder & Crystal  Soft Drink               450        $3.1           0.05%       723        $7.9           0.03%
 Drink Mix         Canisters
Frozen Breakfast  Frzn Breakfast           451        $3.1           0.05%       647        $9.8           0.03%
 Foods             Sausage
Ss/Vending--      Vendor Size/Single       452        $3.1           0.05%       770        $6.8           0.02%
 Cookie/Cracker    Serve Cookie
Water--(Sparklin  Sparkling Water--        453        $3.1           0.05%       355       $24.1           0.08%
 g & Still)        Flvrd Sweet
Service Case      Stuffed/Mixed Beef       454        $3.1           0.05%       416       $19.2           0.06%
 Meat
Meat--Shelf       Vienna Sausage           455        $3.1           0.05%       867        $5.1           0.02%
 Stable
Mushrooms         Mushrooms White          456        $3.1           0.05%       288       $29.6           0.09%
                   Whole Pkg
Teas              Tea Bags/Herbal          457        $3.1           0.05%       272       $31.2           0.10%
Meat Frozen       Frzn Meat--Offals        458        $3.0           0.05%     1,053        $2.6           0.01%
Bulk Service      Bulk Semi-Soft           459        $3.0           0.05%       363       $23.3           0.07%
 Case Cheese
Bag Snacks        Bagged Popped            460        $3.0           0.05%       566       $12.5           0.04%
                   Popcorn
Condiments &      Yellow Mustard           461        $3.0           0.05%       571       $12.4           0.04%
 Sauces
Vegetables Salad  Green Onions             462        $3.0           0.05%       361       $23.5           0.07%
Frozen Bread/     Frzn Dinner Rolls        463        $3.0           0.05%       398       $20.9           0.07%
 Dough
Baking Needs      Marshmallows             464        $3.0           0.05%       467       $16.4           0.05%
Warehouse Snacks  Snack Mix                465        $3.0           0.05%       450       $17.5           0.06%
Fluid Milk        Whipping Cream           466        $3.0           0.04%       249       $35.2           0.11%
 Products
Dried Fruit       Raisins                  467        $2.9           0.04%       330       $26.0           0.08%
Dinner Sausage    Dnr Sausage--Links       468        $2.9           0.04%       722        $8.0           0.03%
                   Beef Ckd
Rolls             Rolls: Croissants/       469        $2.9           0.04%       464       $16.5           0.05%
                   Breadsticks
Lunchmeat         Lunchmeat--Brauns/       470        $2.9           0.04%       632       $10.3           0.03%
                   Liver/Loave
Cookie/Cracker    Multi-Pack Cookies       471        $2.9           0.04%       596       $11.4           0.04%
 Multi-Pks
Snack Meat        Snack Meat--Salami/      472        $2.9           0.04%       481       $15.8           0.05%
                   Smr Sausage
Shortening & Oil  Solid Shortening         473        $2.9           0.04%       525       $14.0           0.04%
Salad Mix         Salad Bowls              474        $2.9           0.04%       572       $12.3           0.04%
Hot Cereal        Grits                    475        $2.8           0.04%       774        $6.7           0.02%
Cereals           Cereal--Cold             476        $2.8           0.04%       178       $47.8           0.15%
Frozen Vegetable  Fz Bag Vegetables--      477        $2.8           0.04%       505       $14.7           0.05%
 & Veg Dish        Value-Added
Traditional       Asian Other Sauces/      478        $2.8           0.04%       422       $18.9           0.06%
 Asian Foods       Marinade
Frozen            Cups/Push Ups/           479        $2.8           0.04%       661        $9.6           0.03%
 Novelties--Wate   Other [Frozen
 r Ice             Novelties]
Refrigerated      Refrigerated             480        $2.8           0.04%       669        $9.4           0.03%
 Hispanic          Tortillas
 Grocery
Frzn Prepared     Whole Muscle             481        $2.8           0.04%       555       $12.8           0.04%
 Chicken           Unbreaded Chicken
Meat--Shelf       Luncheon Meat            482        $2.8           0.04%       693        $8.9           0.03%
 Stable            (Spam)
Frzn Prepared     Boneless Snack/          483        $2.8           0.04%       836        $5.5           0.02%
 Chicken           Value/Small
Croutons/Bread    Croutons                 484        $2.8           0.04%       526       $14.0           0.04%
 Stick & Salad
 Top
Apples            Apples Other (Bulk       485        $2.8           0.04%       314       $27.4           0.09%
                   & Bag)
Apples            Apples Fuji (Bulk        486        $2.8           0.04%       242       $36.2           0.11%
                   & Bag)
Apples            Apples Gold              487        $2.8           0.04%       443       $17.9           0.06%
                   Delicious (Bulk &
                   Bag)
Salad & Dips      Sal: Hommus              488        $2.8           0.04%       189       $45.4           0.14%
Dinner Sausage    Dnr Sausage--            489        $2.7           0.04%       562       $12.7           0.04%
                   Cocktails
Can Vegetables--  Mushrooms Cnd &          490        $2.7           0.04%       521       $14.3           0.05%
 Shelf Stable      Glass
Frozen Desserts   Frzn Pie Shells/         491        $2.7           0.04%       475       $16.0           0.05%
                   Pastry Shell
Lunchmeat         Lunchmeat--Variety       492        $2.7           0.04%       677        $9.3           0.03%
                   Pack
Frozen Desserts   Frozen Cakes/            493        $2.7           0.04%       611       $11.0           0.03%
                   Desserts
Pickle/Relish/    Peppers                  494        $2.7           0.04%       537       $13.5           0.04%
 Pckld Veg &
 Olives
Cakes             Cakes: Angel Fds/        495        $2.7           0.04%       440       $18.1           0.06%
                   Cke Rolls
Berries           Blackberries             496        $2.7           0.04%       283       $29.9           0.09%
Frozen Bread/     Frzn Garlic Bread        497        $2.7           0.04%       608       $11.1           0.04%
 Dough
Traditional       Mexican Enchilada        498        $2.7           0.04%       532       $13.7           0.04%
 Mexican Foods     Sauce
Fluid Milk        Egg Nog/Boiled           499        $2.7           0.04%       539       $13.3           0.04%
 Products          Custard
Hot Dogs          Hot Dogs--Base           500        $2.7           0.04%       667        $9.4           0.03%
                   Poultry
Beef: Thin Meats  Brisket [Beef]           501        $2.7           0.04%       446       $17.8           0.06%
Cookies           Wellness/Portion         502        $2.7           0.04%       358       $23.8           0.08%
                   Control [Cookies]
Baking Needs      Pie Filling/             503        $2.7           0.04%       345       $24.8           0.08%
                   Mincemeat/Glazes
Soft Drinks       Tea Can With             504        $2.7           0.04%       807        $6.1           0.02%
                   Sweetener/Sugar
Citrus            Limes                    505        $2.7           0.04%       369       $22.7           0.07%
Warehouse Snacks  Misc Snacks              506        $2.6           0.04%       541       $13.2           0.04%
Traditional       Mexican Taco Sauce       507        $2.6           0.04%       761        $7.0           0.02%
 Mexican Foods
Soft Drinks       Soft Drink Bottle        508        $2.6           0.04%       887        $4.7           0.02%
                   Non-Carb
Seafood--Salmon-  Salmon Wc--Pink          509        $2.6           0.04%       612       $11.0           0.03%
 Wild Caught
Frozen Bread/     Frzn Biscuits            510        $2.6           0.04%       550       $12.9           0.04%
 Dough
Frzn Pasta        Frozen Pasta             511        $2.6           0.04%       458       $16.9           0.05%
Chicken Frozen    Frzn Chicken--Drk        512        $2.6           0.04%       818        $5.9           0.02%
                   Meat
Syrups Toppings   Ice Cream Toppings       513        $2.6           0.04%       524       $14.1           0.04%
 & Cones
Candy--Packaged   Seasonal Candy           514        $2.6           0.04%       502       $14.9           0.05%
                   Bags Non-
                   Chocolate
Salad & Dips      Pasta/Grain              515        $2.6           0.04%       631       $10.3           0.03%
                   Salads--Prepack
Cakes             Cakes: Ice Cream         516        $2.6           0.04%       700        $8.6           0.03%
Nuts              Mixed Nuts               517        $2.6           0.04%       309       $27.6           0.09%
Sushi             Sushi--Prepackaged       518        $2.6           0.04%       414       $19.2           0.06%
Pickle/Relish/    Green Olives             519        $2.6           0.04%       483       $15.8           0.05%
 Pckld Veg &
 Olives
Candy--Packaged   Candy Bars Multi         520        $2.6           0.04%       695        $8.8           0.03%
                   Pack W/Flour
Stone Fruit       Nectarines Yellow        521        $2.5           0.04%       430       $18.6           0.06%
                   Flesh
Onions            Onions Red (Bulk &       522        $2.5           0.04%       397       $20.9           0.07%
                   Bag)
Flour & Meals     Cornmeal                 523        $2.5           0.04%       746        $7.3           0.02%
Tropical Fruit    Pineapple Whole &        524        $2.5           0.04%       377       $22.1           0.07%
                   Peel/Cored
Bagels & Cream    Refrigerated             525        $2.5           0.04%       731        $7.7           0.02%
 Cheese            Bagels
Onions            Onions White (Bulk       526        $2.5           0.04%       482       $15.8           0.05%
                   & Bag)
Meat Frozen       Frzn Meat--Turkey        527        $2.5           0.04%       652        $9.7           0.03%
Pickle/Relish/    Relishes                 528        $2.5           0.04%       590       $11.6           0.04%
 Pckld Veg &
 Olives
Candy--Packaged   Candy Bags--             529        $2.5           0.04%       496       $15.2           0.05%
                   Chocolate W/Flour
Nuts              Cashews                  530        $2.5           0.04%       437       $18.3           0.06%
Cakes             Cakes:Birthday/          531        $2.5           0.04%       684        $9.1           0.03%
                   Celebration Lay
Smoked Pork       Smoked Offal             532        $2.4           0.04%       940        $4.1           0.01%
                   [Pork]
Apples            Apples Honeycrisp        533        $2.4           0.04%       235       $36.9           0.12%
Sweet Goods &     Sw Gds: Swt/Flvrd        534        $2.4           0.04%       528       $13.9           0.04%
 Snacks            Loaves
Fluid Milk        Buttermilk               535        $2.4           0.04%       478       $15.9           0.05%
 Products
Cakes             Cakes: Sheet             536        $2.4           0.04%       750        $7.2           0.02%
Cookies           Cookies: Gourmet         537        $2.4           0.04%       399       $20.8           0.07%
Citrus            Grapefruit               538        $2.4           0.04%       388       $21.2           0.07%
Coffee &          Flavored Bag             539        $2.4           0.04%       328       $26.2           0.08%
 Creamers          Coffee
Stone Fruit       Plums                    540        $2.4           0.04%       543       $13.1           0.04%
Refrigerated      Refrigerated Pasta       541        $2.4           0.04%       290       $29.3           0.09%
 Italian
Spices &          Gourmet Spices           542        $2.4           0.04%       259       $33.2           0.11%
 Extracts
Baked Breads      Diet/Light Bread         543        $2.4           0.04%       356       $24.0           0.08%
Bacon             Bacon--Trad Center       544        $2.3           0.04%       395       $21.0           0.07%
                   Cut
Salad & Dips      Pasta/Grain              545        $2.3           0.04%       460       $16.9           0.05%
                   Salads--Bulk
Rice Cakes        Mini-Cakes               546        $2.3           0.04%       454       $17.2           0.05%
Authentic         Authentic Sauces/        547        $2.3           0.03%       678        $9.2           0.03%
 Hispanic Fds &    Salsa/Picante
 Product
Ice Cream Ice     Premium Pints [Ice       548        $2.3           0.03%       787        $6.5           0.02%
 Milk & Sherbets   Cream & Sherbert]
Can Fruit/Jar     Mandarin Oranges/        549        $2.3           0.03%       564       $12.6           0.04%
 Applesauce        Citrus Sect
Baby Foods        Baby Juices              550        $2.3           0.03%      1013        $3.1           0.01%
Salad Mix         Salad Mix Blends         551        $2.3           0.03%       239       $36.5           0.12%
                   Organic
Salad & Dips      Salad: Lettuce           552        $2.2           0.03%       576       $12.2           0.04%
Baked Breads      Fruit/Breakfast          553        $2.2           0.03%       427       $18.7           0.06%
                   Bread
Seafood--Salad/   Breading [Seafood]       554        $2.2           0.03%       966        $3.7           0.01%
 Dip/Sce/Cond
Seafood--Finfish  Finfish--Other           555        $2.2           0.03%       826        $5.8           0.02%
 Other
Frozen Bread/     Frzn Breadsticks         556        $2.2           0.03%       871        $5.0           0.02%
 Dough
Bag Snacks        Pork Skins/              557        $2.2           0.03%       804        $6.2           0.02%
                   Cracklins
Frozen Juice And  Frzn Conc Allieds        558        $2.2           0.03%       638       $10.1           0.03%
 Smoothies         Over 50% Juice
Broccoli/         Cauliflower Whole        559        $2.2           0.03%       352       $24.5           0.08%
 Cauliflower
Mushrooms         Mushrooms                560        $2.2           0.03%       372       $22.6           0.07%
                   Portabella
Tropical Fruit    Mango                    561        $2.2           0.03%       522       $14.1           0.04%
Seafood--Lobster  Lobster--Tails           562        $2.2           0.03%       546       $13.0           0.04%
Can Fruit/Jar     Apple Sauce              563        $2.2           0.03%       530       $13.8           0.04%
 Applesauce        (Excludes Cup)
Traditional       Mexican Peppers          564        $2.2           0.03%       487       $15.7           0.05%
 Mexican Foods     Chilies
Candy--Checklane  Mints/Candy &            565        $2.1           0.03%       582       $12.1           0.04%
                   Breath
Citrus            Tangerines &             566        $2.1           0.03%       600       $11.3           0.04%
                   Tangelos
Juices Super      Juices Smoothies/        567        $2.1           0.03%       613       $11.0           0.03%
 Premium           Blended
Can Vegetables--  Fried Onions             568        $2.1           0.03%       574       $12.3           0.04%
 Shelf Stable
Carrots           Carrots Bagged           569        $2.0           0.03%       453       $17.2           0.05%
Eggs/Muffins/     Eggs--Jumbo              570        $2.0           0.03%       548       $13.0           0.04%
 Potatoes
Potatoes          Potatoes Gourmet         571        $2.0           0.03%       405       $20.3           0.06%
Can Vegetables--  Sweet Potatoes           572        $2.0           0.03%       777        $6.7           0.02%
 Shelf Stable
Seafood--Value-   Value-Added Shrimp       573        $2.0           0.03%       840        $5.4           0.02%
 Added Seafood
Baked Breads      Rye Breads               574        $2.0           0.03%       375       $22.3           0.07%
Salad Dresing &   Dry Salad Dressing       575        $2.0           0.03%       498       $15.1           0.05%
 Sandwich          & Dip Mixes
 Spreads
Condiments &      Mustard--All Other       576        $2.0           0.03%       436       $18.3           0.06%
 Sauces
Fluid Milk        Organic Milk             577        $2.0           0.03%       245       $35.4           0.11%
 Products
Dry Mix Desserts  Gelatin                  578        $2.0           0.03%       517       $14.3           0.05%
Nuts              Sunflower/Other          579        $1.9           0.03%       656        $9.7           0.03%
                   Seeds
Vinegar &         Vinegar/White &          580        $1.9           0.03%       515       $14.4           0.05%
 Cooking Wines     Cider
Dinner Sausage    Dnr Sausage--            581        $1.9           0.03%       618       $10.9           0.03%
                   Poultry Rope Ckd
Corn              Corn Is Packaged         582        $1.9           0.03%       556       $12.8           0.04%
Candy--Packaged   Miscellaneous            583        $1.9           0.03%       607       $11.2           0.04%
                   Candy
Milk By-Products  Ricotta Cheese           584        $1.9           0.03%       490       $15.6           0.05%
Hot Cereal        Other Hot Cereal         585        $1.9           0.03%       628       $10.3           0.03%
Frozen Juice And  Frzn Oj&Oj               586        $1.9           0.03%       472       $16.2           0.05%
 Smoothies         Substitutes (Over
                   50%)
Sweet Goods &     Sw Gds: Brownie/         587        $1.9           0.03%       606       $11.2           0.04%
 Snacks            Bar Cookie
Rolls             Rolls: Bagels            588        $1.9           0.03%       494       $15.4           0.05%
Melons            Watermelon               589        $1.9           0.03%       477       $15.9           0.05%
                   Personal
Nuts              Pecans Shelled           590        $1.9           0.03%       448       $17.6           0.06%
Infant Formula    Baby Isotonic            591        $1.9           0.03%       878        $4.9           0.02%
                   Drinks
Mixers            Cocktail Mixes-          592        $1.9           0.03%       468       $16.4           0.05%
                   Fluid: Add Liq
Bananas           Bananas Organic          593        $1.9           0.03%       428       $18.7           0.06%
Seafood--Crab     Crab--King               594        $1.9           0.03%       725        $7.9           0.02%
Bacon             Bacon--Other             595        $1.9           0.03%       655        $9.7           0.03%
Can Fruit/Jar     Pears                    596        $1.9           0.03%       646       $10.0           0.03%
 Applesauce
Baking Mixes      Biscuit Flour &          597        $1.9           0.03%       529       $13.8           0.04%
                   Mixes
Chicken           Chicken Breast           598        $1.9           0.03%       343       $24.9           0.08%
 Specialty/        Boneless
 Natural
Sweet Goods       Sw Gds: Coffee           599        $1.8           0.03%       588       $11.9           0.04%
                   Cakes
Refrigerated      Eggs                     600        $1.8           0.03%       289       $29.5           0.09%
 Dairy Case
Condiments &      Wing Sauce               601        $1.8           0.03%       872        $5.0           0.02%
 Sauces
Seafood--Salmon-  Salmon Wc--Sockeye       602        $1.8           0.03%       335       $25.7           0.08%
 Wild Caught
Baking Needs      Pie Crust Mixes &        603        $1.8           0.03%       676        $9.3           0.03%
                   Shells
Salad Mix         Salad Spinach            604        $1.8           0.03%       442       $17.9           0.06%
Eggs/Muffins/     Eggs Substitute          605        $1.8           0.03%       329       $26.2           0.08%
 Potatoes
Crackers & Misc   Aerosol Cheese           606        $1.8           0.03%       857        $5.2           0.02%
 Baked Food
Poultry Other     Cornish Hen              607        $1.8           0.03%       773        $6.7           0.02%
Tomato Products-  Tomato Paste             608        $1.8           0.03%       633       $10.2           0.03%
 Shelf Stable
Turkey Frozen     Turkey Breast Bone       609        $1.8           0.03%       553       $12.8           0.04%
                   In
Sweet Goods &     Sw Gds: Puff             610        $1.8           0.03%       573       $12.3           0.04%
 Snacks            Pastry
Seafood--Catfish  Catfish--Whole           611        $1.8           0.03%     1,055        $2.6           0.01%
Cake Decor        Cake Decors &            612        $1.8           0.03%       645       $10.0           0.03%
                   Icing
Convenience/      Convenience/             613        $1.8           0.03%       670        $9.4           0.03%
 Snacking          Snacking Fruit
Salad & Dips      Sal: Salsa/Dips          614        $1.8           0.03%       730        $7.7           0.02%
                   Bulk
Pork Bone In      Dry [Pork Bone In        615        $1.8           0.03%       734        $7.6           0.02%
 Loin/Rib          Loin/Rib]
Authentic         Authentic Pasta/         616        $1.7           0.03%       884        $4.8           0.02%
 Hispanic Fds &    Rice/Beans
 Product
Spices &          Pure Extracts            617        $1.7           0.03%       493       $15.4           0.05%
 Extracts
Powder & Crystal  Enhanced Stick           618        $1.7           0.03%       621       $10.7           0.03%
 Drink Mix         [Powder Drink
                   Mix]
Bread             Bread: Artisan           619        $1.7           0.03%       237       $36.7           0.12%
Infant Formula    Infant Formula Soy       620        $1.7           0.03%     1,270        $1.1           0.00%
                   Base
Juices Super      Juices Proteins          621        $1.7           0.03%       640       $10.1           0.03%
 Premium
Salad & Dips      Sal: Dip Prepack         622        $1.7           0.03%       584       $12.1           0.04%
                   [Salad & Dips]
Dietary Aid       Diet Energy Drinks       623        $1.7           0.03%       554       $12.8           0.04%
 Prdct/Med Liq
 Nutr
Nuts              Peanuts All              624        $1.7           0.03%       594       $11.5           0.04%
Rts/Micro Soup/   Microwavable Soups       625        $1.7           0.03%       495       $15.3           0.05%
 Broth
Service Case      Marinated Pork           626        $1.7           0.03%       519       $14.3           0.05%
 Meat
Chicken &         Chix: Baked 8pc          627        $1.7           0.03%       837        $5.5           0.02%
 Poultry           Cut Up (Cold)
Vegetables        Beans                    628        $1.7           0.03%       457       $16.9           0.05%
 Cooking Bulk
Baby Foods        Baby Spring Waters       629        $1.7           0.03%     1,128        $2.0           0.01%
Shelf Stable      Tomato Juice (Over       630        $1.7           0.03%       662        $9.6           0.03%
 Juice             50% Jce)
Authentic         Authentic                631        $1.7           0.03%       998        $3.2           0.01%
 Hispanic Fds &    Vegetables And
 Product           Foods
Meat Snacks       Meat Sticks/Bites        632        $1.7           0.03%       972        $3.6           0.01%
Refrigerated      Hispanic Cheese          633        $1.7           0.03%       769        $6.9           0.02%
 Hispanic
 Grocery
Can Fruit/Jar     Cranberry Sauce          634        $1.7           0.03%       642       $10.0           0.03%
 Applesauce
Fitness & Diet    Fitness & Diet--         635        $1.7           0.03%       298       $28.7           0.09%
                   Bars W/O Flour
Pies              Pies: Cream/             636        $1.6           0.02%       728        $7.8           0.02%
                   Meringue
Berries           Strawberries             637        $1.6           0.02%       386       $21.4           0.07%
                   Organic
Candy--Packaged   Novelty Candy            638        $1.6           0.02%       827        $5.7           0.02%
Party Tray        Deli Tray:               639        $1.6           0.02%       636       $10.2           0.03%
                   Sandwiches
Value-Added       Cut Fruit All            640        $1.6           0.02%       704        $8.5           0.03%
 Fruit             Other Prepack
Nuts              Walnuts Shelled          641        $1.6           0.02%       431       $18.5           0.06%
Turkey Offal      External [Turkey]        642        $1.6           0.02%     1,133        $2.0           0.01%
Flour & Meals     Flour: Misc/             643        $1.6           0.02%       533       $13.6           0.04%
                   Specialty/Blend
Frozen Ethnic     Frozen                   644        $1.6           0.02%       771        $6.7           0.02%
                   Internaional
                   [Ethnic Foods]
Deli Meat:        Deli Meat:               645        $1.6           0.02%       336       $25.5           0.08%
 Presliced         Specialty Dry
                   Meats
Dressings/Dips    Dressing Creamy          646        $1.6           0.02%       512       $14.5           0.05%
Spices &          Table Salt/Popcorn       647        $1.6           0.02%       698        $8.6           0.03%
 Extracts          Salt
Meat--Shelf       Hash: Canned             648        $1.6           0.02%       863        $5.1           0.02%
 Stable            [Meat]
Water--(Sparklin  Distilled Water          649        $1.6           0.02%       579       $12.2           0.04%
 g & Still)
Frozen Desserts   Frzn Pastry &            650        $1.6           0.02%       694        $8.8           0.03%
                   Cookies
Potatoes          Potatoes Gold            651        $1.6           0.02%       503       $14.8           0.05%
                   (Bulk & Bag)
Herbs/Garlic      Garlic Whole             652        $1.6           0.02%       557       $12.7           0.04%
                   Cloves
Salad Mix         Coleslaw                 653        $1.6           0.02%       589       $11.9           0.04%
Apples            Caramel/Candy            654        $1.6           0.02%       985        $3.4           0.01%
                   Apples
Nuts              Almonds Shelled          655        $1.5           0.02%       412       $19.8           0.06%
Service Case      Marinated Poultry        656        $1.5           0.02%       702        $8.5           0.03%
 Meat
Carrots           Carrots Bagged           657        $1.5           0.02%       429       $18.6           0.06%
                   Organic
Frozen Desserts   Single Serv/             658        $1.5           0.02%       898        $4.6           0.01%
                   Portion Control
Seasonal          Pumpkins                 659        $1.5           0.02%       626       $10.3           0.03%
Chicken Offal     Internal [Chicken        660        $1.5           0.02%       929        $4.3           0.01%
                   Offal]
Specialty Cheese  Specialty Ppk            661        $1.5           0.02%       299       $28.7           0.09%
 Pre Pack          Cheese Hard/
                   Grated
Pears             Pears Bartlett           662        $1.5           0.02%       486       $15.7           0.05%
Meat--Shelf       Beef Stew                663        $1.5           0.02%       897        $4.6           0.01%
 Stable
Bread             Bread: Pita/Pocket/      664        $1.5           0.02%       523       $14.1           0.04%
                   Flatbrd
Chicken &         Chix: Rotisserie         665        $1.5           0.02%       848        $5.4           0.02%
 Poultry           Cold
Dry/Ramen         Bouillon                 666        $1.5           0.02%       663        $9.6           0.03%
 Bouillon
Nuts              Trail Mix                667        $1.5           0.02%       610       $11.0           0.03%
Enhancements      Enhancements--Sala       668        $1.5           0.02%       858        $5.2           0.02%
 (Pickles/         ds/Spreads
 Spreads)
Smoked Pork       Bacon--Belly/Jowl        669        $1.5           0.02%       783        $6.6           0.02%
Seafood--Cod      Cod--Fillet              670        $1.5           0.02%       587       $12.0           0.04%
Refrgrated Dough  Refrigerated             671        $1.5           0.02%       834        $5.5           0.02%
 Products          Cookies--Seasonal
Traditional       Asian Soy Sauce          672        $1.5           0.02%       630       $10.3           0.03%
 Asian Foods
Salad Dresing &   Sand/Horseradish &       673        $1.4           0.02%       749        $7.2           0.02%
 Sandwich          Tartar Sauce
 Spreads
Refrgrated Dough  Refrigerated Pie         674        $1.4           0.02%       538       $13.5           0.04%
 Products          Crust
Frozen Juice And  Frzn Fruit Drinks        675        $1.4           0.02%       685        $9.1           0.03%
 Smoothies         (Under 10% Juice)
Sweet Goods &     Sw Gds: Specialty        676        $1.4           0.02%       784        $6.6           0.02%
 Snacks            Desserts
Dinner Mixes-Dry  Pizza Mix Dry            677        $1.4           0.02%       845        $5.4           0.02%
Authentic         Central American         678        $1.4           0.02%       838        $5.5           0.02%
 Central           Foods
 American Fds
Cereal Bars       Breakfast Bars/          679        $1.4           0.02%       360       $23.6           0.07%
                   Tarts/Scones
Service Case      Seasoned Beef            680        $1.4           0.02%       724        $7.9           0.03%
 Meat
Herbs/Garlic      Herbs Cilanto            681        $1.4           0.02%       637       $10.1           0.03%
Value-Added       Fruit Party Tray         682        $1.4           0.02%       785        $6.5           0.02%
 Fruit             Prepack
Dried Fruit       Dried Fruit--Other       683        $1.4           0.02%       491       $15.6           0.05%
Non-Dairy/Dairy   Aseptic Milk             684        $1.4           0.02%       535       $13.6           0.04%
 Aseptic
Eggs/Muffins/     Misc Dairy               685        $1.4           0.02%       686        $9.1           0.03%
 Potatoes          Refigerated
Shelf Stable      Pineapple Juice          686        $1.4           0.02%       788        $6.4           0.02%
 Juice             (Over 50% Juice)
Frozen Entrees    Meatless/                687        $1.4           0.02%       382       $21.5           0.07%
                   Vegetarian
Powder & Crystal  Sugar Sweetened          688        $1.4           0.02%     1,071        $2.5           0.01%
 Drink Mix         Sticks
Lunchmeat         Lunchmeat--Other         689        $1.4           0.02%       951        $3.9           0.01%
Dietary Aid       Diet Cntrl Bars          690        $1.4           0.02%       409       $19.9           0.06%
 Prdct/Med Liq     Nutritional
 Nutr
Popcorn           Popcorn--Other           691        $1.4           0.02%       641       $10.0           0.03%
Salad & Dips      Sal: Desserts-           692        $1.4           0.02%       906        $4.5           0.01%
                   Prepack
Dry Cheese        Misc Dry Cheese          693        $1.4           0.02%       739        $7.3           0.02%
Shelf Stable      Cranberry Juice          694        $1.4           0.02%       706        $8.4           0.03%
 Juice             (Over 50% Juice)
Baking Mixes      Cookies Mix              695        $1.4           0.02%       699        $8.6           0.03%
Frozen Potatoes   Frzn Baked/Stuffed/      696        $1.3           0.02%       689        $9.0           0.03%
                   Mashed
Turkey Fresh      Whole Hen (Under         697        $1.3           0.02%       658        $9.7           0.03%
                   16lbs) [Turkey]
Vegetables        Broccoli/                698        $1.3           0.02%       567       $12.5           0.04%
 Cooking           Cauliflower
 Packaged          Processed
Dressings/Dips    Dips Caramel/Fruit       699        $1.3           0.02%       819        $5.9           0.02%
                   Glazes
Dressings/Dips    Dips Guacamole/          700        $1.3           0.02%       563       $12.6           0.04%
                   Salsa/Queso
Meat--Shelf       Hot Dog Chili            701        $1.3           0.02%     1,063        $2.6           0.01%
 Stable            Sauce
Breakfast         Bkfst Sausage--          702        $1.3           0.02%       986        $3.4           0.01%
 Sausage           Bkfast Side
Traditional       Asian Noodles/Rice       703        $1.3           0.02%       623       $10.5           0.03%
 Asian Foods
Deli Meat:        Deli Meat: Semi-         704        $1.3           0.02%       674        $9.3           0.03%
 Presliced         Dry Sausage
Breakfast         Bkfst Sausage--          705        $1.3           0.02%       916        $4.4           0.01%
 Sausage           Other Forms
Shortening & Oil  Corn Oil                 706        $1.3           0.02%       943        $4.1           0.01%
Nuts              Almonds                  707        $1.3           0.02%       404       $20.5           0.06%
Hot Cereal        Instant Breakfast        708        $1.3           0.02%       718        $8.1           0.03%
Traditional       Asian Foods And          709        $1.3           0.02%       793        $6.3           0.02%
 Asian Foods       Meals
Can Vegetables--  Mixed Vegetables         710        $1.3           0.02%       905        $4.5           0.01%
 Shelf Stable
Authentic         Authentic Peppers        711        $1.3           0.02%       910        $4.5           0.01%
 Hispanic Fds &
 Product
Dinner Sausage    Dnr Sausage--Links       712        $1.3           0.02%       766        $7.0           0.02%
                   Poultry Ck
Snack             Tortilla Chips           713        $1.3           0.02%       408       $19.9           0.06%
Salad & Dips      Sal: Salsa Prepack       714        $1.3           0.02%       531       $13.7           0.04%
Fluid Milk        Soy Milk                 715        $1.3           0.02%       753        $7.1           0.02%
 Products
Bread             Bread: Sweet/            716        $1.3           0.02%       707        $8.4           0.03%
                   Breakfast
Bulk Food         Trail Mix/Nuts           717        $1.3           0.02%       441       $18.0           0.06%
                   Bulk
Service Case      Seasoned Pork            718        $1.3           0.02%       744        $7.3           0.02%
 Meat
Refrigerated      Vegetarian Meats         719        $1.3           0.02%       625       $10.4           0.03%
 Vegetarian
Candy--Packaged   Seasonal                 720        $1.2           0.02%       754        $7.1           0.02%
                   Miscellaneous W/
                   Flour [Candy]
Teas              Tea Bags/Green           721        $1.2           0.02%       604       $11.2           0.04%
Chicken           Chicken Wings            722        $1.2           0.02%     1,111        $2.1           0.01%
 Specialty/
 Natural
Refrgrated Dough  Refrigerated             723        $1.2           0.02%       634       $10.2           0.03%
 Products          Breads
Shelf Stable      Lemon Juice & Lime       724        $1.2           0.02%       727        $7.8           0.02%
 Juice             Juice
Specialty Cheese  Specialty Ppk            725        $1.2           0.02%       469       $16.2           0.05%
 Pre Pack          Cheese Spreads
Baking            Flours/Grains/           726        $1.2           0.02%       509       $14.6           0.05%
                   Sugar
Smoked Hams       Hams--Dry Cured/         727        $1.2           0.02%       917        $4.4           0.01%
                   Country
Coffee &          Specialty Instant        728        $1.2           0.02%       732        $7.7           0.02%
 Creamers          Coffee W/Swe
Cookies           Fruit Filled             729        $1.2           0.02%       601       $11.3           0.04%
                   Cookies
Traditional       Mexican Con Queso        730        $1.2           0.02%     1,009        $3.1           0.01%
 Mexican Foods
Nuts              Dry Roast Peanuts        731        $1.2           0.02%       479       $15.9           0.05%
Can Seafood--     Sardines                 732        $1.2           0.02%       822        $5.8           0.02%
 Shelf Stable
Service Case      Stuffed/Mixed            733        $1.2           0.02%       717        $8.2           0.03%
 Meat              Poultry
Citrus            Oranges Non Navel        734        $1.2           0.02%       868        $5.0           0.02%
                   All
Seafood--Catfish  Catfish--Nuggets         735        $1.2           0.02%     1,151        $1.8           0.01%
Snack             Soy/Rice Snacks          736        $1.2           0.02%       488       $15.7           0.05%
Bread             Bread: Sourdough         737        $1.2           0.02%       456       $17.1           0.05%
Refrigerated      Misc Hispanic            738        $1.2           0.02%       635       $10.2           0.03%
 Hispanic          Grocery
 Grocery
Prepared/Pdgd     Boxed Prepared/          739        $1.2           0.02%       489       $15.6           0.05%
 Foods             Entree/Dry Prep
Shelf Stable      Prune Juice (Over        740        $1.2           0.02%       711        $8.3           0.03%
 Juice             50% Juice)
Specialty Cheese  Specialty Ppk            741        $1.2           0.02%       433       $18.5           0.06%
 Pre Pack          Cheese Feta
Teas              Instant Tea & Tea        742        $1.1           0.02%       914        $4.4           0.01%
                   Mix (W/Sugar)
Pre-Slice         Pre-Sliced Semi-         743        $1.1           0.02%       514       $14.4           0.05%
 Service Case      Soft Cheese
 Cheese
Shortening & Oil  Cooking Oil:             744        $1.1           0.02%       775        $6.7           0.02%
                   Peanut/Safflower
Authentic         Hispanic Cookies         745        $1.1           0.02%     1,152        $1.8           0.01%
 Hispanic Fds &    Crackers
 Product
Can Vegetables--  Carrots                  746        $1.1           0.02%       900        $4.5           0.01%
 Shelf Stable
Juice Drinks--    Juice (Over 50%          747        $1.1           0.02%       659        $9.7           0.03%
 Carb              juice)
Juices Super      Juice Single Blend       748        $1.1           0.02%       673        $9.4           0.03%
 Premium
Nuts              Oil Roast Peanuts        749        $1.1           0.02%       615       $10.9           0.03%
Beef: Thin Meats  Skirt [Beef]             750        $1.1           0.02%       798        $6.3           0.02%
Nuts              Nuts Other               751        $1.1           0.02%       593       $11.5           0.04%
Peppers           Peppers Yellow           752        $1.1           0.02%       599       $11.4           0.04%
                   Bell
Baking Needs      Baking Powder &          753        $1.1           0.02%       715        $8.2           0.03%
                   Soda
Frzn Meatless     Meatless Burgers         754        $1.1           0.02%       639       $10.1           0.03%
Candy--Checklane  Misc Checklane           755        $1.1           0.02%     1,052        $2.6           0.01%
                   Candy
Pears             Pears Anjou              756        $1.1           0.02%       649        $9.8           0.03%
Powder & Crystal  Fluid Pouch              757        $1.1           0.02%       781        $6.6           0.02%
 Drink Mix         [Powder Drink
                   Mix]
Pasta & Pizza     Pizza Sauce              758        $1.1           0.02%       810        $6.1           0.02%
 Sauce
Spices/Jarred     Garlic Jar               759        $1.1           0.02%       729        $7.7           0.02%
 Garlic
Sweet Goods &     Sweet Goods: Candy       760        $1.1           0.02%       920        $4.4           0.01%
 Snacks
Soft Drinks       Tea Bottles With         761        $1.1           0.02%     1,148        $1.9           0.01%
                   Sweetener/Sugar
Random Weight     Lunch Meats              762        $1.1           0.02%       947        $4.0           0.01%
 Meat Products
Authentic         Hispanic                 763        $1.1           0.02%       979        $3.5           0.01%
 Hispanic Fds &    Carbonated
 Product           Beverages
Isotonic Drinks   Isotonic Drinks          764        $1.1           0.02%       889        $4.7           0.01%
                   Multi-Serve
Juices Super      Juices Antioxidant/      765        $1.0           0.02%       719        $8.1           0.03%
 Premium           Wellness
Spices/Jarred     Spices &                 766        $1.0           0.02%       892        $4.6           0.01%
 Garlic            Seasonings
Trail Mix &       Trail Mixes/Snack        767        $1.0           0.02%       650        $9.8           0.03%
 Snacks
Lunchmeat         Lunchmeat--Natural/      768        $1.0           0.02%       559       $12.7           0.04%
                   Organic
Lunchmeat         Lunchmeat--Peggabl       769        $1.0           0.02%       877        $4.9           0.02%
                   e Deli Fresh
Bread             Bread: Tortillas/        770        $1.0           0.02%       648        $9.8           0.03%
                   Wraps
Ice Cream Ice     Quarts [Ice Cream        771        $1.0           0.02%       924        $4.3           0.01%
 Milk & Sherbets   & Sherbert]
Infant Formula    Infant Formula Up        772        $1.0           0.02%     1,015        $3.0           0.01%
                   Age
Tropical Fruit    Kiwi Fruit               773        $1.0           0.02%       764        $7.0           0.02%
Peppers           Peppers Jalapeno         774        $1.0           0.02%       911        $4.4           0.01%
Tomatoes          Tomatoes Cherry          775        $1.0           0.02%       580       $12.1           0.04%
Trail Mix &       Candy W/O Flour          776        $1.0           0.02%       844        $5.4           0.02%
 Snacks
Condiments        Oils/Vinegar             777        $1.0           0.02%       643       $10.0           0.03%
Value-Added       Instore Cut              778        $1.0           0.02%       654        $9.7           0.03%
 Vegetables        Vegetables
Candy--Packaged   Candy Boxed              779        $1.0           0.02%       852        $5.3           0.02%
                   Chocolates W/
                   Flour
Dried Fruit       Dried Plums              780        $1.0           0.02%       609       $11.0           0.03%
Shelf Stable      Apple Juice &            781        $1.0           0.02%     1,024        $3.0           0.01%
 Juice             Cider (50% And
                   Under)
Pre-Slice         Pre-Sliced Semi-         782        $1.0           0.02%       520       $14.3           0.05%
 Service Case      Hard [Cheese]
 Cheese
Tomato Products-  Tomato Stewed            783        $1.0           0.02%       790        $6.4           0.02%
 Shelf Stable
Nuts              Misc Snack Nuts          784        $1.0           0.02%       726        $7.8           0.02%
Beef: Thin Meats  Flank [Beef]             785        $1.0           0.02%       547       $13.0           0.04%
Cookies           Cookies: Message         786        $1.0           0.02%       876        $4.9           0.02%
Baking Mixes      Miscellaneous            787        $1.0           0.02%       752        $7.2           0.02%
                   Package Mixes
Mediterranean     Sal: Olives/             788        $1.0           0.02%       492       $15.5           0.05%
 Bar               Pickles--Bulk
Dry Sce/Gravy/    Cooking Bags With        789        $1.0           0.01%     1,078        $2.4           0.01%
 Potatoes/         Spices/Season
 Stuffng
Stone Fruit       Cherries Ranier          790        $1.0           0.01%       691        $9.0           0.03%
Energy Drinks     Energy Drink--           791        $1.0           0.01%       671        $9.4           0.03%
                   Multi-Pack
Meat--Shelf       Beef/Pork--Dried         792        $1.0           0.01%       990        $3.3           0.01%
 Stable            Sliced
Cookies           Cookies/Sweet            793        $1.0           0.01%       542       $13.1           0.04%
                   Goods
Turkey Fresh      Whole Tom (Over          794        $1.0           0.01%       747        $7.3           0.02%
                   16lbs) [Turkey]
Ss/Vending--      Vending Size/Sngl        795        $1.0           0.01%     1,090        $2.3           0.01%
 Cookie/Cracker    Serve Cracker
Can Vegetables--  White Potatoes           796        $1.0           0.01%       927        $4.3           0.01%
 Shelf Stable
Can Seafood--     Oysters                  797        $0.9           0.01%     1,025        $3.0           0.01%
 Shelf Stable
Dressings/Dips    Dips Veggie              798        $0.9           0.01%       740        $7.3           0.02%
Snacks            Snacks: Pita Chips       799        $0.9           0.01%       484       $15.7           0.05%
Candy--Packaged   Candy Boxed              800        $0.9           0.01%       772        $6.7           0.02%
                   Chocolates
Chicken Grinds    Ground Chicken           801        $0.9           0.01%       767        $6.9           0.02%
Candy--Packaged   Seasonal Candy Box       802        $0.9           0.01%       949        $4.0           0.01%
                   Non-Chocola
Frozen Meat       Alternatives Soy/        803        $0.9           0.01%       688        $9.0           0.03%
                   Tofu
Can Vegetables--  Kraut & Cabbage          804        $0.9           0.01%       814        $6.0           0.02%
 Shelf Stable
Cereals           Granola                  805        $0.9           0.01%       501       $15.1           0.05%
Baking Needs      Cooking Chocolate        806        $0.9           0.01%       627       $10.3           0.03%
                   (Ex Smi-Swt)
Candy--Packaged   Candy Box Non-           807        $0.9           0.01%       953        $3.9           0.01%
                   Chocolate
Dinner Sausage    Dnr Sausage--            808        $0.9           0.01%       585       $12.1           0.04%
                   Natural/Organic
Dressings/Dips    Dressing Blue            809        $0.9           0.01%       666        $9.5           0.03%
                   Cheese
Herbs/Garlic      Herbs Fresh Other        810        $0.9           0.01%       518       $14.3           0.05%
                   Organic
Shelf Stable      Tomato Juice (50%        811        $0.9           0.01%       975        $3.5           0.01%
 Juice             And Under)
Popcorn           Caramel Coated           812        $0.9           0.01%     1,006        $3.1           0.01%
                   Snacks
Deli Meat:        Deli Meat: Turkey        813        $0.9           0.01%       516       $14.3           0.05%
 Presliced
Cake Decor        Cake Decors--            814        $0.9           0.01%       841        $5.4           0.02%
                   Candies
Specialty Cheese  Specialty Ppk            815        $0.9           0.01%       471       $16.2           0.05%
 Pre Pack          Cheese Mozzarell
Shelf Stable      Cranapple/Cran           816        $0.9           0.01%       797        $6.3           0.02%
 Juice             Grape Juice
Rtd Tea/New Age   Juice (Over 50%          817        $0.9           0.01%     1,047        $2.7           0.01%
 Juice             Juice)
Crackers & Misc   Specialty Crackers       818        $0.9           0.01%       444       $17.8           0.06%
 Baked Food
Salad & Dips      Salad Bar                819        $0.9           0.01%       644       $10.0           0.03%
Service Case      Marinated Beef           820        $0.9           0.01%       782        $6.6           0.02%
 Meat
Juice             Non-Carb Jce             821        $0.9           0.01%       880        $4.8           0.02%
                   (Under 50% Juice)
Organics Fruit &  Organic Salad Mix        822        $0.9           0.01%       499       $15.1           0.05%
 Vegetables
Chilled Ready     Store Brand              823        $0.9           0.01%       932        $4.2           0.01%
 Meals
Frzn Meatless     Meatless Breakfast       824        $0.9           0.01%       697        $8.6           0.03%
Dry Tea/Coffee/   Tea Bags                 825        $0.9           0.01%       681        $9.2           0.03%
 Coco Mixes        (Supplement)
Melons            Watermelon W/Seeds       826        $0.9           0.01%     1,019        $3.0           0.01%
                   Whole
Dry Mix Desserts  Misc: Cheesecake/        827        $0.9           0.01%     1,087        $2.3           0.01%
                   Mousse Mixes
Value-Added       Parfait Cups             828        $0.8           0.01%     1,032        $2.9           0.01%
 Fruit             Instore
Vinegar &         Specialty Vinegar        829        $0.8           0.01%       552       $12.9           0.04%
 Cooking Wines
Pork Shoulder     Fresh Hams               830        $0.8           0.01%     1,030        $2.9           0.01%
Specialty Cheese  Specialty Ppk            831        $0.8           0.01%       815        $6.0           0.02%
 Pre Pack          Cheese Processed
Turkey Smoked     Turkey Wings             832        $0.8           0.01%     1,228        $1.3           0.00%
Frzn Seafood      Frz Non-Coated           833        $0.8           0.01%       860        $5.2           0.02%
                   Fish Fillets
Vegetables Salad  Radish                   834        $0.8           0.01%       713        $8.3           0.03%
Cookies           Specialty Cookies        835        $0.8           0.01%       622       $10.7           0.03%
Traditional       Traditional Thai         836        $0.8           0.01%       710        $8.3           0.03%
 Asian Foods       Foods
Yogurt            Yogurt/Adult             837        $0.8           0.01%       958        $3.8           0.01%
                   Drinks
Specialty Cheese  Specialty Ppk            838        $0.8           0.01%       527       $13.9           0.04%
 Pre Pack          Cheese Cheddar
Peppers           Peppers All Other        839        $0.8           0.01%       864        $5.1           0.02%
Pickle/Relish/    Pickld Veg/Peppers/      840        $0.8           0.01%       820        $5.9           0.02%
 Pckld Veg &       Etc.
 Olives
Candy--Packaged   Candy Bags-Non           841        $0.8           0.01%       965        $3.7           0.01%
                   Chocolate W/Flour
Frozen Juice And  Frzn Conc Under          842        $0.8           0.01%       983        $3.4           0.01%
 Smoothies         50% Juice
Pickle/Relish/    Specialty Olives         843        $0.8           0.01%       614       $11.0           0.03%
 Pckld Veg &
 Olives
Salad & Dips      Sal: Desserts--          844        $0.8           0.01%       890        $4.7           0.01%
                   Bulk
Authentic Asian   Authentic Japanese       845        $0.8           0.01%       755        $7.1           0.02%
 Foods             Foods
Crackers          Crackers                 846        $0.8           0.01%       508       $14.6           0.05%
Smoked Pork       Smoked Picnics           847        $0.8           0.01%     1,105        $2.2           0.01%
                   [Pork]
Condiments        Nut Butters/Peanut       848        $0.8           0.01%       549       $12.9           0.04%
                   Butter
Tomato Products-  Tomatoes/Whole           849        $0.8           0.01%       865        $5.1           0.02%
 Shelf Stable
Party Tray Deli   Tray: Appetizers &       850        $0.8           0.01%       957        $3.9           0.01%
                   Hors D'oe
Soup              Cans Soup/Chili          851        $0.8           0.01%       561       $12.7           0.04%
Service Case      Kabobs Beef              852        $0.8           0.01%       843        $5.4           0.02%
 Meat
Vegetables Salad  Variety Lettuce          853        $0.8           0.01%       568       $12.5           0.04%
                   Organic
Melons            Honeydew Whole           854        $0.8           0.01%       817        $5.9           0.02%
Grapes            Grapes Red Globe         855        $0.8           0.01%       980        $3.5           0.01%
Condiments &      Chili Sauce/             856        $0.7           0.01%       813        $6.0           0.02%
 Sauces            Cocktail Sauce
Tropical Fruit    Pomegranates             857        $0.7           0.01%       926        $4.3           0.01%
Organics Fruit &  Organic Value-           858        $0.7           0.01%       762        $7.0           0.02%
 Vegetables        Added Vegetables
Grapes            Grapes Other             859        $0.7           0.01%       960        $3.8           0.01%
Chicken Fresh     Mixed Packs              860        $0.7           0.01%       923        $4.3           0.01%
                   [Chicken]
Nuts              Nuts Inshell             861        $0.7           0.01%       894        $4.6           0.01%
Authentic         Hispanic Juice           862        $0.7           0.01%     1,123        $2.0           0.01%
 Hispanic Fds &    Under 50% Juice
 Product
Coffee &          Flavored Can             863        $0.7           0.01%       823        $5.8           0.02%
 Creamers          Coffee
Prepared/Pdgd     Vegetables/Dry           864        $0.7           0.01%       575       $12.2           0.04%
 Foods             Beans
Bread             Bread: Rye/              865        $0.7           0.01%       720        $8.1           0.03%
                   Cocktail
Baking Needs      Maraschino               866        $0.7           0.01%       944        $4.1           0.01%
                   Cherries
Seafood--Crab     Crab--Dungy              867        $0.7           0.01%       952        $3.9           0.01%
Bread             Whole Grain Bread        868        $0.7           0.01%       680        $9.2           0.03%
Smoked Hams       Hams--Whole Bone-        869        $0.7           0.01%     1,092        $2.3           0.01%
                   In
Apples            Apples Braeburn          870        $0.7           0.01%       668        $9.4           0.03%
                   (Bulk & Bag)
Shelf Stable      Grapefruit Juice         871        $0.7           0.01%       939        $4.1           0.01%
 Juice             (Over 50% Juice)
Water             Fortified/Water          872        $0.7           0.01%       913        $4.4           0.01%
Meat--Shelf       Potted Meats And         873        $0.7           0.01%     1,103        $2.2           0.01%
 Stable            Spreads
Water--(Sparklin  Sparkling Water--        874        $0.7           0.01%       581       $12.1           0.04%
 g & Still)        Unflavored
Seafood--Trout    Steelhead Fr             875        $0.7           0.01%       812        $6.0           0.02%
                   [Trout]
Can Vegetables--  Beets                    876        $0.7           0.01%       825        $5.8           0.02%
 Shelf Stable
Frozen Juice And  Smoothies-Frozen         877        $0.7           0.01%       950        $4.0           0.01%
 Smoothies
Frozen Breakfast  Frzn Bagels              878        $0.7           0.01%     1,035        $2.9           0.01%
 Foods
Party Tray Deli   Tray: Fruit And          879        $0.7           0.01%       758        $7.1           0.02%
                   Vegetable
Chicken           Whole Chicken            880        $0.7           0.01%       902        $4.5           0.01%
 Specialty/        (Roasters/Fryer)
 Natural
Bread             Bread: Wheat/Whl         881        $0.7           0.01%       629       $10.3           0.03%
                   Grain
Non-Dairy/Dairy   Soy Beverage             882        $0.7           0.01%       849        $5.3           0.02%
 Aseptic
Fitness & Diet    Fitness & Diet-          883        $0.7           0.01%       741        $7.3           0.02%
                   Powder Ntrtnl
Frzn Meatless     Meatless Poultry         884        $0.7           0.01%       799        $6.2           0.02%
Pies              Pies: Sugar Free         885        $0.7           0.01%       904        $4.5           0.01%
Dinner Sausage    Dnr Sausage--Fresh       886        $0.7           0.01%       918        $4.4           0.01%
                   Poultry
Spices &          Imitation Extracts       887        $0.7           0.01%       973        $3.5           0.01%
 Extracts
Beverages         Can/Btl Carb Beve        888        $0.7           0.01%       736        $7.6           0.02%
                   50% And Under
Vegetables        Vegetables Cooking       889        $0.7           0.01%       821        $5.9           0.02%
 Cooking           Packaged
 Packaged
Frozen Vegetable  Fz Box Vegetables--      890        $0.7           0.01%       824        $5.8           0.02%
 & Veg Dish        Plain
Soup              Broths                   891        $0.7           0.01%       560       $12.7           0.04%
Bread             Bread: Brand             892        $0.7           0.01%       679        $9.2           0.03%
Can Vegetables--  Peas Fresh Pack/         893        $0.7           0.01%       978        $3.5           0.01%
 Shelf Stable      Crowder
Snacks            Snacks: Salty            894        $0.7           0.01%       703        $8.5           0.03%
Salad & Dips      Protein Salads--         895        $0.6           0.01%       946        $4.0           0.01%
                   Prepack
Turkey Smoked     Turkey Drums             896        $0.6           0.01%     1,250        $1.2           0.00%
Apples            Apples Gala (Bulk        897        $0.6           0.01%       672        $9.4           0.03%
                   & Bag) Organic
Stone Fruit       Peaches White            898        $0.6           0.01%       833        $5.5           0.02%
                   Flesh
Tomatoes          Tomatoes--Other          899        $0.6           0.01%     1,003        $3.2           0.01%
Service Case      Kabobs Poultry           900        $0.6           0.01%       879        $4.9           0.02%
 Meat
Frzn Meatless     Meatless                 901        $0.6           0.01%       869        $5.0           0.02%
                   Miscellaneous
Seafood--Scallop  Scallops--Sea            902        $0.6           0.01%       791        $6.4           0.02%
 s
Convenience/      Jarred Fruit Multi       903        $0.6           0.01%       901        $4.5           0.01%
 Snacking          Serve
Traditional       Asian Vegetables         904        $0.6           0.01%       847        $5.4           0.02%
 Asian Foods
Shelf Stable      Cranapple/Cran           905        $0.6           0.01%       760        $7.0           0.02%
 Juice             Grape Juice
Frozen Juice And  Cocktail Mixes-Frz       906        $0.6           0.01%     1,107        $2.2           0.01%
 Smoothies
Shelf Stable      Grapefruit Juice         907        $0.6           0.01%     1,007        $3.1           0.01%
 Juice             (50% And Under)
Tomato Products-  Tomato Crushed           908        $0.6           0.01%       780        $6.6           0.02%
 Shelf Stable
Condiments &      Misc Meat Sauces         909        $0.6           0.01%       962        $3.7           0.01%
 Sauces
Shelf Stable      Blended Juice &          910        $0.6           0.01%     1,022        $3.0           0.01%
 Juice             Combinations
Coffee &          Bulk Coffee              911        $0.6           0.01%       701        $8.6           0.03%
 Creamers
Specialty Cheese  Specialty Ppk            912        $0.6           0.01%       595       $11.4           0.04%
 Pre Pack          Cheese Semi Soft
Non-Dairy/Dairy   Nut Milk                 913        $0.6           0.01%       763        $7.0           0.02%
 Aseptic
Specialty Cheese  Specialty Ppk            914        $0.6           0.01%       620       $10.8           0.03%
 Pre Pack          Cheese Soft &
                   Ripe
Authentic         Authentic Soups/         915        $0.6           0.01%     1,200        $1.5           0.00%
 Hispanic Fds &    Bouillons
 Product
Authentic Asian   Authentic Chinese        916        $0.6           0.01%       931        $4.2           0.01%
 Foods             Foods
Baby Food         Baby Food                917        $0.6           0.01%       835        $5.5           0.02%
Deli Meat:        Deli Meat: Ham           918        $0.6           0.01%       665        $9.5           0.03%
 Presliced
Bacon             Bacon--Natural/          919        $0.6           0.01%       759        $7.1           0.02%
                   Organic
Frozen Potatoes   Frzn Onion Rings         920        $0.6           0.01%     1,177        $1.6           0.01%
Margarines        Margarine: Squeeze       921        $0.6           0.01%       930        $4.2           0.01%
Deli Specialties  Dl Spec: Dry/            922        $0.6           0.01%       850        $5.3           0.02%
 (Retail Pk)       Refrig Pastas
Seafood--Crab     Crab--Other              923        $0.6           0.01%     1,213        $1.4           0.00%
Specialty Cheese  Specialty Ppk            924        $0.6           0.01%       619       $10.8           0.03%
 Pre Pack          Cheese Blue/Gorg
Tomatoes          Tomatoes Others          925        $0.6           0.01%       808        $6.1           0.02%
                   Organic
Teas              Instant Tea & Tea        926        $0.6           0.01%     1,038        $2.9           0.01%
                   Mix
Refrigerated      Vegetarian Misc          927        $0.6           0.01%       963        $3.7           0.01%
 Vegetarian
Canned & Dry      Non Fat Dry Milk         928        $0.6           0.01%       859        $5.2           0.02%
 Milk
Refrigerated      Kefir                    929        $0.6           0.01%       751        $7.2           0.02%
 Dairy Case
Coffee &          Specialty Instant        930        $0.6           0.01%     1,043        $2.8           0.01%
 Creamers          Coffee
Can Vegetables--  Artichokes               931        $0.6           0.01%       682        $9.1           0.03%
 Shelf Stable
Soft Drinks       Mixers (Tonic            932        $0.5           0.01%       540       $13.2           0.04%
                   Water/Gngr Ale)
Refrigerated      Refrigerated Pasta       933        $0.5           0.01%       742        $7.3           0.02%
 Italian           Sauce
Baking Needs      Baking Cocoa             934        $0.5           0.01%       851        $5.3           0.02%
Vegetables Salad  Spinach Bulk             935        $0.5           0.01%       883        $4.8           0.02%
Infant Formula    Infant Formula           936        $0.5           0.01%     1,455        $0.3           0.00%
                   Milk Base
Seafood--Salad/   Dips/Spreads             937        $0.5           0.01%     1,069        $2.5           0.01%
 Dip/Sce/Cond
Authentic         Hispanic Baking          938        $0.5           0.01%     1,233        $1.3           0.00%
 Hispanic Fds &    Needs
 Product
Baking Needs      Marshmallow Creme        939        $0.5           0.01%       977        $3.5           0.01%
Buffalo           Grinds [Buffalo]         940        $0.5           0.01%       712        $8.3           0.03%
Baking Needs      Yeast: Dry               941        $0.5           0.01%       816        $5.9           0.02%
Lamb              Round/Leg [Lamb]         942        $0.5           0.01%       936        $4.2           0.01%
Seafood--Smoked   Seafood Smoked           943        $0.5           0.01%       709        $8.4           0.03%
                   Salmon
Processed         Packaged Dry Mixes       944        $0.5           0.01%     1,039        $2.9           0.01%
Frozen Meat       Micro Protein            945        $0.5           0.01%       899        $4.6           0.01%
 Alternatives      [Meats]
Refrgrated Dough  Misc Refrig Dough        946        $0.5           0.01%     1,162        $1.7           0.01%
 Products          Products
Deli Meat:        Deli Meat: Beef          947        $0.5           0.01%       862        $5.2           0.02%
 Presliced
Vegetables        Celery Organic           948        $0.5           0.01%       779        $6.6           0.02%
 Cooking Bulk
Cakes             Cakes: Creme/            949        $0.5           0.01%     1,171        $1.7           0.01%
                   Pudding Novelties
Lamb              Loin [Lamb]              950        $0.5           0.01%       882        $4.8           0.02%
Refrgratd Juices/ Dairy Case Tea No        951        $0.5           0.01%     1,002        $3.2           0.01%
 Drinks            Sugar Or Sweetner
Baking Needs      Coconut [Baking          952        $0.5           0.01%       873        $4.9           0.02%
                   Needs]
Salad Mix         Salad Spinach            953        $0.5           0.01%       696        $8.7           0.03%
                   Organic
Pork Grinds       Ground Pork              954        $0.5           0.01%       928        $4.3           0.01%
Processed         Squeeze Lemons/          955        $0.5           0.01%       988        $3.3           0.01%
                   Limes
Lamb              Chuck/Shoulder           956        $0.5           0.01%     1,083        $2.4           0.01%
                   [Lamb]
Berries           Raspberries              957        $0.5           0.01%       683        $9.1           0.03%
                   Organic
Rolls             Rolls: Biscuits/         958        $0.5           0.01%       886        $4.7           0.02%
                   Eng Muffins
Snacks            Snacks: Tortilla         959        $0.5           0.01%       874        $4.9           0.02%
                   Chips
Condiments        Honey/Syrup              960        $0.5           0.01%       921        $4.3           0.01%
Rice Cakes        Large Cakes              961        $0.5           0.01%       855        $5.2           0.02%
Authentic         Italian Vegetables       962        $0.5           0.01%       738        $7.4           0.02%
 Italian Foods
Dressings/Dips    Dips Fruit And           963        $0.5           0.01%     1,149        $1.9           0.01%
                   Chocolate
Potatoes          Potatoes Other           964        $0.5           0.01%       789        $6.4           0.02%
                   Organic
Juices Super      Juices (50% And          965        $0.5           0.01%     1,141        $1.9           0.01%
 Premium           Under Juice)
Specialty Cheese  Specialty Ppk            966        $0.5           0.01%     1,192        $1.5           0.00%
 Pre Pack          Cheese Hispanic
Seafood--Value-   Seafood Value-           967        $0.5           0.01%       997        $3.2           0.01%
 Added             Added Crab
Service Case      Stuffed/Mixed Pork       968        $0.5           0.01%     1,051        $2.7           0.01%
 Meat
Herbs/Garlic      Sprouts                  969        $0.5           0.01%       955        $3.9           0.01%
Pears             Pears Bosc               970        $0.5           0.01%       922        $4.3           0.01%
Meat--Shelf       Corn Beef                971        $0.5           0.01%     1,169        $1.7           0.01%
 Stable
Refrigerated      Non-Dairy Cheese         972        $0.5           0.01%       893        $4.6           0.01%
 Vegetarian
Isotonic Drinks   Sports Drink N/          973        $0.5           0.01%     1,017        $3.0           0.01%
                   Supplmnt Milk
Soft Drinks       Seltzer Unflavored       974        $0.5           0.01%       757        $7.1           0.02%
Refrigerated      Tofu                     975        $0.5           0.01%       809        $6.1           0.02%
 Vegetarian
Berries           Blueberries              976        $0.5           0.01%       660        $9.6           0.03%
                   Organic
Trail Mix &       Candy W/Flour            977        $0.5           0.01%     1,027        $2.9           0.01%
 Snacks
Cakes             Cakes: Cheesecake        978        $0.5           0.01%     1,115        $2.1           0.01%
                   Novelties
Water--(Sparklin  Sparkling Water--        979        $0.5           0.01%       675        $9.3           0.03%
 g & Still)        Flvrd Unsweetened
Powder & Crystal  Breakfast Crystals       980        $0.5           0.01%     1,209        $1.4           0.00%
 Drink Mix
Non-Dairy/Dairy   Rice Beverage            981        $0.5           0.01%       891        $4.6           0.01%
 Aseptic
Pies              Pies: Tarts/Minis/       982        $0.5           0.01%     1,045        $2.7           0.01%
                   Crstdas
Specialty Cheese  Specialty Ppk            983        $0.5           0.01%       721        $8.0           0.03%
 Pre Pack          Cheese Gouda &
                   Eda
Enhancements      Enhancements--Spic       984        $0.5           0.01%     1,082        $2.4           0.01%
 (Pickles/         es/Sauces
 Spreads)
Snacks            Snacks: Crackers/        985        $0.5           0.01%       705        $8.4           0.03%
                   Cookies
Baking Needs      Corn Starch              986        $0.5           0.01%     1,062        $2.6           0.01%
Candy--Packaged   Bulk Candy               987        $0.5           0.01%     1,031        $2.9           0.01%
Prepared/Pdgd     Pasta/Ramen              988        $0.5           0.01%       801        $6.2           0.02%
 Foods
Specialty Cheese  Specialty Ppk            989        $0.5           0.01%       624       $10.4           0.03%
 Pre Pack          Cheese Goat Milk
Herbs/Garlic      Herbs Basil              990        $0.4           0.01%       692        $9.0           0.03%
                   Organic
Bakery Party      Party Trays: Cakes       991        $0.4           0.01%     1,147        $1.9           0.01%
 Trays
Mushrooms         Mushrooms White          992        $0.4           0.01%       830        $5.7           0.02%
                   Bulk
Candy             Candy/Chocolate          993        $0.4           0.01%       786        $6.5           0.02%
Candy--Packaged   Seasonal Candy           994        $0.4           0.01%       999        $3.2           0.01%
                   Bags-Chocolate
Tomatoes          Tomatoes Cocktail        995        $0.4           0.01%       714        $8.3           0.03%
Pears             Pears Asian              996        $0.4           0.01%       961        $3.8           0.01%
Authentic         Caribbean Foods          997        $0.4           0.01%     1,273        $1.1           0.00%
 Caribbean Foods
Dry Bean Veg &    Misc Grain Mixes         998        $0.4           0.01%       735        $7.6           0.02%
 Rice
Can Vegetables--  Peas & Onions/Peas       999        $0.4           0.01%     1,136        $1.9           0.01%
 Shelf Stable      & Carrot
Seafood--Shellfi  Other Shellfish--      1,000        $0.4           0.01%     1,225        $1.3           0.00%
 sh                Other
                                               -----------------------------------------------------------------
  Top 1,000                                       $6,580.5            100%             $31,513.8            100%
   Totals
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.


EAppendix B. Crosswalk of Top 1,000 Subcommodities to Summary Categories
------------------------------------------------------------------------
       Commodity               Subcommodity           Summary Category
------------------------------------------------------------------------
Baby Food               Baby Food                  Baby food
Baby Foods              Baby Food--Beginner        Baby food
Baby Foods              Baby Food                  Junior/All Brands
                                                    Baby food
Baby Foods              Baby Food                  Cereals Baby food
Baby Foods              Baby Juices                Baby food
Baby Foods              Baby Spring Waters         Baby food
Infant Formula          Infant Formula             Starter/Solutio Baby
                                                    food
Infant Formula          Infant Formula             Specialty Baby food
Infant Formula          Infant Formula             Starter Large P Baby
                                                    food
Infant Formula          Infant Formula             Toddler Baby food
Infant Formula          Infant Formula             Solutions Large Baby
                                                    food
Infant Formula          Infant Formula             Concentrate Baby food
Infant Formula          Infant Formula             Ready To Use Baby
                                                    food
Infant Formula          Baby Isotonic Drinks       Baby food
Infant Formula          Infant Formula Soy Base    Baby food
Infant Formula          Infant Formula Up Age      Baby food
Infant Formula          Infant Formula Milk Base   Baby food
Can Beans               Prepared Beans--Baked W/   Beans
                         Pork
Can Beans               Variety Beans--Kidney/     Beans
                         Pinto/E
Dry Bean Veg & Rice     Dry Beans/Peas/Barley:     Beans
                         Bag & B
Frozen Meat             Soy/Tofu                   Beans
 Alternatives
Salad & Dips            Sal: Hommus                Beans
Traditional Mexican     Mexican Beans/Refried      Beans
 Foods
Vegetables Cooking      Beans                      Beans
 Bulk
Frozen Ice              Ice--Crushed/Cubed         Bottled water
Water                   Fortified/Water            Bottled water
Water--(Sparkling &     Still Water Drnking/Mnrl   Bottled water
 Still)                  Water
Water--(Sparkling &     Spring Water               Bottled water
 Still)
Water--(Sparkling &     Distilled Water            Bottled water
 Still)
Water--(Sparkling &     Sparkling Water--          Bottled water
 Still)                  Unflavored
Water--(Sparkling &     Sparkling Water--Flvrd     Bottled water
 Still)                  Unswee
Bagels & Cream Cheese   Refrigerated Bagels        Bread and Crackers
Baked Breads            Mainstream White Bread     Bread and Crackers
Baked Breads            Mainstream Variety Breads  Bread and Crackers
Baked Breads            Hamburger Buns             Bread and Crackers
Baked Breads            Hot Dog Buns               Bread and Crackers
Baked Breads            Premium Bread              Bread and Crackers
Baked Breads            Bagels                     Bread and Crackers
Baked Breads            Sandwich Buns              Bread and Crackers
Baked Breads            English Muffins/Waffles    Bread and Crackers
Baked Breads            Main Meal Bread            Bread and Crackers
Baked Breads            Dinner Rolls               Bread and Crackers
Baked Breads            Diet/Light Bread           Bread and Crackers
Baked Breads            Fruit/Breakfast Bread      Bread and Crackers
Baked Breads            Rye Breads                 Bread and Crackers
Baking Mixes            Biscuit Flour & Mixes      Bread and Crackers
Bread                   Bread: Italian/French      Bread and Crackers
Bread                   Bread: Specialty           Bread and Crackers
Bread                   Bread: Artisan             Bread and Crackers
Bread                   Bread: Pita/Pocket/        Bread and Crackers
                         Flatbrd
Bread                   Bread: Sweet/Breakfast     Bread and Crackers
Bread                   Bread: Sourdough           Bread and Crackers
Bread                   Bread: Tortillas/Wraps     Bread and Crackers
Bread                   Bread: Rye/Cocktail        Bread and Crackers
Bread                   Whole Grain Bread          Bread and Crackers
Bread                   Bread: Wheat/Whl Grain     Bread and Crackers
Bread                   Bread: Brand               Bread and Crackers
Cookie/Cracker Multi-   Multi-Pack Crackers        Bread and Crackers
 Pks
Crackers                Crackers                   Bread and Crackers
Crackers & Misc Baked   Cheese Crackers            Bread and Crackers
 Food
Crackers & Misc Baked   Butter Spray Cracker       Bread and Crackers
 Food
Crackers & Misc Baked   Snack Crackers             Bread and Crackers
 Food
Crackers & Misc Baked   Saltine/Oyster             Bread and Crackers
 Food
Crackers & Misc Baked   Specialty Crackers         Bread and Crackers
 Food
Croutons/Bread          Croutons                   Bread and Crackers
 Stick&Salad Top
Dry Sce/Gravy/Potatoes/ Stuffing Mixes             Bread and Crackers
 Stuffng
Frozen Bread/Dough      Frzn Garlic Toast          Bread and Crackers
Frozen Bread/Dough      Frzn Dinner Rolls          Bread and Crackers
Frozen Bread/Dough      Frzn Garlic Bread          Bread and Crackers
Frozen Bread/Dough      Frzn Biscuits              Bread and Crackers
Frozen Bread/Dough      Frzn Breadsticks           Bread and Crackers
Frozen Breakfast Foods  Frzn Bagels                Bread and Crackers
Refrgrated Dough        Refrigerated Biscuits      Bread and Crackers
 Products
Refrgrated Dough        Refrigerated Specialty     Bread and Crackers
 Products                Rolls
Refrgrated Dough        Refrigerated Crescent      Bread and Crackers
 Products                Rolls
Refrgrated Dough        Refrigerated Breads        Bread and Crackers
 Products
Refrgrated Dough        Misc Refrig Dough          Bread and Crackers
 Products                Products
Refrigerated Hispanic   Refrigerated Tortillas     Bread and Crackers
 Grocery
Rice Cakes              Mini-Cakes                 Bread and Crackers
Rice Cakes              Large Cakes                Bread and Crackers
Rolls                   Rolls: Dinner              Bread and Crackers
Rolls                   Rolls: Sandwich            Bread and Crackers
Rolls                   Rolls: Croissants/         Bread and Crackers
                         Breadsticks
Rolls                   Rolls: Bagels              Bread and Crackers
Rolls                   Rolls: Biscuits/Eng        Bread and Crackers
                         Muffins
Ss/Vending--Cookie/     Vending Size/Sngl Serve    Bread and Crackers
 Cracker                 Cracke
Traditional Mexican     Mexican Soft Tortillas     Bread and Crackers
 Foods                   And Wra
Traditional Mexican     Mexican Taco/Tostado/      Bread and Crackers
 Foods                   Shells
Apples                  Caramel/Candy Apples       Candy
Candy                   Candy/Chocolate            Candy
Candy--Checklane        Candy Bars (Singles)       Candy
                         (Including)
Candy--Checklane        Chewing Gum                Candy
Candy--Checklane        Candy Bars (Singles)       Candy
                         (Including)
Candy--Checklane        Mints/Candy & Breath (Not  Candy
                         Life)
Candy--Checklane        Misc Checklane Candy       Candy
Candy--Checklane        Mints/Candy & Breath (Not  Candy
                         Life)
Candy--Packaged         Candy Bags-Chocolate       Candy
Candy--Packaged         Candy Bars (Multi Pack)    Candy
Candy--Packaged         Candy Bags-Non Chocolate   Candy
Candy--Packaged         Seasonal Miscellaneous     Candy
                         [Candy]
Candy--Packaged         Seasonal Candy Bags-       Candy
                         Chocolate
Candy--Packaged         Gum (Packaged)             Candy
Candy--Packaged         Miscellaneous Candy        Candy
                         (Including)
Candy--Packaged         Seasonal Candy Box-        Candy
                         Chocolate
Candy--Packaged         Seasonal Candy Bags Non-   Candy
                         Chocol
Candy--Packaged         Candy Bars Multi Pack W/   Candy
                         Flour
Candy--Packaged         Candy Bags-Chocolate W/    Candy
                         Flour
Candy--Packaged         Miscellaneous Candy        Candy
                         (Including)
Candy--Packaged         Novelty Candy              Candy
Candy--Packaged         Seasonal Miscellaneous W/  Candy
                         Flour
Candy--Packaged         Candy Boxed Chocolates W/  Candy
                         Flour
Candy--Packaged         Candy Boxed Chocolates     Candy
Candy--Packaged         Seasonal Candy Box Non-    Candy
                         Chocola
Candy--Packaged         Candy Box Non-Chocolate    Candy
Candy--Packaged         Candy Bags-Non Chocolate   Candy
                         W/Flo
Candy--Packaged         Bulk Candy                 Candy
Candy--Packaged         Seasonal Candy Bags-       Candy
                         Chocolate
Candy--Packaged         Seasonal Candy Bags Non-   Candy
                         Chocol
Candy--Packaged         Seasonal Candy Box Non-    Candy
                         Chocola
Sweet Goods & Snacks    Sweet Goods: Candy         Candy
Trail Mix & Snacks      Candy W/O Flour            Candy
Trail Mix & Snacks      Candy W/Flour              Candy
Cereal Bars             Breakfast Bars/Tarts/      Cereal
                         Scones
Cereals                 Cereal--Cold               Cereal
Cereals                 Granola                    Cereal
Cnv Breakfast &         Granola Bars               Cereal
 Wholesome Snks
Cnv Breakfast &         Cereal Bars                Cereal
 Wholesome Snks
Cold Cereal             Kids Cereal                Cereal
Cold Cereal             All Family Cereal          Cereal
Cold Cereal             Adult Cereal               Cereal
Hot Cereal              Instant Oatmeal            Cereal
Hot Cereal              Standard Oatmeal           Cereal
Hot Cereal              Grits                      Cereal
Hot Cereal              Other Hot Cereal           Cereal
Hot Cereal              Instant Breakfast          Cereal
Coffee & Creamers       Unflavored Can Coffee      Coffee and tea
Coffee & Creamers       Unflavored Bag Coffee      Coffee and tea
Coffee & Creamers       Unflavored Instant Coffee  Coffee and tea
Coffee & Creamers       Ready To Drink Coffee      Coffee and tea
Coffee & Creamers       Coffee Pods/Singles/       Coffee and tea
                         Filter Pac
Coffee & Creamers       Flavored Bag Coffee        Coffee and tea
Coffee & Creamers       Specialty Instant Coffee   Coffee and tea
                         W/Swe
Coffee & Creamers       Flavored Can Coffee        Coffee and tea
Coffee & Creamers       Bulk Coffee                Coffee and tea
Coffee & Creamers       Specialty Instant Coffee   Coffee and tea
                         W/O S
Dry Tea/Coffee/Coco     Tea Bags (Supplement)      Coffee and tea
 Mixes
Refrgratd Juices/       Tea No Sugar Or Swe        Coffee and tea
 Drinks Dairy Case
Teas                    Tea Bags & Bulk Tea        Coffee and tea
Teas                    Tea Bags/Herbal            Coffee and tea
Teas                    Tea Bags/Green             Coffee and tea
Teas                    Instant Tea & Tea Mix      Coffee and tea
Authentic Hispanic Fds  Authentic Sauces/Salsa/    Condiments and
 & Product               Picante                    seasoning
Bag Snacks              Salsa & Dips               Condiments and
                                                    seasoning
Can Vegetables--Shelf   Fried Onions               Condiments and
 Stable                                             seasoning
Condiments              Oils/Vinegar               Condiments and
                                                    seasoning
Condiments & Sauces     Bbq Sauce                  Condiments and
                                                    seasoning
Condiments & Sauces     Catsup                     Condiments and
                                                    seasoning
Condiments & Sauces     Steak & Worchester Sauce   Condiments and
                                                    seasoning
Condiments & Sauces     Hot Sauce                  Condiments and
                                                    seasoning
Condiments & Sauces     Marinades                  Condiments and
                                                    seasoning
Condiments & Sauces     Yellow Mustard             Condiments and
                                                    seasoning
Condiments & Sauces     Mustard--All Other         Condiments and
                                                    seasoning
Condiments & Sauces     Wing Sauce                 Condiments and
                                                    seasoning
Condiments & Sauces     Chili Sauce/Cocktail       Condiments and
                         Sauce                      seasoning
Condiments & Sauces     Misc Meat Sauces           Condiments and
                                                    seasoning
Croutons/Bread Stick &  Salad Toppers              Condiments and
 Salad Top                                          seasoning
Dressings/Dips          Dips Guacamole/Salsa/      Condiments and
                         Queso                      seasoning
Dressings/Dips          Dips Veggie                Condiments and
                                                    seasoning
Dressings/Dips          Dips Fruit And Chocolate   Condiments and
                                                    seasoning
Dry Sce/Gravy/Potatoes/ Sauce Mixes/Gravy Mixes    Condiments and
 Stuffng                 Dry                        seasoning
Dry Sce/Gravy/Potatoes/ Gravy Can/Glass            Condiments and
 Stuffng                                            seasoning
Dry Sce/Gravy/Potatoes/ Cooking Bags With Spices/  Condiments and
 Stuffng                 Seaso                      seasoning
Enhancements            Enhancements--Pickles/     Condiments and
                         Kraut                      seasoning
Enhancements            Enhancements--Salads/      Condiments and
                         Spreads                    seasoning
Enhancements            Enhancements--Spices/      Condiments and
                         Sauces                     seasoning
Herbs/Garlic            Herbs Cilanto              Condiments and
                                                    seasoning
Herbs/Garlic            Herbs Fresh Other Organic  Condiments and
                                                    seasoning
Herbs/Garlic            Herbs Basil Organic        Condiments and
                                                    seasoning
Mediterranean Bar       Sal: Olives/Pickles--Bulk  Condiments and
                                                    seasoning
Mediterranean Bar       Sal: Olives/Pickles--Bulk  Condiments and
                                                    seasoning
Pickle/Relish/Pckld     Ripe Olives                Condiments and
 Veg & Olives                                       seasoning
Pickle/Relish/Pckld     Peppers                    Condiments and
 Veg & Olives                                       seasoning
Pickle/Relish/Pckld     Green Olives               Condiments and
 Veg & Olives                                       seasoning
Pickle/Relish/Pckld     Relishes                   Condiments and
 Veg & Olives                                       seasoning
Pickle/Relish/Pckld     Pickld Veg/Peppers/Etc.    Condiments and
 Veg & Olives                                       seasoning
Pickle/Relish/Pckld     Specialty Olives           Condiments and
 Veg & Olives                                       seasoning
Refrigerated Italian    Refrigerated Pasta Sauce   Condiments and
                                                    seasoning
Salad & Dips            Sal: Salsa/Dips Bulk       Condiments and
                                                    seasoning
Salad & Dips            Sal: Dip Prepack           Condiments and
                                                    seasoning
Salad & Dips            Sal: Salsa Prepack         Condiments and
                                                    seasoning
Salad Dresing &         Dry Salad Dressing & Dip   Condiments and
 Sandwich Spreads        Mixes                      seasoning
Seafood--Salad/Dip/Sce/ Dips/Spreads               Condiments and
 Cond                                               seasoning
Spices & Extracts       Traditional Spices         Condiments and
                                                    seasoning
Spices & Extracts       Gourmet Spices             Condiments and
                                                    seasoning
Spices & Extracts       Pure Extracts              Condiments and
                                                    seasoning
Spices & Extracts       Table Salt/Popcorn Salt/   Condiments and
                         Ice Cr                     seasoning
Spices & Extracts       Imitation Extracts         Condiments and
                                                    seasoning
Spices/Jarred Garlic    Spices & Seasonings        Condiments and
                                                    seasoning
Traditional Asian       Asian Other Sauces/        Condiments and
 Foods                   Marinad                    seasoning
Traditional Asian       Asian Soy Sauce            Condiments and
 Foods                                              seasoning
Traditional Mexican     Mexican Sauces And         Condiments and
 Foods                   Picante Sau                seasoning
Traditional Mexican     Mexican Seasoning Mixes    Condiments and
 Foods                                              seasoning
Traditional Mexican     Mexican Taco Sauce         Condiments and
 Foods                                              seasoning
Vinegar & Cooking       Vinegar/White & Cider      Condiments and
 Wines                                              seasoning
Vinegar & Cooking       Specialty Vinegar          Condiments and
 Wines                                              seasoning
Eggs/Muffins/Potatoes   Eggs--Large                Eggs
Eggs/Muffins/Potatoes   Eggs--Medium               Eggs
Eggs/Muffins/Potatoes   Eggs--X-Large              Eggs
Eggs/Muffins/Potatoes   Eggs--Jumbo                Eggs
Eggs/Muffins/Potatoes   Eggs Substitute            Eggs
Eggs/Muffins/Potatoes   Misc Dairy Refigerated     Eggs
Refrigerated Dairy      Eggs                       Eggs
 Case
Dressings/Dips          Creamy                     Fats and oils
 Dressing
Dressings/Dips          Blue Cheese                Fats and oils
 Dressing
Margarines              Margarine: Tubs And Bowls  Fats and oils
Margarines              Butter                     Fats and oils
Margarines              Margarine Stick            Fats and oils
Margarines              Margarine: Squeeze         Fats and oils
Salad Dresing &         Pourable Salad Dressings   Fats and oils
 Sandwich Spreads
Salad Dresing &         Mayonnaise & Whipped       Fats and oils
 Sandwich Spreads        Dressing
Salad Dresing &         Sand/Horseradish & Tartar  Fats and oils
 Sandwich Spreads        Sauce
Shortening & Oil        Vegetable Oil              Fats and oils
Shortening & Oil        Canola Oils                Fats and oils
Shortening & Oil        Olive Oil                  Fats and oils
Shortening & Oil        Cooking Sprays             Fats and oils
Shortening & Oil        Solid Shortening           Fats and oils
Shortening & Oil        Corn Oil                   Fats and oils
Shortening & Oil        Cooking Oil: Peanut/       Fats and oils
                         Safflower/
Baking                  Flours/Grains/Sugar        Flour and prepared
                                                    flour mixes
Flour & Meals           Flour: White & Self        Flour and prepared
                         Rising                     flour mixes
Flour & Meals           Breadings/Coatings/Crumbs  Flour and prepared
                                                    flour mixes
Flour & Meals           Flour: Misc/Specialty/     Flour and prepared
                         Blend Et                   flour mixes
Molasses/Syrups/        Pancake Mixes              Flour and prepared
 Pancake Mixes                                      flour mixes
Frozen Breakfast Foods  Frzn Breakfast Sandwiches  Frozen prepared foods
Frozen Breakfast Foods  Waffles/Pancakes/French    Frozen prepared foods
                         Toast
Frozen Breakfast Foods  Frzn Breakfast Entrees     Frozen prepared foods
Frozen Entrees          Meatless/Vegetarian        Frozen prepared foods
Frozen Ethnic           Frozen International       Frozen prepared foods
                         [Ethnic Food]
Frozen Handhelds &      Snacks/Appetizers          Frozen prepared foods
 Snacks
Frozen Handhelds &      Sandwiches & Handhelds     Frozen prepared foods
 Snacks
Frozen Handhelds &      Corn Dogs                  Frozen prepared foods
 Snacks
Frozen Handhelds &      Burritos                   Frozen prepared foods
 Snacks
Frozen Meat             Micro Protein [Meat]       Frozen prepared foods
 Alternatives
Frozen Pizza            Pizza/Premium              Frozen prepared foods
Frozen Pizza            Pizza/Economy              Frozen prepared foods
Frozen Pizza            Pizza/Traditional          Frozen prepared foods
Frozen Pizza            Pizza/Single Serve/        Frozen prepared foods
                         Microwave
Frzn Meatless           Meatless Burgers           Frozen prepared foods
Frzn Meatless           Meatless Breakfast         Frozen prepared foods
Frzn Meatless           Meatless Poultry           Frozen prepared foods
Frzn Meatless           Meatless Miscellaneous     Frozen prepared foods
Frzn Multi Serve        Fz Family Style Entrees    Frozen prepared foods
Frzn Multi Serve        Fz Skillet Meals           Frozen prepared foods
Frzn Multi Serve        Fz Meatballs               Frozen prepared foods
Frzn Pasta              Frozen Pasta               Frozen prepared foods
Frzn Prepared Chicken   Whole Muscle Breaded/18oz  Frozen prepared foods
                         And
Frzn Prepared Chicken   Boneless Snack/18oz And    Frozen prepared foods
                         Larger
Frzn Prepared Chicken   Bone-In Wings              Frozen prepared foods
Frzn Prepared Chicken   Fz Meal Kits/Stuffed/      Frozen prepared foods
                         Other
Frzn Prepared Chicken   Whole Muscle Unbreaded     Frozen prepared foods
Frzn Prepared Chicken   Boneless Snack/Value/      Frozen prepared foods
                         Small
Frzn Seafood            Frz Coated Fish Fillets    Frozen prepared foods
Frzn Seafood            Frz Fishsticks/Tenders/    Frozen prepared foods
                         Nuggets
Frzn Seafood            Frz Non-Coated Fish        Frozen prepared foods
                         Fillets
Frzn Ss Economy Meals   Fz Ss Economy Meals All    Frozen prepared foods
Frzn Ss Premium Meals   Fz Ss Prem Traditional     Frozen prepared foods
                         Meals
Frzn Ss Premium Meals   Fz Ss Prem Nutritional     Frozen prepared foods
                         Meals
Apples                  Apples Gala (Bulk & Bag)   Fruits
Apples                  Apples Red Delicious       Fruits
                         (Bulk & Bag)
Apples                  Apples Granny Smith (Bulk  Fruits
                         & Bag)
Apples                  Mixed Fruit Bags           Fruits
Apples                  Apples Other (Bulk & Bag)  Fruits
Apples                  Apples Fuji (Bulk & Bag)   Fruits
Apples                  Apples Gold Delicious      Fruits
                         (Bulk & Bag)
Apples                  Apples Honeycrisp          Fruits
Apples                  Apples Braeburn (Bulk &    Fruits
                         Bag)
Apples                  Apples Gala (Bulk & Bag)   Fruits
                         Organic
Apples                  Apples Red Delicious       Fruits
                         (Bulk & Bag)
Apples                  Apples Granny Smith (Bulk  Fruits
                         & Bag)
Apples                  Apples Gold Delicious      Fruits
                         (Bulk & Bag)
Bananas                 Bananas                    Fruits
Bananas                 Bananas Organic            Fruits
Berries                 Strawberries               Fruits
Berries                 Blueberries                Fruits
Berries                 Raspberries                Fruits
Berries                 Blackberries               Fruits
Berries                 Strawberries Organic       Fruits
Berries                 Raspberries Organic        Fruits
Berries                 Blueberries Organic        Fruits
Can Fruit/Jar           Pineapple                  Fruits
 Applesauce
Can Fruit/Jar           Peaches                    Fruits
 Applesauce
Can Fruit/Jar           Fruit Cocktail/Fruit       Fruits
 Applesauce              Salad
Can Fruit/Jar           Mandarin Oranges/Citrus    Fruits
 Applesauce              Sect
Can Fruit/Jar           Apple Sauce (Excludes      Fruits
 Applesauce              Cup)
Can Fruit/Jar           Pears                      Fruits
 Applesauce
Can Fruit/Jar           Cranberry Sauce            Fruits
 Applesauce
Citrus                  Oranges Navels All         Fruits
Citrus                  Clementines                Fruits
Citrus                  Lemons                     Fruits
Citrus                  Limes                      Fruits
Citrus                  Grapefruit                 Fruits
Citrus                  Tangerines & Tangelos      Fruits
Citrus                  Oranges Non Navel All      Fruits
Convenience/Snacking    Jarred Fruit Single Serve  Fruits
Convenience/Snacking    Convenience/Snacking       Fruits
                         Fruit Pro
Convenience/Snacking    Jarred Fruit Multi Serve   Fruits
Dried Fruit             Raisins                    Fruits
Dried Fruit             Dried Fruit--Other         Fruits
Dried Fruit             Dried Plums                Fruits
Frozen Fruits           Frozen Fruit               Fruits
Grapes                  Grapes Red                 Fruits
Grapes                  Grapes White               Fruits
Grapes                  Grapes Black/Blue          Fruits
Grapes                  Grapes Red Globe           Fruits
Grapes                  Grapes Other               Fruits
Melons                  Watermelon Seedless Whole  Fruits
Melons                  Cantaloupe Whole           Fruits
Melons                  Watermelon Personal        Fruits
Melons                  Watermelon W/Seeds Whole   Fruits
Melons                  Honeydew Whole             Fruits
Pears                   Pears Bartlett             Fruits
Pears                   Pears Anjou                Fruits
Pears                   Pears Bosc                 Fruits
Single Serve Fruit/     Fruit Cup                  Fruits
 Applesauce
Single Serve Fruit/     Applesauce Cup             Fruits
 Applesauce
Stone Fruit             Cherries Red               Fruits
Stone Fruit             Peaches Yellow Flesh       Fruits
Stone Fruit             Nectarines Yellow Flesh    Fruits
Stone Fruit             Plums                      Fruits
Stone Fruit             Cherries Ranier            Fruits
Stone Fruit             Peaches White Flesh        Fruits
Tropical Fruit          Avocado                    Fruits
Tropical Fruit          Pineapple Whole&Peel/      Fruits
                         Cored
Tropical Fruit          Mango                      Fruits
Tropical Fruit          Kiwi Fruit                 Fruits
Tropical Fruit          Pomegranates               Fruits
Value-Added Fruit       Instore Cut Fruit          Fruits
Value-Added Fruit       Melons Instore Cut         Fruits
Value-Added Fruit       Cut Fruit All Other        Fruits
                         Prepack
Value-Added Fruit       Fruit Party Tray Prepack   Fruits
Bagels & Cream Cheese   Cream Cheese               High fat dairy/cheese
Bulk Service Case       Bulk Semi-Hard [Cheese]    High fat dairy/cheese
 Cheese
Bulk Service Case       Bulk Processed [Cheese]    High fat dairy/cheese
 Cheese
Bulk Service Case       Bulk Semi-Soft [Cheese]    High fat dairy/cheese
 Cheese
Cheese                  Shredded Cheese            High fat dairy/cheese
Cheese                  American Single Cheese     High fat dairy/cheese
Cheese                  Natural Cheese Chunks      High fat dairy/cheese
Cheese                  String Cheese              High fat dairy/cheese
Cheese                  Natural Cheese Slices      High fat dairy/cheese
Cheese                  Miscellaneous Cheese       High fat dairy/cheese
Coffee & Creamers       Non Dairy Creamer          High fat dairy/cheese
Crackers & Misc Baked   Aerosol Cheese             High fat dairy/cheese
 Food
Dry Cheese              Loaf Cheese                High fat dairy/cheese
Dry Cheese              Grated Cheese              High fat dairy/cheese
Dry Cheese              Misc Dry Cheese            High fat dairy/cheese
Fluid Milk Products     Refrigerated Coffee        High fat dairy/cheese
                         Creamers
Fluid Milk              Products Half & Half       High fat dairy/cheese
Fluid Milk Products     Whipping Cream             High fat dairy/cheese
Fluid Milk Products     Egg Nog/Boiled Custard     High fat dairy/cheese
Fluid Milk Products     Buttermilk                 High fat dairy/cheese
Ice Cream Ice Milk &    Premium [Ice Cream &       High fat dairy/cheese
 Sherbets                Sherbert]
Ice Cream Ice Milk &    Traditional [Ice Cream &   High fat dairy/cheese
 Sherbets                Sherbert]
Ice Cream Ice Milk &    Pails [Ice Cream &         High fat dairy/cheese
 Sherbets                Sherbert]
Ice Cream Ice Milk &    Super Premium Pints [Ice   High fat dairy/cheese
 Sherbets                Cream & Sherbert]
Ice Cream Ice Milk &    Premium Pints [Ice Cream   High fat dairy/cheese
 Sherbets                & Sherbert]
Ice Cream Ice Milk &    Quarts [Ice Cream &        High fat dairy/cheese
 Sherbets                Sherbert]
Milk By-Products        Sour Creams                High fat dairy/cheese
Milk By-Products        Cottage Cheese             High fat dairy/cheese
Milk By-Products        Refrig Dips                High fat dairy/cheese
Milk By-Products        Aerosol Toppings [Milk By- High fat dairy/cheese
                         Products]
Milk By-Products        Ricotta Cheese             High fat dairy/cheese
Pre-Slice Service Case  Pre-Sliced Semi-Soft       High fat dairy/cheese
 Cheese                  [Cheese]
Pre-Slice Service Case  Pre-Sliced Semi-Hard       High fat dairy/cheese
 Cheese                  [Cheese]
Refrigerated Hispanic   Hispanic Cheese            High fat dairy/cheese
 Grocery
Specialty Cheese Pre    Specialty Ppk Cheese Hard/ High fat dairy/cheese
 Pack                    Grat
Specialty Cheese Pre    Specialty Ppk Cheese       High fat dairy/cheese
 Pack                    Spreads
Specialty Cheese Pre    Specialty Ppk Cheese Feta  High fat dairy/cheese
 Pack
Specialty Cheese Pre    Specialty Ppk Cheese       High fat dairy/cheese
 Pack                    Mozzarell
Specialty Cheese Pre    Specialty Ppk Cheese       High fat dairy/cheese
 Pack                    Processed
Specialty Cheese Pre    Specialty Ppk Cheese       High fat dairy/cheese
 Pack                    Cheddar & C
Specialty Cheese Pre    Specialty Ppk Cheese Semi  High fat dairy/cheese
 Pack                    Soft
Specialty Cheese Pre    Specialty Ppk Cheese Soft  High fat dairy/cheese
 Pack                    & Ripe
Specialty Cheese Pre    Specialty Ppk Cheese Blue/ High fat dairy/cheese
 Pack                    Gorg
Specialty Cheese Pre    Specialty Ppk Cheese       High fat dairy/cheese
 Pack                    Hispanic
Specialty Cheese Pre    Specialty Ppk Cheese       High fat dairy/cheese
 Pack                    Gouda & Eda
Specialty Cheese Pre    Specialty Ppk Cheese Goat  High fat dairy/cheese
 Pack                    Milk
Traditional Mexican     Mexican Con Queso          High fat dairy/cheese
 Foods
Fruit Snacks            Fruit Snacks               Jams, jellies,
                                                    preserves and other
                                                    sweets
Peanut Butter/Jelly/    Preserves/Jam/Marmalade    Jams, jellies,
 Jams & Honey                                       preserves and other
                                                    sweets
Peanut Butter/Jelly/    Jelly                      Jams, jellies,
 Jams & Honey                                       preserves and other
                                                    sweets
Aseptic Juice           Aseptic Pack Juice And     Juices
                         Drinks
Frozen Juice And        Frzn Conc Allieds Over     Juices
 Smoothies               50% Jui
Frozen Juice And        Frzn Oj & Oj Substitutes   Juices
 Smoothies               (Over 5
Juice                   Non-Carb Jce(Over 50%      Juices
                         Jce)
Juice                   Drinks--Carb Juice (Over   Juices
                         50%)
Juices Super Premium    Juices Superfoods/         Juices
                         Enhanced
Juices Super Premium    Juices Proteins            Juices
Juices Super Premium    Juice Single Blend         Juices
Processed               Squeeze Lemons/Limes       Juices
Refrgratd Juices/       Dairy Case 100% Pure       Juices
 Drinks                  Juice--O
Refrgratd Juices/       Dairy Case 100% Pure       Juices
 Drinks                  Juice Oth
Rtd Tea/New Age Juice   Juice (Over 50% Juice)     Juices
Shelf Stable Juice      Apple Juice & Cider (Over  Juices
                         50%)
Shelf Stable Juice      Blended Juice &            Juices
                         Combinations (Ov)
Shelf Stable Juice      Grape Juice (Over 50%      Juices
                         Juice)
Shelf Stable Juice      Veg Juice (Except Tomato)  Juices
                         (Ove)
Shelf Stable Juice      Tomato Juice (Over 50%     Juices
                         Jce)
Shelf Stable Juice      Pineapple Juice (Over 50%  Juices
                         Juic)
Shelf Stable Juice      Cranberry Juice (Over 50%  Juices
                         Jce)
Shelf Stable Juice      Lemon Juice & Lime Juice   Juices
                         (Over)
Shelf Stable Juice      Prune Juice (Over 50%      Juices
                         Juice)
Shelf Stable Juice      Cranapple/Cran Grape       Juices
                         Juice (Ov)
Shelf Stable Juice      Grapefruit Juice (Over     Juices
                         50% Jui)
Shelf Stable Juice      Cranapple/Cran Grape       Juices
                         Juice (Un)
Shelf Stable Juice      Grapefruit Juice (50% And  Juices
                         Unde)
Bacon                   Bacon--Trad 16oz Or Less   Meat/Poultry/Seafood
Bacon                   Bacon--Trad Greater Than   Meat/Poultry/Seafood
                         16oz
Bacon                   Bacon--Poultry             Meat/Poultry/Seafood
Bacon                   Bacon--Pre-Cooked          Meat/Poultry/Seafood
Bacon                   Bacon--Trad Center Cut     Meat/Poultry/Seafood
Bacon                   Bacon--Other               Meat/Poultry/Seafood
Bacon                   Bacon--Natural/Organic     Meat/Poultry/Seafood
Beef: Grinds            Lean [Beef]                Meat/Poultry/Seafood
Beef: Grinds            Primal [Beef]              Meat/Poultry/Seafood
Beef: Grinds            Angus [Beef]               Meat/Poultry/Seafood
Beef: Grinds            Patties [Beef]             Meat/Poultry/Seafood
Beef: Loins             Choice Beef                Meat/Poultry/Seafood
Beef: Loins Select      Beef                       Meat/Poultry/Seafood
Beef: Rib               Angus [Beef]               Meat/Poultry/Seafood
Beef: Round             Choice Beef                Meat/Poultry/Seafood
Beef: Round             Angus Beef                 Meat/Poultry/Seafood
Beef: Round             Select Beef                Meat/Poultry/Seafood
Beef: Thin Meats        Soup/Stew                  Meat/Poultry/Seafood
Beef: Thin Meats        Cubed Meats [Beef]         Meat/Poultry/Seafood
Beef: Thin Meats        Corned Beef                Meat/Poultry/Seafood
Beef: Thin Meats        Brisket [Beef]             Meat/Poultry/Seafood
Beef: Thin Meats        Skirt [Beef]               Meat/Poultry/Seafood
Beef: Thin Meats        Flank [Beef]               Meat/Poultry/Seafood
Breakfast Sausage       Bkfst Sausage--Fresh       Meat/Poultry/Seafood
                         Rolls
Breakfast Sausage       Bkfst Sausage--Fresh       Meat/Poultry/Seafood
                         Links
Breakfast Sausage       Bkfst Sausage--Fresh       Meat/Poultry/Seafood
                         Patties
Breakfast Sausage       Bkfst Sausage--Precooked   Meat/Poultry/Seafood
Breakfast Sausage       Bkfst Sausage--Bkfast      Meat/Poultry/Seafood
                         Side Di
Breakfast Sausage       Bkfst Sausage--Other       Meat/Poultry/Seafood
                         Forms
Buffalo                 Grinds [Buffalo]           Meat/Poultry/Seafood
Can Seafood--Shelf      Tuna                       Meat/Poultry/Seafood
 Stable
Can Seafood--Shelf      Salmon                     Meat/Poultry/Seafood
 Stable
Can Seafood--Shelf      Sardines                   Meat/Poultry/Seafood
 Stable
Can Seafood--Shelf      Oysters                    Meat/Poultry/Seafood
 Stable
Chicken & Poultry       Chix: Value-Added (Cold)   Meat/Poultry/Seafood
Chicken & Poultry       Chix: Frd 8pc/Cut Up       Meat/Poultry/Seafood
                         (Cold)
Chicken & Poultry       Chix: Baked 8pc Cut Up     Meat/Poultry/Seafood
                         (Cold)
Chicken & Poultry       Chix: Rotisserie Cold      Meat/Poultry/Seafood
Chicken Fresh           Chicken Breast Boneless    Meat/Poultry/Seafood
Chicken Fresh           Chicken Wings              Meat/Poultry/Seafood
Chicken Fresh           Chicken Drums              Meat/Poultry/Seafood
Chicken Fresh           Whole Chicken (Roasters/   Meat/Poultry/Seafood
                         Fryer)
Chicken Fresh           Chicken Thighs             Meat/Poultry/Seafood
Chicken Fresh           Chicken Legs/Quarters      Meat/Poultry/Seafood
Chicken Fresh           Mixed Packs [Chicken]      Meat/Poultry/Seafood
Chicken Frozen          Frzn Chicken--Wht Meat     Meat/Poultry/Seafood
Chicken Frozen          Frzn Chicken--Wings        Meat/Poultry/Seafood
Chicken Frozen          Frzn Chicken--Drk Meat     Meat/Poultry/Seafood
Chicken Grinds          Ground Chicken             Meat/Poultry/Seafood
Chicken Offal           Internal Chicken Offal     Meat/Poultry/Seafood
Chicken Specialty/      Chicken Breast Boneless    Meat/Poultry/Seafood
 Natural
Chicken Specialty/      Chicken Wings              Meat/Poultry/Seafood
 Natural
Chicken Specialty/      Whole Chicken (Roasters/   Meat/Poultry/Seafood
 Natural                 Fryer)
Deli Meat: Bulk         Meat: Turkey Bulk          Meat/Poultry/Seafood
Deli Meat: Bulk         Meat: Ham Bulk             Meat/Poultry/Seafood
Deli Meat: Bulk         Meat: Beef Bulk            Meat/Poultry/Seafood
Deli Meat: Bulk         Meat Bulk: Specialty Dry   Meat/Poultry/Seafood
                         Meats
Deli Meat: Bulk         Bologna/Loaves/Franks      Meat/Poultry/Seafood
Deli Meat: Bulk         Meat: Chicken Bulk         Meat/Poultry/Seafood
Deli Meat: Presliced    Deli Meat: Specialty Dry   Meat/Poultry/Seafood
                         Meats
Deli Meat: Presliced    Deli Meat: Semi-Dry        Meat/Poultry/Seafood
                         Sausage
Deli Meat: Presliced    Deli Meat: Turkey          Meat/Poultry/Seafood
Deli Meat: Presliced    Deli Meat: Ham             Meat/Poultry/Seafood
Deli Meat: Presliced    Deli Meat: Beef            Meat/Poultry/Seafood
Dinner Sausage          Dnr Sausage--Links Pork    Meat/Poultry/Seafood
                         Ckd/S
Dinner Sausage          Dnr Sausage--Links Fresh   Meat/Poultry/Seafood
Dinner Sausage          Dnr Sausage--Pork Rope     Meat/Poultry/Seafood
                         Ckd/Sm
Dinner Sausage          Dnr Sausage--Beef Rope     Meat/Poultry/Seafood
                         Ckd/Sm
Dinner Sausage          Dnr Sausage--Other Forms   Meat/Poultry/Seafood
Dinner Sausage          Dnr Sausage--Links Beef    Meat/Poultry/Seafood
                         Ckd/S
Dinner Sausage          Dnr Sausage--Poultry Rope  Meat/Poultry/Seafood
                         Ckd
Dinner Sausage          Dnr Sausage--Links         Meat/Poultry/Seafood
                         Poultry Ck
Dinner Sausage          Dnr Sausage--Natural/      Meat/Poultry/Seafood
                         Organic
Dinner Sausage          Dnr Sausage--Fresh         Meat/Poultry/Seafood
                         Poultry
Frozen Breakfast Foods  Frzn Breakfast Sausage     Meat/Poultry/Seafood
Frzn Multi Serve        Frzn Burgers               Meat/Poultry/Seafood
Frzn Prepared Chicken   Value Forms/18oz And       Meat/Poultry/Seafood
                         Larger [Chicken]
Hot Dogs                Hot Dogs--Base Meat        Meat/Poultry/Seafood
Hot Dogs                Hot Dogs--Base Beef        Meat/Poultry/Seafood
Hot Dogs                Hot Dogs--Premium          Meat/Poultry/Seafood
Hot Dogs                Hot Dogs--Base Poultry     Meat/Poultry/Seafood
Lamb                    Round/Leg [Lamb]           Meat/Poultry/Seafood
Lamb                    Loin [Lamb]                Meat/Poultry/Seafood
Lamb                    Chuck/Shoulder [Lamb]      Meat/Poultry/Seafood
Lunchmeat               Lunchment--Deli Fresh      Meat/Poultry/Seafood
Lunchmeat               Lunchment--Bologna/        Meat/Poultry/Seafood
                         Sausage
Lunchmeat               Lunchmeat--Chop/Form       Meat/Poultry/Seafood
                         Pltry & Ha
Lunchmeat               Lunchmeat--Whole Muscle    Meat/Poultry/Seafood
                         Pltry
Lunchmeat               Lunchmeat--Chip Meat       Meat/Poultry/Seafood
Lunchmeat               Lunchmeat--Brauns/Liver/   Meat/Poultry/Seafood
                         Loave
Lunchmeat               Lunchmeat--Variety Pack    Meat/Poultry/Seafood
Lunchmeat               Lunchmeat--Other           Meat/Poultry/Seafood
Lunchmeat               Lunchment--Natural/        Meat/Poultry/Seafood
                         Organic
Lunchmeat               Lunchmeat--Peggable Deli   Meat/Poultry/Seafood
                         Fres
Meat Frozen             Frzn Meat--Beef            Meat/Poultry/Seafood
Meat Frozen             Frzn Meat--Breakfast       Meat/Poultry/Seafood
                         Sausage
Meat Frozen             Frzn Meat--Offals          Meat/Poultry/Seafood
Meat Frozen             Frzn Meat--Turkey          Meat/Poultry/Seafood
Meat Snacks             Jerky/Nuggets/Tenders      Meat/Poultry/Seafood
Meat Snacks             Meat Sticks/Bites          Meat/Poultry/Seafood
Party Tray Deli         Tray: Meat And Cheese      Meat/Poultry/Seafood
Pork Bone In Loin/Rib   Dry [Pork Bone In Loin/    Meat/Poultry/Seafood
                         Rib]
Pork Boneless Loin/Rib  Enhanced [Pork Boneless    Meat/Poultry/Seafood
                         Loin/Rib]
Pork Grinds             Ground Pork                Meat/Poultry/Seafood
Pork Offal              External Fresh [Pork       Meat/Poultry/Seafood
                         Offal]
Pork Shoulder           Butts [Pork Shoulder]      Meat/Poultry/Seafood
Pork Shoulder           Fresh Hams                 Meat/Poultry/Seafood
Pork Thin Meats         Ribs [Pork]                Meat/Poultry/Seafood
Poultry                 Other Cornish Hen          Meat/Poultry/Seafood
Random Weight Meat      Lunch Meats                Meat/Poultry/Seafood
 Products
Seafood--Catfish        Catfish--Fillet            Meat/Poultry/Seafood
Seafood--Catfish        Catfish--Whole             Meat/Poultry/Seafood
Seafood--Catfish        Catfish--Nuggets           Meat/Poultry/Seafood
Seafood--Cod            Cod--Fillet                Meat/Poultry/Seafood
Seafood--Crab           Crab--Snow                 Meat/Poultry/Seafood
Seafood--Crab           Crab--King                 Meat/Poultry/Seafood
Seafood--Crab           Crab--Dungy                Meat/Poultry/Seafood
Seafood--Crab           Crab--Other                Meat/Poultry/Seafood
Seafood--Finfish        Other Finfish--Other       Meat/Poultry/Seafood
Seafood--Finfish        Other Finfish--Other       Meat/Poultry/Seafood
Seafood--Lobster        Lobster--Tails             Meat/Poultry/Seafood
Seafood--Party Trays    Party Tray--Shrimp         Meat/Poultry/Seafood
Seafood--Salmon-Farm    Salmon Fr--Altantic        Meat/Poultry/Seafood
 Raised
Seafood--Salmon-Wild    Salmon Wc--Pink            Meat/Poultry/Seafood
 Caught
Seafood--Salmon-Wild    Salmon Wc--Sockeye         Meat/Poultry/Seafood
 Caught
Seafood--Scallops       Scallops--Sea              Meat/Poultry/Seafood
Seafood--Shrimp         Shrimp--Raw                Meat/Poultry/Seafood
Seafood--Shrimp         Shrimp--Cooked             Meat/Poultry/Seafood
Seafood--Smoked         Smoked Salmon              Meat/Poultry/Seafood
 Seafood
Seafood--Tilapia        Tilapia--Fillet            Meat/Poultry/Seafood
Seafood--Trout          Steelhead Fr [Trout]       Meat/Poultry/Seafood
Seafood--Value-Added    Value-Added Breaded        Meat/Poultry/Seafood
 Seafood                 Shrimp
Seafood--Value-Added    Value-Added Shrimp         Meat/Poultry/Seafood
 Seafood
Seafood--Value-Added    Value-Added Crab           Meat/Poultry/Seafood
 Seafood
Service Case Meat       Seasoned Poultry           Meat/Poultry/Seafood
Service Case Meat       Stuffed/Mixed Beef         Meat/Poultry/Seafood
Service Case Meat       Marinated Pork             Meat/Poultry/Seafood
Service Case Meat       Marinated Poultry          Meat/Poultry/Seafood
Service Case Meat       Seasoned Beef              Meat/Poultry/Seafood
Service Case Meat       Seasoned Pork              Meat/Poultry/Seafood
Service Case Meat       Stuffed/Mixed Poultry      Meat/Poultry/Seafood
Service Case Meat       Marinated Beef             Meat/Poultry/Seafood
Service Case Meat       Kabobs Beef                Meat/Poultry/Seafood
Service Case Meat       Kabobs Poultry             Meat/Poultry/Seafood
Service Case Meat       Stuffed/Mixed Pork         Meat/Poultry/Seafood
Smoked Hams             Hams--Half/Port Bone-In    Meat/Poultry/Seafood
Smoked Hams             Hams--Spiral               Meat/Poultry/Seafood
Smoked Hams             Hams--Whole Boneless       Meat/Poultry/Seafood
Smoked Hams             Hams--Half/Port Boneless   Meat/Poultry/Seafood
Smoked Hams             Hams--Dry Cured/Country    Meat/Poultry/Seafood
Smoked Hams             Hams--Whole Bone-In        Meat/Poultry/Seafood
Smoked Pork             Ham Steaks/Cubes/Slices    Meat/Poultry/Seafood
Smoked Pork             Smoked Offal [Pork]        Meat/Poultry/Seafood
Smoked Pork             Bacon--Belly/Jowl          Meat/Poultry/Seafood
Smoked Pork             Smoked Picnics [Pork]      Meat/Poultry/Seafood
Snack Meat              Snack Meat--Pepperoni      Meat/Poultry/Seafood
Snack Meat              Snack Meat--Salami/Smr     Meat/Poultry/Seafood
                         Sausag
Turkey Fresh            Whole Hen (Under 16lbs)    Meat/Poultry/Seafood
                         [Turkey]
Turkey Fresh            Whole Tom (Over 16lbs)     Meat/Poultry/Seafood
                         [Turkey]
Turkey Frozen           Whole Toms (Over 16lbs)    Meat/Poultry/Seafood
                         [Turkey]
Turkey Frozen           Whole Hens (Under 16lbs)   Meat/Poultry/Seafood
                         [Turkey]
Turkey Frozen           Turkey Breast Bone In      Meat/Poultry/Seafood
Turkey Grinds           Ground Turkey              Meat/Poultry/Seafood
Turkey Offal            External [Turkey Offal]    Meat/Poultry/Seafood
Turkey Smoked           Turkey Wings               Meat/Poultry/Seafood
Turkey Smoked           Turkey Drums               Meat/Poultry/Seafood
Fluid Milk Products     Fluid Milk/White Only      Milk
Fluid Milk Products     Flavored Milk              Milk
Fluid Milk Products     Specialty/Lactose Free     Milk
                         Milk
Fluid Milk Products     Organic Milk               Milk
Fluid Milk Products     Soy Milk                   Milk
Non-Dairy/Dairy         Aseptic Milk               Milk
 Aseptic
Non-Dairy/Dairy         Soy Beverage               Milk
 Aseptic
Non-Dairy/Dairy         Nut Milk                   Milk
 Aseptic
Non-Dairy/Dairy         Rice Beverage              Milk
 Aseptic
Refrigerated Dairy      Non-Dairy Milks            Milk
 Case
Refrigerated Dairy      Fluid Milk                 Milk
 Case
Authentic Asian Foods   Authentic Japanese Foods   Miscellaneous
Authentic Asian Foods   Authentic Chinese Foods    Miscellaneous
Authentic Central       Central American Foods     Miscellaneous
 American Fds
Authentic Hispanic Fds  Hispanic Baking Needs      Miscellaneous
 & Product
Baking Needs            Baking Powder & Soda       Miscellaneous
Baking Needs            Yeast: Dry                 Miscellaneous
Baking Needs            Corn Starch                Miscellaneous
Dietary Aid Prdct/Med   Diet Cntrl Liqs            Miscellaneous
 Liq Nutr                Nutritional
Dietary Aid Prdct/Med   Diet Energy Drinks         Miscellaneous
 Liq Nutr
Dietary Aid Prdct/Med   Diet Cntrl Bars            Miscellaneous
 Liq Nutr                Nutritional
Fitness & Diet          Fitness & Diet--Bars W/    Miscellaneous
                         Flour
Fitness & Diet          Fitness & Diet--Bars W/O   Miscellaneous
                         Flour
Fitness & Diet          Fitness & Diet--Powder     Miscellaneous
                         Ntrtnl
Refrigerated Hispanic   Misc Hispanic Grocery      Miscellaneous
 Grocery
Baking Needs            Baking Nuts                Nuts and seeds
Bulk Food               Trail Mix/Nuts Bulk        Nuts and seeds
Condiments              Nut Butters/Peanut Butter  Nuts and seeds
Nuts                    Pistachios                 Nuts and seeds
Nuts                    Mixed Nuts                 Nuts and seeds
Nuts                    Cashews                    Nuts and seeds
Nuts                    Sunflower/Other Seeds      Nuts and seeds
Nuts                    Pecans Shelled             Nuts and seeds
Nuts                    Peanuts All                Nuts and seeds
Nuts                    Walnuts Shelled            Nuts and seeds
Nuts                    Almonds Shelled            Nuts and seeds
Nuts                    Trail Mix                  Nuts and seeds
Nuts                    Almonds                    Nuts and seeds
Nuts                    Dry Roast Peanuts          Nuts and seeds
Nuts                    Oil Roast Peanuts          Nuts and seeds
Nuts                    Nuts Other                 Nuts and seeds
Nuts                    Misc Snack Nuts            Nuts and seeds
Nuts                    Nuts Inshell               Nuts and seeds
Peanut Butter/Jelly/    Peanut Butter              Nuts and seeds
 Jams & Honey
Trail Mix & Snacks      Trail Mixes/Snack          Nuts and seeds
Canned & Dry Milk       Canned Milk                Other dairy products
Canned & Dry Milk       Non Fat Dry Milk           Other dairy products
Refrigerated Dairy      Yogurt                     Other dairy products
 Case
Refrigerated Dairy      Kefir                      Other dairy products
 Case
Yogurt                  Yogurt/Kids                Other dairy products
Yogurt                  Yogurt/Ss Regular          Other dairy products
Yogurt                  Yogurt/Ss Light            Other dairy products
Yogurt                  Yogurt/Pro Active Health   Other dairy products
Yogurt                  Yogurt/Adult Multi-Packs   Other dairy products
Yogurt                  Yogurt/Specialty Greek     Other dairy products
Yogurt                  Yogurt/Large Size (16oz    Other dairy products
                         Or Lar)
Yogurt                  Yogurt/Adult Drinks        Other dairy products
Deli Specialties        Dl Spec: Dry/Refrig        Pasta, cornmeal,
 (Retail Pk)             Pastas                     other cereal
                                                    products
Dry Bean Veg & Rice     Noodle Side Dish Mixes     Pasta, cornmeal,
                                                    other cereal
                                                    products
Dry Noodles & Pasta     Long Cut Pasta             Pasta, cornmeal,
                                                    other cereal
                                                    products
Dry Noodles & Pasta     Short Cut Pasta            Pasta, cornmeal,
                                                    other cereal
                                                    products
Dry Noodles & Pasta     Noodles Dry                Pasta, cornmeal,
                                                    other cereal
                                                    products
Dry/Ramen Bouillon      Ramen Noodles/Ramen Cups   Pasta, cornmeal,
                                                    other cereal
                                                    products
Flour & Meals           Cornmeal                   Pasta, cornmeal,
                                                    other cereal
                                                    products
Prepared/Pdgd Foods     Pasta/Ramen                Pasta, cornmeal,
                                                    other cereal
                                                    products
Refrigerated Italian    Refrigerated Pasta         Pasta, cornmeal,
                                                    other cereal
                                                    products
Salad & Dips            Pasta/Grain Salads--       Pasta, cornmeal,
                         Prepack                    other cereal
                                                    products
Salad & Dips            Pasta/Grain Salads--Bulk   Pasta, cornmeal,
                                                    other cereal
                                                    products
Seafood--Salad/Dip/Sce/ Breading                   Pasta, cornmeal,
 Cond                                               other cereal
                                                    products
Traditional Asian       Asian Noodles/Rice         Pasta, cornmeal,
 Foods                                              other cereal
                                                    products
Authentic Hispanic Fds  Hispanic Cookies/Crackers  Prepared Desserts
 & Product
Baked Sweet Goods       Snack Cake--Multi Pack     Prepared Desserts
Baked Sweet Goods       Sweet Goods--Full Size     Prepared Desserts
Bakery Party Trays      Party Trays: Cakes         Prepared Desserts
Baking Mixes            Layer Cake Mix             Prepared Desserts
Baking Mixes            Frosting                   Prepared Desserts
Baking Mixes            Muffin & Corn Bread Mix    Prepared Desserts
Baking Mixes            Brownie Mix                Prepared Desserts
Baking Mixes            Cookies Mix                Prepared Desserts
Baking Mixes            Miscellaneous Package      Prepared Desserts
                         Mixes
Baking Needs            Bits & Morsels [Baking     Prepared Desserts
                         Needs]
Baking Needs            Marshmallows               Prepared Desserts
Baking Needs            Pie Filling/Mincemeat/     Prepared Desserts
                         Glazes
Baking Needs            Pie Crust Mixes & Shells   Prepared Desserts
Baking Needs            Cooking Chocolate (Ex:     Prepared Desserts
                         Smi-Swt)
Baking Needs            Maraschino Cherries        Prepared Desserts
Baking Needs            Baking Cocoa               Prepared Desserts
Baking Needs            Marshmallow Creme          Prepared Desserts
Baking Needs            Coconut [Baking Needs]     Prepared Desserts
Cake Decor              Cake Decors & Icing        Prepared Desserts
Cake Decor              Cake Decors--Candies       Prepared Desserts
Cakes                   Cakes: Birthday/           Prepared Desserts
                         Celebration Sh
Cakes                   Cakes: Cupcakes            Prepared Desserts
Cakes                   Cakes: Layers              Prepared Desserts
Cakes                   Cakes: Creme/Pudding       Prepared Desserts
Cakes                   Cakes: Cheesecake          Prepared Desserts
Cakes                   Cakes: Fancy/Service Case  Prepared Desserts
Cakes                   Cakes: Layers/Sheets       Prepared Desserts
                         Novelties
Cakes                   Cakes: Angel Fds/Cke       Prepared Desserts
                         Rolls
Cakes                   Cakes: Ice Cream           Prepared Desserts
Cakes                   Cakes: Birthday/           Prepared Desserts
                         Celebration Lay
Cakes                   Cakes: Sheet               Prepared Desserts
Cakes                   Cakes: Creme/Pudding       Prepared Desserts
                         Novelties
Cakes                   Cakes: Cheesecake          Prepared Desserts
                         Novelties
Cnv Breakfast &         Toaster Pastries           Prepared Desserts
 Wholesome Snks
Cnv Breakfast &         Treats                     Prepared Desserts
 Wholesome Snks
Cookie/Cracker Multi-   Multi-Pack Cookies         Prepared Desserts
 Pks
Cookies                 Sandwich Cookies           Prepared Desserts
Cookies                 Tray Pack/Choc Chip        Prepared Desserts
                         Cookies
Cookies                 Cookies: Regular           Prepared Desserts
Cookies                 Vanilla Wafer/Kids         Prepared Desserts
                         Cookies
Cookies                 Cookies: Holiday/Special   Prepared Desserts
                         Occas
Cookies                 Premium Cookies (Ex:       Prepared Desserts
                         Pepperidg)
Cookies                 Graham Crackers            Prepared Desserts
Cookies                 Chocolate Covered Cookies  Prepared Desserts
Cookies                 Wellness/Portion Control   Prepared Desserts
                         [Cookies]
Cookies                 Cookies: Gourmet           Prepared Desserts
Cookies                 Fruit Filled Cookies       Prepared Desserts
Cookies                 Cookies: Message           Prepared Desserts
Cookies                 Cookies/Sweet Goods        Prepared Desserts
Cookies                 Specialty Cookies          Prepared Desserts
Dry Mix Desserts        Pudding & Gelatin Cups/    Prepared Desserts
                         Cans
Dry Mix Desserts        Puddings Dry               Prepared Desserts
Dry Mix Desserts        Gelatin                    Prepared Desserts
Dry Mix Desserts        Misc: Cheesecake/Mousse    Prepared Desserts
                         Mixes
Frozen Breakfast Foods  Frzn Breakfast Pastry      Prepared Desserts
Frozen Desserts         Frozen Fruit Pies &        Prepared Desserts
                         Cobblers
Frozen Desserts         Frozen Cream Pies          Prepared Desserts
Frozen Desserts         Frzn Pie Shells/Pastry     Prepared Desserts
                         Shell/F
Frozen Desserts         Frozen Cakes/Desserts      Prepared Desserts
Frozen Desserts         Frzn Pastry & Cookies      Prepared Desserts
Frozen Desserts         Single Serv/Portion        Prepared Desserts
                         Control
Frozen Novelties--      Sticks/Enrobed [Frozen     Prepared Desserts
 Water Ice               Novelties]
Frozen Novelties--      Water Ice [Frozen          Prepared Desserts
 Water Ice               Novelties]
Frozen Novelties--      Cones [Frozen Novelties]   Prepared Desserts
 Water Ice
Frozen Novelties--      Ice Cream Sandwiches       Prepared Desserts
 Water Ice
Frozen Novelties--      Adult Premium [Frozen      Prepared Desserts
 Water Ice               Novelties]
Frozen Novelties--      Cups/Push Ups/Other        Prepared Desserts
 Water Ice               [Frozen Novelties]
Frozen Whipped Topping  Frzn Whipped Topping       Prepared Desserts
Pies                    Pies: Fruit/Nut            Prepared Desserts
Pies                    Pies: Pumpkin/Custard      Prepared Desserts
Pies                    Pies: Cream/Meringue       Prepared Desserts
Pies                    Pies: Sugar Free           Prepared Desserts
Pies                    Pies: Tarts/Minis/Crstdas  Prepared Desserts
Refrgrated Dough        Refrigerated Cookies--     Prepared Desserts
 Products                Break N B
Refrgrated Dough        Refrigerated Cookie Dough  Prepared Desserts
 Products
Refrgrated Dough        Refrigerated Cookies--     Prepared Desserts
 Products                Seasonal
Refrgrated Dough        Refrigerated Pie Crust     Prepared Desserts
 Products
Refrigerated Desserts   Refrigerated Pudding       Prepared Desserts
Salad & Dips            Sal: Desserts--Prepack     Prepared Desserts
Salad & Dips            Sal: Desserts--Bulk        Prepared Desserts
Single Serve Sweet      Snack Cake--Single Serve   Prepared Desserts
 Goods
Ss/Vending--Cookie/     Vendor Size/Single Serve   Prepared Desserts
 Cracker                 Cooki
Sweet Goods             Sw Gds: Donuts             Prepared Desserts
Sweet Goods             Sw Gds: Sw Rolls/Dan       Prepared Desserts
Sweet Goods             Sw Gds: Muffins            Prepared Desserts
Sweet Goods             Sw Gds: Coffee Cakes       Prepared Desserts
Sweet Goods & Snacks    Sw Gds: Swt/Flvrd Loaves   Prepared Desserts
Sweet Goods & Snacks    Sw Gds: Brownie/Bar        Prepared Desserts
                         Cookie
Sweet Goods & Snacks    Sw Gds: Puff Pastry        Prepared Desserts
Sweet Goods & Snacks    Sw Gds: Specialty          Prepared Desserts
                         Desserts
Syrups Toppings &       Ice Cream Toppings         Prepared Desserts
 Cones
Value-Added Fruit       Parfait Cups Instore       Prepared Desserts
Canned Pasta & Mwv Fd-  Can Pasta                  Prepared Foods
 Shlf Stbl
Canned Pasta & Mwv Fd-  Microwavable Cups [Pasta]  Prepared Foods
 Shlf Stbl
Chilled Ready Meals     Store Brand                Prepared Foods
Convenient Meals        Convenient Meals--Kids     Prepared Foods
                         Meal C
Convenient Meals        Convenient Meals--Adult    Prepared Foods
                         Meal
Dinner Mixes--Dry       Macaroni & Cheese Dnrs     Prepared Foods
Dinner Mixes--Dry       Skillet Dinners            Prepared Foods
Dinner Mixes--Dry       Microwave Dinners          Prepared Foods
Dinner Mixes--Dry       Package Dinners/Pasta      Prepared Foods
                         Salads
Dinner Mixes--Dry       Pizza Mix Dry              Prepared Foods
Dinner Sausage          Dnr Sausage--Cocktails     Prepared Foods
Meat--Shelf Stable      Chili: Canned              Prepared Foods
Meat--Shelf Stable      Chunk Meats--Chix/Ham/     Prepared Foods
                         Etc.
Meat--Shelf Stable      Sandwich Sauce (Manwich)   Prepared Foods
Meat--Shelf Stable      Vienna Sausage             Prepared Foods
Meat--Shelf Stable      Luncheon Meat (Spam)       Prepared Foods
Meat--Shelf Stable      Hash: Canned               Prepared Foods
Meat--Shelf Stable      Beef Stew                  Prepared Foods
Meat--Shelf Stable      Hot Dog Chili Sauce        Prepared Foods
Meat--Shelf Stable      Beef/Pork--Dried Sliced W/ Prepared Foods
                         Gra
Meat--Shelf Stable      Potted Meats And Spreads   Prepared Foods
Meat--Shelf Stable      Corn Beef                  Prepared Foods
Party Tray              Deli Tray: Sandwiches      Prepared Foods
Party Tray              Deli Tray:                 Prepared Foods
                         Appetizers&Hors D'oe
Prepared/Pdgd Foods     Boxed Prepared/Entree/Dry  Prepared Foods
                         Prep
Prepared/Pdgd Foods     Vegetables/Dry Beans       Prepared Foods
Refrigerated            Vegetarian Meats           Prepared Foods
 Vegetarian
Refrigerated            Vegetarian Misc            Prepared Foods
 Vegetarian
Refrigerated            Non-Dairy Cheese           Prepared Foods
 Vegetarian
Refrigerated            Tofu                       Prepared Foods
 Vegetarian
Salad & Dips            Protein Salads--Bulk       Prepared Foods
Salad & Dips            Protein Salads--Prepack    Prepared Foods
Sandwiches              Sandwiches--(Cold)         Prepared Foods
Sushi                   Sushi--In Store Prepared   Prepared Foods
Sushi                   Sushi--Prepackaged         Prepared Foods
Traditional Asian       Asian Foods And Meals      Prepared Foods
 Foods
Traditional Asian       Traditional Thai Foods     Prepared Foods
 Foods
Traditional Mexican     Mexican Dinners And Foods  Prepared Foods
 Foods
Traditional Mexican     Mexican Enchilada Sauce    Prepared Foods
 Foods
Authentic Hispanic Fds  Authentic Pasta/Rice/      Rice
 & Product               Beans
Dry Bean Veg & Rice     Rice Side Dish Mixes Dry   Rice
Dry Bean Veg & Rice     Rice--Dry Bag And Box      Rice
Dry Bean Veg & Rice     Rice--Instant & Microwave  Rice
Bag Snacks              Potato Chips               Salty snacks
Bag Snacks              Tortilla/Nacho Chips       Salty snacks
Bag Snacks              Mult Pk Bag Snacks         Salty snacks
Bag Snacks              Bagged Cheese Snacks       Salty snacks
Bag Snacks              Corn Chips                 Salty snacks
Bag Snacks              Pretzels                   Salty snacks
Bag Snacks              Store Brand                Salty snacks
Bag Snacks              Misc Bag Snacks            Salty snacks
Bag Snacks              Bagged Popped Popcorn      Salty snacks
Bag Snacks              Pork Skins/Cracklins       Salty snacks
Popcorn                 Popcorn--Microwave         Salty snacks
Popcorn                 Popcorn--Other             Salty snacks
Popcorn                 Caramel Coated Snacks      Salty snacks
Snack                   Tortilla Chips             Salty snacks
Snack                   Soy/Rice Snacks            Salty snacks
Snacks                  Snacks: Pita Chips         Salty snacks
Snacks                  Snacks: Salty              Salty snacks
Snacks                  Snacks: Tortilla Chips     Salty snacks
Snacks                  Snacks: Crackers/Cookies   Salty snacks
Ss/Vending--Salty       Salty Snacks Vending       Salty snacks
 Snacks
Warehouse Snacks        Canister Snacks            Salty snacks
Warehouse Snacks        Snack Mix                  Salty snacks
Warehouse Snacks        Misc Snacks                Salty snacks
Authentic Hispanic Fds  Authentic Soups/Bouillons  Soup
 & Product
Canned Soups            Condensed Soup             Soup
Dry/Ramen Bouillon      Dry Soup                   Soup
Dry/Ramen Bouillon      Bouillon                   Soup
Rts/Micro Soup/Broth    Rts Soup: Chunky/          Soup
                         Homestyle/Et
Rts/Micro Soup/Broth    Broth                      Soup
Rts/Micro Soup/Broth    Microwavable Soups         Soup
Soup                    Cans Soup/Chili            Soup
Soup                    Broths                     Soup
Condiments              Honey/Syrup                Sugars
Dressings/Dips          Dips Caramel/Fruit Glazes  Sugars
Molasses/Syrups/        Molasses & Syrups          Sugars
 Pancake Mixes
Peanut Butter/Jelly/    Honey                      Sugars
 Jams & Honey
Sugars & Sweeteners     Sugar                      Sugars
Sugars & Sweeteners     Sweeteners                 Sugars
Aseptic Juice           Aseptic Pack Juice And     Sweetened Beverages
                         Drinks
Aseptic Juice           Aseptic Pack Juice And     Sweetened Beverages
                         Drinks
Authentic Hispanic Fds  Hispanic Carbonated        Sweetened Beverages
 & Product               Beverages
Authentic Hispanic Fds  Hispanic Juice Under 50%   Sweetened Beverages
 & Product               Juice
Beverages               Can/Btl Carb Beve 50% And  Sweetened Beverages
                         Unde
Cocoa Mixes             Malted Mlk/Syrup/Pwdrs     Sweetened Beverages
                         (Eggnog)
Cocoa Mixes             Hot Chocolate/Cocoa Mix    Sweetened Beverages
Energy Drinks           Energy Drink--Single       Sweetened Beverages
                         Serve
Energy Drinks           Energy Drink--Single       Sweetened Beverages
                         Serve (N)
Energy Drinks           Energy Drink--Multi-Pack   Sweetened Beverages
Energy Drinks           Energy Drink--Multi-Pack   Sweetened Beverages
                         (Non)
Frozen Juice And        Frzn Fruit Drinks (Under   Sweetened Beverages
 Smoothies               10% J)
Frozen Juice And        Frzn Conc Under 50% Juice  Sweetened Beverages
 Smoothies
Frozen Juice And        Smoothies-Frz              Sweetened Beverages
 Smoothies
Frozen Juice And        Cocktail Mixes-Frz         Sweetened Beverages
 Smoothies
Isotonic Drinks         Isotonic Drinks Single     Sweetened Beverages
                         Serve
Isotonic Drinks         Isotonic Drinks Multi-     Sweetened Beverages
                         Pack
Isotonic Drinks         Isotonic Drinks Multi-     Sweetened Beverages
                         Serve
Isotonic Drinks         Sports Drink N/Supplmnt    Sweetened Beverages
                         Milk/M
Juice                   Non-Carb Jce (Under 50%    Sweetened Beverages
                         Jce)
Juices Super Premium    Juices Smoothies/Blended   Sweetened Beverages
Juices Super Premium    Juices Antioxidant/        Sweetened Beverages
                         Wellness
Juices Super Premium    Juices (50% And Under      Sweetened Beverages
                         Juice)
Mixers Cocktail         Mixes--Fluid: Add Liq      Sweetened Beverages
Powder & Crystal Drink  Unsweetened Envelope       Sweetened Beverages
 Mix                     [Powder Drink Mix]
Powder & Crystal Drink  Sugar Free Canister        Sweetened Beverages
 Mix                     [Powder Drink Mix]
Powder & Crystal Drink  Sugar Free Sticks [Powder  Sweetened Beverages
 Mix                     Drink Mix]
Powder & Crystal Drink  Soft Drink Canisters       Sweetened Beverages
 Mix
Powder & Crystal Drink  Enhanced Stick [Powder     Sweetened Beverages
 Mix                     Drink Mix]
Powder & Crystal Drink  Sugar Sweetened Sticks     Sweetened Beverages
 Mix
Powder & Crystal Drink  Fluid Pouch [Powder Drink  Sweetened Beverages
 Mix                     Mix]
Powder & Crystal Drink  Breakfast Crystals         Sweetened Beverages
 Mix
Processed               Packaged Dry Mixes         Sweetened Beverages
Refrgratd Juices/       Dairy Case Juice Drnk      Sweetened Beverages
 Drinks                  Under 10
Refrgratd Juices/       Dairy Case Citrus Pnch/Oj  Sweetened Beverages
 Drinks                  Subs
Refrgratd Juices/       Dairy Case Tea With Sugar  Sweetened Beverages
 Drinks                  Or S
Refrgratd Juices/       Dairy Case Fruit Drinks    Sweetened Beverages
 Drinks                  (No Ju)
Rtd Tea/New Age Juice   Tea Sweetened              Sweetened Beverages
Rtd Tea/New Age Juice   Juice (Under 10% Juice)    Sweetened Beverages
Shelf Stable Juice      Fruit Drinks: Canned &     Sweetened Beverages
                         Glass
Shelf Stable Juice      Cranapple/Cran Grape       Sweetened Beverages
                         Juice (50)
Shelf Stable Juice      Cranberry Juice (50% And   Sweetened Beverages
                         Under)
Shelf Stable Juice      Blended Juice &            Sweetened Beverages
                         Combinations (50)
Shelf Stable Juice      Fruit Drinks: Canned &     Sweetened Beverages
                         Glass
Shelf Stable Juice      Apple Juice & Cider (50%   Sweetened Beverages
                         And U)
Shelf Stable Juice      Tomato Juice (50% And      Sweetened Beverages
                         Under)
Shelf Stable Juice      Blended Juice &            Sweetened Beverages
                         Combinations (Un)
Shelf Stable Juice      Fruit Drinks: Canned &     Sweetened Beverages
                         Glass
Soft Drinks             Soft Drinks 12/18 & 15pk   Sweetened Beverages
                         Can Car
Soft Drinks             Sft Drnk 2 Liter Btl Carb  Sweetened Beverages
                         Incl
Soft Drinks             Soft Drinks 20pk & 24pk    Sweetened Beverages
                         Can Carb
Soft Drinks             Sft Drnk Mlt-Pk Btl Carb   Sweetened Beverages
                         (Excp)
Soft Drinks             Sft Drnk Sngl Srv Btl      Sweetened Beverages
                         Carb (Ex)
Soft Drinks             Soft Drinks Can Non-Carb   Sweetened Beverages
                         (Exce)
Soft Drinks             Soft Drinks 6pk Can Carb   Sweetened Beverages
                         (Exp)
Soft Drinks             Sft Drnk 1 Liter Btl Carb  Sweetened Beverages
                         (Exc)
Soft Drinks             Tea Can With Sweetener/    Sweetened Beverages
                         Sugar
Soft Drinks             Soft Drink Bottle Non-     Sweetened Beverages
                         Carb (Ex)
Soft Drinks             Tea Bottles With           Sweetened Beverages
                         Sweetener/Sug
Soft Drinks             Mixers (Tonic Water/Gngr   Sweetened Beverages
                         Ale)
Soft Drinks             Seltzer Unflavored         Sweetened Beverages
Teas                    Instant Tea & Tea Mix (W/  Sweetened Beverages
                         Sugar)
Water                   Non-Carb Water Flvr--Drnk/ Sweetened Beverages
                         Mnr
Water--(Sparkling &     Still Water Flvrd Drnk/    Sweetened Beverages
 Still)                  Mnrl Wt
Water--(Sparkling &     Sparkling Water--Flvrd     Sweetened Beverages
 Still)                  Sweet
Authentic Hispanic Fds  Authentic Vegetables And   Vegetables
 & Product               Foods
Authentic Hispanic Fds  Authentic Peppers          Vegetables
 & Product
Authentic Italian       Italian Vegetables         Vegetables
 Foods
Broccoli/Cauliflower    Broccoli Whole & Crowns    Vegetables
Broccoli/Cauliflower    Cauliflower Whole          Vegetables
Can Vegetables--Shelf   Green Beans: Fs/Whl/Cut    Vegetables
 Stable
Can Vegetables--Shelf   Corn                       Vegetables
 Stable
Can Vegetables--Shelf   Peas/Green                 Vegetables
 Stable
Can Vegetables--Shelf   Spinach & Greens           Vegetables
 Stable
Can Vegetables--Shelf   Mushrooms Cnd & Glass      Vegetables
 Stable
Can Vegetables--Shelf   Sweet Potatoes             Vegetables
 Stable
Can Vegetables--Shelf   Mixed Vegetables           Vegetables
 Stable
Can Vegetables--Shelf   Carrots                    Vegetables
 Stable
Can Vegetables--Shelf   White Potatoes             Vegetables
 Stable
Can Vegetables--Shelf   Kraut & Cabbage            Vegetables
 Stable
Can Vegetables--Shelf   Beets                      Vegetables
 Stable
Can Vegetables--Shelf   Peas Fresh Pack/Crowder    Vegetables
 Stable
Can Vegetables--Shelf   Artichokes                 Vegetables
 Stable
Carrots                 Carrots Mini Peeled        Vegetables
Carrots                 Carrots Bagged             Vegetables
Carrots                 Carrots Bagged Organic     Vegetables
Corn                    Corn Bulk                  Vegetables
Corn                    Corn Is Packaged           Vegetables
Dry Sce/Gravy/Potatoes/ Potatoes: Dry              Vegetables
 Stuffng
Frozen Potatoes         Frzn French Fries          Vegetables
Frozen Potatoes         Frzn Tater Tots/Other      Vegetables
                         Extruded
Frozen Potatoes         Frzn Hashbrown Potatoes    Vegetables
Frozen Potatoes         Frzn Baked/Stuffed/Mashed  Vegetables
                         & Spec
Frozen Potatoes         Frzn Onion Rings           Vegetables
Frozen Vegetable & Veg  Fz Bag Vegetables--Plain   Vegetables
 Dish
Frozen Vegetable & Veg  Frzn Steamable Vegetables  Vegetables
 Dish
Frozen Vegetable & Veg  Fz Box Vegetables--Value-  Vegetables
 Dish                    Added
Frozen Vegetable & Veg  Frzn Corn On The Cob       Vegetables
 Dish
Frozen Vegetable & Veg  Fz Bag Vegetables--Value-  Vegetables
 Dish                    Added
Frozen Vegetable & Veg  Fz Box Vegetables--Plain   Vegetables
 Dish
Herbs/Garlic            Garlic Whole Cloves        Vegetables
Herbs/Garlic            Sprouts                    Vegetables
Mushrooms               Mushrooms White Sliced     Vegetables
                         Pkg
Mushrooms               Mushrooms White Whole Pkg  Vegetables
Mushrooms               Mushrooms Portabella       Vegetables
Mushrooms               Mushrooms White Bulk       Vegetables
Onions                  Onions Yellow (Bulk &      Vegetables
                         Bag)
Onions                  Onions Sweet (Bulk & Bag)  Vegetables
Onions                  Onions Red (Bulk & Bag)    Vegetables
Onions                  Onions White (Bulk & Bag)  Vegetables
Organics Fruit &        Organic Salad Mix          Vegetables
 Vegetables
Organics Fruit &        Organic Value-Added        Vegetables
 Vegetables              Vegetables
Party Tray              Deli Tray: Fruit And       Vegetables
                         Vegetable
Pasta & Pizza Sauce     Mainstream [Pasta & Pizza  Vegetables
                         Sauce]
Pasta & Pizza Sauce     Value [Pasta & Pizza       Vegetables
                         Sauce]
Pasta & Pizza Sauce     Pizza Sauce                Vegetables
Peppers                 Peppers Green Bell         Vegetables
Peppers                 Peppers Red Bell           Vegetables
Peppers                 Peppers Other Bell         Vegetables
Peppers                 Peppers Yellow Bell        Vegetables
Peppers                 Peppers Jalapeno           Vegetables
Peppers                 Peppers All Other          Vegetables
Potatoes                Potatoes Russet (Bulk &    Vegetables
                         Bag)
Potatoes                Potatoes Sweet & Yams      Vegetables
Potatoes                Potatoes Red (Bulk & Bag)  Vegetables
Potatoes                Potatoes Gourmet           Vegetables
Potatoes                Potatoes Gold (Bulk &      Vegetables
                         Bag)
Potatoes                Potatoes Other Organic     Vegetables
Salad & Dips            Vegetable Salads--Prepack  Vegetables
Salad & Dips            Vegetable Salads--Bulk     Vegetables
Salad & Dips            Salad: Lettuce             Vegetables
Salad & Dips            Salad Bar                  Vegetables
Salad Bar               Salad Bar Other            Vegetables
Salad Mix               Blends [Salad Mix]         Vegetables
Salad Mix               Regular Garden             Vegetables
Salad Mix               Garden Plus [Salad Mix]    Vegetables
Salad Mix               Kits [Salad Mix]           Vegetables
Salad Mix               Shredded Lettuce           Vegetables
Salad Mix               Salad Bowls                Vegetables
Salad Mix               Salad Mix Blends Organic   Vegetables
Salad Mix               Salad Spinach              Vegetables
Salad Mix               Coleslaw                   Vegetables
Salad Mix               Salad Spinach Organic      Vegetables
Seasonal                Pumpkins                   Vegetables
Spices/Jarred Garlic    Garlic Jar                 Vegetables
Tomato Products--Shelf  Tomatoes Diced             Vegetables
 Stable
Tomato Products--Shelf  Tomato Sauce               Vegetables
 Stable
Tomato Products--Shelf  Tomato Paste               Vegetables
 Stable
Tomato Products--Shelf  Tomato Stewed              Vegetables
 Stable
Tomato Products--Shelf  Tomatoes/Whole             Vegetables
 Stable
Tomato Products--Shelf  Tomato Crushed             Vegetables
 Stable
Tomatoes                Tomatoes Hothouse On The   Vegetables
                         Vine
Tomatoes                Roma Tomatoes (Bulk/Pkg)   Vegetables
Tomatoes                Tomatoes Vine Ripe Bulk    Vegetables
Tomatoes                Tomatoes Hot House Bulk    Vegetables
Tomatoes                Tomatoes Grape             Vegetables
Tomatoes                Tomatoes Vine Ripe Pkg     Vegetables
Tomatoes                Tomatoes Cherry            Vegetables
Tomatoes                Tomatoes--Other            Vegetables
Tomatoes                Tomatoes Others Organic    Vegetables
Tomatoes                Tomatoes Cocktail          Vegetables
Traditional Asian       Asian Vegetables           Vegetables
 Foods
Traditional Mexican     Mexican Peppers Chilies    Vegetables
 Foods
Value-Added Vegetables  Vegetable Party Tray       Vegetables
Value-Added Vegetables  Cut Vegetables All Other   Vegetables
Value-Added Vegetables  Instore Cut Vegetables     Vegetables
Vegetables Cooking      Celery                     Vegetables
 Bulk
Vegetables Cooking      Cabbage                    Vegetables
 Bulk
Vegetables Cooking      Asparagus                  Vegetables
 Bulk
Vegetables Cooking      Celery Organic             Vegetables
 Bulk
Vegetables Cooking      Broccoli/Cauliflower       Vegetables
 Packaged                Processed
Vegetables Cooking      Vegetables Cooking         Vegetables
 Packaged                Packaged
Vegetables Salad        Head Lettuce               Vegetables
Vegetables Salad        Cucumbers                  Vegetables
Vegetables Salad        Variety Lettuce            Vegetables
Vegetables Salad        Green Onions               Vegetables
Vegetables Salad        Radish                     Vegetables
Vegetables Salad        Variety Lettuce Organic    Vegetables
Vegetables Salad        Spinach Bulk               Vegetables
------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ
  International, LLC, 2016.


                     Appendix C. Crosswalk of Subcommodities to USDA Food Pattern Categories
----------------------------------------------------------------------------------------------------------------
                                       USDA Food           SoFAS              Composite              Other
   Commodity        Subcommodity        Pattern        Subcategories        Subcategories        Subcategories
----------------------------------------------------------------------------------------------------------------
Aseptic Juice    Kids Milk Drinks--  Dairy
                  Aseptic
Bag Snacks       Bagged Cheese       Dairy
                  Snacks
Bulk Service     Bulk Processed      Dairy
 Case Cheese      [Cheese]
Bulk Service     Bulk Semi-Hard      Dairy
 Case Cheese      [Cheese]
Bulk Service     Bulk Semi-Soft      Dairy
 Case Cheese      [Cheese]
Bulk Service     Cheese:             Dairy
 Case Cheese      Cheeseballs/
                  Spreads
Bulk Service     Cheese: Specialty   Dairy
 Case Cheese      Bulk
Bulk Service     Cheese: Specialty   Dairy
 Case Cheese      Prepack
Bulk Service     Service Case        Dairy
 Case Cheese      Natural [Cheese]
Bulk Service     Service Case        Dairy
 Case Cheese      Natural
                  Prepackage
                  [Cheese]
Bulk Service     Service Case        Dairy
 Case Cheese      Processed Prepack
                  [Cheese]
Canned & Dry     Aseptic Milk &      Dairy
 Milk             Milk Drinks
Canned & Dry     Canned Milk         Dairy
 Milk
Canned & Dry     Non Fat Dry Milk    Dairy
 Milk
Cheese           American Single     Dairy
                  Cheese
Cheese           Miscellaneous       Dairy
                  Cheese
Cheese           Natural Cheese      Dairy
                  Chunks
Cheese           Natural Cheese      Dairy
                  Random Wt
Cheese           Natural Cheese      Dairy
                  Slices
Cheese           Shredded Cheese     Dairy
Cheese           String Cheese       Dairy
Crackers & Misc  Aerosol Cheese      Dairy
 Baked Food
Cubes/           Cubes Cheese        Dairy
 Prepackage
 Cheese
Cubes/           Prepackage Cheese   Dairy
 Prepackage
 Cheese
Dry Cheese       Grated Cheese       Dairy
Dry Cheese       Loaf Cheese         Dairy
Dry Cheese       Misc Dry Cheese     Dairy
Fluid Milk       Buttermilk          Dairy
 Products
Fluid Milk       Egg Nog/Boiled      Dairy
 Products         Custard
Fluid Milk       Flavored Milk       Dairy
 Products
Fluid Milk       Fluid Milk/White    Dairy
 Products         Only
Fluid Milk       Half & Half         Dairy
 Products
Fluid Milk       Organic Milk        Dairy
 Products
Fluid Milk       Soy Milk            Dairy
 Products
Fluid Milk       Specialty/Lactose   Dairy
 Products         Free Milk
Milk By-         Cottage Cheese      Dairy
 Products
Milk By-         Ricotta Cheese      Dairy
 Products
Non-Dairy/Dairy  Aseptic Milk        Dairy
 Aseptic
Non-Dairy/Dairy  Soy Beverage        Dairy
 Aseptic
Pre-Slice        Pre-Sliced          Dairy
 Service Case     Processed
 Cheese           [Cheese]
Pre-Slice        Pre-Sliced Semi-    Dairy
 Service Case     Hard [Cheese]
 Cheese
Pre-Slice        Pre-Sliced Semi-    Dairy
 Service Case     Soft [Cheese]
 Cheese
Refrigerated     Cheese Spreads      Dairy
 Dairy Case
Refrigerated     Dairy Cheese        Dairy
 Dairy Case
Refrigerated     Fluid Milk          Dairy
 Dairy Case
Refrigerated     Kefir               Dairy
 Dairy Case
Refrigerated     Yogurt              Dairy
 Dairy Case
Refrigerated     Hispanic Cheese     Dairy
 Hispanic
 Grocery
Service          Sv Bev: Milk/Milk   Dairy
 Beverage         Products
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Blue
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Cheddar
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Cheeseba
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Feta
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Fresh
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Gift Pac
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Goat
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Gouda &
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Hard
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Hispanic
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Mozzarel
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Semi-Sof
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Smallwar
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Soft Rip
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Spreads
Specialty Bulk   Specialty Bulk      Dairy
 Cheese           Cheese Swiss
Specialty        Ppk Cheese Shoppe   Dairy
 Cheese Pre
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Blue/Gorg
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Cheddar &
 Pack             C
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Feta
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Fresh
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Gift Pack
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Goat Milk
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Gouda &
 Pack             Eda
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Hard/Grat
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Hispanic
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Mozzarell
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Processed
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Semi Soft
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Soft &
 Pack             Ripe
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Spreads
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese Swiss
 Pack
Specialty        Specialty Ppk       Dairy
 Cheese Pre       Cheese: Smallwar
 Pack
Traditional      Mexican Con Queso   Dairy
 Mexican Foods
Yogurt           Yogurt/Adult        Dairy
                  Drinks
Yogurt           Yogurt/Adult Multi- Dairy
                  Packs
Yogurt           Yogurt/Kids         Dairy
Yogurt           Yogurt/Large Size   Dairy
                  (16oz Or Lar)
Yogurt           Yogurt/Pro Active   Dairy
                  Health
Yogurt           Yogurt/Specialty    Dairy
                  Greek
Yogurt           Yogurt/Ss Light     Dairy
Yogurt           Yogurt/Ss Regular   Dairy
Apples           Apples Braeburn     Fruit
                  (Bulk & Bag)
Apples           Apples Braeburn     Fruit
                  (Bulk & Bag) Org
Apples           Apples Fuji (Bulk   Fruit
                  & Bag)
Apples           Apples Fuji (Bulk   Fruit
                  & Bag) Organic
Apples           Apples Gala (Bulk   Fruit
                  & Bag)
Apples           Apples Gala (Bulk   Fruit
                  & Bag) Organic
Apples           Apples Gold         Fruit
                  Delicious (Bulk &
                  Bag)
Apples           Apples Gold         Fruit
                  Delicious (Bulk &
                  Bag)
Apples           Apples Granny       Fruit
                  Smith (Bulk &
                  Bag)
Apples           Apples Granny       Fruit
                  Smith (Bulk &
                  Bag)
Apples           Apples Honeycrisp   Fruit
Apples           Apples Honeycrisp   Fruit
                  Organic
Apples           Apples Other (Bulk  Fruit
                  & Bag)
Apples           Apples Other (Bulk  Fruit
                  & Bag) Organic
Apples           Apples Red          Fruit
                  Delicious (Bulk &
                  Bag)
Apples           Apples Red          Fruit
                  Delicious (Bulk &
                  Bag)
Apples           Caramel/Candy       Fruit
                  Apples
Apples           Mixed Fruit Bags    Fruit
Authentic        Hispanic Juices     Fruit
 Hispanic Foods   Over 50% Juice
 & Products
Baking Needs     Maraschino          Fruit
                  Cherries
Bananas          Bananas             Fruit
Bananas          Bananas Organic     Fruit
Bananas          Bananas: Variety    Fruit
Berries          Berries Other       Fruit
Berries          Berries Other       Fruit
                  Organic
Berries          Blackberries        Fruit
Berries          Blackberries        Fruit
                  Organic
Berries          Blueberries         Fruit
Berries          Blueberries         Fruit
                  Organic
Berries          Cranberries         Fruit
Berries          Cranberries         Fruit
                  Organic
Berries          Raspberries         Fruit
Berries          Raspberries         Fruit
                  Organic
Berries          Strawberries        Fruit
Berries          Strawberries        Fruit
                  Organic
Beverages        Can/Btl Beverage    Fruit
                  Over 50% Juice
Bulk Food        Fruit Bulk          Fruit
Bulk Food        Fruit W/Sweetener   Fruit
Can Fruit/Jar    Apple Sauce         Fruit
 Applesauce       (Excludes Cup)
Can Fruit/Jar    Apples/Crabapples   Fruit
 Applesauce
Can Fruit/Jar    Berries/Cnd (Blu/   Fruit
 Applesauce       Blk/Rasp)
Can Fruit/Jar    Cherries (Except    Fruit
 Applesauce       Maraschino)
Can Fruit/Jar    Cranberry Sauce     Fruit
 Applesauce
Can Fruit/Jar    Fruit Cocktail/     Fruit
 Applesauce       Fruit Salad
Can Fruit/Jar    Mandarin Oranges/   Fruit
 Applesauce       Citrus Sect
Can Fruit/Jar    Misc. Cnd Fruit     Fruit
 Applesauce       (Grapes/Figs)
Can Fruit/Jar    Peaches             Fruit
 Applesauce
Can Fruit/Jar    Pears               Fruit
 Applesauce
Can Fruit/Jar    Pineapple           Fruit
 Applesauce
Citrus           Citrus--Other       Fruit
Citrus           Citrus Other        Fruit
                  Organic
Citrus           Clementines         Fruit
Citrus           Clementines         Fruit
                  Organic
Citrus           Grapefruit          Fruit
Citrus           Grapefruit Organic  Fruit
Citrus           Lemons              Fruit
Citrus           Lemons Organic      Fruit
Citrus           Limes               Fruit
Citrus           Limes Organic       Fruit
Citrus           Oranges Navels All  Fruit
Citrus           Oranges Navels All  Fruit
                  Organic
Citrus           Oranges Non Navel   Fruit
                  All
Citrus           Oranges Non Navel   Fruit
                  All Organic
Citrus           Tangerines &        Fruit
                  Tangelos
Citrus           Tangerines &        Fruit
                  Tangelos Organic
Coffee Shop      Sv Bev: Bev/Juice   Fruit
                  50-100% Jce
Coffee Shop      Sv Bev: Bev/Juice   Fruit
                  50-100% Jce
Convenience/     Convenience/        Fruit
 Snacking         Snacking Fruit
                  Pro
Convenience/     Jarred Fruit Multi  Fruit
 Snacking         Serve
Convenience/     Jarred Fruit        Fruit
 Snacking         Single Serve
Convenience/     Squeeze Fruits      Fruit
 Snacking
Dried Fruit      Dates Fruit
Dried Fruit      Dried Fruit--Other  Fruit
Dried Fruit      Dried Fruit         Fruit
                  Cranberries
Dried Fruit      Dried Fruit Other   Fruit
                  Organic
Dried Fruit      Dried Fruit W/      Fruit
                  Sweetener
Dried Fruit      Dried Plums         Fruit
Dried Fruit      Glace Fruit         Fruit
Dried Fruit      Raisins             Fruit
Frozen           Juice Over 50%      Fruit
 Breakfast        Juice
Frozen Fruits    Frozen Fruit        Fruit
Frozen Juice     Frzn Conc Allieds   Fruit
 And Smoothies    Over 50% Juice
Frozen Juice     Frozen Oj & Oj      Fruit
 And Smoothies    Substitutes
Fruit Snacks     Fruit Snacks        Fruit
Gift & Fruit     Fruit Baskets       Fruit
 Baskets
Gift & Fruit     In Store Made       Fruit
 Baskets          Fruit Baskets
Gift & Fruit     Ready To Sell       Fruit
 Baskets          Fruit Baskets
Grapes           Grapes Black/Blue   Fruit
Grapes           Grapes Black/Blue   Fruit
                  Organic
Grapes           Grapes Other        Fruit
Grapes           Grapes Other        Fruit
                  Organic
Grapes           Grapes Red          Fruit
Grapes           Grapes Red Globe    Fruit
Grapes           Grapes Red Globe    Fruit
                  Organic
Grapes           Grapes Red Organic  Fruit
Grapes           Grapes White        Fruit
Grapes           Grapes White        Fruit
                  Organic
Grapes           Grapes Wine         Fruit
Juice            Drinks--Carb Juice  Fruit
                  (Over 50% Juice)
Juice            Non-Carb Jce(Over   Fruit
                  50% Juice)
Juices Super     Cider               Fruit
 Premium
Juices Super     Juice Single Blend  Fruit
 Premium
Juices Super     Juices Organic      Fruit
 Premium          (Over 50% Juice)
Melons           Cantaloupe Whole    Fruit
Melons           Cantaloupe Whole    Fruit
                  Organic
Melons           Honeydew Whole      Fruit
Melons           Honeydew Whole      Fruit
                  Organic
Melons           Melons Whole Other  Fruit
Melons           Melons Whole Other  Fruit
                  Organic
Melons           Watermelon          Fruit
                  Personal
Melons           Watermelon          Fruit
                  Personal Organic
Melons           Watermelon          Fruit
                  Seedless Whole
Melons           Watermelon          Fruit
                  Seedless Whole
                  Organic
Melons           Watermelon W/Seeds  Fruit
                  Whole
Packaged         Dried Fruit         Fruit
 Natural Snacks
Packaged         Dried Fruit W/      Fruit
 Natural Snacks   Sweetener
Peanut Butter/   Apple Butter/Fruit  Fruit
 Jelly/Jams &     Butter
 Honey
Pears            Pears Anjou         Fruit
Pears            Pears Anjou         Fruit
                  Organic
Pears            Pears Asian         Fruit
Pears            Pears Asian         Fruit
                  Organic
Pears            Pears Bartlett      Fruit
Pears            Pears Bartlett      Fruit
                  Organic
Pears            Pears Bosc          Fruit
Pears            Pears Bosc Organic  Fruit
Pears            Pears Other         Fruit
Pears            Pears Other         Fruit
                  Organic
Pears            Pears Red           Fruit
Prepared/Pdgd    Apple Sauce/        Fruit
 Foods            Pudding
Prepared/Pdgd    Canned Fruit        Fruit
 Foods
Processed        Jarred Fruit        Fruit
Processed        Juice               Fruit
Processed        Squeeze Lemons/     Fruit
                  Limes
Refrgratd        Dairy Case 100%     Fruit
 Juices/Drinks    Pure Juice--
                  Orange
Refrgratd        Dairy Case 100%     Fruit
 Juices/Drinks    Pure Juice Other
Refrigerated     Nut Refrig Juice    Fruit
 Dairy Case       Over 50%
Rtd Tea/New Age  Juice (100% Juice)  Fruit
 Juice
Rtd Tea/New Age  Juice (Over 50%     Fruit
 Juice            Juice)
Salad Bar        Salad Bar Fresh     Fruit
                  Fruit
Seasonal Fruit   Baskets             Fruit
Service          Sv Bev: Bev/Juice   Fruit
 Beverage         50-100% Juice
Shelf Stable     Apple Juice &       Fruit
 Juice            Cider (Over 50%
                  Juice)
Shelf Stable     Blended Juice &     Fruit
 Juice            Combinations
Shelf Stable     Cranapple/Cran      Fruit
 Juice            Grape Juice
Shelf Stable     Cranapple/Cran      Fruit
 Juice            Grape Juice
Shelf Stable     Cranberry Juice     Fruit
 Juice            (Over 50% Juice)
Shelf Stable     Grape Juice (Over   Fruit
 Juice            50% Juice)
Shelf Stable     Grapefruit Juice    Fruit
 Juice            (Over 50% Juice)
Shelf Stable     Lemon Juice & Lime  Fruit
 Juice            Juice (Over 50%
                  Juice)
Shelf Stable     Nectars (Over 50%   Fruit
 Juice            Juice)
Shelf Stable     Orange Juice (Over  Fruit
 Juice            50% Juice)
Shelf Stable     Other Citrus        Fruit
 Juice            Juices (50% And
                  Under Juice)
Shelf Stable     Other Citrus        Fruit
 Juice            Juices (Over 50%
                  Juice)
Shelf Stable     Pineapple Juice     Fruit
 Juice            (Over 50% Juice)
Shelf Stable     Prune Juice (Over   Fruit
 Juice            50% Juice)
Single Serve     Applesauce Cup      Fruit
 Fruit/
 Applesauce
Single Serve     Applesauce Pouch    Fruit
 Fruit/
 Applesauce
Single Serve     Fruit Cup           Fruit
 Fruit/
 Applesauce
Stone Fruit      Apricots            Fruit
Stone Fruit      Cherries Ranier     Fruit
Stone Fruit      Cherries Red        Fruit
Stone Fruit      Cherries Red        Fruit
                  Organic
Stone Fruit      Nectarines White    Fruit
                  Flesh
Stone Fruit      Nectarines Yellow   Fruit
                  Flesh
Stone Fruit      Nectarines Yellow   Fruit
                  Flesh Organic
Stone Fruit      Peaches White       Fruit
                  Flesh
Stone Fruit      Peaches White       Fruit
                  Flesh Organic
Stone Fruit      Peaches Yellow      Fruit
                  Flesh
Stone Fruit      Peaches Yellow      Fruit
                  Flesh Organic
Stone Fruit      Plums               Fruit
Stone Fruit      Plums Organic       Fruit
Stone Fruit      Pluots              Fruit
Stone Fruit      Stone Fruit Other   Fruit
                  Organic
Tropical Fruit   Kiwi Fruit          Fruit
Tropical Fruit   Kiwi Fruit Organic  Fruit
Tropical Fruit   Mango               Fruit
Tropical Fruit   Mango Organic       Fruit
Tropical Fruit   Papaya              Fruit
Tropical Fruit   Pineapple Whole &   Fruit
                  Peel/Cored
Tropical Fruit   Pineapple Whole &   Fruit
                  Peel/Cored
                  Organic
Tropical Fruit   Pomegranates        Fruit
Tropical Fruit   Pomegranates        Fruit
                  Organic
Tropical Fruit   Tropical Fruit--    Fruit
                  Other
Tropical Fruit   Tropical Fruit      Fruit
                  Other Organic
Unknown          Frozen Fruit        Fruit
Value-Added      Cut Fruit All       Fruit
 Fruit            Other Prepack
Value-Added      Fruit Party Tray    Fruit
 Fruit            Prepack
Value-Added      Instore Cut Fruit   Fruit
 Fruit
Value-Added      Melon Halves/       Fruit
 Fruit            Quarters Prepack
Value-Added      Melons Instore Cut  Fruit
 Fruit
Value-Added      Pineapple Wedge/    Fruit
 Fruit            Sliced/Chunks
Value-Added      Value-Added Fruit   Fruit
 Fruit            Organic
Authentic        Hispanic Tostados   Grains
 Hispanic Fds &   & Tortillas
 Product
Bag Snacks       Bagged Popped       Grains
                  Popcorn
Bag Snacks       Bagged Popped       Grains
                  Popcorn W/
                  Sweetener
Bag Snacks       Corn Chips          Grains
Bag Snacks       Pretzel W/Sweetner  Grains
Bag Snacks       Pretzels            Grains
Bag Snacks       Tortilla/Nacho      Grains
                  Chips
Bagels & Cream   Refrigerated        Grains
 Cheese           Bagels
Baked Breads     Bagels              Grains
Baked Breads     Diet/Light Bread    Grains
Baked Breads     Dinner Rolls        Grains
Baked Breads     English Muffins/    Grains
                  Waffles
Baked Breads     Fruit/Breakfast     Grains
                  Bread
Baked Breads     Hamburger Buns      Grains
Baked Breads     Hot Dog Buns        Grains
Baked Breads     Main Meal Bread     Grains
Baked Breads     Mainstream Variety  Grains
                  Breads
Baked Breads     Mainstream White    Grains
                  Bread
Baked Breads     Pita/Tortillas      Grains
Baked Breads     Premium Bread       Grains
Baked Breads     Rye Breads          Grains
Baked Breads     Sandwich Buns       Grains
Bakery Party     Trays Party Trays:  Grains
                  Rolls
Baking Mixes     Biscuit Flour &     Grains
                  Mixes
Baking Mixes     Muffin & Corn       Grains
                  Bread Mix
Baking Needs     Corn Starch         Grains
Bread            All Other Bread     Grains
Bread            Bread--Ingredients  Grains
Bread            Bread Snacks        Grains
Bread            Bread: Diet/        Grains
                  Organic
Bread            Bread: Kosher       Grains
Bread            Bread: Artisan      Grains
Bread            Bread: Italian/     Grains
                  French
Bread            Bread: Pita/Pocket/ Grains
                  Flatbrd
Bread            Bread: Retail       Grains
                  Seasonings
Bread            Bread: Rye/         Grains
                  Cocktail
Bread            Bread: Sourdough    Grains
Bread            Bread: Specialty    Grains
Bread            Bread: Sweet/       Grains
                  Breakfast
Bread            Bread: Brand        Grains
Bread            Bread: Tortillas/   Grains
                  Wraps
Bread            Bread: Wheat/Whl    Grains
                  Grain
Bread            Bread: White Loaf   Grains
Bread            Gluten Free         Grains
Bread            Whole Grain Bread   Grains
Bulk Food        Cereal Bulk         Grains
Cereal Bars      Breakfast Bars/     Grains
                  Tarts/Scones
Cereals          Cereal--Cold        Grains
Cereals          Cereal--Hot         Grains
Cereals          Grains              Grains
Cereals          Granola             Grains
Cnv Breakfast &  Cereal Bars         Grains
 Wholesome Snks
Cnv Breakfast &  Granola Bars        Grains
 Wholesome Snks
Cnv Breakfast &  Toaster Pastries    Grains
 Wholesome Snks
Coffee Shop      Coffee Shop:        Grains
 Sweet Goods &    Bagged Snacks
 Rtl
Cold Cereal      Adult Cereal        Grains
Cold Cereal      All Family Cereal   Grains
Cold Cereal      Kids Cereal         Grains
Cold Cereal      Misc. Cereal        Grains
Cookie/Cracker   Multi-Pack          Grains
 Multi-Pks        Crackers
Cookies          Graham Crackers     Grains
Crackers         Crackers            Grains
Crackers & Misc  Butter Spray        Grains
 Baked Food       Cracker
Crackers & Misc  Cheese Crackers     Grains
 Baked Food
Crackers & Misc  Saltine/Oyster      Grains
 Baked Food
Crackers & Misc  Snack Crackers      Grains
 Baked Food
Crackers & Misc  Specialty Crackers  Grains
 Baked Food
Croutons/Bread   Bread Sticks        Grains
 Stick & Salad
 Toppings
Croutons/Bread   Croutons            Grains
 Stick & Salad
 Toppings
Croutons/Bread   Salad Toppers       Grains
 Stick & Salad
 Toppings
Deli             Dl Spec: Dry/       Grains
 Specialties      Refrig Pastas
 (Retail Pk)
Dietary Aid      Diabetic Dry        Grains
 Prdct/Med Liq    Cereal
 Nutr
Dinner Mixes--   Pizza Mix Dry       Grains
 Dry
Dry Bean Veg &   Misc Grain Mixes    Grains
 Rice
Dry Bean Veg &   Noodle Side Dish    Grains
 Rice             Mixes
Dry Bean Veg &   Rice--Dry Bag And   Grains
 Rice             Box
Dry Bean Veg &   Rice--Instant &     Grains
 Rice             Microwave
Dry Bean Veg &   Rice Side Dish      Grains
 Rice             Mixes Dry
Dry Noodles &    Long Cut Pasta      Grains
 Pasta
Dry Noodles &    Noodles Dry         Grains
 Pasta
Dry Noodles &    Short Cut Pasta     Grains
 Pasta
Dry Noodles &    Specialty Pasta     Grains
 Pasta
Dry Sauce/Gravy/ Stuffing Mixes      Grains
 Potatoes/
 Stuffing
Dry/Ramen        Ramen Noodles/      Grains
 Bouillon         Ramen Cups
Eggs/Muffins/    Refrigerated        Grains
 Potatoes         English Muffins
Flour & Meals    Breadings/Coatings/ Grains
                  Crumbs
Flour & Meals    Cornmeal            Grains
Flour & Meals    Flour: Misc/        Grains
                  Specialty/Blend
                  Et
Flour & Meals    Flour: White &      Grains
                  Self Rising
Frozen Bread     Allergen Free       Grains
 And Desserts     [Frozen Bread]
Frozen Bread     Breads              Grains
 And Desserts
Frozen Bread     Muffins/Bagels      Grains
 And Desserts
Frozen Bread     Rolls               Grains
 And Desserts
Frozen Bread     Sprouted Breads     Grains
 And Desserts
Frozen Bread/    Frzn Biscuits       Grains
 Dough
Frozen Bread/    Frzn Bread Dough    Grains
 Dough
Frozen Bread/    Frzn Breadsticks    Grains
 Dough
Frozen Bread/    Frzn Dinner Rolls   Grains
 Dough
Frozen Bread/    Frzn Garlic Bread   Grains
 Dough
Frozen Bread/    Frzn Garlic Toast   Grains
 Dough
Frozen Bread/    Frzn Sweet Rolls &  Grains
 Dough            Muffins
Frozen           Pancakes/French     Grains
 Breakfast        Toast
Frozen           Waffles             Grains
 Breakfast
Frozen           Frzn Bagels         Grains
 Breakfast
 Foods
Frozen           Frzn Breakfast      Grains
 Breakfast        Pastry
 Foods
Frozen           Waffles/Pancakes/   Grains
 Breakfast        French Toast
 Foods
Frzn Pasta       Frozen Pasta        Grains
Hot Cereal       Grits               Grains
Hot Cereal       Instant Breakfast   Grains
Hot Cereal       Instant Oatmeal     Grains
Hot Cereal       Other Hot Cereal    Grains
Hot Cereal       Standard Oatmeal    Grains
Kosher Foods     Kosher Matzas       Grains
 And Products
Kosher Foods     Kosher Noodles And  Grains
 And Products     Rice
Meat--Shelf      Tamales             Grains
 Stable
Molasses/Syrups/ Pancake Mixes       Grains
 Pancake Mixes
Multicultural    Rice Bulk/Bag       Grains
 Products
Non-Dairy/Dairy  Rice Beverage       Grains
 Aseptic
Pies             Pies: Sugar Free    Grains
Popcorn          Caramel Coated      Grains
                  Snacks
Popcorn          Popcorn--Microwave  Grains
Popcorn          Popcorn--Other      Grains
Prepared/Pdgd    Grains              Grains
 Foods
Prepared/Pdgd    Pasta/Ramen         Grains
 Foods
Refrgrated       Misc Refrig Dough   Grains
 Dough Products   Products
Refrgrated       Refrigerated        Grains
 Dough Products   Biscuits
Refrgrated       Refrigerated        Grains
 Dough Products   Breads
Refrgrated       Refrigerated        Grains
 Dough Products   Crescent Rolls
Refrgrated       Refrigerated        Grains
 Dough Products   Specialty Rolls
Refrigerated     Refrigerated        Grains
 Hispanic         Tortillas
 Grocery
Refrigerated     Refrigerated Pasta  Grains
 Italian
Rice Cakes       Large--Rice Cakes   Grains
Rice Cakes       Large Cakes         Grains
Rice Cakes       Mini--Rice Cakes    Grains
Rice Cakes       Mini-Cakes          Grains
Rice Cakes       Other--Rice Cakes   Grains
Rolls            Rolls: Bagels       Grains
Rolls            Rolls: Bagels--     Grains
                  Less Than 6
Rolls            Rolls: Biscuits/    Grains
                  Eng Muffins
Rolls            Rolls: Croissants/  Grains
                  Breadsticks
Rolls            Rolls: Diet/        Grains
                  Organic
Rolls            Rolls: Dinner       Grains
Rolls            Rolls: Kosher       Grains
Rolls            Rolls: Sandwich     Grains
Salad & Dips     Salads--Bulk        Grains
 Pasta/Grain
Salad & Dips     Salads--Prepack     Grains
 Pasta/Grain
Salad Toppings   Croutons Organic    Grains
Seafood--Salad/  Breading            Grains
 Dip/Sce/Cond
Snack            Popcorn             Grains
Snack            Popcorn W/          Grains
                  Sweetener
Snack            Tortilla Chips      Grains
Snacks           Snacks: Crackers/   Grains
                  Cookies
Snacks           Snacks: Bagel       Grains
                  Chips
Snacks           Snacks: Pita Chips  Grains
Snacks           Snacks: Tortilla    Grains
                  Chips
Specialty        Gourmet Crackers    Grains
 Cheese Pre
 Pack
Ss/Vending--     Vending Size/Sngl   Grains
 Cookie/Cracker   Serve Cracke
Syrups Toppings  Cones [Frozen       Grains
 & Cones          Novelties]
Traditional      Asian Noodles/Rice  Grains
 Asian Foods
Traditional      Mexican Soft        Grains
 Mexican Foods    Tortillas And Wra
Traditional      Mexican Taco/       Grains
 Mexican Foods    Tostado/Shells
Unknown          Frozen Bread        Grains
Unknown          Frozen Convenience/ Grains
                  Pockets
Bacon            Bacon--Natural/     Protein Foods
                  Organic
Bacon            Bacon--Other        Protein Foods
Bacon            Bacon--Poultry      Protein Foods
Bacon            Bacon--Pre-Cooked   Protein Foods
Bacon            Bacon--Trad 16oz    Protein Foods
                  Or Less
Bacon            Bacon--Trad Center  Protein Foods
                  Cut
Bacon            Bacon--Trad         Protein Foods
                  Greater Than 16oz
Baking Needs     Baking Nuts         Protein Foods
Beef: Chuck/     Choice Beef         Protein Foods
 Shoulder
Beef: Chuck/     Natural Beef        Protein Foods
 Shoulder
Beef: Chuck/     Organic Beef        Protein Foods
 Shoulder
Beef: Grinds     Angus [Beef]        Protein Foods
Beef: Grinds     Lean [Beef]         Protein Foods
Beef: Grinds     Natural [Beef]      Protein Foods
Beef: Grinds     Organic [Beef]      Protein Foods
Beef: Grinds     Patties [Beef]      Protein Foods
Beef: Grinds     Primal [Beef]       Protein Foods
Beef: Grinds     Sausage [Beef]      Protein Foods
Beef: Loins      Choice Beef         Protein Foods
Beef: Loins      Select Beef         Protein Foods
Beef: Offal      External [Beef      Protein Foods
                  Offal]
Beef: Rib        Angus Beef          Protein Foods
Beef: Rib        Prime Beef          Protein Foods
Beef: Round      Angus Beef          Protein Foods
Beef: Round      Choice Beef         Protein Foods
Beef: Round      Natural Beef        Protein Foods
Beef: Round      Organic Beef        Protein Foods
Beef: Round      Prime Beef          Protein Foods
Beef: Round      Select Beef         Protein Foods
Beef: Thin       Brisket             Protein Foods
 Meats
Beef: Thin       Corned Beef         Protein Foods
 Meats
Beef: Thin       Cubed Meats [Beef]  Protein Foods
 Meats
Beef: Thin       Flank [Beef]        Protein Foods
 Meats
Beef: Thin       Lifter Meat [Beef]  Protein Foods
 Meats
Beef: Thin       Skirt [Beef]        Protein Foods
 Meats
Beef: Thin       Soup/Stew           Protein Foods
 Meats
Breakfast        Bkfst Sausage--     Protein Foods
 Sausage          Bkfast Side Di
Breakfast        Bkfst Sausage--     Protein Foods
 Sausage          Fresh Links
Breakfast        Bkfst Sausage--     Protein Foods
 Sausage          Fresh Patties
Breakfast        Bkfst Sausage--     Protein Foods
 Sausage          Fresh Rolls
Breakfast        Bkfst Sausage--     Protein Foods
 Sausage          Other Forms
Breakfast        Bkfst Sausage--     Protein Foods
 Sausage          Precooked
Buffalo          Chuck/Shoulder      Protein Foods
                  [Buffalo]
Buffalo          Grinds [Buffalo]    Protein Foods
Buffalo          Loin [Buffalo]      Protein Foods
Buffalo          Natural [Buffalo]   Protein Foods
Buffalo          Rib [Buffalo]       Protein Foods
Buffalo          Round/Leg           Protein Foods
                  [Buffalo]
Buffalo          Thin Meats          Protein Foods
                  [Buffalo]
Bulk Food        Nuts Bulk W/        Protein Foods
                  Sweetener
Bulk Food        Trail Mix/Nuts      Protein Foods
                  Bulk
Can Beans        Prepared Beans--    Protein Foods
                  Baked W/Pork
Can Beans        Variety Beans--     Protein Foods
                  Kidney/Pinto/E
Can Seafood--    Anchovies           Protein Foods
 Shelf Stable
Can Seafood--    Caviar              Protein Foods
 Shelf Stable
Can Seafood--    Clam Juice          Protein Foods
 Shelf Stable
Can Seafood--    Clams               Protein Foods
 Shelf Stable
Can Seafood--    Crabmeat            Protein Foods
 Shelf Stable
Can Seafood--    Kipper Snack        Protein Foods
 Shelf Stable
Can Seafood--    Mackerel            Protein Foods
 Shelf Stable
Can Seafood--    Misc. Cnd Seafoods  Protein Foods
 Shelf Stable     (Crab/Etc.)
Can Seafood--    Oysters             Protein Foods
 Shelf Stable
Can Seafood--    Salmon              Protein Foods
 Shelf Stable
Can Seafood--    Sardines            Protein Foods
 Shelf Stable
Can Seafood--    Shrimp              Protein Foods
 Shelf Stable
Can Seafood--    Tuna                Protein Foods
 Shelf Stable
Chicken &        Chix/Poultry        Protein Foods
 Poultry          Ingredients
Chicken &        Chix: Baked 8pc     Protein Foods
 Poultry          Cut Up (Cold)
Chicken &        Chix: Chicken       Protein Foods
 Poultry          Dinners/Snacks C
Chicken &        Chix: Chicken       Protein Foods
 Poultry          Dinners/Snacks H
Chicken &        Chix: Kosher        Protein Foods
 Poultry          (Cold)
Chicken &        Chix: Rotisserie    Protein Foods
 Poultry          Cold
Chicken &        Chix: Frd 8pc/Cut   Protein Foods
 Poultry          Up (Cold)
Chicken &        Chix: Value-Added   Protein Foods
 Poultry          (Cold)
Chicken Fresh    Chicken Breast      Protein Foods
                  Boneless
Chicken Fresh    Chicken Drums       Protein Foods
Chicken Fresh    Chicken Legs/       Protein Foods
                  Quarters
Chicken Fresh    Chicken Thighs      Protein Foods
Chicken Fresh    Chicken Wings       Protein Foods
Chicken Fresh    Mixed Packs         Protein Foods
Chicken Fresh    Whole Chicken       Protein Foods
                  (Roasters/Fryer)
Chicken Frozen   Chicken--Frz Iqf--  Protein Foods
                  Raw
Chicken Frozen   Frzn Chicken--Drk   Protein Foods
                  Meat
Chicken Frozen   Frzn Chicken--Wht   Protein Foods
                  Meat
Chicken Frozen   Frzn Chicken--      Protein Foods
                  Wings
Chicken Frozen   Whole/Cutup         Protein Foods
                  [Chicken]
Chicken Frozen   Chicken Breast      Protein Foods
 (Rw)             Bone In
Chicken Frozen   Chicken Breast      Protein Foods
 (Rw)             Boneless
Chicken Frozen   Chicken Drums       Protein Foods
 (Rw)
Chicken Frozen   Chicken Legs/       Protein Foods
 (Rw)             Quarters
Chicken Frozen   Chicken Thighs      Protein Foods
 (Rw)
Chicken Frozen   Chicken Wings       Protein Foods
 (Rw)
Chicken Frozen   Whole Chicken       Protein Foods
 (Rw)             (Roasters/Fryer)
Chicken Grinds   Ground Chicken      Protein Foods
Chicken Offal    External [Chicken   Protein Foods
                  Offal]
Chicken Offal    Internal [Chicken   Protein Foods
                  Offal]
Chicken Organic  Chicken Breast      Protein Foods
                  Bone In
Chicken Smoked   Chicken Breast      Protein Foods
                  Bone In
Chicken          Chicken Breast      Protein Foods
 Specialty/       Bone In
 Natural
Chicken          Chicken Breast      Protein Foods
 Specialty/       Boneless
 Natural
Chicken          Chicken Drums       Protein Foods
 Specialty/
 Natural
Chicken          Chicken Legs/       Protein Foods
 Specialty/       Quarters
 Natural
Chicken          Chicken Thighs      Protein Foods
 Specialty/
 Natural
Chicken          Chicken Wings       Protein Foods
 Specialty/
 Natural
Chicken          Mixed Packs         Protein Foods
 Specialty/       [Chicken]
 Natural
Chicken          Whole Chicken       Protein Foods
 Specialty/       (Roasters/Fryer)
 Natural
Condiments       Nut Butters/Peanut  Protein Foods
                  Butter
Deli Meat: Bulk  Bologna/Loaves/     Protein Foods
                  Franks
Deli Meat: Bulk  Meat Bulk:          Protein Foods
                  Specialty Dry
                  Meats
Deli Meat: Bulk  Meat: Bacon         Protein Foods
Deli Meat: Bulk  Meat: Beef Bulk     Protein Foods
Deli Meat: Bulk  Meat: Chicken Bulk  Protein Foods
Deli Meat: Bulk  Meat: Gift Pack     Protein Foods
Deli Meat: Bulk  Meat: Ham Ppk/      Protein Foods
                  Prslc
Deli Meat: Bulk  Meat: Pates/Mousse  Protein Foods
Deli Meat: Bulk  Meat: Saus Dry Ppk/ Protein Foods
                  Prslc
Deli Meat: Bulk  Meat: Turkey Bulk   Protein Foods
Deli Meat: Bulk  Meat:Ham Bulk       Protein Foods
Deli Meat: Bulk  Meat: Lnchmt Ppk/   Protein Foods
                  Prslc
Deli Meat:       Deli Meat: Bacon    Protein Foods
 Other
Deli Meat:       Deli Meat: Kosher   Protein Foods
 Other
Deli Meat:       Deli Meat: Pates/   Protein Foods
 Other            Mousse
Deli Meat:       Deli Meat:          Protein Foods
 Other            Shippers/Gift
                  Packs
Deli Meat:       Deli Meat: Beef     Protein Foods
 Presliced
Deli Meat:       Deli Meat: Bologna/ Protein Foods
 Presliced        Loaves/Fran
Deli Meat:       Deli Meat: Chicken  Protein Foods
 Presliced
Deli Meat:       Deli Meat: Ham      Protein Foods
 Presliced
Deli Meat:       Deli Meat: Semi-    Protein Foods
 Presliced        Dry Sausage
Deli Meat:       Deli Meat:          Protein Foods
 Presliced        Specialty Dry
                  Meats
Deli Meat:       Deli Meat: Turkey   Protein Foods
 Presliced
Dinner Sausage   Dnr Sausage--Beef   Protein Foods
                  Rope Ckd/Sm
Dinner Sausage   Dnr Sausage--       Protein Foods
                  Cocktails
Dinner Sausage   Dnr Sausage--Fresh  Protein Foods
                  Poultry
Dinner Sausage   Dnr Sausage--Links  Protein Foods
                  Beef Ckd
Dinner Sausage   Dnr Sausage--Links  Protein Foods
                  Fresh
Dinner Sausage   Dnr Sausage--Links  Protein Foods
                  Pork Ckd
Dinner Sausage   Dnr Sausage--Links  Protein Foods
                  Poultry Ck
Dinner Sausage   Dnr Sausage--       Protein Foods
                  Natural/Organic
Dinner Sausage   Dnr Sausage--Other  Protein Foods
                  Forms
Dinner Sausage   Dnr Sausage--Pork   Protein Foods
                  Rope Ckd/Sm
Dinner Sausage   Dnr Sausage--       Protein Foods
                  Poultry Rope Ckd
Dinner Sausage   Dnr Saus-Rope/Link- Protein Foods
                  Smkd/Preckd
Eggs/Muffins/    Eggs--Jumbo         Protein Foods
 Potatoes
Eggs/Muffins/    Eggs--Large         Protein Foods
 Potatoes
Eggs/Muffins/    Eggs--Medium        Protein Foods
 Potatoes
Eggs/Muffins/    Eggs--Small         Protein Foods
 Potatoes
Eggs/Muffins/    Eggs--X-Large       Protein Foods
 Potatoes
Eggs/Muffins/    Eggs Substitute     Protein Foods
 Potatoes
Eggs/Muffins/    Specialty Eggs      Protein Foods
 Potatoes
Exotic           Goat                Protein Food
Exotic           Rabbit              Protein Foods
Frozen           Frzn Breakfast      Protein Foods
 Breakfast        Sausage
 Foods
Frozen           Frzn Egg            Protein Foods
 Breakfast        Substitutes
 Foods
Frozen Entrees   Meat Protein        Protein Foods
Frozen Meat      Frozen Meat         Protein Foods
Frozen Meat      Alternatives Meat   Protein Foods
Frozen Meat      Alternatives Soy/   Protein Foods
                  Tofu
Frzn Multi       Frzn Burgers        Protein Foods
 Serve
Frzn Multi       Fz Bbq              Protein Foods
 Serve
Frzn Multi       Fz Meatballs        Protein Foods
 Serve
Frzn Prepared    Bone-In Wings       Protein Foods
 Chicken
Frzn Prepared    Boneless Snack/     Protein Foods
 Chicken          18oz And Larger
Frzn Prepared    Boneless Snack/     Protein Foods
 Chicken          Value/Small
Frzn Prepared    Value Forms/18oz    Protein Foods
 Chicken          And Larger
                  [Chicken]
Frzn Prepared    Whole Muscle        Protein Foods
 Chicken          Breaded/18oz And
Frzn Prepared    Whole Muscle        Protein Foods
 Chicken          Unbreaded
Frzn Seafood     Frz Coated Fish     Protein Foods
                  Fillets
Frzn Seafood     Frz Fishsticks/     Protein Foods
                  Tenders/Nuggets
Frzn Seafood     Frz Non-Coated      Protein Foods
                  Fish Fillets
Frzn Seafood     Frz Seafood         Protein Foods
                  Entrees
Frzn Seafood     Frzn Misc Seafood   Protein Foods
Hot Dogs         Hot Dogs--Base      Protein Foods
                  Beef
Hot Dogs         Hot Dogs--Base      Protein Foods
                  Meat
Hot Dogs         Hot Dogs--Base      Protein Foods
                  Poultry
Hot Dogs         Hot Dogs--Premium   Protein Foods
Hot Dogs         Hot Dogs-Rw-All     Protein Foods
Kosher           Beef                Protein Foods
Kosher           Chicken             Protein Foods
Kosher           Lamb                Protein Foods
Kosher           Turkey              Protein Foods
Kosher           Veal                Protein Foods
Kosher Foods     Kosher Seafood      Protein Foods
 And Products
Lamb             Chuck/Shoulder      Protein Foods
                  [Lamb]
Lamb             Grinds [Lamb]       Protein Foods
Lamb             Loin [Lamb]         Protein Foods
Lamb             Offals [Lamb]       Protein Foods
Lamb             Rib [Lamb]          Protein Foods
Lamb             Round/Leg [Lamb]    Protein Foods
Lamb             Thin Meats [Lamb]   Protein Foods
Lunchmeat        Lunchmeat--Brauns/  Protein Foods
                  Liver/Loave
Lunchmeat        Lunchmeat--Chip     Protein Foods
                  Meat
Lunchmeat        Lunchmeat--Chop/    Protein Foods
                  Form Pltry & Ha
Lunchmeat        Lunchmeat--Other    Protein Foods
Lunchmeat        Lunchmeat--Peggabl  Protein Foods
                  e Deli Fres
Lunchmeat        Lunchmeat--Variety  Protein Foods
                  Pack
Lunchmeat        Lunchmeat--Whole    Protein Foods
                  Muscle Pltry
Lunchmeat        Lunchmeat--Rw-All   Protein Foods
Lunchmeat        Lunchmeat--Bologna/ Protein Foods
                  Sausage
Lunchmeat        Lunchmeat--Deli     Protein Foods
                  Fresh
Lunchmeat        Lunchmeat--Natural/ Protein Foods
                  Organic
Meat--Shelf      Beef Stew           Protein Foods
 Stable
Meat--Shelf      Beef/Pork--Dried    Protein Foods
 Stable           Sliced W/Gra
Meat--Shelf      Chicken &           Protein Foods
 Stable           Dumplings
Meat--Shelf      Chili: Canned       Protein Foods
 Stable
Meat--Shelf      Chunk Meats--Chix/  Protein Foods
 Stable           Ham/Etc.
Meat--Shelf      Corn Beef           Protein Foods
 Stable
Meat--Shelf      Hash: Canned        Protein Foods
 Stable
Meat--Shelf      Hot Dog Chili       Protein Foods
 Stable           Sauce
Meat--Shelf      Luncheon Meat       Protein Foods
 Stable           (Spam)
Meat--Shelf      Misc Cnd Meats      Protein Foods
 Stable
Meat--Shelf      Potted Meats And    Protein Foods
 Stable           Spreads
Meat--Shelf      Sandwich Sauce      Protein Foods
 Stable           (Manwich)
Meat--Shelf      Vienna Sausage      Protein Foods
 Stable
Meat Frozen      Frzn Meat--Beef     Protein Foods
Meat Frozen      Frzn Meat--         Protein Foods
                  Breakfast Sausage
Meat Frozen      Frzn Meat--Exotic   Protein Foods
Meat Frozen      Frzn Meat--Natural/ Protein Foods
                  Organic
Meat Frozen      Frzn Meat--Offals   Protein Foods
Meat Frozen      Frzn Meat--Pork     Protein Foods
Meat Frozen      Frzn Meat--Turkey   Protein Foods
Meat Frozen      Meat--Misc-Misc     Protein Foods
Meat Snacks      Jerky/Nuggets/      Protein Foods
                  Tenders
Meat Snacks      Meat Sticks/Bites   Protein Foods
Nat Foods--      Ntrn Refrig Meat:   Protein Foods
 Refrigerated     Breakfast Me
 Meat
Nat Foods--      Ntrn Refrig Meat:   Protein Foods
 Refrigerated     Hot Dogs/Sau
 Meat
Nat Foods--      Ntrn Refrig Meat:   Protein Foods
 Refrigerated     Lunchmeat
 Meat
Non-Dairy/Dairy  Nut Milk            Protein Foods
 Aseptic
Nuts             Almonds             Protein Foods
Nuts             Almonds Shelled     Protein Foods
Nuts             Almonds W/          Protein Foods
                  Sweetener
Nuts             Cashews             Protein Foods
Nuts             Cashews W/          Protein Foods
                  Sweetener
Nuts             Dry Roast Peanuts   Protein Foods
Nuts             Dry Roast Peanuts   Protein Foods
                  W/Sweetener
Nuts             Misc Snack Nuts     Protein Foods
Nuts             Misc Snacks Nuts W/ Protein Foods
                  Sweetener
Nuts             Mixed Nuts          Protein Foods
Nuts             Mixed Nuts W/       Protein Foods
                  Sweetener
Nuts             Nuts Inshell        Protein Foods
Nuts             Nuts Other          Protein Foods
Nuts             Nuts Other Organic  Protein Foods
Nuts             Nuts Sugar Coated   Protein Foods
                  All
Nuts             Oil Roast Peanuts   Protein Foods
Nuts             Oil Roast Peanuts   Protein Foods
                  W/Sweetener
Nuts             Peanuts All         Protein Foods
Nuts             Pecans Shelled      Protein Foods
Nuts             Pecans W/Sweetener  Protein Foods
Nuts             Pistachios          Protein Foods
Nuts             Sunflower/Other     Protein Foods
                  Seeds
Nuts             Sunflower/Other     Protein Foods
                  Seeds W/Sweete
Nuts             Trail Mix           Protein Foods
Nuts             Walnuts Shelled     Protein Foods
Packaged         Nuts                Protein Foods
 Natural Snacks
Packaged         Nuts W/Sweetener    Protein Foods
 Natural Snacks
Peanut Butter/   Peanut Butter       Protein Foods
 Jelly/Jams &
 Honey
Pkgd Meat Corp   Only Pkgd Meat      Protein Foods
 Use              Corp Use Only
Pork Bone In     Dry [Pork Bone In   Protein Foods
 Loin/Rib         Loin/Rib]
Pork Boneless    Enhanced [Pork      Protein Foods
 Loin/Rib         Boneless Loin/
                  Rib]
Pork Boneless    Natural [Pork       Protein Foods
 Loin/Rib         Boneless Loin/
                  Rib]
Pork Grinds      Ground Pork         Protein Foods
Pork Offal       External Fresh      Protein Foods
                  [Pork Offal]
Pork Offal       Internal Fresh      Protein Foods
                  [Pork Offal]
Pork Shoulder    Butts [Pork         Protein Foods
                  Shoulder]
Pork Shoulder    Fresh Hams          Protein Foods
Pork Thin Meats  Kabobs [Pork]       Protein Foods
Pork Thin Meats  Organics [Pork]     Protein Foods
Pork Thin Meats  Ribs [Pork]         Protein Foods
Pork Thin Meats  Stir Fry/Strips/    Protein Foods
                  Fajitas [Pork]
Poultry Other    Capons              Protein Foods
Poultry Other    Cornish Hen         Protein Foods
Poultry Other    Ducks               Protein Foods
Poultry Other    Geese               Protein Foods
Poultry Other    Poultry/Other       Protein Foods
Prepared/Pdgd    Meat--Can/Pouch     Protein Foods
 Foods
Processed        Beans Dried         Protein Foods
Random Weight    Lunch Meats         Protein Foods
 Meat Products
Refrigerated     Eggs                Protein Foods
 Dairy Case
Refrigerated     Non-Dairy Cheese    Protein Foods
 Vegetarian
Refrigerated     Tofu                Protein Foods
 Vegetarian
Refrigerated     Vegetarian Meats    Protein Foods
 Vegetarian
Restricted Diet  Pnut Btr/Jelly      Protein Foods
Salad & Dips     Protein Salads--    Protein Foods
                  Bulk
Salad & Dips     Protein Salads--    Protein Foods
                  Prepack
Seafood--Catfis  Catfish--Fillet     Protein Foods
 h
Seafood--Catfis  Catfish--Nuggets    Protein Foods
 h
Seafood--Catfis  Catfish--Other      Protein Foods
 h                Form
Seafood--Catfis  Catfish--Whole      Protein Foods
 h
Seafood--Cod     Cod--Fillet         Protein Foods
Seafood--Cod     Cod--Other Form     Protein Foods
Seafood--Cod     Cod--Whole          Protein Foods
Seafood--Crab    Crab--Dungy         Protein Foods
Seafood--Crab    Crab--King          Protein Foods
Seafood--Crab    Crab--Other         Protein Foods
Seafood--Crab    Crab--Snow          Protein Foods
Seafood--Exotic  Exotic--Mahi Mahi   Protein Foods
Seafood--Exotic  Exotic--Other       Protein Foods
Seafood--Exotic  Exotic--Red         Protein Foods
                  Snapper
Seafood--Exotic  Exotic--Shark       Protein Foods
Seafood--Exotic  Exotic--Swordfish   Protein Foods
Seafood--Exotic  Exotic--Tuna        Protein Foods
Seafood--Finfis  Finfish--Halibut    Protein Foods
 h Other
Seafood--Finfis  Finfish--Other      Protein Foods
 h Other
Seafood--Finfis  Finfish--Other      Protein Foods
 h Other
Seafood--Finfis  Finfish--Rockfish   Protein Foods
 h Other
Seafood--Finfis  Finfish--Sole/      Protein Foods
 h Other          Flounder
Seafood--Finfis  Finfish--Sole/      Protein Foods
 h Other          Flounder
Seafood--Imitat  Imitation Crab      Protein Foods
 ion Seafood
Seafood--Imitat  Imitation Other     Protein Foods
 ion Seafood
Seafood--Imitat  Imitation Shrimp    Protein Foods
 ion Seafood
Seafood--Lobste  Lobster--Live       Protein Foods
 r
Seafood--Lobste  Lobster--Meat       Protein Foods
 r
Seafood--Lobste  Lobster--Other      Protein Foods
 r                Form
Seafood--Lobste  Lobster--Tails      Protein Foods
 r
Seafood--Oyster  Oyster--Bulk        Protein Foods
Seafood--Oyster  Oyster--Cup         Protein Foods
                  (Packaged)
Seafood--Oyster  Oyster--Cup         Protein Foods
                  (Packaged)
Seafood--Party   Party Tray--Shrimp  Protein Foods
 Trays
Seafood--Salmon- Salmon Fr--         Protein Foods
 Farm Raised      Altantic
Seafood--Salmon- Salmon Fr--Other    Protein Foods
 Farm Raised      Form
Seafood--Salmon- Salmon Fr--         Protein Foods
 Farm Raised      Atlantic
Seafood--Salmon- Salmon Fr--Coho     Protein Foods
 Farm Raised
Seafood--Salmon- Salmon Fr--King     Protein Foods
 Farm Raised
Seafood--Salmon- Seafood--Fre-       Protein Foods
 Farm Raised      Catfish
Seafood--Salmon- Seafood--Fre-Misc   Protein Foods
 Farm Raised
Seafood--Salmon- Seafood--Fre-Raw    Protein Foods
 Farm Raised      Finfish--Other
Seafood--Salmon- Salmon Wc--Other    Protein Foods
 Wild Caught      Form
Seafood--Salmon- Salmon Wc--Coho     Protein Foods
 Wild Caught
Seafood--Salmon- Salmon Wc--King     Protein Foods
 Wild Caught
Seafood--Salmon- Salmon Wc--Pink     Protein Foods
 Wild Caught
Seafood--Salmon- Salmon Wc--         Protein Foods
 Wild Caught      Silverbrite
Seafood--Salmon- Salmon Wc--         Protein Foods
 Wild Caught      Silverbrite
Seafood--Salmon- Salmon Wc--Sockeye  Protein Foods
 Wild Caught
Seafood--Scallo  Scallops--Bay       Protein Foods
 ps
Seafood--Scallo  Scallops--Sea       Protein Foods
 ps
Seafood--Shellf  Shellfish--Clams    Protein Foods
 ish Other
Seafood--Shellf  Shellfish--Clams    Protein Foods
 ish Other
Seafood--Shellf  Shellfish--Mussles  Protein Foods
 ish Other
Seafood--Shellf  Shellfish--Other    Protein Foods
 ish Other
Seafood--Shrimp  Shrimp--Cooked      Protein Foods
Seafood--Shrimp  Shrimp--Natural/    Protein Foods
                  Organic
Seafood--Shrimp  Shrimp--Raw         Protein Foods
Seafood--Smoked  Smoked Other        Protein Foods
 Seafood
Seafood--Smoked  Smoked Salmon       Protein Foods
 Seafood
Seafood--Tilapi  Tilapia--Fillet     Protein Foods
 a
Seafood--Tilapi  Tilapia--Other      Protein Foods
 a                Form
Seafood--Tilapi  Tilapia--Whole      Protein Foods
 a
Seafood--Trout   Steelhead Fr        Protein Foods
Seafood--Trout   Trout--Fillet       Protein Foods
Seafood--Trout   Trout--Whole        Protein Foods
Seafood--Value-  Value-Added         Protein Foods
 Added Seafood    Catfish
Seafood--Value-  Value-Added In-     Protein Foods
 Added Seafood    Store Cooked Ho
Seafood--Value-  Value-Added         Protein Foods
 Added Seafood    Breaded Shrimp
Seafood--Value-  Value-Added Crab    Protein Foods
 Added Seafood
Seafood--Value-  Value-Added         Protein Foods
 Added Seafood    Finfish
Seafood--Value-  Value-Added In-     Protein Foods
 Added Seafood    Store Cooked Co
Seafood--Value-  Value-Added Kabobs  Protein Foods
 Added Seafood
Seafood--Value-  Value-Added Other   Protein Foods
 Added Seafood
Seafood--Value-  Value-Added Salmon  Protein Foods
 Added Seafood
Seafood--Value-  Value-Added Shrimp  Protein Foods
 Added Seafood
Seafood--Value-  Value-Added         Protein Foods
 Added Seafood    Tilapia
Seafood--Salad/  Herring             Protein Foods
 Dips/Sce/Cond
Service Case     Cooked              Protein Foods
 Meat
Service Case     Ingredients         Protein Foods
 Meat
Service Case     Kabobs Beef         Protein Foods
 Meat
Service Case     Kabobs Pork         Protein Foods
 Meat
Service Case     Kabobs Poultry      Protein Foods
 Meat
Service Case     Marinated Beef      Protein Foods
 Meat
Service Case     Marinated Pork      Protein Foods
 Meat
Service Case     Marinated Poultry   Protein Foods
 Meat
Service Case     Seasoned            Protein Foods
 Meat
Service Case     Seasoned Beef       Protein Foods
 Meat
Service Case     Seasoned Pork       Protein Foods
 Meat
Service Case     Seasoned Poultry    Protein Foods
 Meat
Service Case     Stuffed/Mixed Beef  Protein Foods
 Meat
Service Case     Stuffed/Mixed Pork  Protein Foods
 Meat
Service Case     Stuffed/Mixed       Protein Foods
 Meat             Poultry
Smoked Hams      Hams--Canned        Protein Foods
Smoked Hams      Hams--Dry Cured/    Protein Foods
                  Country
Smoked Hams      Hams--Half/Port     Protein Foods
                  Bone-In
Smoked Hams      Hams--Half/Port     Protein Foods
                  Boneless
Smoked Hams      Hams--Spiral        Protein Foods
Smoked Hams      Hams--Whole Bone-   Protein Foods
                  In
Smoked Hams      Hams--Whole         Protein Foods
                  Boneless
Smoked Pork      Bacon--Belly/Jowl   Protein Foods
Smoked Pork      Ham Steaks/Cubes/   Protein Foods
                  Slices
Smoked Pork      Smoked Chops Bone-  Protein Foods
                  In [Pork]
Smoked Pork      Smoked Chops        Protein Foods
                  Boneless [Pork]
Smoked Pork      Smoked Offal        Protein Foods
                  [Pork]
Smoked Pork      Smoked Picnics      Protein Foods
                  [Pork]
Snack Meat       Grnd/Patty--Chuck   Protein Foods
Snack Meat       Snack Meat--Other   Protein Foods
Snack Meat       Snack Meat--        Protein Foods
                  Pepperoni
Snack Meat       Snack Meat--Salami/ Protein Foods
                  Smr Sausag
Snacks           Snacks: Deli Nuts   Protein Foods
Ss/Vending--     Tube Nuts           Protein Foods
 Salty Snacks
Ss/Vending--     Tube Nuts W/        Protein Foods
 Salty Snacks     Sweetener
Turkey Fresh     Turkey Legs         Protein Foods
Turkey Fresh     Whole Hen (Under    Protein Foods
                  16lbs) [Turkey]
Turkey Fresh     Whole Tom (Over     Protein Foods
                  16lbs) [Turkey]
Turkey Frozen    Turkey Breast Bone  Protein Foods
                  In
Turkey Frozen    Turkey Breast       Protein Foods
                  Boneless
Turkey Frozen    Turkey Halves/      Protein Foods
                  Quarters
Turkey Frozen    Turkey Thighs       Protein Foods
Turkey Frozen    Whole Hens (Under   Protein Foods
                  16lbs) [Turkey]
Turkey Frozen    Whole Toms (Over    Protein Foods
                  16lbs) [Turkey]
Turkey Grinds    Ground Turkey       Protein Foods
Turkey Offal     External [Turkey    Protein Foods
                  Offal]
Turkey Offal     Internal [Turkey    Protein Foods
                  Offal]
Turkey Organic   Whole Hens (Under   Protein Foods
                  15lbs) [Turkey]
Turkey Organic   Whole Toms (Over    Protein Foods
                  15lbs) [Turkey]
Turkey Smoked    Turkey Drums        Protein Foods
Turkey Smoked    Turkey Wings        Protein Foods
Turkey           Whole Hens (Under   Protein Foods
 Specialty        15lbs) [Turkey]
 Natural
Turkey           Whole Toms (Over    Protein Foods
 Specialty        15lbs) [Turkey]
 Natural
Unknown          Beef--Boneless-     Protein Foods
                  Choice
Unknown          Beef--Grinds        Protein Foods
Unknown          Breast--Bone-In     Protein Foods
                  (Frz)
Unknown          Frozen Burgers      Protein Foods
Unknown          Frozen Meat         Protein Foods
Unknown          Frozen Meat         Protein Foods
                  (Vegetarian)
Unknown          Ham--Bone-In Whole  Protein Foods
Unknown          Ham--Boneless Half/ Protein Foods
                  Port
Unknown          Marinated           Protein Foods
Unknown          Meal Sol--          Protein Foods
                  Precooked Meats
Unknown          Meal Sol--Raw       Protein Foods
                  Frthr Preprd Mt
Unknown          Meat Frz--Misc      Protein Foods
Unknown          Seafood--Frz--Rw--  Protein Foods
                  All
Unknown          Smkd Ham Country--  Protein Foods
                  All
Unknown          Turkey--Grinds      Protein Foods
Unknown          Turkey--Other       Protein Foods
                  Parts/Pieces--Fre
Unknown          Whole--Tom (16 Lbs  Protein Foods
                  & Over Frz
Veal             Whole/Half [Veal]   Protein Foods
Nuts             Pecans              Protein Foods
Authentic        Authentic Peppers   Vegetables
 Hispanic Fds &
 Product
Authentic        Authentic Sauces/   Vegetables
 Hispanic Fds &   Salsa/Picante
 Product
Authentic        Authentic           Vegetables
 Hispanic Fds &   Vegetables And
 Product          Foods
Authentic        Italian Vegetables  Vegetables
 Italian Foods
Broccoli/        Brocco--Flower      Vegetables
 Cauliflower
Broccoli/        Broccoli Whole &    Vegetables
 Cauliflower      Crowns Organi
Broccoli/        Broccoli            Vegetables
 Cauliflower      Whole&Crowns
Broccoli/        Cauliflower Whole   Vegetables
 Cauliflower
Broccoli/        Cauliflower Whole   Vegetables
 Cauliflower      Organic
Can Vegetables-- Artichokes          Vegetables
 Shelf Stable
Can Vegetables-- Beans/Wax/Shellies  Vegetables
 Shelf Stable
Can Vegetables-- Beets               Vegetables
 Shelf Stable
Can Vegetables-- Carrots             Vegetables
 Shelf Stable
Can Vegetables-- Corn                Vegetables
 Shelf Stable
Can Vegetables-- Fried Onions        Vegetables
 Shelf Stable
Can Vegetables-- Green Beans: Fs/    Vegetables
 Shelf Stable     Whl/Cut
Can Vegetables-- Hominy              Vegetables
 Shelf Stable
Can Vegetables-- Kraut & Cabbage     Vegetables
 Shelf Stable
Can Vegetables-- Lima Beans          Vegetables
 Shelf Stable
Can Vegetables-- Miscellaneous       Vegetables
 Shelf Stable     Vegetables
Can Vegetables-- Mixed Vegetables    Vegetables
 Shelf Stable
Can Vegetables-- Mushrooms Cnd &     Vegetables
 Shelf Stable     Glass
Can Vegetables-- Peas & Onions/Peas  Vegetables
 Shelf Stable     & Carrot
Can Vegetables-- Peas Fresh Pack/    Vegetables
 Shelf Stable     Crowder
Can Vegetables-- Peas/Green          Vegetables
 Shelf Stable
Can Vegetables-- Pimentos            Vegetables
 Shelf Stable
Can Vegetables-- Salads Cnd (Bean/   Vegetables
 Shelf Stable     Potato)
Can Vegetables-- Spinach & Greens    Vegetables
 Shelf Stable
Can Vegetables-- Squash              Vegetables
 Shelf Stable
Can Vegetables-- Sweet Potatoes      Vegetables
 Shelf Stable
Can Vegetables-- White Potatoes      Vegetables
 Shelf Stable
Carrots          Carrots--Bulk       Vegetables
Carrots          Carrots Bagged      Vegetables
Carrots          Carrots Bagged      Vegetables
                  Organic
Carrots          Carrots Bulk        Vegetables
                  Organic
Carrots          Carrots Mini        Vegetables
                  Peeled
Carrots          Carrots Mini        Vegetables
                  Peeled Organic
Condiments       Salsa/Dips          Vegetables
Convenience/     Convenience/        Vegetables
 Snacking         Snacking Organic
Convenience/     Convenience/        Vegetables
 Snacking         Snacking
                  Vegetable
Corn             Corn Bulk           Vegetables
Corn             Corn Is Packaged    Vegetables
Corn             Corn Organic        Vegetables
Corn             Corn Packaged       Vegetables
Corn             Corn White          Vegetables
Dry Sauce/Gravy/ Potatoes: Dry       Vegetables
 Potatoes/
 Stuffing
Frozen Potatoes  Frzn Baked/Stuffed/ Vegetables
                  Mashed & Spec
Frozen Potatoes  Frzn French Fries   Vegetables
Frozen Potatoes  Frzn Hashbrown      Vegetables
                  Potatoes
Frozen Potatoes  Frzn Onion Rings    Vegetables
Frozen Potatoes  Frzn Tater Tots/    Vegetables
                  Other Extruded
Frozen           Frzn Breaded        Vegetables
 Vegetable &      Vegetables
 Veg Dish
Frozen           Frzn Corn On The    Vegetables
 Vegetable &      Cob
 Veg Dish
Frozen           Frzn Organic        Vegetables
 Vegetable &      Vegetables
 Veg Dish
Frozen           Frzn Steamable      Vegetables
 Vegetable &      Vegetables
 Veg Dish
Frozen           Fz Bag Vegetables-- Vegetables
 Vegetable &      Plain
 Veg Dish
Frozen           Fz Bag Vegetables-- Vegetables
 Vegetable &      Value-Added
 Veg Dish
Frozen           Fz Box Vegetables-- Vegetables
 Vegetable &      Plain
 Veg Dish
Frozen           Fz Box Vegetables-- Vegetables
 Vegetable &      Value-Added
 Veg Dish
Frozen           Bag Vegetables      Vegetables
 Vegetables And
 Potatoes
Frozen           Box Vegetables      Vegetables
 Vegetables And
 Potatoes
Frozen           Edamame             Vegetables
 Vegetables And
 Potatoes
Frozen           Potatoes            Vegetables
 Vegetables And
 Potatoes
Fruit & Veg      Herbs (Outdoor)     Vegetables
 Plants
 (Outdoor)
Fruit & Veg      Vegetable           Vegetables
 Plants
 (Outdoor)
Herbs/Garlic     Garlic Whole        Vegetables
                  Cloves
Herbs/Garlic     Garlic Whole        Vegetables
                  Cloves Organic
Herbs/Garlic     Herbs Basil         Vegetables
Herbs/Garlic     Herbs Basil         Vegetables
                  Organic
Herbs/Garlic     Herbs Cilanto       Vegetables
Herbs/Garlic     Herbs Cilantro      Vegetables
                  Organic
Herbs/Garlic     Herbs Fresh Other   Vegetables
Herbs/Garlic     Herbs Fresh Other   Vegetables
                  Organic
Herbs/Garlic     Herbs Parsley       Vegetables
Herbs/Garlic     Herbs Parsley       Vegetables
                  Organic
Herbs/Garlic     Sprouts             Vegetables
Kosher Foods     Kosher Potato       Vegetables
 And Products     Vegetable
Mushrooms        Mushrooms Dried     Vegetables
Mushrooms        Mushrooms Other     Vegetables
Mushrooms        Mushrooms Others    Vegetables
                  Organic
Mushrooms        Mushrooms           Vegetables
                  Portabella
Mushrooms        Mushrooms White     Vegetables
                  Bulk
Mushrooms        Mushrooms White     Vegetables
                  Sliced Pkg
Mushrooms        Mushrooms White     Vegetables
                  Whole Pkg
Mushrooms        Mushrooms White     Vegetables
                  Whole Pkg Organic
Onions           Onions Gourmet      Vegetables
Onions           Onions Other        Vegetables
Onions           Onions Other        Vegetables
                  Organic
Onions           Onions Red (Bulk &  Vegetables
                  Bag)
Onions           Onions Sweet (Bulk  Vegetables
                  & Bag)
Onions           Onions White (Bulk  Vegetables
                  & Bag)
Onions           Onions Yellow       Vegetables
                  (Bulk & Bag)
Organics Fruit   Organic Broccoli/   Vegetables
 & Vegetables     Cauliflower
Organics Fruit   Organic Fruit/Veg   Vegetables
 & Vegetables     Instore Proc
Organics Fruit   Organic Other       Vegetables
 & Vegetables
Organics Fruit   Organic Processed   Vegetables
 & Vegetables
Organics Fruit   Organic Salad Mix   Vegetables
 & Vegetables
Organics Fruit   Organic Value-      Vegetables
 & Vegetables     Added Vegetables
Organics Fruit   Organic Vegetables  Vegetables
 & Vegetables     Salad
Pasta & Pizza    Mainstream [Pasta   Vegetables
 Sauce            & Pizza Sauce]
Pasta & Pizza    Pizza Sauce         Vegetables
 Sauce
Pasta & Pizza    Specialty Italian   Vegetables
 Sauce            Sauce
Pasta & Pizza    Value [Pasta &      Vegetables
 Sauce            Pizza Sauce]
Peppers          Peppers All Other   Vegetables
Peppers          Peppers All Others  Vegetables
                  Organic
Peppers          Peppers Green Bell  Vegetables
Peppers          Peppers Green Bell  Vegetables
                  Organic
Peppers          Peppers Jalapeno    Vegetables
Peppers          Peppers Mini Sweet  Vegetables
                  Packaged
Peppers          Peppers Other Bell  Vegetables
Peppers          Peppers Other Bell  Vegetables
                  Organic
Peppers          Peppers Red Bell    Vegetables
Peppers          Peppers Red Bell    Vegetables
                  Organic
Peppers          Peppers Serrano     Vegetables
Peppers          Peppers Yellow      Vegetables
                  Bell
Peppers          Peppers Yellow      Vegetables
                  Bell Organic
Potatoes         Potatoes Gold       Vegetables
                  (Bulk & Bag)
Potatoes         Potatoes Gourmet    Vegetables
Potatoes         Potatoes Other      Vegetables
Potatoes         Potatoes Other      Vegetables
                  Organic
Potatoes         Potatoes Red (Bulk  Vegetables
                  & Bag)
Potatoes         Potatoes Russet     Vegetables
                  (Bulk & Bag)
Potatoes         Potatoes            Vegetables
                  Sweet&Yams
Potatoes         Potatoes White      Vegetables
                  (Bulk & Bag)
Prepared/Pdgd    Vegetables/Dry      Vegetables
 Foods            Beans
Processed        Jarred Vegetables   Vegetables
Refrigerated     Refrigerated Pasta  Vegetables
 Italian          Sauce
Salad & Dips     Sal: Hommus         Vegetables
Salad & Dips     Sal: Salsa/Dips     Vegetables
                  Bulk
Salad & Dips     Sal: Salsa Prepack  Vegetables
Salad & Dips     Salad Bar           Vegetables
Salad & Dips     Salad: Ingredients  Vegetables
Salad & Dips     Salad: Lettuce      Vegetables
Salad & Dips     Vegetable Salads--  Vegetables
                  Bulk
Salad & Dips     Vegetable Salads--  Vegetables
                  Prepack
Salad Bar        Processed Salad     Vegetables
Salad Mix        Blends [Salad Mix]  Vegetables
Salad Mix        Coleslaw            Vegetables
Salad Mix        Garden Plus [Salad  Vegetables
                  Mix]
Salad Mix        Kits [Salad Mix]    Vegetables
Salad Mix        Regular Garden      Vegetables
                  [Salad Mix]
Salad Mix        Salad Bowls         Vegetables
Salad Mix        Salad Mix Blends    Vegetables
                  Organic
Salad Mix        Salad Mix Kits      Vegetables
                  Organic
Salad Mix        Salad Mix Other     Vegetables
Salad Mix        Salad Spinach       Vegetables
Salad Mix        Salad Spinach       Vegetables
                  Organic
Salad Mix        Shredded Lettuce    Vegetables
Seasonal         Pumpkins            Vegetables
Shelf Stable     Tomato Juice (50%   Vegetables
 Juice            And Under)
Shelf Stable     Tomato Juice (Over  Vegetables
 Juice            50% Juice)
Shelf Stable     Veg Juice (Except   Vegetables
 Juice            Tomato) (50% And
                  Under)
Shelf Stable     Veg Juice (Except   Vegetables
 Juice            Tomato) (Over 50%
                  Juice)
Snack            Salsa               Vegetables
Spices/Jarred    Garlic Jar          Vegetables
 Garlic
Spices/Jarred    Garlic Jar Organic  Vegetables
 Garlic
Spices/Jarred    Herbs Dried         Vegetables
 Garlic
Spices/Jarred    Herbs Squeeze Tube  Vegetables
 Garlic           Organic
Spices/Jarred    Peppers Dried       Vegetables
 Garlic
Tomato           Tomato Stewed       Vegetables
 Products--Shel
 f
Tomato           Tomato Paste        Vegetables
 Products--Shel
 f Stable
Tomato           Tomatoes Diced      Vegetables
 Products--Shel
 f Stable
Tomato           Tomato Crushed      Vegetables
 Products--Shel
 f Stable
Tomato           Tomato Puree        Vegetables
 Products--Shel
 f Stable
Tomato           Tomato Sauce        Vegetables
 Products--Shel
 f Stable
Tomato           Tomato Sun Dried    Vegetables
 Products--Shel
 f Stable
Tomato           Tomatoes/Whole      Vegetables
 Products--Shel
 f Stable
Tomatoes         Roma Tomatoes       Vegetables
                  (Bulk/Pkg)
Tomatoes         Tomatoes Cherry     Vegetables
Tomatoes         Tomatoes Cherry     Vegetables
                  Organic
Tomatoes         Tomatoes Cocktail   Vegetables
Tomatoes         Tomatoes Grape      Vegetables
Tomatoes         Tomatoes Grape      Vegetables
                  Organic
Tomatoes         Tomatoes Hot House  Vegetables
                  Bulk
Tomatoes         Tomatoes Hothouse   Vegetables
                  On The Vine
Tomatoes         Tomatoes Hothouse   Vegetables
                  Pkg
Tomatoes         Tomatoes Others     Vegetables
                  Organic
Tomatoes         Tomatoes Snacking   Vegetables
                  Colored
Tomatoes         Tomatoes Vine Ripe  Vegetables
                  Bulk
Tomatoes         Tomatoes Vine Ripe  Vegetables
                  Pkg
Tomatoes         Tomatoes--Other     Vegetables
Traditional      Asian Vegetables    Vegetables
 Asian Foods
Traditional      Mexican Beans/      Vegetables
 Mexican Foods    Refried
Traditional      Mexican Enchilada   Vegetables
 Mexican Foods    Sauce
Traditional      Mexican Peppers     Vegetables
 Mexican Foods    Chilies
Traditional      Mexican Sauces And  Vegetables
 Mexican Foods    Picante Sau
Tropical Fruit   Avocado             Vegetables
Tropical Fruit   Avocado Organic     Vegetables
Unknown          Frozen Vegetables   Vegetables
Value-Added      Celery Chopped/     Vegetables
 Vegetables       Sticks
Value-Added      Cut Vegetables All  Vegetables
 Vegetables       Other
Value-Added      Instore Cut         Vegetables
 Vegetables       Vegetables
Value-Added      Onions Processed    Vegetables
 Vegetables
Value-Added      Vegetable Party     Vegetables
 Vegetables       Tray
Vegetables       Asparagus           Vegetables
 Cooking Bulk
Vegetables       Beans               Vegetables
 Cooking Bulk
Vegetables       Beans Organic       Vegetables
 Cooking Bulk
Vegetables       Cabbage             Vegetables
 Cooking Bulk
Vegetables       Cabbage Organic     Vegetables
 Cooking Bulk
Vegetables       Celery              Vegetables
 Cooking Bulk
Vegetables       Celery Organic      Vegetables
 Cooking Bulk
Vegetables       Greens Bulk         Vegetables
 Cooking Bulk
Vegetables       Greens Bulk         Vegetables
 Cooking Bulk     Organic
Vegetables       Hard Squash         Vegetables
 Cooking Bulk
Vegetables       Organic Vegetables  Vegetables
 Cooking Bulk     All Others
Vegetables       Squash Other        Vegetables
 Cooking Bulk
Vegetables       Squash Other        Vegetables
 Cooking Bulk     Organic
Vegetables       Vegetables All      Vegetables
 Cooking Bulk     Other
Vegetables       Vegetables Cooking  Vegetables
 Cooking          Packaged Organic
 Packaged
Vegetables       Broccoli/           Vegetables
 Cooking          Cauliflower
 Packaged         Processed
Vegetables       Potatoes/Onions     Vegetables
 Cooking          Processed
 Packaged
Vegetables       Vegetables Cooking  Vegetables
 Cooking          Packaged
 Packaged
Vegetables       Cucumbers           Vegetables
 Salad
Vegetables       Cucumbers Organic   Vegetables
 Salad
Vegetables       Green Onions        Vegetables
 Salad
Vegetables       Green Onions        Vegetables
 Salad            Organic
Vegetables       Head Lettuce        Vegetables
 Salad
Vegetables       Head Lettuce        Vegetables
 Salad            Organic
Vegetables       Radish              Vegetables
 Salad
Vegetables       Radishes Organic    Vegetables
 Salad
Vegetables       Spinach Bulk        Vegetables
 Salad
Vegetables       Spring Mix Bulk     Vegetables
 Salad
Vegetables       Variety Lettuce     Vegetables
 Salad
Vegetables       Variety Lettuce     Vegetables
 Salad            Organic
Authentic        Italian Oils And    Oils
 Italian Foods    Dressings
Deli             Dl Spec: Sauces/    Oils
 Specialties      Sld Dressings
 (Retail Pk)
Dressings/Dips   Dressing Blue       Oils
                  Cheese
Dressings/Dips   Dressing Cole Slaw  Oils
Dressings/Dips   Dressing Creamy     Oils
Dressings/Dips   Dressing Ginger     Oils
Dressings/Dips   Dressing Organics   Oils
Dressings/Dips   Dressing            Oils
                  Vinegarette
Dressings/Dips   Dressing Yogurt     Oils
                  Based
Margarines       Margarine: Squeeze  Oils
Margarines       Margarine: Tubs     Oils
                  And Bowls
Processed        Dressings           Oils
Salad Dresing &  Mayonnaise &        Oils
 Sandwich         Whipped Dressing
 Spreads
Salad Dresing &  Pourable Salad      Oils
 Sandwich         Dressings
 Spreads
Salad Dresing &  Sand/Horseradish &  Oils
 Sandwich         Tartar Sauce
 Spreads
Shortening &     Canola Oils         Oils
 Oil
Shortening &     Cooking Oil:        Oils
 Oil              Peanut/Safflower
Shortening &     Cooking Sprays      Oils
 Oil
Shortening &     Corn Oil            Oils
 Oil
Shortening &     Misc Oils           Oils
 Oil
Shortening &     Olive Oil           Oils
 Oil
Shortening &     Vegetable Oil       Oils
 Oil
Aseptic Juice    Aseptic Pack Juice  Solid Fats &   sweetened beverage
                  And Drinks          Added Sugar
Aseptic Juice    Aseptic Pack Juice  Solid Fats &   sweetened beverage
                  And Drinks          Added Sugar
Aseptic Juice    Aseptic Pack Juice  Solid Fats &   sweetened beverage
                  And Drinks          Added Sugar
Authentic        Central American    Solid Fats &   candy/sweet
 Central          Candy W/O Flour     Added Sugar
 American Fds
Authentic        Central American    Solid Fats &   sweetened beverage
 Central          Carbonated Bev      Added Sugar
 American Fds
Authentic        Hispanic            Solid Fats &   sweetened beverage
 Hispanic Fds &   Carbonated          Added Sugar
 Product          Beverages
Authentic        Authentic Dry       Solid Fats &   sweetened beverage
 Hispanic Fds &   Beverages W/        Added Sugar
 Product          Sweetener
Authentic        Hispanic Juice      Solid Fats &   sweetened beverage
 Hispanic Fds &   Under 50% Juice     Added Sugar
 Product
Authentic South  South American      Solid Fats &   candy/sweet
 American Fds     Candy W/O Flour     Added Sugar
Bag Snacks       Pork Skins/         Solid Fats &   butter/cream/solid
                  Cracklins           Added Sugar    fat
Bagels & Cream   Cream Cheese        Solid Fats &   butter/cream/solid
 Cheese                               Added Sugar    fat
Baking           Chocolate Chips &   Solid Fats &   candy/sweet
                  Bars (Sweete)       Added Sugar
Baking Mixes     Frosting            Solid Fats &   candy/sweet
                                      Added Sugar
Baking Needs     Coconut [Baking     Solid Fats &   butter/cream/solid
                  Needs]              Added Sugar    fat
Baking Needs     Marshmallow Creme   Solid Fats &   candy/sweet
                                      Added Sugar
Baking Needs     Marshmallows        Solid Fats &   candy/sweet
                                      Added Sugar
Beverages        Can/Btl Carb Beve   Solid Fats &   sweetened beverage
                  50% And Under       Added Sugar
Beverages        Can/Btl N/Carb      Solid Fats &   sweetened beverage
                  Beve 50% And        Added Sugar
                  Under
Beverages        Tea (Canned/        Solid Fats &   sweetened beverage
                  Bottled) W/         Added Sugar
                  Sweetener
Bulk Food        Candy Bulk          Solid Fats &   candy/sweet
                                      Added Sugar
Bulk Food        Candy Bulk W/Flour  Solid Fats &   candy/sweet
                                      Added Sugar
Cake Decor       Cake Decors--       Solid Fats &   candy/sweet
                  Candies             Added Sugar
Cake Decor       Cake Decors &       Solid Fats &   candy/sweet
                  Icing               Added Sugar
Candy            Candy W/Flour       Solid Fats &   candy/sweet
                                      Added Sugar
Candy            Candy/Chocolate     Solid Fats &   candy/sweet
                                      Added Sugar
Candy--Checklan  Candy Bars          Solid Fats &   candy/sweet
 e                (Singles)           Added Sugar
                  (Including)
Candy--Checklan  Candy Bars          Solid Fats &   candy/sweet
 e                (Singles)           Added Sugar
                  (Including)
Candy--Checklan  Chewing Gum         Solid Fats &   candy/sweet
 e                                    Added Sugar
Candy--Checklan  Mints/Candy &       Solid Fats &   candy/sweet
 e                Breath (Not         Added Sugar
                  Lifesavers)
Candy--Checklan  Mints/Candy &       Solid Fats &   candy/sweet
 e                Breath (Not         Added Sugar
                  Lifesavers)
Candy--Checklan  Misc Checklane      Solid Fats &   candy/sweet
 e                Candy               Added Sugar
Candy--Packaged  Bulk Candy          Solid Fats &   candy/sweet
                                      Added Sugar
Candy--Packaged  Bulk Candy W/Flour  Solid Fats &   candy/sweet
                                      Added Sugar
Candy--Packaged  Candy & Breath      Solid Fats &   candy/sweet
                  Mints (Pkgd)        Added Sugar
Candy--Packaged  Candy & Breath      Solid Fats &   candy/sweet
                  Mints (Pkgd)        Added Sugar
Candy--Packaged  Candy Bags--        Solid Fats &   candy/sweet
                  Chocolate           Added Sugar
Candy--Packaged  Candy Bags--        Solid Fats &   candy/sweet
                  Chocolate W/Flour   Added Sugar
Candy--Packaged  Candy Bags--Non     Solid Fats &   candy/sweet
                  Chocolate           Added Sugar
Candy--Packaged  Candy Bags--Non     Solid Fats &   candy/sweet
                  Chocolate W/Flour   Added Sugar
Candy--Packaged  Candy Bars (Multi   Solid Fats &   candy/sweet
                  Pack)               Added Sugar
Candy--Packaged  Candy Bars Multi    Solid Fats &   candy/sweet
                  Pack W/Flour        Added Sugar
Candy--Packaged  Candy Box Non-      Solid Fats &   candy/sweet
                  Chocolate           Added Sugar
Candy--Packaged  Candy Box Non-      Solid Fats &   candy/sweet
                  Chocolate W/Flour   Added Sugar
Candy--Packaged  Candy Boxed         Solid Fats &   candy/sweet
                  Chocolates          Added Sugar
Candy--Packaged  Candy Boxed         Solid Fats &   candy/sweet
                  Chocolates W/       Added Sugar
                  Flour
Candy--Packaged  Candy Refrigerated  Solid Fats &   candy/sweet
                                      Added Sugar
Candy--Packaged  Gum (Packaged)      Solid Fats &   candy/sweet
                                      Added Sugar
Candy--Packaged  Hispanic Candy      Solid Fats &   candy/sweet
                                      Added Sugar
Candy--Packaged  Miscellaneous       Solid Fats &   candy/sweet
                  Candy               Added Sugar
Candy--Packaged  Miscellaneous       Solid Fats &   candy/sweet
                  Candy               Added Sugar
Candy--Packaged  Novelty Candy       Solid Fats &   candy/sweet
                                      Added Sugar
Candy--Packaged  Novelty Candy W/    Solid Fats &   candy/sweet
                  Flour               Added Sugar
Candy--Packaged  Novelty Candy--     Solid Fats &   candy/sweet
                  Taxable             Added Sugar
Candy--Packaged  Seasonal Candy      Solid Fats &   candy/sweet
                  Bags Non-           Added Sugar
                  Chocolate
Candy--Packaged  Seasonal Candy      Solid Fats &   candy/sweet
                  Bags Non-           Added Sugar
                  Chocolate
Candy--Packaged  Seasonal Candy      Solid Fats &   candy/sweet
                  Bags--Chocolate     Added Sugar
Candy--Packaged  Seasonal Candy      Solid Fats &   candy/sweet
                  Bags--Chocolate     Added Sugar
Candy--Packaged  Seasonal Candy Box  Solid Fats &   candy/sweet
                  Non-Chocolate       Added Sugar
Candy--Packaged  Seasonal Candy Box  Solid Fats &   candy/sweet
                  Non-Chocolate       Added Sugar
Candy--Packaged  Seasonal Candy      Solid Fats &   candy/sweet
                  Box--Chocolate      Added Sugar
Candy--Packaged  Seasonal Candy      Solid Fats &   candy/sweet
                  Box--Chocolate W/   Added Sugar
                  Flour
Candy--Packaged  Seasonal            Solid Fats &   candy/sweet
                  Miscellaneous       Added Sugar
                  [Candy]
Candy--Packaged  Seasonal            Solid Fats &   candy/sweet
                  Miscellaneous W/    Added Sugar
                  Flour
Cocoa Mixes      Hot Chocolate/      Solid Fats &   sweetened beverage
                  Cocoa Mix           Added Sugar
Cocoa Mixes      Malted Mlk/Syrup/   Solid Fats &   sweetened beverage
                  Pwdrs (Eggnog)      Added Sugar
Coffee &         Coffee Sweeteners   Solid Fats &   sweetened beverage
 Creamers                             Added Sugar
Coffee &         Non Dairy Creamer   Solid Fats &   sweetened beverage
 Creamers                             Added Sugar
Coffee Shop      Coffee Shop: Candy  Solid Fats &   candy/sweet
 Sweet Goods &                        Added Sugar
 Rtl
Condiments       Honey/Syrup         Solid Fats &   candy/sweet
                                      Added Sugar
Condiments       Jellies/Preserves/  Solid Fats &   candy/sweet
                  Apple Butter        Added Sugar
Deli             Dl Spec: Jellies/   Solid Fats &   Sugar candy/sweet
 Specialties      Toppings            Added
 (Retail Pk)
Dressings/Dips   Dips Caramel/Fruit  Solid Fats &   candy/sweet
                  Glazes              Added Sugar
Dressings/Dips   Dips Fruit And      Solid Fats &   candy/sweet
                  Chocolate           Added Sugar
Dry Mix          Desserts Topping    Solid Fats &   butter/cream/solid
                  Mixes/Whip          Added Sugar    fat
                  Topping
Dry Tea/Coffee/  Coco Mix            Solid Fats &   sweetened beverage
 Coco Mixes                           Added Sugar
Dry Tea/Coffee/  Tea Concentrate W/  Solid Fats &   sweetened beverage
 Coco Mixes       Sweetener/Su        Added Sugar
Dry Tea/Coffee/  Tea Rtd With        Solid Fats &   sweetened beverage
 Coco Mixes       Sweetener/Sugar     Added Sugar
Energy Drinks    Energy Drink--      Solid Fats &   sweetened beverage
                  Multi-Pack          Added Sugar
Energy Drinks    Energy Drink--      Solid Fats &   sweetened beverage
                  Multi-Pack (Non)    Added Sugar
Energy Drinks    Energy Drink--      Solid Fats &   sweetened beverage
                  Single Serve        Added Sugar
Energy Drinks    Energy Drink--      Solid Fats &   sweetened beverage
                  Single Serve        Added Sugar
European Foods   British Carbonated  Solid Fats &   sweetened beverage
                  Beverages           Added Sugar
European Foods   European            Solid Fats &   sweetened beverage
                  Carbonated          Added Sugar
                  Beverages
Fluid Milk       Refrigerated        Solid Fats &   butter/cream/solid
 Products         Coffee Creamers     Added Sugar    fat
Fluid Milk       Whipping Cream      Solid Fats &   butter/cream/solid
 Products                             Added Sugar    fat
Frozen           Frzn Non-Dairy      Solid Fats &   butter/cream/solid
 Breakfast        Creamers            Added Sugar    fat
 Foods
Frozen Juice     Cocktail Mixes-Frz  Solid Fats &   sweetened beverage
 And Smoothies                        Added Sugar
Frozen Juice     Frzn Conc Under     Solid Fats &   sweetened beverage
 And Smoothies    50% Juice           Added Sugar
Frozen Juice     Frzn Fruit Drinks   Solid Fats &   sweetened beverage
 And Smoothies    (Under 10% J)       Added Sugar
Frozen Whipped   Frzn Whipped        Solid Fats &   butter/cream/solid
 Topping          Topping             Added Sugar    fat
Gift & Fruit     Candy Arrangements  Solid Fats &   candy/sweet
 Baskets          Food Only           Added Sugar
Juice            Drinks--Carb Juice  Solid Fats &   sweetened beverage
                  (Under 50%)         Added Sugar
Juice            Non-Carb Jce        Solid Fats &   sweetened beverage
                  (Under 50% Juice)   Added Sugar
Juices Super     Juices (50% And     Solid Fats &   sweetened beverage
 Premium          Under Juice)        Added Sugar
Juices Super     Juices Organic      Solid Fats &   sweetened beverage
 Premium          (50% And Under)     Added Sugar
Juices Super     Juices Smoothies/   Solid Fats &   sweetened beverages
 Premium          Blended             Added Sugar
Juices Super     Juices Superfoods/  Solid Fats &   sweetened beverages
 Premium          Enhanced            Added Sugar
Juices Super     Juices/Smoothies    Solid Fats &   sweetened beverages
 Premium          Instore Produ       Added Sugar
Kosher Foods     Kosher Beverage     Solid Fats &   sweetened beverages
 And Products                         Added Sugar
Kosher Foods     Kosher Candy        Solid Fats &   candy/sweet
 And Products                         Added Sugar
Kosher Foods     Kosher Carbonated   Solid Fats &   sweetened beverage
 And Products     Soft Drinks         Added Sugar
Margarines       Butter              Solid Fats &   butter/cream/solid
                                      Added Sugar    fat
Margarines       Margarine Stick     Solid Fats &   butter/cream/solid
                                      Added Sugar    fat
Milk By-         Aerosol Toppings    Solid Fats &   butter/cream/solid
 Products         [Milk By-           Added Sugar    fat
                  Products]
Milk By-         Refrig Dips         Solid Fats &   butter/cream/solid
 Products                             Added Sugar    fat
Milk By-         Sour Creams         Solid Fats &   butter/cream/solid
 Products                             Added Sugar    fat
Mixers           Cocktail Mixes--    Solid Fats &   sweetened beverage
                  Dry                 Added Sugar
Mixers           Cocktail Mixes--    Solid Fats &   sweetened beverage
                  Fluid: Add Liq      Added Sugar
Molasses/Syrups/ Molasses & Syrups   Solid Fats &   candy/sweet
 Pancake Mixes                        Added Sugar
Packaged         Candy               Solid Fats &   candy/sweet
 Natural Snacks                       Added Sugar
Peanut Butter/   Preserves/Jam/      Solid Fats &   candy/sweet
 Jelly/Jams &     Marmalade           Added Sugar
 Honey
Peanut Butter/   Honey               Solid Fats &   candy/sweet
 Jelly/Jams &                         Added Sugar
 Honey
Peanut Butter/   Jelly               Solid Fats &   candy/sweet
 Jelly/Jams &                         Added Sugar
 Honey
Powder &         Breakfast Crystals  Solid Fats &   sweetened beverage
 Crystal Drink                        Added Sugar
 Mix
Powder &         Enhanced Stick      Solid Fats &   sweetened beverage
 Crystal Drink    [Powder Drink       Added Sugar
 Mix              Mix]
Powder &         Fluid Pouch         Solid Fats &   sweetened beverage
 Crystal Drink    [Powder Drink       Added Sugar
 Mix              Mix]
Powder &         Soft Drink          Solid Fats &   sweetened beverage
 Crystal Drink    Canisters [Powder   Added Sugar
 Mix              Drink Mix]
Powder &         Sugar Sweetened     Solid Fats &   candy/sweet
 Crystal Drink    Envelopes           Added Sugar
 Mix
Powder &         Sugar Sweetened     Solid Fats &   candy/sweet
 Crystal Drink    Sticks              Added Sugar
 Mix
Processed        Dips                Solid Fats &   butter/cream/solid
                                      Added Sugar    fat
Processed        Packaged Dry        Solid Fats &   sweetened beverages
                  Smoothie Mix        Added Sugar
Refrgratd        Dairy Case Citrus   Solid Fats &   sweetened beverage
 Juices/Drinks    Pnch/Oj Subs        Added Sugar
Refrgratd        Dairy Case Fruit    Solid Fats &   sweetened beverage
 Juices/Drinks    Drinks (No Ju)      Added Sugar
Refrgratd        Dairy Case Juice    Solid Fats &   sweetened beverage
 Juices/Drinks    Drnk Under 10       Added Sugar
Refrgratd        Dairy Case Tea      Solid Fats &   sweetened beverage
 Juices/Drinks    With Sugar Or S     Added Sugar
Refrigerated     Ntrn Refrig Juice   Solid Fats &   sweetened beverage
 Dairy Case       Under 50%           Added Sugar
Refrigerated     Sour Cream/Cottage  Solid Fats &   butter/cream/solid
 Dairy Case       Cheese              Added Sugar    fat
Refrigerated     Tea With Sweetener/ Solid Fats &   sweetened beverage
 Dairy Case       Sugar               Added Sugar
Rtd Tea/New Age  Juice (Under 10%    Solid Fats &   sweetened beverage
 Juice            Juice)              Added Sugar
Rtd Tea/New Age  Juice (Under 50%    Solid Fats &   sweetened beverage
 Juice            Juice)              Added Sugar
Rtd Tea/New Age  Tea Sweetened       Solid Fats &   sweetened beverage
 Juice                                Added Sugar
Service          Sv Bev: Bev/Juic    Solid Fats &   sweetened beverage
 Beverage         10-50% Juice        Added Sugar
Shelf Stable     Apple Juice &       Solid Fats &   sweetened beverage
 Juice            Cider (50% And      Added Sugar
                  Under Juice)
Shelf Stable     Apple Juice &       Solid Fats &   sweetened beverage
 Juice            Cider (Under 10%    Added Sugar
                  Juice)
Shelf Stable     Blended Juice &     Solid Fats &   sweetened beverage
 Juice            Combinations        Added Sugar
Shelf Stable     Blended Juice &     Solid Fats &   sweetened beverage
 Juice            Combinations        Added Sugar
Shelf Stable     Cranapple/Cran      Solid Fats &   sweetened beverage
 Juice            Grape Juice         Added Sugar
Shelf Stable     Cranberry Juice     Solid Fats &   sweetened beverage
 Juice            (50% And Under      Added Sugar
                  Juice)
Shelf Stable     Fruit Drinks:       Solid Fats &   sweetened beverage
 Juice            Canned & Glass      Added Sugar
Shelf Stable     Fruit Drinks:       Solid Fats &   sweetened beverage
 Juice            Canned & Glass      Added Sugar
Shelf Stable     Fruit Drinks:       Solid Fats &   sweetened beverage
 Juice            Canned & Glass      Added Sugar
Shelf Stable     Fruit Drinks:       Solid Fats &   sweetened beverage
 Juice            Canned & Glass      Added Sugar
Shelf Stable     Grape Juice (50%    Solid Fats &   sweetened beverage
 Juice            And Under Juice)    Added Sugar
Shelf Stable     Grapefruit Juice    Solid Fats &   sweetened beverage
 Juice            (50% And Under      Added Sugar
                  Juice)
Shelf Stable     Lemon Juice & Lime  Solid Fats &   sweetened beverage
 Juice            Juice (50% And      Added Sugar
                  Under Juice)
Shelf Stable     Lemon Juice & Lime  Solid Fats &   sweetened beverage
 Juice            Juice               Added Sugar
Shelf Stable     Nectars (50% And    Solid Fats &   sweetened beverage
 Juice            Under Juice)        Added Sugar
Shelf Stable     Prune Juice (50%    Solid Fats &   sweetened beverage
 Juice            And Under Juice)    Added Sugar
Shortening &     Solid Shortening    Solid Fats &   butter/cream/solid
 Oil                                  Added Sugar    fat
Soft Drinks      Mixers (Tonic       Solid Fats &   sweetened beverage
                  Water/Gngr Ale)     Added Sugar
Soft Drinks      Mixers (Tonic Wtr/  Solid Fats &   sweetened beverage
                  Gngr Ale)           Added Sugar
Soft Drinks      Sft Drnk 1 Liter    Solid Fats &   sweetened beverage
                  Btl Carb            Added Sugar
Soft Drinks      Sft Drnk 2 Liter    Solid Fats &   sweetened beverage
                  Btl Carb Incl       Added Sugar
Soft Drinks      Sft Drnk 3 Liter    Solid Fats &   sweetened beverage
                  Btl Carb            Added Sugar
Soft Drinks      Sft Drnk Misc Btl   Solid Fats &   sweetened beverage
                  (Any Btl)           Added Sugar
Soft Drinks      Sft Drnk Misc Can   Solid Fats &   sweetened beverage
                  (Ex: 4/8/18pk)      Added Sugar
Soft Drinks      Sft Drnk Mlt-Pk     Solid Fats &   sweetened beverage
                  Btl Carb            Added Sugar
Soft Drinks      Sft Drnk Sngl Srv   Solid Fats &   sweetened beverage
                  Btl Carb            Added Sugar
Soft Drinks      Soft Drink Bottle   Solid Fats &   sweetened beverage
                  Non-Carb            Added Sugar
Soft Drinks      Soft Drinks 12/18   Solid Fats &   sweetened beverage
                  & 15pk Can Car      Added Sugar
Soft Drinks      Soft Drinks 20pk &  Solid Fats &   sweetened beverage
                  24pk Can Carb       Added Sugar
Soft Drinks      Soft Drinks 6pk     Solid Fats &   sweetened beverage
                  Can Carb            Added Sugar
Soft Drinks      Soft Drinks Bottle  Solid Fats &   sweetened beverage
                  Returnable          Added Sugar
Soft Drinks      Soft Drinks Can     Solid Fats &   sweetened beverage
                  Non-Carb            Added Sugar
Soft Drinks      Soft Drinks Single  Solid Fats &   sweetened beverage
                  Cans Carb           Added Sugar
Soft Drinks      Tea Bottles With    Solid Fats &   sweetened beverage
                  Sweetener/Sugar     Added Sugar
Soft Drinks      Tea Can With        Solid Fats &   sweetened beverage
                  Sweetener/Sugar     Added Sugar
Sugars &         Sugar               Solid Fats &   candy/sweet
 Sweeteners                           Added Sugar
Sugars &         Sweeteners          Solid Fats &   candy/sweet
 Sweeteners                           Added Sugar
Sweet Goods &    Sweet Goods: Candy  Solid Fats &   candy/sweet
 Snacks                               Added Sugar
Sweet Goods &    Sweet Goods: Candy  Solid Fats &   candy/sweet
 Snacks           W/Flour             Added Sugar
Syrups Toppings  Ice Cream Toppings  Solid Fats &   candy/sweet
 & Cones                              Added Sugar
Teas             Instant Tea & Tea   Solid Fats &   sweetened beverage
                  Mix (W/Sugar)       Added Sugar
Traditional      Mexican Candy       Solid Fats &   candy/sweet
 Mexican Foods                        Added Sugar
Trail Mix &      Candy W/Flour       Solid Fats &   candy/sweet
 Snacks                               Added Sugar
Trail Mix &      Candy W/O Flour     Solid Fats &   candy/sweet
 Snacks                               Added Sugar
Trail Mix &      Candy W/O Flour     Solid Fats &   candy/sweet
 Snacks           Organic             Added Sugar
Water            Carb Water--Flvrd   Solid Fats &   sweetened beverage
                  Sweetened           Added Sugar
Water            Energy Drinks       Solid Fats &   sweetened beverage
                                      Added Sugar
Authentic        Authentic Pasta/    Composite                           entree/meal
 Hispanic Fds &   Rice/Beans
 Product
Authentic        Authentic Soups/    Composite                           soup
 Hispanic Fds &   Bouillons
 Product
Authentic        Hispanic Cookies/   Composite                           desserts
 Hispanic Fds &   Crackers
 Product
Authentic        Italian Pasta And   Composite                           entree/meal
 Italian Foods    Pasta Sauce
Bag Snacks       Store Brand         Composite                           snacks
Bag Snacks       Misc Bag Snacks     Composite                           snacks
Bag Snacks       Mult Pk Bag Snacks  Composite                           snacks
Bag Snacks       Potato Chips        Composite                           snacks
Bag Snacks       Salsa & Dips        Composite                           snacks
Baked Sweet      Snack Cake--Multi   Composite                           desserts
 Goods            Pack
Baked Sweet      Sweet Goods--Full   Composite                           desserts
 Goods            Size
Bakery Party                         Composite                           desserts
 Trays
Bakery Party     Party Trays:        Composite                           desserts
 Trays            Breakfast Sweets
Bakery Party     Party Trays: Cakes  Composite                           desserts
 Trays
Bakery Party     Party Trays:        Composite                           desserts
 Trays            Cookies--Rolls
Baking Mixes     Brownie Mix         Composite                           desserts
Baking Mixes     Cookies Mix         Composite                           desserts
Baking Mixes     Layer Cake Mix      Composite                           desserts
Baking Mixes     Microwavable Cake   Composite                           desserts
                  Mix
Baking Needs     Pie Crust Mixes &   Composite                           desserts
                  Shells
Baking Needs     Pie Filling/        Composite                           desserts
                  Mincemeat/Glazes
Bulk Food        Grain/Beans Bulk    Composite                           entree/meal
Bulk Food        Misc Bulk Snacks    Composite                           snacks
                  Sweetened
Bulk Food        Snacks Bulk         Composite                           snacks
Cakes            Cakes Ingredients   Composite                           desserts
Cakes            Cakes: Angel Fds/   Composite                           desserts
                  Cke Rolls
Cakes            Cakes: Angl Fd/     Composite                           desserts
                  Roll Novelties
Cakes            Cakes: Birthday/    Composite                           desserts
                  Celebration Sheet
Cakes            Cakes: Cheesecake   Composite                           desserts
Cakes            Cakes: Cheesecake   Composite                           desserts
                  Novelties
Cakes            Cakes: Cndles/Retl  Composite                           desserts
                  Accss
Cakes            Cakes: Creme/       Composite                           desserts
                  Pudding
Cakes            Cakes: Creme/       Composite                           desserts
                  Pudding Novelties
Cakes            Cakes: Cupcakes     Composite                           desserts
Cakes            Cakes: Fancy/       Composite                           desserts
                  Service Case
Cakes            Cakes: Ice Cream    Composite                           desserts
Cakes            Cakes: Kosher       Composite                           desserts
Cakes            Cakes: Layers       Composite                           desserts
Cakes            Cakes: Layers/      Composite                           desserts
                  Sheets Novelties
Cakes            Cakes: Novelties    Composite                           desserts
Cakes            Cakes: Pound        Composite                           desserts
Cakes            Cakes: Pound Cake   Composite                           desserts
                  Novelties
Cakes            Cakes: Sheet        Composite                           desserts
Cakes            Cakes: Birthday/    Composite                           desserts
                  Celebration Layer
Cakes            Cakes: Wedding/     Composite                           desserts
                  Designer Series
Canned Pasta &   Can Pasta           Composite                           entree/meal
 Mwv Fd--Shlf
 Stbl
Canned Pasta &   Microwavable Cups   Composite                           entree/meal
 Mwv Fd--Shlf     [Canned Pasta]
 Stbl
Canned Pasta &   Microwavable Trays  Composite                           entree/meal
 Mwv Fd--Shlf     [Canned Pasta]
 Stbl
Canned Soups     Condensed Soup      Composite                           soup
Chilled Ready    Store Brand         Composite                           entree/meal
 Meals
Chilled Ready    Fresh Meals         Composite                           entree/meal
 Meals
Chilled Ready    Fresh Side Dishes   Composite                           entree/meal
 Meals
Cnv Breakfast &  Treats              Composite                           snacks
 Wholesome Snks
Convenient       Convenient Meals--  Composite                           entree/meal
 Meals            Adult Meal
Convenient       Convenient Meals--  Composite                           entree/meal
 Meals            Kids Meal
Cookie/Cracker   Multi-Pack Cookies  Composite                           desserts
 Multi-Pks
Cookies          Chocolate Covered   Composite                           desserts
                  Cookies
Cookies          Cookies/Sweet       Composite                           desserts
                  Goods
Cookies          Cookies: Gourmet    Composite                           desserts
Cookies          Cookies: Holiday/   Composite                           desserts
                  Special Occas
Cookies          Cookies: Kosher     Composite                           desserts
Cookies          Cookies: Less Than  Composite                           desserts
                  6
Cookies          Cookies: Message    Composite                           desserts
Cookies          Cookies: Party      Composite                           desserts
Cookies          Cookies: Regular    Composite                           desserts
Cookies          Fruit Filled        Composite                           desserts
                  Cookies
Cookies          Premium Cookies     Composite                           desserts
                  (Ex: Pepperidge)
Cookies          Sandwich Cookies    Composite                           desserts
Cookies          Specialty Cookies   Composite                           desserts
Cookies          Tray Pack/Choc      Composite                           desserts
                  Chip Cookies
Cookies          Vanilla Wafer/Kids  Composite                           desserts
                  Cookies
Cookies          Wellness/Portion    Composite                           desserts
                  Control [Cookies]
Dinner Mixes--   Macaroni & Cheese   Composite                           entree/meal
 Dry              Dnrs
Dinner Mixes--   Microwave Dinners   Composite                           entree/meal
 Dry
Dinner Mixes--   Package Dinners     Composite                           entree/meal
 Dry              Meat Included
Dinner Mixes--   Package Dinners W/  Composite                           entree/meal
 Dry              O Meat
Dinner Mixes--   Package Dinners/    Composite                           entree/meal
 Dry              Pasta Salads
Dinner Mixes--   Skillet Dinners     Composite                           entree/meal
 Dry
Dressings/Dips   Dips Guacamole/     Composite                           snacks
                  Salsa/Queso
Dressings/Dips   Dips Organic        Composite                           snacks
Dressings/Dips   Dips Veggie         Composite                           snacks
Dry Bean Veg &   Dry Beans/Peas/     Composite                           entree/meal
 Rice             Barley: Bag & B
Dry Mix          Freeze Mixes/Pwdrs/ Composite                           desserts
 Desserts         Liquids
Dry Mix          Misc: Cheesecake/   Composite                           desserts
 Desserts         Mousse Mixes
Dry Mix          Pudding & Gelatin   Composite                           desserts
 Desserts         Cups/Cans
Dry Mix          Puddings Dry        Composite                           desserts
 Desserts
Dry/Ramen        12 Pack Soup/Case   Composite                           soup
 Bouillon         Soup/Etc.
Dry/Ramen        Bouillon            Composite                           soup
 Bouillon
Dry/Ramen        Dry Soup            Composite                           soup
 Bouillon
Fitness & Diet   Fitness & Diet--    Composite                           snacks
                  Bars (Supplement)
Fitness & Diet   Fitness & Diet--    Composite                           snacks
                  Bars W/Flour
Fitness & Diet   Fitness & Diet--    Composite                           snacks
                  Bars W/O Flour
Frozen Bread     Desserts            Composite                           desserts
 And Desserts
Frozen           Donuts              Composite                           desserts
 Breakfast
Frozen           Meals/Sandwichs     Composite                           entree/meal
 Breakfast
Frozen           Foods Frzn          Composite                           entree/meal
 Breakfast        Breakfast Entrees
Frozen           Foods Frzn          Composite                           entree/meal
 Breakfast        Breakfast
                  Sandwiches
Frozen Desserts  Frozen Cakes/       Composite                           desserts
                  Desserts
Frozen Desserts  Frozen Cream Pies   Composite                           desserts
Frozen Desserts  Frozen Fruit Pies   Composite                           desserts
                  & Cobblers
Frozen Desserts  Frzn                Composite                           desserts
                  Pastry&Cookies
Frozen Desserts  Frzn Pie Shells/    Composite                           desserts
                  Pastry Shell/F
Frozen Desserts  Single Serv/        Composite                           desserts
                  Portion Control
Frozen Entrees   Bowls               Composite                           entree/meal
Frozen Entrees   Meatless/           Composite                           entree/meal
                  Vegetarian
Frozen Entrees   Pasta/Skillet       Composite                           entree/meal
                  Meals
Frozen Entrees   Soup                Composite                           soup
Frozen           Burritos            Composite                           entree/meal
 Handhelds &
 Snacks
Frozen           Corn Dogs           Composite                           snacks
 Handhelds &
 Snacks
Frozen           Sandwiches &        Composite                           entree/meal
 Handhelds &      Handhelds
 Snacks
Frozen           Snacks/Appetizers   Composite                           snacks
 Handhelds &
 Snacks
Frozen Ice       Almond              Composite                           desserts
 Cream &
 Novelties
Frozen Ice       Ice Cream           Composite                           desserts
 Cream &
 Novelties
Frozen Ice       Novelties--Dairy    Composite                           desserts
 Cream &
 Novelties
Frozen Ice       Novelties--Non      Composite                           desserts
 Cream &          Dairy
 Novelties
Frozen Ice       Novelties--Water    Composite                           desserts
 Cream &          Base
 Novelties
Frozen Ice       Rice                Composite                           desserts
 Cream &
 Novelties
Frozen Ice       Soy                 Composite                           desserts
 Cream &
 Novelties
Frozen Ice       Yogurt/Sorbet And   Composite                           desserts
 Cream &          Kefir
 Novelties
Frozen Juice     Smoothies--Frz      Composite                           desserts
 And Smoothies
Frozen           Adult Premium       Composite                           desserts
 Novelties--Wat   [Frozen
 er Ice           Novelties]
Frozen           Cones [Frozen       Composite                           desserts
 Novelties--Wat   Novelties]
 er Ice
Frozen           Cups/Push Ups/      Composite                           desserts
 Novelties--Wat   Other [Frozen
 er Ice           Novelties]
Frozen           Ice Cream           Composite                           desserts
 Novelties--Wat   Sandwiches
 er Ice
Frozen           Sticks/Enrobed      Composite                           desserts
 Novelties--Wat   [Frozen
 er Ice           Novelties]
Frozen           Water Ice [Frozen   Composite                           desserts
 Novelties--Wat   Novelties]
 er Ice
Frozen Pizza     Meatless/           Composite                           entree/meal
                  Vegetarian
Frozen Pizza     Pizza/Economy       Composite                           entree/meal
Frozen Pizza     Pizza/Premium       Composite                           entree/meal
Frozen Pizza     Pizza/Single Serve/ Composite                           entree/meal
                  Microwave
Frozen Pizza     Pizza/Traditional   Composite                           entree/meal
Frozen Pizza     Pizza/Value         Composite                           entree/meal
Frozen Pizza     Single Serve        Composite                           entree/meal
Frozen Snacks    Burritos--Meatless/ Composite                           entree/meal
 And              Vegetarian
Frozen Snacks    Appetizers          Composite                           snacks
 And Handhelds
Frozen Snacks    Burritos--Meat      Composite                           entree/meal
 And Handhelds    Protein
Frozen Snacks    Wraps/Handhelds--   Composite                           entree/meal
 And Handhelds    Meat
Frozen Snacks    Wraps/Handhelds--   Composite                           entree/meal
 And Handhelds    Meatless
Frozen           Meals               Composite                           entree/meal
 Vegetables And
 Potatoes
Frzn Meatless    Meatless Breakfast  Composite                           entree/meal
Frzn Meatless    Meatless Burgers    Composite                           entree/meal
Frzn Meatless    Meatless Entrees    Composite                           entree/meal
Frzn Meatless    Meatless Meal       Composite                           entree/meal
                  Starters
Frzn Meatless    Meatless            Composite                           entree/meal
                  Miscellaneous
Frzn Meatless    Meatless Poultry    Composite                           entree/meal
Frzn Meatless    Meatless Snacks     Composite                           snacks
Frzn Multi       Fz Crockpots/Soups  Composite                           soup
 Serve
Frzn Multi       Fz Family Style     Composite                           entree/meal
 Serve            Entrees
Frzn Multi       Fz Skillet Meals    Composite                           entree/meal
 Serve
Frzn Prepared    Fz Meal Kits/       Composite                           entree/meal
 Chicken          Stuffed/Other
Frzn Ss Economy  Fz Ss Economy       Composite                           entree/meal
 Meals            Meals All
Frzn Ss Premium  Fz Regional/Other   Composite                           entree/meal
 Meals
Frzn Ss Premium  Fz Ss Prem          Composite                           entree/meal
 Meals            Nutritional Meals
Frzn Ss Premium  Fz Ss Prem          Composite                           entree/meal
 Meals            Traditional Meals
Gift & Fruit     Snack Packs W/Soda  Composite                           snacks
 Baskets
Ice Cream Ice    Pails [Ice Cream &  Composite                           desserts
 Milk &           Sherbert]
 Sherbets
Ice Cream Ice    Premium [Ice Cream  Composite                           desserts
 Milk &           & Sherbert]
 Sherbets
Ice Cream Ice    Premium Pints [Ice  Composite                           desserts
 Milk &           Cream & Sherbert]
 Sherbets
Ice Cream Ice    Quarts [Ice Cream   Composite                           desserts
 Milk &           & Sherbert]
 Sherbets
Ice Cream Ice    Super Premium       Composite                           desserts
 Milk &           Pints [Ice Cream
 Sherbets         & Sherbert]
Ice Cream Ice    Traditional [Ice    Composite                           desserts
 Milk &           Cream & Sherbert]
 Sherbets
Kosher Foods     Kosher Snacks       Composite                           snacks
 And Products
Kosher Foods     Kosher Soups        Composite                           soup
 And Products
Packaged         Trail Mixes         Composite                           snacks
 Natural Snacks
Party Tray       Deli Tray--         Composite                           entree/meal
                  Includes Non-
                  Foods
Party Tray       Deli Tray:          Composite                           entree/meal
                  Appetizers & Hors
                  D'oe
Party Tray       Deli Tray: Chicken  Composite                           entree/meal
Party Tray       Deli Tray: Fruit    Composite                           entree/meal
                  And Vegetable
Party Tray       Deli Tray: Meat     Composite                           entree/meal
                  And Cheese
Party Tray       Deli Tray:          Composite                           entree/meal
                  Sandwiches
Party Tray       Deli Trays: Hot     Composite                           entree/meal
Pies             Pie Ingredients     Composite                           desserts
Pies             Pies: Cream/        Composite                           desserts
                  Meringue
Pies             Pies: Fruit/Nut     Composite                           desserts
Pies             Pies: Kosher        Composite                           desserts
Pies             Pies: Pumpkin/      Composite                           desserts
                  Custard
Pies             Pies: Tarts/Minis/  Composite                           desserts
                  Crstdas
Prepared/Pdgd    Boxed Prepared/     Composite                           entree/meal
 Foods            Entree/Dry Prep
Refrgrated       Refrigerated        Composite                           desserts
 Dough Products   Cookie Dough
Refrgrated       Refrigerated        Composite                           desserts
 Dough Products   Cookies--Brand
Refrgrated       Refrigerated        Composite                           desserts
 Dough Products   Cookies--Seasonal
Refrgrated       Refrigerated Pie    Composite                           desserts
 Dough Products   Crust
Refrigerated     Refrigerated        Composite                           desserts
 Desserts         Pudding
Restricted Diet  Cookies             Composite                           desserts
Rts/Micro Soup/  Broth               Composite                           soup
 Broth
Rts/Micro Soup/  Microwavable Soups  Composite                           soup
 Broth
Rts/Micro Soup/  Rts Soup: Chunky/   Composite                           soup
 Broth            Homestyle/Et
Salad & Dips     Sal: Desserts--     Composite                           desserts
                  Bulk
Salad & Dips     Sal: Desserts--     Composite                           desserts
                  Prepack
Salad Bar        Soups               Composite                           soup
Sandwiches       Sandwich            Composite                           entree/meals
                  Ingredients
Sandwiches       Sandwiches--(Cold)  Composite                           entree/meals
Sandwiches       Sandwiches: Kosher  Composite                           entree/meals
                  (Cold)
Seafood--Party   Party Tray Other    Composite                           entree/meal
 Trays
Seafood--Party   Party Tray Other    Composite                           entree/meal
 Trays
Seafood--Salad/  Salads              Composite                           entree/meal
 Dips/Sce/Cond
Service Case     Side Dishes         Composite                           entree/meal
 Meat
Service Case     Stuffed/Mixed       Composite                           entree/meal
 Meat
Single Serve     Single Serve        Composite                           desserts
 Items            Desserts
Single Serve     Single Serve        Composite                           snacks
 Items            Snacks
Single Serve     Snack Cake--Single  Composite                           desserts
 Sweet Goods      Serve
Snack            Nuts/Trail Mix/     Composite                           snacks
                  Dried Fruit
Snack            Soy/Rice Snacks     Composite                           snacks
Snack            Specialty Chips     Composite                           snacks
Snacks           Snacks: Dry         Composite                           snacks
Snacks           Snacks: Gift Packs  Composite                           snacks
Snacks           Snacks: Salty       Composite                           snacks
Snacks           Snacks:Chippery     Composite                           snacks
Soup             Asceptic            Composite                           soup
Soup             Broths              Composite                           soup
Soup             Cans Soup/Chili     Composite                           soup
Soup             Cups                Composite                           soup
Ss/Vending--     Vendor Size/Single  Composite                           desserts
 Cookie/Cracker   Serve Cookie
Ss/Vending--     Salty Snacks        Composite                           snacks
 Salty Snacks     Vending
Ss/Vending--     Salty Snacks W/     Composite                           snacks
 Salty Snacks     Sweetener Vending
Sushi            Sushi--In Store     Composite                           entree/meal
                  Prepared
Sushi            Sushi--Kosher       Composite                           entree/meal
Sushi            Sushi--Prepackaged  Composite                           entree/meal
Sushi            Sushi: In Store     Composite                           entree/meal
                  Prepared (Hot)
Sushi            Sushi: Ingredients  Composite                           entree/meal
Sushi            Sushi: In-Store     Composite                           entree/meal
                  Prepared (Dine)
Sushi            Sushi: Smallwares   Composite                           entree/meal
Sweet Goods      Sw Gds: Kosher      Composite                           desserts
                  Breakfast
Sweet Goods      Sw Gds: Muffins     Composite                           desserts
Sweet Goods      Sw Gds: Sw Rolls/   Composite                           desserts
                  Dan
Sweet Goods      Sw Gds: Coffee      Composite                           desserts
                  Cakes
Sweet Goods      Sw Gds: Donuts      Composite                           desserts
Sweet Goods      Sw Gds: Donuts--    Composite                           desserts
                  Less Than 6
Sweet Goods      Sw Gds: Muffins--   Composite                           desserts
                  Lss Thn 6
Sweet Goods      Swt Gds             Composite                           desserts
                  Ingredients
Sweet Goods &    Sw Gds: Brownie/    Composite                           desserts
 Snacks           Bar Cookie
Sweet Goods &    Sw Gds: Kosher      Composite                           desserts
 Snacks
Sweet Goods &    Sw Gds: Puff        Composite                           desserts
 Snacks           Pastry
Sweet Goods &    Sw Gds: Specialty   Composite                           desserts
 Snacks           Desserts
Sweet Goods &    Sw Gds: Swt/Flvrd   Composite                           desserts
 Snacks           Loaves
Traditional      Asian Foods And     Composite                           entree/meal
 Asian Foods      Meals
Traditional      Mexican Dinners     Composite                           entree/meal
 Mexican Foods    And Foods
Trail Mix &      Trail Mixes/Snack   Composite                           snacks
 Snacks
Trail Mix &      Trail Mixes/Snacks  Composite                           snacks
 Snacks           Organic
Unknown          Frozen Breakfast    Composite                           entree/meal
Unknown          Frozen Dessert      Composite                           desserts
                  (Ice Cream Cake)
Unknown          Frozen Entrees      Composite                           entree/meal
Unknown          Frozen Ice Cream    Composite                           desserts
Unknown          Frozen Side Dish    Composite                           entree/meal
Value-Added      Parfait Cups        Composite                           desserts
 Fruit            Instore
Warehouse        Canister Snacks     Composite                           snacks
 Snacks
Warehouse        Misc Snacks         Composite                           snacks
 Snacks
Warehouse        Misc Snacks W/      Composite                           snacks
 Snacks           Sweetener
Warehouse        Snack Mix           Composite                           snacks
 Snacks
Authentic Asian  Authentic Chinese   Other                                                    misc
 Foods            Foods
Authentic Asian  Authentic Japanese  Other                                                    misc
 Foods            Foods
Authentic Asian  Authentic Thai      Other                                                    misc
 Foods            Foods
Authentic Asian  Other Authentic     Other                                                    misc
 Foods            Asian Foods
Authentic        Caribbean Foods     Other                                                    misc
 Caribbean
 Foods
Authentic        Central American    Other                                                    misc
 Central          Foods
 American Fds
Authentic        Hispanic Baking     Other                                                    seasoning/baking
 Hispanic Fds &   Needs                                                                        need
 Product
Authentic        Authentic Dry       Other                                                    unsweetened
 Hispanic Fds &   Beverages W/O                                                                beverage
 Product          Sweetener
Authentic        Hispanic            Other                                                    condiments
 Hispanic Fds &   Condiments
 Product
Authentic        Hispanic Spices     Other                                                    seasoning/baking
 Hispanic Fds &   And Seasonings                                                               need
 Product
Authentic        Other Italian       Other                                                    misc
 Italian Foods    Foods
Authentic South  South American      Other                                                    misc
 American Fds     Foods
Baby Food        Baby Cereal         Other                                                    infant formula/
                                                                                               baby food
Baby Food        Baby Crackers       Other                                                    infant formula/
                                                                                               baby food
Baby Food        Baby Food           Other                                                    infant formula/
                                                                                               baby food
Baby Food        Baby Formula        Other                                                    infant formula/
                                                                                               baby food
Baby Food        Baby Misc           Other                                                    infant formula/
                                                                                               baby food
Baby Foods       Baby Food--         Other                                                    infant formula/
                  Beginner                                                                     baby food
Baby Foods       Baby Food Cereals   Other                                                    infant formula/
                                                                                               baby food
Baby Foods       Baby Food Junior/   Other                                                    infant formula/
                  All Brands                                                                   baby food
Baby Foods       Baby Juices         Other                                                    infant formula/
                                                                                               baby food
Baby Foods       Baby Spring Waters  Other                                                    infant formula/
                                                                                               baby food
Baking           Flours/Grains/      Other                                                    seasoning/baking
                  Sugar                                                                        need
Baking           Mixes               Other                                                    seasoning/baking
                                                                                               need
Baking           Spices              Other                                                    seasoning/baking
                                                                                               need
Baking Mixes     Microwave Mixes:    Other                                                    seasoning/baking
                  All Other                                                                    need
Baking Mixes     Miscellaneous       Other                                                    seasoning/baking
                  Package Mixes                                                                need
Baking Needs     Baking Cocoa        Other                                                    seasoning/baking
                                                                                               need
Baking Needs     Baking Powder &     Other                                                    seasoning/baking
                  Soda                                                                         need
Baking Needs     Bits & Morsels      Other                                                    seasoning/baking
                  [Baking Needs]                                                               need
Baking Needs     Cooking Chocolate   Other                                                    seasoning/baking
                  (Ex.: Smi-Swt)                                                               need
Baking Needs     Cooking Chocolate   Other                                                    seasoning/baking
                  Unsweetened                                                                  need
Baking Needs     Yeast: Dry          Other                                                    seasoning/baking
                                                                                               need
Beverages        Tea Unsweetened     Other                                                    unsweetened
                  (Can/Bottle)                                                                 beverage
Bulk Food        Bulk Spices         Other                                                    seasoning/baking
                                                                                               need
Bulk Food        Coffee & Tea Bulk   Other                                                    unsweetened
                                                                                               beverage
Bulk Food        Misc Bulk           Other                                                    misc
Coffee &         Bulk Coffee         Other                                                    unsweetened
 Creamers                                                                                      beverage
Coffee &         Coffee Pods/        Other                                                    unsweetened
 Creamers         Singles/Filter                                                               beverage
                  Pac
Coffee &         Flavored Bag        Other                                                    unsweetened
 Creamers         Coffee                                                                       beverage
Coffee &         Flavored Can        Other                                                    unsweetened
 Creamers         Coffee                                                                       beverage
Coffee &         Flavored Instant    Other                                                    unsweetened
 Creamers         Coffee                                                                       beverage
Coffee &         Ready To Drink      Other                                                    unsweetened
 Creamers         Coffee                                                                       beverage
Coffee &         Ready To Drink      Other                                                    unsweetened
 Creamers         Coffee Suppleme                                                              beverage
Coffee &         Specialty Instant   Other                                                    unsweetened
 Creamers         Coffee W/O S                                                                 beverage
Coffee &         Specialty Instant   Other                                                    unsweetened
 Creamers         Coffee W/Swe                                                                 beverage
Coffee &         Unflavored Bag      Other                                                    unsweetened
 Creamers         Coffee                                                                       beverage
Coffee &         Unflavored Can      Other                                                    unsweetened
 Creamers         Coffee                                                                       beverage
Coffee &         Unflavored Instant  Other                                                    unsweetened
 Creamers         Coffee                                                                       beverage
Coffee Shop      Sv Bev: Inged/      Other                                                    unsweetened
                  Portion Pk                                                                   beverage
Coffee Shop      Sv Bev: Carb Wat-   Other                                                    unsweetened
                  Flv/Unflv                                                                    beverage
Coffee Shop      Coff Shop: Instant  Other                                                    unsweetened
 Sweet Goods &    Retail Pack                                                                  beverage
 Rtl
Coffee Shop      Coff Shop: Retail   Other                                                    unsweetened
 Sweet Goods &    Pack Beverag                                                                 beverage
 Rtl
Coffee Shop      Coff Shop: Whole    Other                                                    unsweetened
 Sweet Goods &    Bean Retail P                                                                beverage
 Rtl
Condiments       Ketchup/Mustard/    Other                                                    condiments
                  Bbq Sce/Marina
Condiments       Oils/Vinegar        Other                                                    condiments
Condiments       Pickles/Olives/     Other                                                    condiments
                  Kraut
Condiments &     Bbq Sauce           Other                                                    condiments
 Sauces
Condiments &     Catsup              Other                                                    condiments
 Sauces
Condiments &     Chili Sauce/        Other                                                    condiments
 Sauces           Cocktail Sauce
Condiments &     Hot Sauce           Other                                                    condiments
 Sauces
Condiments &     Marinades           Other                                                    condiments
 Sauces
Condiments &     Misc Meat Sauces    Other                                                    condiments
 Sauces
Condiments &     Mustard--All Other  Other                                                    condiments
 Sauces
Condiments &     Steak & Worchester  Other                                                    condiments
 Sauces           Sauce
Condiments &     Wing Sauce          Other                                                    condiments
 Sauces
Condiments &     Yellow Mustard      Other                                                    condiments
 Sauces
Deli             Dl Spec: Beverages  Other                                                    unsweetened
 Specialties                                                                                   beverage
 (Retail Pk)
Deli             Dl Spec: Must/Oils/ Other                                                    condiments
 Specialties      Vinegars
 (Retail Pk)
Deli/Bakery      Deli/Bakery         Other                                                    misc
 Discontnued      Discontinued
 Items            Items
Dietary Aid      Diet Cntrl Liqs     Other                                                    supplements/meal
 Prdct/Med Liq    Supplement                                                                   replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Diet Cntrl Powders  Other                                                    supplements/meal
 Prdct/Med Liq    Nutritional                                                                  replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Diet Control Water  Other                                                    supplements/meal
 Prdct/Med Liq                                                                                 replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Diet Cntrl Bars     Other                                                    supplements/meal
 Prdct/Med Liq    (Supplement)                                                                 replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Diet Cntrl Bars     Other                                                    supplements/meal
 Prdct/Med Liq    Nutritional                                                                  replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Diet Cntrl Bars     Other                                                    supplements/meal
 Prdct/Med Liq    Nutritional W/                                                               replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Diet Cntrl Liqs     Other                                                    supplements/meal
 Prdct/Med Liq    Nutritional                                                                  replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Diet Energy Drinks  Other                                                    supplements/meal
 Prdct/Med Liq                                                                                 replacements/
 Nutr                                                                                          energy drinks
Dietary Aid      Powder Nutrition    Other                                                    supplements/meal
 Prdct/Med Liq    Products                                                                     replacements/
 Nutr                                                                                          energy drinks
Dry Mix          Desserts Gelatin    Other                                                    seasoning/baking
                                                                                               need
Dry Tea/Coffee/  Coffee Ground       Other                                                    unsweetened
 Coco Mixes                                                                                    beverage
Dry Tea/Coffee/  Coffee Whole Bean   Other                                                    unsweetened
 Coco Mixes                                                                                    beverage
Dry Tea/Coffee/  Tea Bags            Other                                                    unsweetened
 Coco Mixes       (Supplement)                                                                 beverage
Dry Tea/Coffee/  Tea Dry             Other                                                    unsweetened
 Coco Mixes                                                                                    beverage
Dry Sauce/Gravy/ Cooking Bags With   Other                                                    seasoning/baking
 Potatoes/        Spices/Seaso                                                                 need
 Stuffing
Dry Sauce/Gravy/ Gravy Can/Glass     Other                                                    seasoning/baking
 Potatoes/                                                                                     need
 Stuffing
Dry Sauce/Gravy/ Sauce Mixes/Gravy   Other                                                    seasoning/baking
 Potatoes/        Mixes Dry                                                                    need
 Stuffing
Eggs/Muffins/    Misc Dairy          Other                                                    misc
 Potatoes         Refigerated
Enhancements     Enhancements--Othe  Other                                                    supplements/meal
                  r                                                                            replacements/
                                                                                               energy drinks
Enhancements     Enhancements--Pick  Other                                                    condiments
                  led Items
Enhancements     Enhancements--Pick  Other                                                    condiments
                  les/Kraut
Enhancements     Enhancements--Sala  Other                                                    condiments
                  ds/Spreads
Enhancements     Enhancements--Spic  Other                                                    seasoning/baking
                  es/Sauces                                                                    need
European Foods   British Foods       Other                                                    misc
European Foods   French Foods        Other                                                    misc
European Foods   German Foods        Other                                                    misc
European Foods   Mediterranean/      Other                                                    misc
                  Greek Foods
European Foods   Other Ethnic Foods  Other                                                    misc
European Foods   Polish Foods        Other                                                    misc
European Foods   Scandinavian Foods  Other                                                    misc
Fitness & Diet   Fitness & Diet      Other                                                    supplements/meal
                  Energy Drinks F/S                                                            replacements/
                                                                                               energy drinks
Fitness & Diet   Fitness & Diet      Other                                                    supplements/meal
                  Energy Drinks Non                                                            replacements/
                                                                                               energy drinks
Fitness & Diet   Fitness & Diet      Other                                                    supplements/meal
                  Isotonic Drinks                                                              replacements/
                                                                                               energy drinks
Fitness & Diet   Fitness & Diet      Other                                                    supplements/meal
                  Isotonic Drinks                                                              replacements/
                                                                                               energy drinks
Fitness & Diet   Fitness & Diet--    Other                                                    supplements/meal
                  Liq (Supplement)                                                             replacements/
                                                                                               energy drinks
Fitness & Diet   Fitness & Diet--    Other                                                    supplements/meal
                  Liq Ntrtnl                                                                   replacements/
                                                                                               energy drinks
Fitness & Diet   Fitness & Diet--    Other                                                    supplements/meal
                  Powder                                                                       replacements/
                  (Supplement)                                                                 energy drinks
Fitness & Diet   Fitness & Diet--    Other                                                    supplements/meal
                  Powder Ntrtnl                                                                replacements/
                                                                                               energy drinks
Fitness & Diet   Fitness/Diet--Meal  Other                                                    supplements/meal
                  Replacement                                                                  replacements/
                                                                                               energy drinks
Frozen Ethnic    Frozen              Other                                                    misc
                  Internaional
Frozen Ethnic    Frozen Kosher       Other                                                    misc
Frozen Meat      Alternatives Micro  Other                                                    supplements/meal
                  Protein                                                                      replacements/
                                                                                               energy drinks
Frzn Multi       Frozen Other        Other                                                    misc
 Serve
Gift & Fruit     Gift Baskets W/     Other                                                    misc
 Baskets          Food
Gift & Fruit     Snack Packs W/Food  Other                                                    misc
 Baskets
Indian Foods     Authentic Indian    Other                                                    misc
                  Foods
Infant Formula   Baby Isotonic       Other                                                    infant formula/
                  Drinks                                                                       baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Concentrate                                                                  baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Milk Base                                                                    baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Ready To Use                                                                 baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Solutions Large                                                              baby food
Infant Formula   Infant Formula Soy  Other                                                    infant formula/
                  Base                                                                         baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Specialty                                                                    baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Starter Large Pk                                                             baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Starter/Solution                                                             baby food
Infant Formula   Infant Formula      Other                                                    infant formula/
                  Toddler                                                                      baby food
Infant Formula   Infant Formula Up   Other                                                    infant formula/
                  Age                                                                          baby food
Isotonic Drinks  Isotonic Drinks     Other                                                    supplements/meal
                  Multi-Pack                                                                   replacements/
                                                                                               energy drinks
Isotonic Drinks  Isotonic Drinks     Other                                                    supplements/meal
                  Multi-Serve                                                                  replacements/
                                                                                               energy drinks
Isotonic Drinks  Isotonic Drinks     Other                                                    supplements/meal
                  Powdered                                                                     replacements/
                                                                                               energy drinks
Isotonic Drinks  Isotonic Drinks     Other                                                    supplements/meal
                  Single Serve                                                                 replacements/
                                                                                               energy drinks
Isotonic Drinks  Sports Bars         Other                                                    supplements/meal
                                                                                               replacements/
                                                                                               energy drinks
Isotonic Drinks  Sports Drink N/     Other                                                    supplements/meal
                  Supplmnt Milk                                                                replacements/
                                                                                               energy drinks
Isotonic Drinks  Sports Drink        Other                                                    supplements/meal
                  Supplement                                                                   replacements/
                                                                                               energy drinks
Juices Super     Juices Antioxidant/ Other                                                    supplements/meal
 Premium          Wellness                                                                     replacements/
                                                                                               energy drinks
Juices Super     Juices Proteins     Other                                                    supplements/meal
 Premium                                                                                       replacements/
                                                                                               energy drinks
Kosher           Exotic [Kosher      Other                                                    misc
                  Foods]
Kosher           Further Prepared    Other                                                    misc
Kosher Foods     Kosher Baking       Other                                                    seasoning/baking
 And Products     Needs                                                                        need
Kosher Foods     Kosher Condiments   Other                                                    condiments
 And Products
Kosher Foods     Passover Products   Other                                                    misc
 And Products
Mediterranean    Sal: Olives/        Other                                                    condiments
 Bar              Pickles--Bulk
Mediterranean    Sal: Olives/        Other                                                    condiments
 Bar              Pickles--Bulk
Mediterranean    Sal: Olives/        Other                                                    condiments
 Bar              Pickls--Prpck
Mediterranean    Sal: Olives/        Other                                                    condiments
 Bar              Pickls--Prpck
Mixers           Margarita Salt/     Other                                                    condiments
                  Sugar/Misc
Multicultural    Asian Processed     Other                                                    misc
 Products
Multicultural    Hispanic Processed  Other                                                    misc
 Products         Produce
Non-Dairy/Dairy  Aseptic Soy/Rice    Other                                                    misc
                  Powder
Pickle/Relish/   Green Olives        Other                                                    condiments
 Pckld Veg &
 Olives
Pickle/Relish/   Peppers             Other                                                    condiments
 Pckld Veg &
 Olives
Pickle/Relish/   Pickld Veg/Peppers/ Other                                                    condiments
 Pckld Veg &      Etc.
 Olives
Pickle/Relish/   Relishes            Other                                                    condiments
 Pckld Veg &
 Olives
Pickle/Relish/   Ripe Olives         Other                                                    condiments
 Pckld Veg &
 Olives
Pickle/Relish/   Specialty Olives    Other                                                    condiments
 Pckld Veg &
 Olives
Powder &         Sugar Free          Other                                                    unsweetened
 Crystal Drink    Canister [Powder                                                             beverage
 Mix              Drink Mix]
Powder &         Sugar Free Sticks   Other                                                    unsweetened
 Crystal Drink    [Powder Drink                                                                beverage
 Mix              Mix]
Powder &         Tea                 Other                                                    unsweetened
 Crystal Drink                                                                                 beverage
 Mix
Powder &         Unsweetened         Other                                                    unsweetened
 Crystal Drink    Envelope [Powder                                                             beverage
 Mix              Drink Mix]
Prepared/Pdgd    Prepared/Pkgd Food  Other                                                    misc
 Foods            Misc
Processed        Packaged Dry Mixes  Other                                                    misc
Processed        Processed Other     Other                                                    misc
Refrgratd        Dairy Case Tea No   Other                                                    unsweetened
 Juices/Drinks    Sugar Or Swe                                                                 beverage
Refrigerated     Non-Dairy Milks     Other                                                    misc
 Dairy Case
Refrigerated     Tea W/O Sweetener/  Other                                                    unsweetened
 Dairy Case       Sugar                                                                        beverage
Refrigerated     Misc: Herring/      Other                                                    condiments
 Grocery          Pickles/Horserad
Refrigerated     Refrigerated        Other                                                    misc
 Grocery          Kosher Products
Refrigerated     Hispanic Cultured   Other                                                    misc
 Hispanic         Products
 Grocery
Refrigerated     Misc Hispanic       Other                                                    misc
 Hispanic         Grocery
 Grocery
Refrigerated     Refrigerated        Other                                                    misc
 Hispanic         Hispanic Drinks
 Grocery
Refrigerated     Vegetarian Misc     Other                                                    misc
 Vegetarian
Restricted Diet  Baking              Other                                                    seasoning/baking
                                                                                               need
Restricted Diet  Beverage            Other                                                    supplements/meal
                                                                                               replacements/
                                                                                               energy drinks
Restricted Diet  Breakfast Foods     Other                                                    supplements/meal
                                                                                               replacements/
                                                                                               energy drinks
Restricted Diet  Diet Bars/Diet      Other                                                    supplements/meal
                  Liquid Meals                                                                 replacements/
                                                                                               energy drinks
Restricted Diet  Misc Diet           Other                                                    supplements/meal
                                                                                               replacements/
                                                                                               energy drinks
Rtd Tea/New Age  Sparkling Tea       Other                                                    unsweetened
 Juice                                                                                         beverage
Rtd Tea/New Age  Tea Unsweetened     Other                                                    unsweetened
 Juice                                                                                         beverage
Salad & Dips     Sal: Kosher         Other                                                    misc
Salad & Dips     Sal:Dip Prepack     Other                                                    condiments
Salad Bar        Condiments/         Other                                                    condiments
                  Supplies
Salad Bar        Salad Bar Other     Other                                                    misc
Salad Dresing &  Dry Salad Dressing  Other                                                    condiments
 Sandwich         & Dip Mixes
 Spreads
Seafood--Salad/  Dips/Spreads        Other                                                    condiments
 Dip/Sce/Cond
Seafood--Salad/  Sauces              Other                                                    condiments
 Dip/Sce/Cond
Seafood--Salad/  Other Pkgd Dip/     Other                                                    condiments
 Dips/Sce/Cond    Sauce/Condiment
Seafood--Salad/  Sauces              Other                                                    condiments
 Dips/Sce/Cond
Seafood--Salad/  Spices/Marinades    Other                                                    condiments
 Dips/Sce/Cond
Service          Sv Bev: Coffee      Other                                                    unsweetened
 Beverage                                                                                      beverage
Service          Sv Bev: Flav Tea    Other                                                    unsweetened
 Beverage         Products                                                                     beverage
Service          Sv Bev: N/Carb Flv  Other                                                    unsweetened
 Beverage         Frk/Minwtr                                                                   beverage
Service          Sv Bev: Spring      Other                                                    unsweetened
 Beverage         Water                                                                        beverage
Shelf Stable     Tea Bottles         Other                                                    unsweetened
 Juice                                                                                         beverage
Soft Drinks      Club Soda           Other                                                    unsweetened
                                                                                               beverage
Soft Drinks      Misc Items For      Other                                                    unsweetened
                  Soft Drinks                                                                  beverage
Soft Drinks      Seltzer Unflavored  Other                                                    unsweetened
                                                                                               beverage
Soft Drinks      Unswntd Flavored    Other                                                    unsweetened
                  Seltzer Water                                                                beverage
Spices &         Food Colorings      Other                                                    seasoning/baking
 Extracts                                                                                      need
Spices &         Gourmet Spices      Other                                                    seasoning/baking
 Extracts                                                                                      need
Spices &         Imitation Extracts  Other                                                    seasoning/baking
 Extracts                                                                                      need
Spices &         Pure Extracts       Other                                                    seasoning/baking
 Extracts                                                                                      need
Spices &         Salt Substitutes    Other                                                    seasoning/baking
 Extracts                                                                                      need
Spices &         Spices &            Other                                                    seasoning/baking
 Extracts         Seasonings                                                                   need
Spices &         Table Salt/Popcorn  Other                                                    seasoning/baking
 Extracts         Salt/Ice Cr                                                                  need
Spices &         Traditional Spices  Other                                                    seasoning/baking
 Extracts                                                                                      need
Spices/Jarred    Spices &            Other                                                    seasoning/baking
 Garlic           Seasonings                                                                   need
Spices/Jarred    Spices &            Other                                                    seasoning/baking
 Garlic           Seasonings                                                                   need
                  Organic
Teas             Bulk Tea            Other                                                    unsweetened
                                                                                               beverage
Teas             Instant Tea & Tea   Other                                                    unsweetened
                  Mix                                                                          beverage
Teas             Supplemental Tea    Other                                                    unsweetened
                                                                                               beverage
Teas             Tea Bags & Bulk     Other                                                    unsweetened
                  Tea                                                                          beverage
Teas             Tea Bags/Chai       Other                                                    unsweetened
                                                                                               beverage
Teas             Tea Bags/Green      Other                                                    unsweetened
                                                                                               beverage
Teas             Tea Bags/Herbal     Other                                                    unsweetened
                                                                                               beverage
Traditional      Asian Other Sauces/ Other                                                    seasoning/baking
 Asian Foods      Marinad                                                                      need
Traditional      Asian Soy Sauce     Other                                                    seasoning/baking
 Asian Foods                                                                                   need
Traditional      Traditional Thai    Other                                                    misc
 Asian Foods      Foods
Traditional      Mexican Seasoning   Other                                                    seasoning/baking
 Mexican Foods    Mixes                                                                        need
Traditional      Mexican Taco Sauce  Other                                                    condiments
 Mexican Foods
Unknown          Frozen Misc         Other                                                    misc
Vinegar &        Cooking Wines       Other                                                    seasoning/baking
 Cooking Wines                                                                                 need
Vinegar &        Specialty Vinegar   Other                                                    seasoning/baking
 Cooking Wines                                                                                 need
Vinegar &        Vinegar/White &     Other                                                    seasoning/baking
 Cooking Wines    Cider                                                                        need
Water            Carb Water Unflvrd  Other                                                    unsweetened
                                                                                               beverage
Water            Carb Water--Flvrd   Other                                                    unsweetened
                  Unsweetened                                                                  beverage
Water            Fortified/Water     Other                                                    unsweetened
                                                                                               beverage
Water            Non-Carb Water      Other                                                    unsweetened
                  Flvr--Drnk/Mnr                                                               beverage
Water            Non-Carb Water      Other                                                    unsweetened
                  Flvr--Unsweetened                                                            beverage
Water--(Sparkli  Distilled Water     Other                                                    unsweetened
 ng & Still)                                                                                   beverage
Water--(Sparkli  Sparkling Water--   Other                                                    unsweetened
 ng & Still)      Flvrd Sweet                                                                  beverage
Water--(Sparkli  Sparkling Water--   Other                                                    unsweetened
 ng & Still)      Flvrd Unsweetened                                                            beverage
Water--(Sparkli  Sparkling Water--   Other                                                    unsweetened
 ng & Still)      Unflavored                                                                   beverage
Water--(Sparkli  Spring Water        Other                                                    unsweetened
 ng & Still)                                                                                   beverage
Water--(Sparkli  Still Water         Other                                                    unsweetened
 ng & Still)      Drnking/Mnrl                                                                 beverage
                  Water
Water--(Sparkli  Still Water Flvrd   Other                                                    unsweetened
 ng & Still)      Drnk/Mnrl Wt                                                                 beverage
Water--(Sparkli  Still Water Flvrd   Other                                                    unsweetened
 ng & Still)      Unsweetened                                                                  beverage
Water--(Sparkli  Water--Supplies     Other                                                    unsweetened
 ng & Still)                                                                                   beverage
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.

Appendix D. Top 100 Subcommodities for SNAP Households By Expenditure 
        for Each USDA Food Pattern Category

                                               Exhibit D-1: Dairy
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
     Dairy                                      ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $191.1        33.25%  1          $853.8        25.69%  1       $1,044.9        26.80%
 White Only
Shredded        2           $74.7        13.00%  2          $342.0        10.29%  2         $416.7        10.69%
 Cheese
American        3           $44.1         7.67%  4          $136.6         4.11%  4         $180.7         4.63%
 Single Cheese
Natural Cheese  4           $35.3         6.14%  3          $216.1         6.50%  3         $251.4         6.45%
 Chunks
Bagged Cheese   5           $17.1         2.98%  16          $52.0         1.56%  15         $69.1         1.77%
 Snacks
Flavored Milk   6           $16.0         2.78%  14          $59.4         1.79%  12         $75.4         1.93%
String Cheese   7           $15.1         2.63%  9           $99.0         2.98%  8         $114.1         2.93%
Yogurt/Kids     8           $14.0         2.44%  20          $42.4         1.28%  17         $56.5         1.45%
Cottage Cheese  9           $13.9         2.42%  7          $108.8         3.27%  6         $122.7         3.15%
Natural Cheese  10          $13.4         2.33%  6          $113.2         3.41%  5         $126.6         3.25%
 Slices
Yogurt/Ss       11          $11.0         1.91%  11          $69.0         2.07%  11         $79.9         2.05%
 Regular
Loaf Cheese     12          $10.9         1.90%  23          $38.1         1.15%  21         $49.1         1.26%
Yogurt/Ss       13          $10.2         1.78%  8          $103.1         3.10%  9         $113.3         2.91%
 Light
Yogurt/Pro      14           $7.4         1.29%  13          $63.5         1.91%  13         $70.9         1.82%
 Active Health
Yogurt/Adult    15           $7.2         1.25%  19          $42.5         1.28%  20         $49.7         1.28%
 Multi-Packs
Specialty/      16           $6.7         1.17%  17          $48.4         1.46%  18         $55.1         1.41%
 Lactose Free
 Milk
Grated Cheese   17           $6.2         1.08%  25          $33.6         1.01%  24         $39.9         1.02%
Bulk Semi-Hard  18           $6.1         1.05%  18          $44.0         1.32%  19         $50.1         1.28%
 [Cheese]
Fluid Milk      19           $5.9         1.02%  5          $113.3         3.41%  7         $119.2         3.06%
Canned Milk     20           $5.5         0.96%  27          $27.9         0.84%  26         $33.4         0.86%
Yogurt/         21           $5.0         0.86%  10          $77.4         2.33%  10         $82.4         2.11%
 Specialty
 Greek
Half & Half     22           $4.4         0.77%  15          $54.6         1.64%  16         $59.1         1.52%
Yogurt/Large    23           $4.4         0.76%  22          $40.4         1.22%  23         $44.8         1.15%
 Size (16oz Or
 Lar)
Miscellaneous   24           $3.8         0.67%  21          $42.1         1.27%  22         $45.9         1.18%
 Cheese
Bulk Processed  25           $3.4         0.59%  29          $19.8         0.60%  29         $23.2         0.59%
 [Cheese]
Yogurt          26           $3.2         0.56%  12          $67.0         2.02%  14         $70.2         1.80%
Bulk Semi-Soft  27           $3.0         0.53%  28          $23.3         0.70%  28         $26.3         0.68%
 [Cheese]
Egg Nog/Boiled  28           $2.7         0.47%  39          $13.3         0.40%  35         $16.0         0.41%
 Custard
Buttermilk      29           $2.4         0.42%  33          $15.9         0.48%  31         $18.3         0.47%
Organic Milk    30           $2.0         0.34%  24          $35.4         1.06%  25         $37.3         0.96%
Ricotta Cheese  31           $1.9         0.33%  34          $15.6         0.47%  32         $17.5         0.45%
Aerosol Cheese  32           $1.8         0.31%  54           $5.2         0.16%  51          $7.0         0.18%
Hispanic        33           $1.7         0.29%  50           $6.9         0.21%  45          $8.6         0.22%
 Cheese
Specialty Ppk   34           $1.5         0.27%  26          $28.7         0.86%  27         $30.2         0.78%
 Cheese Hard/
 Grat
Aseptic Milk    35           $1.4         0.24%  38          $13.6         0.41%  38         $15.0         0.38%
Misc Dry        36           $1.4         0.24%  46           $7.3         0.22%  44          $8.7         0.22%
 Cheese
Soy Milk        37           $1.3         0.22%  49           $7.1         0.22%  47          $8.4         0.22%
Specialty Ppk   38           $1.2         0.21%  31          $16.2         0.49%  33         $17.5         0.45%
 Cheese
 Spreads
Mexican Con     39           $1.2         0.21%  63           $3.1         0.09%  61          $4.3         0.11%
 Queso
Specialty Ppk   40           $1.2         0.20%  30          $18.5         0.56%  30         $19.6         0.50%
 Cheese Feta
Pre-Sliced      41           $1.1         0.20%  35          $14.4         0.43%  36         $15.5         0.40%
 Semi-Soft
 [Cheese]
Pre-Sliced      42           $1.0         0.18%  36          $14.3         0.43%  37         $15.3         0.39%
 Semi-Hard
 [Cheese]
Specialty Ppk   43           $0.9         0.15%  32          $16.2         0.49%  34         $17.1         0.44%
 Cheese
 Mozzarell
Specialty Ppk   44           $0.8         0.15%  52           $6.0         0.18%  52          $6.8         0.17%
 Cheese
 Processed
Yogurt/Adult    45           $0.8         0.14%  60           $3.8         0.12%  60          $4.7         0.12%
 Drinks
Specialty Ppk   46           $0.8         0.14%  37          $13.9         0.42%  39         $14.7         0.38%
 Cheese
 Cheddar & C
Soy Beverage    47           $0.7         0.12%  53           $5.3         0.16%  54          $6.0         0.15%
Specialty Ppk   48           $0.6         0.10%  40          $11.4         0.34%  40         $12.0         0.31%
 Cheese Semi
 Soft
Specialty Ppk   49           $0.6         0.10%  42          $10.8         0.32%  41         $11.4         0.29%
 Cheese Soft &
 Ripe
Specialty Ppk   50           $0.6         0.10%  41          $10.8         0.33%  42         $11.4         0.29%
 Cheese Blue/
 Gorg
Non Fat Dry     51           $0.6         0.10%  55           $5.2         0.16%  55          $5.7         0.15%
 Milk
Kefir           52           $0.6         0.10%  48           $7.2         0.22%  48          $7.8         0.20%
Specialty Ppk   53           $0.5         0.09%  68           $1.5         0.05%  68          $2.0         0.05%
 Cheese
 Hispanic
Specialty Ppk   54           $0.5         0.08%  44           $8.0         0.24%  46          $8.5         0.22%
 Cheese Gouda
 & Eda
Specialty Ppk   55           $0.5         0.08%  43          $10.4         0.31%  43         $10.9         0.28%
 Cheese Goat
 Milk
               -------------------------------------------------------------------------------------------------
  Total Dairy              $571.2        99.37%           $3,989.3        98.04%          $4,767.6        98.22%
   Expenditure
   s * Among
   Top 1,000
   Subcommodit
   ies
               =================================================================================================
    Total                  $574.9          100%           $3,323.6          100%          $3,898.5          100%
     Dairy
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Only 55 dairy subcommodities among the top 1,000 subcommodities.


                                               Exhibit D-2: Fruit
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
     Fruit                                      ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Dairy Case      1           $43.5        10.18%  1          $269.0         9.35%  1         $312.6         9.46%
 100% Pure
 Juice--O
Bananas         2           $34.2         8.00%  2          $242.7         8.43%  2         $276.9         8.38%
Strawberries    3           $23.5         5.48%  3          $178.4         6.20%  3         $201.9         6.11%
Fruit Snacks    4           $17.6         4.13%  17          $43.2         1.50%  12         $60.8         1.84%
Grapes Red      5           $15.8         3.70%  4          $121.7         4.23%  4         $137.5         4.16%
Grapes White    6           $15.5         3.61%  6           $84.9         2.95%  5         $100.4         3.04%
Apple Juice &   7           $13.3         3.11%  14          $45.8         1.59%  13         $59.0         1.79%
 Cider (Over
 50%)
Instore Cut     8           $13.2         3.09%  5           $85.8         2.98%  6          $99.0         3.00%
 Fruit
Oranges Navels  9           $12.6         2.94%  8           $79.3         2.75%  7          $91.8         2.78%
 All
Fruit Cup       10          $10.6         2.47%  19          $42.7         1.49%  14         $53.3         1.61%
Blended Juice   11           $9.3         2.17%  29          $29.6         1.03%  24         $38.9         1.18%
 &
 Combinations
 (Ov)
Clementines     12           $8.8         2.06%  9           $78.6         2.73%  8          $87.5         2.65%
Melons Instore  13           $8.2         1.93%  18          $42.8         1.49%  17         $51.1         1.55%
 Cut
Watermelon      14           $7.9         1.84%  16          $43.9         1.53%  16         $51.8         1.57%
 Seedless
 Whole
Cherries Red    15           $6.9         1.61%  11          $56.7         1.97%  11         $63.6         1.93%
Apples Gala     16           $6.6         1.54%  10          $69.3         2.41%  10         $75.9         2.30%
 (Bulk & Bag)
Cranapple/Cran  17           $6.1         1.43%  31          $27.3         0.95%  29         $33.4         1.01%
 Grape Juice
 (50)
Apples Red      18           $5.8         1.35%  23          $35.2         1.22%  20         $41.0         1.24%
 Delicious
 (Bulk & Bag)
Dairy Case      19           $5.4         1.26%  25          $32.3         1.12%  26         $37.7         1.14%
 100% Pure
 Juice Oth
Cantaloupe      20           $5.3         1.24%  15          $44.4         1.54%  18         $49.7         1.50%
 Whole
Blueberries     21           $5.1         1.19%  7           $79.4         2.76%  9          $84.5         2.56%
Pineapple       22           $4.9         1.15%  33          $24.0         0.83%  33         $28.9         0.87%
Peaches Yellow  23           $4.8         1.13%  22          $35.6         1.24%  21         $40.5         1.22%
 Flesh
Grape Juice     24           $4.8         1.12%  44          $17.1         0.60%  41         $21.9         0.66%
 (Over 50%
 Juice)
Lemons          25           $4.6         1.08%  24          $33.6         1.17%  25         $38.2         1.16%
Peaches         26           $4.6         1.07%  39          $21.3         0.74%  35         $25.9         0.78%
Apples Granny   27           $4.4         1.03%  27          $30.9         1.07%  28         $35.3         1.07%
 Smith (Bulk &
 Bag)
Frozen Fruit    28           $4.3         1.01%  12          $48.6         1.69%  15         $52.9         1.60%
Applesauce Cup  29           $4.1         0.95%  35          $22.6         0.79%  34         $26.7         0.81%
Non-Carb Jce    30           $3.8         0.88%  26          $31.7         1.10%  27         $35.4         1.07%
 (Over 50%
 Jce)
Raspberries     31           $3.5         0.83%  13          $45.8         1.59%  19         $49.3         1.49%
Grapes Black/   32           $3.4         0.80%  37          $21.8         0.76%  37         $25.2         0.76%
 Blue
Fruit Cocktail/ 33           $3.4         0.79%  54          $12.5         0.43%  52         $15.8         0.48%
 Fruit Salad
Mixed Fruit     34           $3.2         0.75%  79           $5.7         0.20%  73          $8.9         0.27%
 Bags
Jarred Fruit    35           $3.1         0.73%  49          $14.6         0.51%  47         $17.7         0.54%
 Single Serve
Raisins         36           $2.9         0.69%  32          $26.0         0.90%  32         $28.9         0.87%
Apples Other    37           $2.8         0.66%  30          $27.4         0.95%  31         $30.2         0.91%
 (Bulk & Bag)
Apples Fuji     38           $2.8         0.65%  21          $36.2         1.26%  23         $39.0         1.18%
 (Bulk & Bag)
Apples Gold     39           $2.8         0.65%  43          $17.9         0.62%  43         $20.7         0.62%
 Delicious
 (Bulk & Bag)
Blackberries    40           $2.7         0.63%  28          $29.9         1.04%  30         $32.6         0.99%
Limes           41           $2.7         0.62%  34          $22.7         0.79%  36         $25.3         0.77%
Nectarines      42           $2.5         0.60%  42          $18.6         0.64%  42         $21.1         0.64%
 Yellow Flesh
Pineapple       43           $2.5         0.59%  36          $22.1         0.77%  38         $24.6         0.75%
 Whole & Peel/
 Cored
Apples          44           $2.4         0.57%  20          $36.9         1.28%  22         $39.4         1.19%
 Honeycrisp
Grapefruit      45           $2.4         0.56%  40          $21.2         0.74%  39         $23.6         0.71%
Plums           46           $2.4         0.56%  52          $13.1         0.46%  53         $15.5         0.47%
Mandarin        47           $2.3         0.53%  53          $12.6         0.44%  54         $14.8         0.45%
 Oranges/
 Citrus Sect
Frzn Conc       48           $2.2         0.52%  57          $10.1         0.35%  56         $12.3         0.37%
 Allieds Over
 50% Jui
Mango           49           $2.2         0.52%  50          $14.1         0.49%  50         $16.3         0.49%
Apple Sauce     50           $2.2         0.51%  51          $13.8         0.48%  51         $16.0         0.48%
 (Excludes
 Cup)
Tangerines &    51           $2.1         0.49%  55          $11.3         0.39%  55         $13.4         0.41%
 Tangelos
Frzn Oj & Oj    52           $1.9         0.44%  45          $16.2         0.56%  45         $18.1         0.55%
 Substitutes
 (Over 5)
Watermelon      53           $1.9         0.44%  46          $15.9         0.55%  46         $17.8         0.54%
 Personal
Bananas         54           $1.9         0.44%  41          $18.7         0.65%  44         $20.6         0.62%
 Organic
Pears           55           $1.9         0.43%  59          $10.0         0.35%  58         $11.8         0.36%
Convenience/    56           $1.8         0.41%  64           $9.4         0.33%  60         $11.2         0.34%
 Snacking
 Fruit Pro
Cranberry       57           $1.7         0.39%  58          $10.0         0.35%  59         $11.6         0.35%
 Sauce
Strawberries    58           $1.6         0.38%  38          $21.4         0.74%  40         $23.0         0.70%
 Organic
Cut Fruit All   59           $1.6         0.38%  69           $8.5         0.29%  65         $10.1         0.31%
 Other Prepack
Caramel/Candy   60           $1.6         0.36%  94           $3.4         0.12%  84          $4.9         0.15%
 Apples
Pears Bartlett  61           $1.5         0.35%  47          $15.7         0.55%  48         $17.2         0.52%
Fruit Party     62           $1.4         0.33%  74           $6.5         0.23%  75          $7.9         0.24%
 Tray Prepack
Dried Fruit--   63           $1.4         0.33%  48          $15.6         0.54%  49         $17.0         0.51%
 Other
Pineapple       64           $1.4         0.33%  75           $6.4         0.22%  76          $7.8         0.24%
 Juice (Over
 50% Juic)
Cranberry       65           $1.4         0.32%  70           $8.4         0.29%  69          $9.8         0.30%
 Juice (Over
 50% Jce)
Lemon Juice &   66           $1.2         0.29%  72           $7.8         0.27%  72          $9.0         0.27%
 Lime Juice
 (Over)
Oranges Non     67           $1.2         0.28%  81           $5.0         0.18%  80          $6.2         0.19%
 Navel All
Prune Juice     68           $1.2         0.27%  71           $8.3         0.29%  71          $9.5         0.29%
 (Over 50%
 Juice)
Drinks--Carb    69           $1.1         0.26%  61           $9.7         0.34%  62         $10.8         0.33%
 Juice (Over
 50%)
Juice Single    70           $1.1         0.26%  66           $9.4         0.33%  63         $10.5         0.32%
 Blend
Pears Anjou     71           $1.1         0.26%  60           $9.8         0.34%  61         $10.9         0.33%
Kiwi Fruit      72           $1.0         0.24%  73           $7.0         0.24%  74          $8.0         0.24%
Dried Plums     73           $1.0         0.24%  56          $11.0         0.38%  57         $12.0         0.36%
Cherries        74           $1.0         0.23%  68           $9.0         0.31%  68         $10.0         0.30%
 Ranier
Cranapple/Cran  75           $0.9         0.21%  77           $6.3         0.22%  77          $7.2         0.22%
 Grape Juice
 (Ov)
Juice (Over     76           $0.9         0.21%  100          $2.7         0.09%  98          $3.6         0.11%
 50% Juice)
Watermelon W/   77           $0.9         0.20%  98           $3.0         0.11%  93          $3.9         0.12%
 Seeds Whole
Honeydew Whole  78           $0.8         0.18%  78           $5.9         0.21%  79          $6.7         0.20%
Grapes Red      79           $0.8         0.18%  92           $3.5         0.12%  91          $4.2         0.13%
 Globe
Pomegranates    80           $0.7         0.17%  85           $4.3         0.15%  83          $5.0         0.15%
Grapes Other    81           $0.7         0.17%  89           $3.8         0.13%  89          $4.6         0.14%
Maraschino      82           $0.7         0.17%  88           $4.1         0.14%  87          $4.8         0.14%
 Cherries
Apples          83           $0.7         0.17%  63           $9.4         0.33%  64         $10.1         0.31%
 Braeburn
 (Bulk & Bag)
Grapefruit      84           $0.7         0.17%  86           $4.1         0.14%  85          $4.8         0.15%
 Juice (Over
 50% Jui)
Apples Gala     85           $0.6         0.15%  65           $9.4         0.33%  67         $10.0         0.30%
 (Bulk & Bag)
 Organic
Peaches White   86           $0.6         0.15%  80           $5.5         0.19%  81          $6.2         0.19%
 Flesh
Jarred Fruit    87           $0.6         0.14%  82           $4.5         0.16%  82          $5.1         0.16%
 Multi Serve
Squeeze Lemons/ 88           $0.5         0.12%  95           $3.3         0.12%  94          $3.9         0.12%
 Limes
Raspberries     89           $0.5         0.12%  67           $9.1         0.32%  70          $9.6         0.29%
 Organic
Pears Bosc      90           $0.5         0.11%  84           $4.3         0.15%  86          $4.8         0.14%
Blueberries     91           $0.5         0.11%  62           $9.6         0.33%  66         $10.1         0.30%
 Organic
Pears Asian     92           $0.4         0.10%  90           $3.8         0.13%  92          $4.2         0.13%
                       -------------------------        --------------------------------------------------------
  Total Fruit              $416.8        97.49%           $2,772.4        96.36%          $3,189.2        96.54%
   Expenditure
   s * Among
   Top 1,000
   subcommodit
   ies
                       =========================        ========================================================
    Total                  $427.6          100%           $2,877.2          100%          $3,304.8          100%
     Fruit
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
*Only 92 fruit subcommodities among top 1,000 subcommodities.


                                               Exhibit D-3: Grains
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
     Grain                                      ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Kids Cereal     1           $78.1         9.88%  3          $186.4         4.51%  1         $264.5         5.37%
Mainstream      2           $48.0         6.07%  7          $136.8         3.31%  6         $184.7         3.75%
 White Bread
Tortilla/Nacho  3           $47.4         5.99%  2          $209.0         5.05%  2         $256.4         5.21%
 Chips
Mainstream      4           $38.4         4.86%  5          $173.2         4.19%  4         $211.7         4.30%
 Variety
 Breads
All Family      5           $36.2         4.58%  1          $214.9         5.20%  3         $251.1         5.10%
 Cereal
Adult Cereal    6           $24.9         3.15%  4          $182.6         4.42%  5         $207.5         4.21%
Mexican Soft    7           $23.7         3.00%  8          $113.1         2.74%  8         $136.8         2.78%
 Tortillas And
 Wra
Waffles/        8           $17.3         2.19%  13          $77.4         1.87%  12         $94.7         1.92%
 Pancakes/
 French Toast
Ramen Noodles/  9           $16.7         2.12%  43          $28.1         0.68%  34         $44.8         0.91%
 Ramen Cups
Cheese          10          $16.5         2.08%  10          $90.2         2.18%  10        $106.7         2.17%
 Crackers
Hamburger Buns  11          $16.2         2.05%  14          $70.2         1.70%  14         $86.4         1.75%
Hot Dog Buns    12          $16.2         2.05%  18          $62.2         1.50%  16         $78.4         1.59%
Refrigerated    13          $14.7         1.86%  30          $45.2         1.09%  26         $59.9         1.22%
 Biscuits
Butter Spray    14          $14.6         1.85%  15          $68.7         1.66%  15         $83.3         1.69%
 Cracker
Toaster         15          $14.0         1.77%  27          $47.6         1.15%  23         $61.6         1.25%
 Pastries
Rice Side Dish  16          $14.0         1.76%  28          $46.7         1.13%  24         $60.6         1.23%
 Mixes Dry
Popcorn--Micro  17          $13.1         1.65%  17          $63.4         1.53%  17         $76.5         1.55%
 wave
Long Cut Pasta  18          $13.0         1.64%  19          $60.4         1.46%  19         $73.4         1.49%
Granola Bars    19          $12.8         1.61%  11          $88.9         2.15%  11        $101.7         2.06%
Premium Bread   20          $12.3         1.55%  6          $144.7         3.50%  7         $157.0         3.19%
Cereal Bars     21          $10.9         1.38%  12          $78.4         1.90%  13         $89.3         1.81%
Short Cut       22           $9.9         1.25%  21          $56.2         1.36%  20         $66.1         1.34%
 Pasta
Rolls: Dinner   23           $9.5         1.21%  23          $50.5         1.22%  25         $60.1         1.22%
Frzn Garlic     24           $9.1         1.16%  44          $27.8         0.67%  39         $36.9         0.75%
 Toast
Corn Chips      25           $9.1         1.15%  29          $45.6         1.10%  28         $54.7         1.11%
Instant         26           $8.9         1.13%  33          $41.1         0.99%  32         $50.0         1.02%
 Oatmeal
Snack Crackers  27           $8.9         1.13%  9           $98.6         2.39%  9         $107.6         2.18%
Saltine/Oyster  28           $8.2         1.03%  31          $43.1         1.04%  30         $51.3         1.04%
Multi-Pack      29           $8.0         1.01%  32          $41.3         1.00%  33         $49.3         1.00%
 Crackers
Bagels          30           $7.8         0.99%  16          $66.9         1.62%  18         $74.7         1.52%
Noodle Side     31           $7.3         0.92%  53          $21.1         0.51%  49         $28.4         0.58%
 Dish Mixes
Rice--Dry Bag   32           $7.1         0.90%  37          $33.9         0.82%  36         $41.1         0.83%
 And Box
Sandwich Buns   33           $7.1         0.90%  20          $56.8         1.37%  21         $63.9         1.30%
Rice--Instant   34           $6.8         0.86%  34          $38.0         0.92%  35         $44.8         0.91%
 & Microwave
Frzn Breakfast  35           $6.5         0.82%  57          $19.0         0.46%  52         $25.4         0.52%
 Pastry
Flour: White &  36           $6.4         0.81%  42          $28.8         0.70%  41         $35.2         0.71%
 Self Rising
Pretzels        37           $6.2         0.79%  22          $55.4         1.34%  22         $61.6         1.25%
Bread: Italian/ 38           $6.1         0.77%  25          $49.0         1.19%  27         $55.1         1.12%
 French
Muffin & Corn   39           $6.0         0.76%  41          $28.9         0.70%  42         $34.9         0.71%
 Bread Mix
Refrigerated    40           $5.5         0.70%  45          $27.5         0.66%  44         $33.0         0.67%
 Specialty
 Rolls
Refrigerated    41           $5.4         0.68%  38          $31.2         0.76%  40         $36.6         0.74%
 Crescent
 Rolls
Mexican Taco/   42           $5.2         0.66%  56          $19.1         0.46%  55         $24.3         0.49%
 Tostado/
 Shells
Noodles Dry     43           $4.5         0.58%  48          $24.9         0.60%  47         $29.4         0.60%
Rolls:          44           $4.1         0.52%  46          $26.7         0.65%  46         $30.9         0.63%
 Sandwich
Salad Toppers   45           $4.1         0.52%  68          $15.1         0.37%  64         $19.2         0.39%
Graham          46           $4.0         0.51%  47          $24.9         0.60%  48         $29.0         0.59%
 Crackers
Standard        47           $3.9         0.49%  39          $29.9         0.72%  43         $33.8         0.69%
 Oatmeal
English         48           $3.8         0.48%  24          $49.5         1.20%  29         $53.3         1.08%
 Muffins/
 Waffles
Main Meal       49           $3.8         0.48%  36          $34.9         0.84%  37         $38.7         0.79%
 Bread
Dinner Rolls    50           $3.5         0.44%  71          $14.5         0.35%  67         $18.0         0.36%
Breadings/      51           $3.2         0.41%  65          $16.0         0.39%  62         $19.3         0.39%
 Coatings/
 Crumbs
Bread:          52           $3.2         0.40%  51          $22.9         0.55%  51         $26.0         0.53%
 Specialty
Bagged Popped   53           $3.0         0.38%  77          $12.5         0.30%  75         $15.5         0.32%
 Popcorn
Frzn Dinner     54           $3.0         0.38%  54          $20.9         0.50%  56         $23.9         0.48%
 Rolls
Rolls:          55           $2.9         0.37%  64          $16.5         0.40%  61         $19.4         0.39%
 Croissants/
 Breadsticks
Grits           56           $2.8         0.36%  96           $6.7         0.16%  92          $9.6         0.19%
Cereal--Cold    57           $2.8         0.36%  26          $47.8         1.16%  31         $50.7         1.03%
Refrigerated    58           $2.8         0.36%  86           $9.4         0.23%  80         $12.3         0.25%
 Tortillas
Croutons        59           $2.8         0.36%  73          $14.0         0.34%  69         $16.8         0.34%
Frzn Garlic     60           $2.7         0.34%  78          $11.1         0.27%  78         $13.8         0.28%
 Bread
Frzn Biscuits   61           $2.6         0.33%  76          $12.9         0.31%  74         $15.6         0.32%
Frozen Pasta    62           $2.6         0.33%  62          $16.9         0.41%  59         $19.6         0.40%
Pasta/Grain     63           $2.6         0.33%  82          $10.3         0.25%  79         $12.9         0.26%
 Salads--Prepa
 ck
Cornmeal        64           $2.5         0.32%  95           $7.3         0.18%  90          $9.8         0.20%
Refrigerated    65           $2.5         0.32%  93           $7.7         0.19%  87         $10.2         0.21%
 Bagels
Refrigerated    66           $2.4         0.30%  40          $29.3         0.71%  45         $31.7         0.64%
 Pasta
Diet/Light      67           $2.4         0.30%  49          $24.0         0.58%  50         $26.3         0.53%
 Bread
Pasta/Grain     68           $2.3         0.30%  63          $16.9         0.41%  63         $19.3         0.39%
 Salads--Bulk
Mini-Cakes      69           $2.3         0.30%  60          $17.2         0.42%  60         $19.5         0.40%
Fruit/          70           $2.2         0.28%  58          $18.7         0.45%  58         $21.0         0.43%
 Breakfast
 Bread
Breading        71           $2.2         0.28%  114          $3.7         0.09%  104         $5.9         0.12%
Frzn            72           $2.2         0.28%  106          $5.0         0.12%  97          $7.2         0.15%
 Breadsticks
Rye Breads      73           $2.0         0.25%  52          $22.3         0.54%  54         $24.3         0.49%
Other Hot       74           $1.9         0.24%  80          $10.3         0.25%  81         $12.2         0.25%
 Cereal
Rolls: Bagels   75           $1.9         0.24%  67          $15.4         0.37%  68         $17.3         0.35%
Biscuit Flour   76           $1.9         0.23%  74          $13.8         0.33%  72         $15.7         0.32%
 & Mixes
Bread: Artisan  77           $1.7         0.22%  35          $36.7         0.89%  38         $38.4         0.78%
Flour: Misc/    78           $1.6         0.20%  75          $13.6         0.33%  77         $15.2         0.31%
 Specialty/
 Blend Et
Bread: Pita/    79           $1.5         0.19%  72          $14.1         0.34%  73         $15.6         0.32%
 Pocket/
 Flatbrd
Pizza Mix Dry   80           $1.4         0.18%  102          $5.4         0.13%  98          $6.8         0.14%
Breakfast Bars/ 81           $1.4         0.18%  50          $23.6         0.57%  53         $25.0         0.51%
 Tarts/Scones
Popcorn--Other  82           $1.4         0.17%  84          $10.0         0.24%  84         $11.4         0.23%
Asian Noodles/  83           $1.3         0.17%  79          $10.5         0.25%  82         $11.8         0.24%
 Rice
Instant         84           $1.3         0.16%  91           $8.1         0.20%  93          $9.4         0.19%
 Breakfast
Tortilla Chips  85           $1.3         0.16%  55          $19.9         0.48%  57         $21.2         0.43%
Bread: Sweet/   86           $1.3         0.16%  90           $8.4         0.20%  91          $9.7         0.20%
 Breakfast
Refrigerated    87           $1.2         0.16%  83          $10.2         0.25%  83         $11.5         0.23%
 Breads
Bread:          88           $1.2         0.15%  61          $17.1         0.41%  66         $18.3         0.37%
 Sourdough
Bread:          89           $1.0         0.13%  85           $9.8         0.24%  86         $10.8         0.22%
 Tortillas/
 Wraps
Vending Size/   90           $1.0         0.12%  124          $2.3         0.06%  120         $3.3         0.07%
 Sngl Serve
 Cracke
Snacks: Pita    91           $0.9         0.12%  66          $15.7         0.38%  70         $16.7         0.34%
 Chips
Granola         92           $0.9         0.12%  69          $15.1         0.37%  71         $16.0         0.33%
Caramel Coated  93           $0.9         0.11%  118          $3.1         0.08%  115         $4.0         0.08%
 Snacks
Specialty       94           $0.9         0.11%  59          $17.8         0.43%  65         $18.7         0.38%
 Crackers
Crackers        95           $0.8         0.10%  70          $14.6         0.35%  76         $15.4         0.31%
Bread: Rye/     96           $0.7         0.09%  92           $8.1         0.20%  95          $8.8         0.18%
 Cocktail
Whole Grain     97           $0.7         0.09%  88           $9.2         0.22%  88          $9.9         0.20%
 Bread
Frzn Bagels     98           $0.7         0.09%  120          $2.9         0.07%  119         $3.6         0.07%
Bread: Wheat/   99           $0.7         0.09%  81          $10.3         0.25%  85         $11.0         0.22%
 Whl Grain
Pies: Sugar     100          $0.7         0.09%  111          $4.5         0.11%  111         $5.2         0.11%
 Free
                       -------------------------        --------------------------------------------------------
  Top 100                  $778.3        98.43%           $3,989.3        96.47%          $4,767.6        96.79%
   Grain
   Expenditure
   s *
                       -------------------------        --------------------------------------------------------
  Total Grain              $783.8        99.13%           $4,049.9        96.28%          $4,833.8        98.63%
   Expenditure
   s Among Top
   1,000
   Subcommodit
   ies
                       =========================        ========================================================
    Total                  $790.7          100%           $4,135.0          100%          $4,925.7          100%
     Grain
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


                                                Exhibit D-4: Oils
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
      Oil                                       ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Pourable Salad  1           $29.0        22.71%  1          $139.4        24.28%  1         $168.4        23.99%
 Dressings
Mayonnaise &    2           $27.3        21.34%  2          $119.1        20.73%  2         $146.3        20.84%
 Whipped
 Dressing
Margarine:      3           $23.4        18.37%  3          $100.9        17.56%  3         $124.3        17.71%
 Tubs And
 Bowls
Vegetable Oil   4           $20.5        16.07%  5           $35.4         6.16%  5          $55.9         7.96%
Canola Oils     5            $8.3         6.49%  6           $29.3         5.10%  6          $37.6         5.35%
Olive Oil       6            $7.3         5.69%  4           $63.8        11.11%  4          $71.1        10.12%
Cooking Sprays  7            $3.2         2.49%  7           $21.0         3.65%  7          $24.1         3.44%
Dressing        8            $1.6         1.23%  8           $14.5         2.53%  8          $16.1         2.30%
 Creamy
Sand/           9            $1.4         1.14%  10           $7.2         1.26%  10          $8.7         1.23%
 Horseradish &
 Tartar Sauce
Corn Oil        10           $1.3         1.01%  14           $4.1         0.71%  12          $5.4         0.77%
Cooking Oil:    11           $1.1         0.89%  11           $6.7         1.17%  11          $7.8         1.12%
 Peanut/
 Safflower/
Dressing Blue   12           $0.9         0.71%  9            $9.5         1.65%  9          $10.4         1.48%
 Cheese
Margarine:      13           $0.6         0.44%  13           $4.2         0.74%  14          $4.8         0.68%
 Squeeze
                       -------------------------        --------------------------------------------------------
  Total Oil                $125.9        98.58%             $555.0        96.65%            $680.9        96.99%
   Expenditure
   s * Among
   Top 1,000
   Subcommodit
   ies
                       =========================        ========================================================
    Total Oil              $127.0          100%             $574.4          100%            $702.1          100%
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Only 13 oil subcommodities among the top 1,000 subcommodities.


                                           Exhibit D-5: Protein Foods
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
 Protein Foods                                  ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Lean [Beef]     1          $112.4         7.38%  2          $257.9         4.03%  1         $370.3         4.67%
Primal [Beef]   2           $62.4         4.10%  5          $219.8         3.43%  5         $282.2         3.56%
Lunchment--Del  3           $55.8         3.67%  4          $242.6         3.79%  4         $298.4         3.76%
 i Fresh
Eggs--Large     4           $52.1         3.43%  3          $251.6         3.93%  3         $303.7         3.83%
Chicken Breast  5           $49.6         3.26%  1          $292.9         4.57%  2         $342.5         4.32%
 Boneless
Enhanced [Pork  6           $41.5         2.73%  6          $168.0         2.62%  6         $209.5         2.64%
 Boneless Loin/
 Rib]
Bacon--Trad     7           $40.7         2.68%  8          $157.6         2.46%  7         $198.3         2.50%
 16oz Or Less
Ribs [Pork]     8           $35.0         2.30%  15         $106.8         1.67%  13        $141.8         1.79%
Frzn Chicken--  9           $30.0         1.97%  17          $99.8         1.56%  16        $129.8         1.64%
 Wht Meat
Choice Beef     10          $28.4         1.87%  11         $136.6         2.13%  10        $165.1         2.08%
 (Loins)
Select Beef     11          $27.9         1.83%  9          $143.7         2.24%  9         $171.5         2.16%
Hot Dogs--Base  12          $25.1         1.65%  27          $56.8         0.89%  23         $81.9         1.03%
 Meat
Choice Beef     13          $24.0         1.58%  20          $72.5         1.13%  19         $96.5         1.22%
 (Rounds)
Chicken Wings   14          $22.2         1.46%  58          $28.6         0.45%  40         $50.9         0.64%
Frzn Chicken--  15          $22.2         1.46%  97          $17.4         0.27%  52         $39.5         0.50%
 Wings
Lunchment--Bol  16          $21.8         1.43%  24          $60.9         0.95%  22         $82.7         1.04%
 ogna/Sausage
Tuna            17          $21.1         1.39%  14         $109.9         1.72%  15        $131.0         1.65%
Peanut Butter   18          $20.4         1.34%  12         $127.8         1.99%  12        $148.2         1.87%
Meat: Turkey    19          $19.3         1.27%  7          $159.6         2.49%  8         $178.9         2.26%
 Bulk
Frzn Meat--     20          $19.0         1.25%  34          $46.3         0.72%  30         $65.2         0.82%
 Beef
Value Forms/    21          $18.6         1.22%  41          $42.6         0.67%  33         $61.2         0.77%
 18oz And
 Larger
 [Chicken]
Chicken Drums   22          $17.3         1.14%  49          $31.5         0.49%  44         $48.8         0.62%
Angus [Beef]    23          $17.1         1.13%  16         $103.8         1.62%  17        $120.9         1.53%
Dnr Sausage--   24          $16.4         1.08%  45          $37.6         0.59%  38         $54.1         0.68%
 Links Pork
 Ckd/S
Meat: Ham Bulk  25          $15.3         1.00%  13         $115.9         1.81%  14        $131.2         1.65%
Bkfst Sausage-- 26          $15.1         0.99%  23          $61.4         0.96%  25         $76.5         0.96%
 Fresh Rolls
Shrimp--Raw     27          $15.0         0.99%  21          $69.0         1.08%  21         $84.1         1.06%
Shrimp--Cooked  28          $14.8         0.97%  29          $54.0         0.84%  28         $68.8         0.87%
Prepared        29          $13.4         0.88%  28          $55.3         0.86%  29         $68.7         0.87%
 Beans--Baked
 W/Pork
Chili: Canned   30          $13.3         0.88%  39          $42.8         0.67%  36         $56.1         0.71%
Ground Turkey   31          $13.1         0.86%  19          $78.0         1.22%  20         $91.1         1.15%
Dnr Sausage--   32          $13.0         0.86%  25          $58.0         0.91%  26         $71.1         0.90%
 Links Fresh
Whole Chicken   33          $12.9         0.85%  26          $56.9         0.89%  27         $69.8         0.88%
 (Roasters/
 Fryer)
Chicken Thighs  34          $12.2         0.80%  31          $50.0         0.78%  31         $62.2         0.78%
Dnr Sausage--   35          $12.1         0.80%  43          $38.2         0.60%  42         $50.4         0.64%
 Pork Rope Ckd/
 Sm
Bacon--Trad     36          $12.0         0.79%  35          $44.6         0.70%  35         $56.6         0.71%
 Greater Than
 16oz
Soup/Stew       37          $11.2         0.74%  36          $44.1         0.69%  37         $55.3         0.70%
Whole Muscle    38          $11.1         0.73%  53          $29.9         0.47%  49         $41.0         0.52%
 Breaded/18oz
 And
Variety Beans-- 39          $10.5         0.69%  22          $68.0         1.06%  24         $78.5         0.99%
 Kidney/Pinto/
 E
Cubed Meats     40          $10.5         0.69%  54          $29.8         0.46%  51         $40.3         0.51%
 [Beef]
Hot Dogs--Base  41          $10.3         0.68%  32          $49.4         0.77%  34         $59.8         0.75%
 Beef
Eggs--Medium    42          $10.1         0.66%  81          $21.0         0.33%  64         $31.1         0.39%
Butts [Pork     43           $9.7         0.63%  56          $29.2         0.46%  54         $38.8         0.49%
 Shoulder]
Boneless Snack/ 44           $9.6         0.63%  77          $21.5         0.33%  65         $31.1         0.39%
 18oz And
 Larger
Chix: Value-    45           $9.5         0.63%  62          $26.7         0.42%  58         $36.2         0.46%
 Added (Cold)
Angus [Beef]    46           $9.3         0.61%  50          $31.4         0.49%  50         $40.6         0.51%
Patties [Beef]  47           $9.1         0.60%  42          $39.7         0.62%  45         $48.8         0.61%
Bkfst Sausage-- 48           $8.9         0.59%  64          $26.3         0.41%  59         $35.3         0.44%
 Fresh Links
Bone-In Wings   49           $8.8         0.58%  123         $12.0         0.19%  94         $20.8         0.26%
Hams--Half/     50           $8.2         0.54%  52          $30.0         0.47%  56         $38.2         0.48%
 Port Bone-In
Meat: Beef      51           $7.9         0.52%  30          $53.4         0.83%  32         $61.3         0.77%
 Bulk
Hams--Spiral    52           $7.6         0.50%  46          $36.5         0.57%  47         $44.1         0.56%
Hot Dogs--      53           $7.4         0.49%  40          $42.7         0.67%  43         $50.1         0.63%
 Premium
Snack Meat--    54           $7.4         0.48%  48          $32.1         0.50%  53         $39.5         0.50%
 Pepperoni
Frzn Meat--     55           $7.3         0.48%  128         $11.3         0.18%  109        $18.6         0.23%
 Breakfast
 Sausage
Angus [Beef]    56           $7.3         0.48%  37          $43.3         0.68%  41         $50.7         0.64%
Select Beef     57           $7.1         0.46%  51          $30.4         0.47%  57         $37.5         0.47%
Frz Coated      58           $6.9         0.45%  79          $21.1         0.33%  74         $28.0         0.35%
 Fish Fillets
Jerky/Nuggets/  59           $6.8         0.45%  67          $25.8         0.40%  62         $32.6         0.41%
 Tenders
Catfish--Fille  60           $6.8         0.45%  110         $13.1         0.20%  102        $19.9         0.25%
 t
Chicken Legs/   61           $6.6         0.43%  109         $13.5         0.21%  101        $20.1         0.25%
 Quarters
Value-Added     62           $6.4         0.42%  98          $16.9         0.26%  86         $23.3         0.29%
 Breaded
 Shrimp
Pancake Mixes   63           $6.3         0.41%  65          $21.9         0.34%  68         $28.1         0.35%
Frz Fishsticks/ 64           $6.1         0.40%  104         $14.7         0.23%  95         $20.8         0.26%
 Tenders/
 Nuggets
Crab--Snow      65           $6.1         0.40%  127         $11.4         0.18%  110        $17.5         0.22%
Chix: Frd 8pc/  66           $6.0         0.39%  117         $12.7         0.20%  107        $18.7         0.24%
 Cut Up (Cold)
Lunchmeat--Cho  67           $5.1         0.34%  121         $12.1         0.19%  111        $17.2         0.22%
 p/Form Pltry
 & Ha
Salmon Fr--     68           $5.0         0.33%  33          $48.8         0.76%  39         $53.8         0.68%
 Altantic
Party Tray--    69           $4.8         0.32%  73          $24.8         0.39%  71         $29.6         0.37%
 Shrimp
Ham Steaks/     70           $4.7         0.31%  63          $26.3         0.41%  66         $31.0         0.39%
 Cubes/Slices
Eggs--X-Large   71           $4.5         0.29%  44          $37.9         0.59%  48         $42.4         0.54%
Bacon--Poultry  72           $4.5         0.29%  91          $18.4         0.29%  88         $22.9         0.29%
Hams--Whole     73           $4.5         0.29%  105         $14.6         0.23%  106        $19.1         0.24%
 Boneless
Meat Bulk:      74           $4.4         0.29%  59          $28.3         0.44%  61         $32.8         0.41%
 Specialty Dry
 Meats
Chunk Meats--   75           $4.4         0.29%  70          $25.3         0.40%  70         $29.7         0.37%
 Chix/Ham/Etc.
Whole Toms      76           $4.3         0.28%  84          $20.0         0.31%  83         $24.2         0.31%
 (Over 16lbs)
 [Turkey]
Lunchmeat--Who  77           $4.2         0.28%  86          $19.7         0.31%  84         $24.0         0.30%
 le Muscle
 Pltry
Bacon--Pre-     78           $4.1         0.27%  72          $24.8         0.39%  72         $28.9         0.36%
 Cooked
Baking Nuts     79           $4.1         0.27%  38          $43.2         0.67%  46         $47.3         0.60%
Bologna/Loaves/ 80           $4.0         0.26%  87          $19.2         0.30%  87         $23.1         0.29%
 Franks
Pistachios      81           $3.9         0.26%  57          $29.1         0.45%  60         $33.0         0.42%
Seasoned        82           $3.9         0.26%  100         $16.5         0.26%  99         $20.4         0.26%
 Poultry
Protein         83           $3.9         0.26%  65          $26.3         0.41%  69         $30.2         0.38%
 Salads--Bulk
Bkfst Sausage-- 84           $3.8         0.25%  136          $9.8         0.15%  126        $13.6         0.17%
 Fresh Patties
Meat: Chicken   85           $3.7         0.25%  47          $34.6         0.54%  55         $38.4         0.48%
 Bulk
Bkfst Sausage-- 86           $3.7         0.25%  78          $21.4         0.33%  80         $25.2         0.32%
 Precooked
Dnr Sausage--   87           $3.7         0.24%  120         $12.2         0.19%  115        $15.9         0.20%
 Beef Rope Ckd/
 Sm
Whole Hens      88           $3.6         0.24%  89          $19.0         0.30%  89         $22.6         0.29%
 (Under 16lbs)
 [Turkey]
Dnr Sausage--   89           $3.6         0.24%  76          $21.6         0.34%  81         $25.2         0.32%
 Other Forms
External Fresh  90           $3.5         0.23%  204          $4.2         0.06%  169         $7.7         0.10%
 [Pork Offal]
Corned Beef     91           $3.5         0.23%  99          $16.9         0.26%  98         $20.4         0.26%
Fz Meatballs    92           $3.5         0.23%  95          $17.7         0.28%  93         $21.1         0.27%
Hams--Half/     93           $3.4         0.23%  80          $21.0         0.33%  82         $24.5         0.31%
 Port Boneless
Lunchmeat--Chi  94           $3.3         0.22%  138          $9.7         0.15%  130        $13.1         0.16%
 p Meat
Salmon          95           $3.2         0.21%  108         $13.6         0.21%  113        $16.8         0.21%
Sandwich Sauce  96           $3.2         0.21%  156          $7.7         0.12%  146        $10.8         0.14%
Tilapia--Fille  97           $3.2         0.21%  101         $16.4         0.26%  103        $19.6         0.25%
 t
Frozen Burgers  98           $3.2         0.21%  217          $3.1         0.05%  185         $6.3         0.08%
Frozen          99           $3.1         0.20%  135          $9.8         0.15%  132        $12.9         0.16%
 Breakfast
 Sausage
Stuffed/Mixed   100          $3.1         0.20%  88          $19.2         0.30%  90         $22.3         0.28%
 Beef
                       -------------------------        --------------------------------------------------------
  Top 100                $1,342.3        87.82%           $5,249.5        81.66%          $6,591.7        82.84%
   Protein
   Foods
   Expenditure
   s *
                       -------------------------        --------------------------------------------------------
  Total                  $1,512.2        98.95%           $6,288.8        97.83%          $7,801.0        98.04%
   Protein
   Foods
   Expenditure
   s Among Top
   1,000
   Subcommodit
   ies
                       =========================        ========================================================
    Total                $1,528.3          100%           $6,428.5          100%          $7,956.9          100%
     Protein
     Foods
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


                              Exhibit D-6: Saturated Fats and Added Sugars (SoFAS)
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
    (SoFAS)                                     ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Soft Drinks 12/ 1          $164.6        18.86%  1          $601.2        16.11%  1         $765.8        16.63%
 18 & 15pk Can
 Car
Sft Drnk 2      2           $70.9         8.12%  2          $230.1         6.17%  2         $301.0         6.54%
 Liter Btl
 Carb Incl
Soft Drinks     3           $39.7         4.55%  9          $106.4         2.85%  8         $146.1         3.17%
 20pk & 24pk
 Can Carb
Sugar           4           $36.9         4.23%  8          $112.7         3.02%  7         $149.6         3.25%
Sft Drnk Mlt-   5           $34.0         3.90%  4          $173.6         4.65%  3         $207.6         4.51%
 Pk Btl Carb
 (Excp)
Sft Drnk Sngl   6           $27.8         3.18%  11          $71.4         1.91%  11         $99.2         2.15%
 Srv Btl Carb
 (Ex)
Aseptic Pack    7           $24.2         2.78%  16          $57.1         1.53%  15         $81.4         1.77%
 Juice And
 Drinks
Refrigerated    8           $24.1         2.76%  6          $147.2         3.95%  5         $171.3         3.72%
 Coffee
 Creamers
Candy Bags--    9           $21.5         2.46%  5          $147.5         3.95%  6         $169.1         3.67%
 Chocolate
Butter          10          $19.6         2.24%  3          $175.6         4.71%  4         $195.2         4.24%
Sour Creams     11          $17.5         2.00%  10          $95.2         2.55%  10        $112.7         2.45%
Cream Cheese    12          $17.2         1.97%  7          $115.5         3.10%  9         $132.7         2.88%
Candy Bars      13          $16.3         1.87%  18          $54.9         1.47%  16         $71.3         1.55%
 (Singles)
 (Including)
Dairy Case      14          $16.0         1.83%  22          $48.0         1.29%  19         $64.0         1.39%
 Juice Drnk
 Under 10
Candy Bars      15          $15.6         1.79%  12          $69.6         1.86%  12         $85.2         1.85%
 (Multi Pack)
Tea Sweetened   16          $13.9         1.59%  13          $68.7         1.84%  13         $82.6         1.79%
Chewing Gum     17          $13.2         1.51%  14          $68.3         1.83%  14         $81.5         1.77%
Candy Bags--    18          $12.6         1.44%  19          $54.9         1.47%  18         $67.5         1.46%
 Non Chocolate
Molasses &      19          $11.7         1.34%  15          $58.7         1.57%  17         $70.4         1.53%
 Syrups
Dairy Case      20          $11.0         1.26%  27          $34.4         0.92%  26         $45.4         0.99%
 Citrus Pnch/
 Oj Subs
Fruit Drinks:   21          $10.6         1.21%  60          $10.9         0.29%  46         $21.5         0.47%
 Canned &
 Glass
Non Dairy       22          $10.5         1.20%  25          $35.4         0.95%  25         $45.9         1.00%
 Creamer
Seasonal        23           $9.2         1.05%  23          $46.9         1.26%  23         $56.0         1.22%
 Miscellaneous
 [Candy]
Dairy Case Tea  24           $8.4         0.96%  36          $23.1         0.62%  33         $31.5         0.68%
 With Sugar Or
 S
Seasonal Candy  25           $7.9         0.90%  20          $54.8         1.47%  21         $62.7         1.36%
 Bags--Chocola
 te
Energy Drink--  26           $7.7         0.88%  32          $26.3         0.70%  29         $33.9         0.74%
 Single Serve
Energy Drink--  27           $7.1         0.82%  24          $39.5         1.06%  24         $46.7         1.01%
 Single Serve
 (N)
Preserves/Jam/  28           $6.7         0.77%  17          $56.2         1.51%  20         $63.0         1.37%
 Marmalade
Margarine       29           $6.7         0.77%  41          $22.3         0.60%  37         $29.0         0.63%
 Stick
Juice (Under    30           $6.7         0.76%  40          $22.4         0.60%  36         $29.1         0.63%
 10% Juice)
Sweeteners      31           $6.4         0.73%  21          $49.8         1.33%  22         $56.2         1.22%
Frosting        32           $6.3         0.72%  31          $27.0         0.72%  30         $33.4         0.72%
Soft Drinks     33           $5.9         0.67%  57          $11.5         0.31%  54         $17.4         0.38%
 Can Non-Carb
 (Exce)
Refrig Dips     34           $5.7         0.66%  34          $24.7         0.66%  34         $30.4         0.66%
Aseptic Pack    35           $5.3         0.61%  46          $17.5         0.47%  44         $22.9         0.50%
 Juice And
 Drinks
Candy Bars      36           $5.1         0.59%  50          $15.9         0.43%  48         $21.1         0.46%
 (Singles)
 (Including)
Cranberry       37           $5.0         0.58%  39          $22.6         0.61%  40         $27.6         0.60%
 Juice (50%
 And Under)
Frzn Whipped    38           $5.0         0.57%  28          $30.9         0.83%  28         $35.9         0.78%
 Topping
Blended Juice   39           $4.8         0.55%  37          $22.9         0.61%  39         $27.7         0.60%
 &
 Combinations
 (50)
Jelly           40           $4.7         0.54%  44          $18.1         0.48%  45         $22.8         0.50%
Energy Drink--  41           $4.3         0.49%  43          $19.0         0.51%  42         $23.3         0.51%
 Multi-Pack
Honey           42           $4.1         0.48%  29          $28.9         0.78%  31         $33.1         0.72%
Gum (Packaged)  43           $4.1         0.47%  33          $25.9         0.69%  35         $30.0         0.65%
Soft Drinks     44           $4.1         0.47%  30          $27.8         0.74%  32         $31.9         0.69%
 6pk Can Carb
 (Exp)
Miscellaneous   45           $4.0         0.46%  42          $19.0         0.51%  43         $23.0         0.50%
 Candy
 (Including)
Juices          46           $3.8         0.44%  38          $22.8         0.61%  41         $26.6         0.58%
 Superfoods/
 Enhanced
Dairy Case      47           $3.7         0.42%  102          $2.8         0.08%  80          $6.5         0.14%
 Fruit Drinks
 (No Ju)
Aseptic Pack    48           $3.5         0.41%  87           $4.2         0.11%  72          $7.7         0.17%
 Juice And
 Drinks
Aerosol         49           $3.5         0.40%  35          $24.5         0.66%  38         $28.0         0.61%
 Toppings
 [Milk By-
 Products]
Hot Chocolate/  50           $3.5         0.40%  45          $17.8         0.48%  47         $21.2         0.46%
 Cocoa Mix
Seasonal Candy  51           $3.4         0.39%  47          $16.6         0.45%  49         $20.0         0.43%
 Box--Chocolat
 e
Sft Drnk 1      52           $3.3         0.38%  65           $8.2         0.22%  63         $11.5         0.25%
 Liter Btl
 Carb (Exc)
Fruit Drinks:   53           $3.2         0.37%  80           $5.0         0.13%  71          $8.2         0.18%
 Canned &
 Glass
Soft Drink      54           $3.1         0.36%  66           $7.9         0.21%  65         $11.1         0.24%
 Canisters
Marshmallows    55           $3.0         0.34%  48          $16.4         0.44%  50         $19.4         0.42%
Whipping Cream  56           $3.0         0.34%  26          $35.2         0.94%  27         $38.1         0.83%
Solid           57           $2.9         0.33%  54          $14.0         0.38%  55         $16.9         0.37%
 Shortening
Tea Can With    58           $2.7         0.31%  74           $6.1         0.16%  67          $8.8         0.19%
 Sweetener/
 Sugar
Soft Drink      59           $2.6         0.30%  83           $4.7         0.13%  76          $7.4         0.16%
 Bottle Non-
 Carb (Ex)
Ice Cream       60           $2.6         0.30%  53          $14.1         0.38%  56         $16.7         0.36%
 Toppings
Seasonal Candy  61           $2.6         0.30%  52          $14.9         0.40%  53         $17.5         0.38%
 Bags Non-
 Chocol
Candy Bars      62           $2.6         0.29%  64           $8.8         0.23%  64         $11.3         0.25%
 Multi Pack W/
 Flour
Candy Bags--    63           $2.5         0.29%  51          $15.2         0.41%  52         $17.7         0.38%
 Chocolate W/
 Flour
Pork Skins/     64           $2.2         0.26%  73           $6.2         0.17%  68          $8.4         0.18%
 Cracklins
Mints/Candy &   65           $2.1         0.25%  56          $12.1         0.32%  57         $14.3         0.31%
 Breath (Not
 Life)
Juices          66           $2.1         0.24%  59          $11.0         0.29%  60         $13.1         0.28%
 Smoothies/
 Blended
Miscellaneous   67           $1.9         0.22%  58          $11.2         0.30%  59         $13.1         0.28%
 Candy
 (Including)
Cocktail        68           $1.9         0.22%  49          $16.4         0.44%  51         $18.3         0.40%
 Mixes--Fluid:
 Add Liq
Cake Decors &   69           $1.8         0.20%  62          $10.0         0.27%  62         $11.7         0.25%
 Icing
Enhanced Stick  70           $1.7         0.20%  61          $10.7         0.29%  61         $12.5         0.27%
 [Powder Drink
 Mix]
Novelty Candy   71           $1.6         0.19%  76           $5.7         0.15%  77          $7.4         0.16%
Sugar           72           $1.4         0.16%  104          $2.5         0.07%  96          $3.9         0.08%
 Sweetened
 Sticks
Dips Caramel/   73           $1.3         0.15%  75           $5.9         0.16%  78          $7.2         0.16%
 Fruit Glazes
Seasonal        74           $1.2         0.14%  68           $7.1         0.19%  69          $8.4         0.18%
 Miscellaneous
 W/Flour
Instant Tea &   75           $1.1         0.13%  84           $4.4         0.12%  85          $5.6         0.12%
 Tea Mix (W/
 Sugar)
Misc Checklane  76           $1.1         0.13%  103          $2.6         0.07%  97          $3.7         0.08%
 Candy
Fluid Pouch     77           $1.1         0.13%  71           $6.6         0.18%  73          $7.7         0.17%
 [Powder Drink
 Mix]
Sweet Goods:    78           $1.1         0.12%  85           $4.4         0.12%  87          $5.4         0.12%
 Candy
Tea Bottles     79           $1.1         0.12%  114          $1.9         0.05%  105         $3.0         0.06%
 With
 Sweetener/Sug
Hispanic        80           $1.1         0.12%  93           $3.5         0.09%  92          $4.6         0.10%
 Carbonated
 Beverages
Candy W/O       81           $1.0         0.12%  78           $5.4         0.15%  81          $6.5         0.14%
 Flour
Candy Boxed     82           $1.0         0.12%  79           $5.3         0.14%  83          $6.3         0.14%
 Chocolates W/
 Flour
Apple Juice &   83           $1.0         0.12%  98           $3.0         0.08%  95          $4.0         0.09%
 Cider (50%
 And U)
Energy Drink--  84           $1.0         0.11%  63           $9.4         0.25%  66         $10.4         0.22%
 Multi-Pack
 (Non)
Candy Boxed     85           $0.9         0.11%  70           $6.7         0.18%  74          $7.7         0.17%
 Chocolates
Seasonal Candy  86           $0.9         0.11%  89           $4.0         0.11%  88          $4.9         0.11%
 Box Non-
 Chocola
Candy Box Non-- 87           $0.9         0.11%  90           $3.9         0.10%  89          $4.8         0.10%
 Chocolate
Cake Decors--   88           $0.9         0.10%  77           $5.4         0.15%  82          $6.3         0.14%
 Candies
Non-Carb Jce    89           $0.9         0.10%  82           $4.8         0.13%  84          $5.7         0.12%
 (Under 50%
 Jce)
Candy Bags--    90           $0.8         0.09%  91           $3.7         0.10%  93          $4.5         0.10%
 Non Chocolate
 W/Flo
Hispanic Juice  91           $0.7         0.08%  113          $2.0         0.07%  109         $2.7         0.05%
 Under 50%
 Juice
Can/Btl Carb    92           $0.7         0.08%  67           $7.6         0.20%  70          $8.3         0.18%
 Beve 50% And
 Unde
Cranapple/Cran  93           $0.6         0.07%  69           $7.0         0.19%  75          $7.6         0.17%
 Grape Juice
 (Un)
Grapefruit      94           $0.6         0.07%  96           $3.1         0.08%  98          $3.7         0.08%
 Juice (50%
 And Unde)
Blended Juice   95           $0.6         0.07%  97           $3.0         0.08%  100         $3.6         0.08%
 &
 Combinations
 (Un)
Mixers (Tonic   96           $0.5         0.06%  55          $13.2         0.35%  58         $13.7         0.30%
 Water/Gngr
 Ale) Un
Marshmallow     97           $0.5         0.06%  92           $3.5         0.09%  94          $4.1         0.09%
 Creme
Coconut         98           $0.5         0.06%  81           $4.9         0.13%  86          $5.5         0.12%
 [Baking
 Needs]
Honey/Syrup     99           $0.5         0.06%  86           $4.3         0.11%  90          $4.8         0.10%
Dips Fruit And  100          $0.5         0.06%  106          $1.9         0.05%  112         $2.4         0.04%
 Chocolate
                       -------------------------        --------------------------------------------------------
  Top 100                  $862.5        98.70%           $3,660.7        97.93%          $4,523.2        98.05%
   SoFAS
   Expenditure
   s *
                       -------------------------        --------------------------------------------------------
  Total SoFAS              $864.1        98.96%           $3,673.1        98.42%          $4,537.3        98.53%
   Expenditure
   s Among Top
   1,000
   Subcommodit
   ies
                       =========================        ========================================================
    Total                  $873.2          100%           $3,731.9          100%          $4,605.0          100%
     SoFAS
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


                                             Exhibit D-7: Vegetables
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
   Vegetable                                    ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Potatoes        1           $35.8         6.74%  1          $154.5         4.60%  1         $190.2         4.89%
 Russet (Bulk
 & Bag)
Fz Bag          2           $25.7         4.85%  2          $131.9         3.93%  2         $157.7         4.05%
 Vegetables--P
 lain
Mainstream      3           $23.0         4.33%  6           $81.0         2.41%  5         $103.9         2.67%
 [Pasta &
 Pizza Sauce]
Frzn French     4           $20.5         3.86%  19          $50.3         1.50%  9          $70.8         1.82%
 Fries
Avocado         5           $13.4         2.52%  4          $112.6         3.35%  4         $126.0         3.24%
Blends [Salad   6           $13.1         2.47%  3          $124.0         3.69%  3         $137.1         3.52%
 Mix]
Green Beans:    7           $12.8         2.41%  15          $53.1         1.58%  15         $65.9         1.69%
 Fs/Whl/Cut
Potatoes: Dry   8           $12.3         2.31%  33          $32.3         0.96%  28         $44.6         1.15%
Corn            9           $12.1         2.28%  22          $44.0         1.31%  19         $56.0         1.44%
Head Lettuce    10          $11.6         2.18%  13          $55.5         1.65%  14         $67.1         1.72%
Frzn Steamable  11          $10.5         1.98%  5           $81.4         2.42%  6          $91.9         2.36%
 Vegetables
Mexican Sauces  12          $10.2         1.93%  9           $62.3         1.85%  8          $72.5         1.86%
 And Picante
 Sau
Tomatoes Diced  13           $9.5         1.79%  11          $59.9         1.78%  11         $69.4         1.79%
Tomatoes        14           $9.2         1.74%  7           $77.7         2.31%  7          $86.9         2.23%
 Hothouse On
 The Vine
Onions Yellow   15           $8.7         1.65%  27          $39.3         1.17%  24         $48.1         1.24%
 (Bulk & Bag)
Cucumbers       16           $8.2         1.55%  12          $58.9         1.75%  13         $67.1         1.73%
Vegetable       17           $7.8         1.48%  29          $36.6         1.09%  29         $44.4         1.14%
 Salads--Prepa
 ck
Peppers Green   18           $7.8         1.47%  25          $41.5         1.24%  22         $49.3         1.27%
 Bell
Regular Garden  19           $7.8         1.46%  35          $31.9         0.95%  31         $39.6         1.02%
Roma Tomatoes   20           $7.5         1.41%  26          $39.6         1.18%  25         $47.1         1.21%
 (Bulk/Pkg)
Carrots Mini    21           $7.0         1.32%  10          $61.4         1.83%  12         $68.5         1.76%
 Peeled
Onions Sweet    22           $6.2         1.16%  20          $47.4         1.41%  21         $53.6         1.38%
 (Bulk & Bag)
Celery          23           $5.9         1.11%  17          $51.2         1.52%  18         $57.1         1.47%
Tomatoes Vine   24           $5.7         1.07%  51          $22.5         0.67%  48         $28.2         0.72%
 Ripe Bulk
Garden Plus     25           $5.5         1.03%  36          $31.8         0.95%  34         $37.2         0.96%
 [Salad Mix]
Cabbage         26           $5.3         1.00%  43          $25.1         0.75%  43         $30.5         0.78%
Frzn Tater      27           $5.2         0.99%  55          $18.8         0.56%  53         $24.1         0.62%
 Tots/Other
 Extruded
Broccoli Whole  28           $5.2         0.97%  16          $52.0         1.55%  17         $57.1         1.47%
 & Crowns
Tomato Sauce    29           $5.1         0.96%  48          $24.2         0.72%  45         $29.3         0.75%
Variety         30           $5.1         0.96%  8           $65.2         1.94%  10         $70.3         1.81%
 Lettuce
Tomatoes Hot    31           $5.0         0.94%  39          $30.3         0.90%  37         $35.3         0.91%
 House Bulk
Potatoes Sweet  32           $4.8         0.91%  28          $37.1         1.11%  30         $41.9         1.08%
 & Yams
Tomatoes Grape  33           $4.7         0.88%  14          $54.6         1.63%  16         $59.3         1.52%
Mexican Beans/  34           $4.7         0.88%  52          $21.0         0.63%  51         $25.6         0.66%
 Refried
Frzn Hashbrown  35           $4.6         0.86%  45          $24.8         0.74%  44         $29.3         0.75%
 Potatoes
Corn Bulk       36           $4.5         0.85%  32          $32.5         0.97%  35         $37.1         0.95%
Fz Box          37           $4.4         0.83%  46          $24.7         0.73%  47         $29.1         0.75%
 Vegetables--V
 alue-Added
Kits [Salad     38           $4.2         0.79%  31          $33.5         1.00%  33         $37.6         0.97%
 Mix]
Potatoes Red    39           $4.1         0.78%  34          $32.0         0.95%  36         $36.1         0.93%
 (Bulk & Bag)
Frzn Corn On    40           $4.0         0.75%  94           $8.4         0.25%  83         $12.4         0.32%
 The Cob
Vegetable       41           $4.0         0.75%  44          $25.1         0.75%  46         $29.1         0.75%
 Party Tray
Cut Vegetables  42           $4.0         0.75%  24          $42.2         1.26%  26         $46.2         1.19%
 All Other
Vegetable       43           $3.8         0.72%  37          $31.0         0.92%  38         $34.8         0.89%
 Salads--Bulk
Veg Juice       44           $3.8         0.72%  38          $30.4         0.91%  39         $34.2         0.88%
 (Except
 Tomato) (Ove)
Asparagus       45           $3.8         0.72%  18          $50.7         1.51%  20         $54.5         1.40%
Tomatoes Vine   46           $3.6         0.68%  101          $7.3         0.22%  89         $10.9         0.28%
 Ripe Pkg
Peppers Red     47           $3.6         0.68%  23          $42.5         1.27%  27         $46.1         1.19%
 Bell
Value (Pasta    48           $3.5         0.67%  87           $9.7         0.29%  78         $13.2         0.34%
 Tomato Sauce)
Peas/Green      49           $3.5         0.66%  64          $14.7         0.44%  61         $18.2         0.47%
Spinach &       50           $3.5         0.66%  103          $7.0         0.21%  92         $10.5         0.27%
 Greens
Peppers Other   51           $3.4         0.63%  41          $28.4         0.85%  41         $31.8         0.82%
 Bell
Mushrooms       52           $3.3         0.63%  42          $27.8         0.83%  42         $31.2         0.80%
 White Sliced
 Pkg
Shredded        53           $3.3         0.62%  81          $10.9         0.32%  75         $14.2         0.36%
 Lettuce
Mushrooms       54           $3.1         0.58%  40          $29.6         0.88%  40         $32.7         0.84%
 White Whole
 Pkg
Green Onions    55           $3.0         0.57%  49          $23.5         0.70%  50         $26.5         0.68%
Salad Bowls     56           $2.9         0.54%  74          $12.3         0.37%  69         $15.2         0.39%
Fz Bag          57           $2.8         0.54%  65          $14.7         0.44%  63         $17.6         0.45%
 Vegetables--V
 alue-Added
Sal: Hommus     58           $2.8         0.52%  21          $45.4         1.35%  23         $48.2         1.24%
Mushrooms Cnd   59           $2.7         0.52%  67          $14.3         0.42%  64         $17.0         0.44%
 & Glass
Mexican         60           $2.7         0.51%  69          $13.7         0.41%  66         $16.4         0.42%
 Enchilada
 Sauce
Onions Red      61           $2.5         0.48%  53          $20.9         0.62%  54         $23.5         0.60%
 (Bulk & Bag)
Onions White    62           $2.5         0.47%  60          $15.8         0.47%  60         $18.3         0.47%
 (Bulk & Bag)
Authentic       63           $2.3         0.43%  89           $9.2         0.27%  87         $11.5         0.30%
 Sauces/Salsa/
 Picante
Salad Mix       64           $2.3         0.43%  30          $36.5         1.09%  32         $38.8         1.00%
 Blends
 Organic
Salad: Lettuce  65           $2.2         0.42%  77          $12.2         0.36%  72         $14.5         0.37%
Cauliflower     66           $2.2         0.42%  47          $24.5         0.73%  49         $26.8         0.69%
 Whole
Mushrooms       67           $2.2         0.42%  50          $22.6         0.67%  52         $24.8         0.64%
 Portabella
Mexican         68           $2.2         0.41%  61          $15.7         0.47%  62         $17.9         0.46%
 Peppers
 Chilies
Fried Onions    69           $2.1         0.39%  75          $12.3         0.37%  73         $14.3         0.37%
Carrots Bagged  70           $2.0         0.39%  58          $17.2         0.51%  58         $19.2         0.49%
Potatoes        71           $2.0         0.38%  54          $20.3         0.60%  55         $22.3         0.57%
 Gourmet
Sweet Potatoes  72           $2.0         0.38%  104          $6.7         0.20%  101         $8.7         0.22%
Corn Is         73           $1.9         0.36%  70          $12.8         0.38%  71         $14.7         0.38%
 Packaged
Salad Spinach   74           $1.8         0.34%  57          $17.9         0.53%  57         $19.7         0.51%
Tomato Paste    75           $1.8         0.34%  83          $10.2         0.30%  84         $12.0         0.31%
Sal: Salsa/     76           $1.8         0.33%  98           $7.7         0.23%  95          $9.5         0.24%
 Dips Bulk
Beans           77           $1.7         0.32%  59          $16.9         0.50%  59         $18.6         0.48%
Tomato Juice    78           $1.7         0.32%  88           $9.6         0.28%  88         $11.2         0.29%
 (Over 50%
 Jce)
Authentic       79           $1.7         0.32%  136          $3.2         0.10%  128         $4.9         0.13%
 Vegetables
 And Foods
Potatoes Gold   80           $1.6         0.29%  63          $14.8         0.44%  65         $16.4         0.42%
 (Bulk & Bag)
Garlic Whole    81           $1.6         0.29%  71          $12.7         0.38%  74         $14.3         0.37%
 Cloves
Coleslaw        82           $1.6         0.29%  79          $11.9         0.35%  77         $13.5         0.35%
Carrots Bagged  83           $1.5         0.29%  56          $18.6         0.55%  56         $20.2         0.52%
 Organic
Pumpkins        84           $1.5         0.29%  82          $10.3         0.31%  85         $11.9         0.31%
Herbs Cilanto   85           $1.4         0.26%  84          $10.1         0.30%  86         $11.5         0.30%
Frzn Baked/     86           $1.3         0.25%  91           $9.0         0.27%  93         $10.4         0.27%
 Stuffed/
 Mashed & Spec
Broccoli/       87           $1.3         0.25%  72          $12.5         0.37%  76         $13.8         0.36%
 Cauliflower
 Processed
Mixed           88           $1.3         0.24%  124          $4.5         0.13%  119         $5.8         0.15%
 Vegetables
Authentic       89           $1.3         0.24%  125          $4.5         0.13%  120         $5.7         0.15%
 Peppers
Sal: Salsa      90           $1.3         0.24%  68          $13.7         0.41%  70         $15.0         0.38%
 Prepack
Carrots         91           $1.1         0.21%  123          $4.5         0.14%  121         $5.7         0.15%
Peppers Yellow  92           $1.1         0.21%  80          $11.4         0.34%  82         $12.5         0.32%
 Bell
Pizza Sauce     93           $1.1         0.21%  110          $6.1         0.18%  107         $7.2         0.18%
Garlic Jar      94           $1.1         0.21%  97           $7.7         0.23%  99          $8.8         0.23%
Peppers         95           $1.0         0.19%  126          $4.4         0.13%  125         $5.5         0.14%
 Jalapeno
Tomatoes        96           $1.0         0.19%  78          $12.1         0.36%  80         $13.1         0.34%
 Cherry
Instore Cut     97           $1.0         0.19%  86           $9.7         0.29%  91         $10.7         0.28%
 Vegetables
Tomato Stewed   98           $1.0         0.19%  108          $6.4         0.19%  105         $7.4         0.19%
White Potatoes  99           $1.0         0.18%  128          $4.3         0.13%  127         $5.2         0.13%
Sauerkraut and  100          $0.9         0.17%  111          $6.0         0.18%  109         $6.9         0.18%
 Cabbage
                       -------------------------        --------------------------------------------------------
  Top 100                  $500.7        94.36%           $3,035.6        90.37%          $3,536.4        90.91%
   Vegetable
   Expenditure
   s *
                       -------------------------        --------------------------------------------------------
  Total                    $520.5        98.08%           $3,251.8        96.80%          $3,772.3        96.97%
   Vegetable
   Expenditure
   s Among Top
   1,000
   Subcommodit
   ies
                       =========================        ========================================================
    Total                  $530.7          100%           $3,359.3          100%          $3,890.0          100%
     Vegetable
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


                                          Exhibit D-8: Composite Foods
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
   Composite                                    ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Potato Chips    1           $64.4         5.19%  2          $253.2         4.88%  1         $317.6         4.94%
Snacks/         2           $44.6         3.59%  10         $100.5         1.94%  7         $145.0         2.26%
 Appetizers
Fz Ss Prem      3           $43.8         3.53%  4          $175.4         3.38%  4         $219.3         3.41%
 Traditional
 Meals
Snack Cake--    4           $41.6         3.36%  9          $101.7         1.96%  9         $143.3         2.23%
 Multi Pack
Fz Ss Economy   5           $40.9         3.30%  15          $80.7         1.56%  11        $121.6         1.89%
 Meals All
Pizza/Premium   6           $39.7         3.20%  6          $153.3         2.95%  5         $193.0         3.00%
Sandwiches &    7           $35.9         2.89%  17          $73.6         1.42%  13        $109.4         1.70%
 Handhelds
Convenient      8           $34.2         2.76%  19          $69.7         1.34%  14        $104.0         1.62%
 Meals--Kids
 Meal C
Premium [Ice    9           $31.2         2.52%  3          $226.0         4.35%  3         $257.2         4.00%
 Cream &
 Sherbert]
Condensed Soup  10          $29.7         2.39%  5          $153.6         2.96%  6         $183.2         2.85%
Fz Family       11          $27.6         2.23%  13          $83.5         1.61%  12        $111.1         1.73%
 Style Entrees
Traditional     12          $25.6         2.07%  8          $118.7         2.29%  8         $144.4         2.25%
 [Ice Cream &
 Sherbert]
Fz Ss Prem      13          $24.7         1.99%  1          $271.6         5.23%  2         $296.3         4.61%
 Nutritional
 Meals
Macaroni &      14          $24.3         1.96%  24          $59.7         1.15%  21         $84.0         1.31%
 Cheese Dnrs
Can Pasta       15          $22.2         1.79%  36          $47.7         0.92%  29         $69.9         1.09%
Mult Pk Bag     16          $21.6         1.74%  38          $43.4         0.84%  32         $65.0         1.01%
 Snacks
Sw Gds: Donuts  17          $21.3         1.72%  14          $82.3         1.58%  15        $103.6         1.61%
Pizza/Economy   18          $19.8         1.60%  37          $45.1         0.87%  33         $65.0         1.01%
Frzn Breakfast  19          $19.1         1.54%  29          $55.7         1.07%  23         $74.8         1.16%
 Sandwiches
Fz Skillet      20          $18.8         1.51%  16          $79.3         1.53%  17         $98.1         1.53%
 Meals
Cakes:          21          $18.6         1.50%  33          $50.3         0.97%  31         $68.9         1.07%
 Birthday/
 Celebration
 Sh
Sandwich        22          $18.0         1.45%  18          $71.8         1.38%  19         $89.8         1.40%
 Cookies
Pizza/          23          $17.9         1.44%  22          $64.1         1.24%  22         $82.0         1.27%
 Traditional
Rts Soup:       24          $17.6         1.42%  7          $119.9         2.31%  10        $137.5         2.14%
 Chunky/
 Homestyle/Et
Salsa & Dips    25          $17.1         1.38%  28          $57.0         1.10%  24         $74.1         1.15%
Sandwiches--(C  26          $16.9         1.36%  20          $67.7         1.30%  20         $84.6         1.32%
 old)
Sweet Goods--   27          $15.8         1.28%  27          $57.9         1.12%  26         $73.8         1.15%
 Full Size
Tray Pack/Choc  28          $15.3         1.23%  31          $53.9         1.04%  30         $69.2         1.08%
 Chip Cookies
Sticks/Enrobed  29          $14.2         1.14%  25          $59.7         1.15%  25         $73.9         1.15%
 [Frozen
 Novelties]
Water Ice       30          $14.0         1.13%  32          $50.6         0.97%  34         $64.6         1.00%
 [Frozen
 Novelties]
Pails [Ice      31          $13.9         1.12%  46          $35.1         0.68%  41         $49.1         0.76%
 Cream &
 Sherbert]
Skillet         32          $13.0         1.05%  57          $25.8         0.50%  49         $38.9         0.60%
 Dinners
Pizza/Single    33          $12.8         1.03%  39          $43.2         0.83%  38         $56.0         0.87%
 Serve/
 Microwave
Super Premium   34          $11.8         0.95%  11          $91.1         1.76%  16        $103.0         1.60%
 Pints [Ice
 Cream &
 Sherbert]
Cakes:          35          $11.1         0.89%  45          $35.3         0.68%  43         $46.3         0.72%
 Cupcakes
Corn Dogs       36          $10.9         0.88%  68          $20.6         0.40%  59         $31.5         0.49%
Cookies:        37          $10.8         0.87%  26          $59.6         1.15%  28         $70.4         1.09%
 Regular
Burritos        38          $10.2         0.82%  69          $20.0         0.39%  61         $30.1         0.47%
Microwave       39           $9.8         0.79%  40          $39.9         0.77%  40         $49.8         0.77%
 Dinners
Cakes: Layers   40           $9.8         0.79%  42          $38.2         0.74%  42         $48.1         0.75%
Sushi--In       41           $9.2         0.74%  12          $85.4         1.64%  18         $94.6         1.47%
 Store
 Prepared
Canister        42           $9.1         0.73%  44          $36.4         0.70%  45         $45.5         0.71%
 Snacks
Pudding &       43           $8.7         0.70%  53          $27.6         0.53%  51         $36.3         0.56%
 Gelatin Cups/
 Cans
Salty Snacks    44           $8.4         0.67%  80          $15.8         0.31%  67         $24.2         0.38%
 Vending
Cones [Frozen   45           $7.9         0.64%  50          $31.2         0.60%  48         $39.2         0.61%
 Novelties]
Vanilla Wafer/  46           $7.5         0.60%  43          $36.7         0.71%  46         $44.2         0.69%
 Kids Cookies
Ice Cream       47           $7.4         0.60%  60          $24.2         0.47%  58         $31.6         0.49%
 Sandwiches
Cakes: Creme/   48           $7.4         0.59%  58          $25.8         0.50%  54         $33.2         0.52%
 Pudding
Refrigerated    49           $7.0         0.57%  34          $49.5         0.95%  37         $56.5         0.88%
 Pudding
Layer Cake Mix  50           $7.0         0.56%  47          $35.1         0.68%  47         $42.1         0.65%
Refrigerated    51           $6.8         0.55%  51          $28.8         0.56%  53         $35.6         0.55%
 Cookies--Bran
 d
Broth           52           $6.7         0.54%  21          $65.6         1.26%  27         $72.3         1.12%
Pies: Fruit/    53           $6.3         0.51%  41          $39.6         0.76%  44         $45.9         0.71%
 Nut
Snack Cake--    54           $5.7         0.46%  77          $16.2         0.31%  74         $22.0         0.34%
 Single Serve
Better For You  55           $5.6         0.45%  35          $48.1         0.93%  39         $53.7         0.84%
 Snacks
Cookies:        56           $5.5         0.44%  56          $26.8         0.52%  56         $32.2         0.50%
 Holiday/
 Special Occas
Misc Bag        57           $5.5         0.44%  98          $11.5         0.22%  83         $17.0         0.26%
 Snacks
Frozen Fruit    58           $5.3         0.43%  62          $23.7         0.46%  62         $28.9         0.45%
 Pies &
 Cobblers
Frozen Cream    59           $4.9         0.39%  71          $18.9         0.36%  69         $23.8         0.37%
 Pies
Sw Gds: Sw      60           $4.8         0.39%  55          $26.9         0.52%  57         $31.7         0.49%
 Rolls/Dan
Brownie Mix     61           $4.8         0.39%  54          $27.5         0.53%  55         $32.3         0.50%
Fz Meal Kits/   62           $4.8         0.38%  96          $12.2         0.23%  84         $16.9         0.26%
 Stuffed/Other
Sw Gds:         63           $4.5         0.36%  48          $31.8         0.61%  50         $36.3         0.57%
 Muffins
Frzn Breakfast  64           $4.5         0.36%  78          $16.2         0.31%  78         $20.7         0.32%
 Entrees
Convenient      65           $4.5         0.36%  102         $11.2         0.22%  92         $15.7         0.24%
 Meals--Adult
 Meal
Dry Beans/Peas/ 66           $4.2         0.34%  72          $18.8         0.36%  71         $23.1         0.36%
 Barley: Bag &
 B
Adult Premium   67           $4.2         0.34%  30          $54.5         1.05%  36         $58.7         0.91%
 [Frozen
 Novelties]
Mexican         68           $4.2         0.34%  100         $11.4         0.22%  93         $15.6         0.24%
 Dinners And
 Foods
Premium         69           $4.2         0.33%  49          $31.5         0.61%  52         $35.7         0.55%
 Cookies (Ex:
 Pepperidg)
Chocolate       70           $4.0         0.32%  73          $18.5         0.36%  73         $22.5         0.35%
 Covered
 Cookies
Microwavable    71           $3.7         0.29%  116          $9.0         0.17%  106        $12.7         0.20%
 Cups
Cakes:          72           $3.6         0.29%  84          $14.7         0.28%  81         $18.3         0.28%
 Cheesecake
Deli Tray:      73           $3.5         0.28%  65          $21.5         0.41%  66         $25.0         0.39%
 Meat And
 Cheese
Dry Soup        74           $3.5         0.28%  63          $23.3         0.45%  64         $26.8         0.42%
Treats          75           $3.5         0.28%  103         $11.2         0.22%  95         $14.6         0.23%
Fitness &       76           $3.4         0.28%  23          $59.8         1.15%  35         $63.2         0.98%
 Diet--Bars W/
 Flour
Refrigerated    77           $3.4         0.28%  90          $12.9         0.25%  89         $16.3         0.25%
 Cookie Dough
Cakes: Fancy/   78           $3.3         0.27%  76          $17.4         0.34%  77         $20.7         0.32%
 Service Case
Package         79           $3.3         0.26%  112          $9.5         0.18%  105        $12.7         0.20%
 Dinners/Pasta
 Salads
Cakes: Layers/  80           $3.3         0.26%  94          $12.5         0.24%  91         $15.8         0.25%
 Sheets
 Novelties
Pies: Pumpkin/  81           $3.2         0.26%  89          $13.1         0.25%  87         $16.3         0.25%
 Custard
Puddings Dry    82           $3.2         0.26%  67          $20.8         0.40%  68         $23.9         0.37%
Vendor Size/    83           $3.1         0.25%  126          $6.8         0.13%  120         $9.9         0.15%
 Single Serve
 Cooki
Snack Mix       84           $3.0         0.24%  75          $17.5         0.34%  79         $20.5         0.32%
Multi-Pack      85           $2.9         0.23%  99          $11.4         0.22%  96         $14.3         0.22%
 Cookies
Cups/Push Ups/  86           $2.8         0.23%  110          $9.6         0.18%  108        $12.4         0.19%
 Other
Frzn Pie        87           $2.7         0.22%  79          $16.0         0.31%  80         $18.7         0.29%
 Shells/Pastry
 Shell/F
Frozen Cakes/   88           $2.7         0.22%  105         $11.0         0.21%  101        $13.7         0.21%
 Desserts
Cakes: Angel    89           $2.7         0.22%  74          $18.1         0.35%  76         $20.8         0.32%
 Fds/Cke Rolls
Wellness/       90           $2.7         0.22%  61          $23.8         0.46%  65         $26.5         0.41%
 Portion
 Control
Pie Filling/    91           $2.7         0.22%  59          $24.8         0.48%  63         $27.5         0.43%
 Mincemeat/
 Glazes
Misc Snacks     92           $2.6         0.21%  87          $13.2         0.25%  90         $15.8         0.25%
Cakes: Ice      93           $2.6         0.21%  120          $8.6         0.17%  113        $11.2         0.17%
 Cream
Sushi--Prepack  94           $2.6         0.21%  70          $19.2         0.37%  75         $21.8         0.34%
 aged
Cakes:          95           $2.5         0.20%  114          $9.1         0.18%  110        $11.6         0.18%
 Birthday/
 Celebration
 Lay
Sw Gds: Swt/    96           $2.4         0.20%  85          $13.9         0.27%  88         $16.3         0.25%
 Flvrd Loaves
Cakes: Sheet    97           $2.4         0.19%  124          $7.2         0.14%  121         $9.6         0.15%
Cookies:        98           $2.4         0.19%  66          $20.8         0.40%  70         $23.2         0.36%
 Gourmet
Premium Pints   99           $2.3         0.18%  128          $6.5         0.13%  125         $8.8         0.14%
 [Ice Cream &
 Sherbert]
Sw Gds:         100          $1.9         0.15%  104         $11.2         0.22%  104        $13.1         0.20%
 Brownie/Bar
 Cookie
                       -------------------------        --------------------------------------------------------
  Top 100                $1,179.3        95.05%           $4,717.8        90.90%          $5,897.1        91.70%
   Composite
   Expenditure
   s *
                       -------------------------        --------------------------------------------------------
  Total                  $1,235.4        99.57%           $5,132.0        98.88%          $6,367.4        99.01%
   Composite
   Expenditure
   s Among Top
   1,000
   Subcommodit
   ies
                       =========================        ========================================================
    Total                $1,240.7          100%           $5,190.0          100%          $6,430.7          100%
     Composite
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


                                        Exhibit D-9: Other Subcommodities
----------------------------------------------------------------------------------------------------------------
                  SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               ---------------------------------           Expenditures          -------------------------------
     Other                                      ---------------------------------
 Subcommodity    Rank      $ in        % of                 $ in        % of       Rank     $ in        % of
                         millions  Expenditures   Rank    millions  Expenditures          millions  Expenditures
----------------------------------------------------------------------------------------------------------------
Infant Formula  1           $54.2         9.60%  14          $45.3         1.70%  6          $99.5         3.07%
 Starter/
 Solution
Still Water     2           $48.8         8.64%  2          $187.7         7.03%  2         $236.5         7.31%
 Drnking/Mnrl
 Water
Unflavored Can  3           $41.3         7.32%  1          $198.0         7.41%  1         $239.3         7.39%
 Coffee
Isotonic        4           $30.5         5.40%  4          $119.5         4.47%  3         $150.0         4.63%
 Drinks Single
 Serve
Spring Water    5           $16.2         2.87%  5           $95.6         3.58%  5         $111.8         3.45%
Traditional     6           $14.1         2.49%  8           $61.2         2.29%  7          $75.2         2.32%
 Spices
Bbq Sauce       7           $12.3         2.17%  16          $38.6         1.45%  16         $50.9         1.57%
Baby Food--     8           $11.7         2.07%  21          $28.1         1.05%  18         $39.8         1.23%
 Beginner
Non-Carb Water  9           $11.6         2.05%  7           $63.4         2.37%  8          $74.9         2.32%
 Flvr--Drnk/
 Mnr
Catsup          10          $11.5         2.03%  15          $41.5         1.55%  15         $53.0         1.64%
Sauce Mixes/    11          $11.5         2.03%  13          $46.7         1.75%  12         $58.2         1.80%
 Gravy Mixes
 Dry
Baby Food       12          $11.2         1.98%  22          $27.5         1.03%  19         $38.7         1.20%
 Junior/All
 Brands
Isotonic        13          $10.8         1.92%  9           $58.1         2.17%  10         $68.9         2.13%
 Drinks Multi-
 Pack
Ice--Crushed/   14           $9.3         1.65%  11          $49.9         1.87%  11         $59.2         1.83%
 Cubed
Unflavored Bag  15           $8.5         1.50%  3          $137.3         5.14%  4         $145.8         4.50%
 Coffee
Infant Formula  16           $8.4         1.49%  71           $9.1         0.34%  47         $17.5         0.54%
 Specialty
Infant Formula  17           $8.3         1.46%  30          $22.8         0.85%  27         $31.0         0.96%
 Starter Large
 P
Steak &         18           $8.2         1.44%  25          $26.7         1.00%  21         $34.9         1.08%
 Worchester
 Sauce
Unflavored      19           $7.6         1.34%  23          $27.3         1.02%  22         $34.8         1.08%
 Instant
 Coffee
Non-Dairy       20           $7.1         1.25%  6           $67.7         2.53%  9          $74.8         2.31%
 Milks
Unsweetened     21           $7.0         1.25%  88           $6.2         0.23%  61         $13.3         0.41%
 Envelope
 [Powder Drink
 Mix]
Malted Mlk/     22           $6.9         1.23%  28          $25.3         0.95%  26         $32.2         1.00%
 Syrup/Pwdrs
 (Eggnog)
Still Water     23           $6.3         1.11%  17          $38.1         1.43%  17         $44.4         1.37%
 Flvrd Drnk/
 Mnrl Wt
Infant Formula  24           $6.0         1.06%  55          $12.4         0.46%  45         $18.4         0.57%
 Toddler
Mexican         25           $5.9         1.05%  33          $20.6         0.77%  32         $26.5         0.82%
 Seasoning
 Mixes
Hot Sauce       26           $5.8         1.03%  42          $16.4         0.61%  38         $22.2         0.69%
Ready To Drink  27           $5.5         0.98%  34          $20.5         0.77%  33         $26.0         0.80%
 Coffee
Tea Bags &      28           $5.4         0.95%  24          $27.2         1.02%  25         $32.5         1.01%
 Bulk Tea
Infant Formula  29           $5.3         0.95%  47          $15.2         0.57%  42         $20.5         0.63%
 Solutions
 Large
Stuffing Mixes  30           $5.3         0.94%  31          $22.1         0.83%  30         $27.4         0.85%
Infant Formula  31           $4.9         0.86%  111          $3.9         0.15%  82          $8.8         0.27%
 Concentrate
Salad Bar       32           $4.5         0.81%  41          $18.2         0.68%  36         $22.8         0.70%
 Other
Bits & Morsels  33           $4.4         0.77%  10          $50.3         1.88%  13         $54.7         1.69%
 [Baking
 Needs]
Ripe Olives     34           $4.1         0.73%  27          $25.3         0.95%  28         $29.5         0.91%
Gravy Can/      35           $4.0         0.72%  44          $15.7         0.59%  44         $19.8         0.61%
 Glass
Marinades       36           $3.9         0.70%  39          $18.4         0.69%  37         $22.4         0.69%
Baby Food       37           $3.8         0.67%  82           $7.1         0.27%  70         $10.9         0.34%
 Cereals
Diet Cntrl      38           $3.7         0.66%  20          $30.3         1.13%  24         $34.0         1.05%
 Liqs
 Nutritional
Enhancements--  39           $3.6         0.64%  36          $19.8         0.74%  35         $23.4         0.72%
 Pickles/Kraut
Infant Formula  40           $3.5         0.61%  85           $6.9         0.26%  72         $10.4         0.32%
 Ready To Use
Sugar Free      41           $3.5         0.61%  32          $21.1         0.79%  34         $24.5         0.76%
 Canister
 [Powder Drink
 Mix]
Coffee Pods/    42           $3.4         0.60%  12          $49.8         1.87%  14         $53.2         1.65%
 Singles/
 Filter Pac
Sugar Free      43           $3.3         0.58%  38          $18.8         0.70%  39         $22.1         0.68%
 Sticks
 [Powder Drink
 Mix]
Sparkling       44           $3.1         0.55%  29          $24.1         0.90%  31         $27.2         0.84%
 Water--Flvrd
 Sweet
Tea Bags/       45           $3.1         0.54%  19          $31.2         1.17%  23         $34.3         1.06%
 Herbal
Yellow Mustard  46           $3.0         0.53%  56          $12.4         0.46%  55         $15.4         0.48%
Asian Other     47           $2.8         0.50%  37          $18.9         0.71%  40         $21.8         0.67%
 Sauces/
 Marinad
Peppers         48           $2.7         0.48%  52          $13.5         0.50%  53         $16.2         0.50%
Mexican Taco    49           $2.6         0.47%  84           $7.0         0.26%  76          $9.7         0.30%
 Sauce
Green Olives    50           $2.6         0.46%  43          $15.8         0.59%  46         $18.3         0.57%
Relishes        51           $2.5         0.44%  60          $11.6         0.43%  57         $14.1         0.44%
Flavored Bag    52           $2.4         0.42%  26          $26.2         0.98%  29         $28.6         0.88%
 Coffee
Gourmet Spices  53           $2.4         0.42%  18          $33.2         1.24%  20         $35.6         1.10%
Baby Juices     54           $2.3         0.40%  118          $3.1         0.11%  105         $5.3         0.16%
Dry Salad       55           $2.0         0.35%  48          $15.1         0.57%  49         $17.1         0.53%
 Dressing &
 Dip Mixes
Mustard--All    56           $2.0         0.35%  40          $18.3         0.69%  43         $20.3         0.63%
 Other
Gelatin         57           $2.0         0.35%  51          $14.3         0.54%  52         $16.3         0.50%
Vinegar/White   58           $1.9         0.34%  50          $14.4         0.54%  51         $16.3         0.50%
 & Cider
Baby Isotonic   59           $1.9         0.33%  101          $4.9         0.18%  92          $6.8         0.21%
 Drinks
Wing Sauce      60           $1.8         0.33%  100          $5.0         0.19%  91          $6.8         0.21%
Pure Extracts   61           $1.7         0.31%  46          $15.4         0.58%  48         $17.2         0.53%
Infant Formula  62           $1.7         0.31%  161          $1.1         0.04%  135         $2.8         0.09%
 Soy Base
Juices          63           $1.7         0.30%  66          $10.1         0.38%  64         $11.8         0.36%
 Proteins
Sal: Dip        64           $1.7         0.30%  59          $12.1         0.45%  58         $13.8         0.43%
 Prepack
Diet Energy     65           $1.7         0.30%  54          $12.8         0.48%  56         $14.5         0.45%
 Drinks
Baby Spring     66           $1.7         0.30%  138          $2.0         0.07%  119         $3.7         0.11%
 Waters
Frozen          67           $1.6         0.28%  86           $6.7         0.25%  83          $8.3         0.26%
 Internaional
Table Salt/     68           $1.6         0.28%  72           $8.6         0.32%  73         $10.2         0.31%
 Popcorn Salt/
 Ice Cr
Distilled       69           $1.6         0.28%  57          $12.2         0.46%  59         $13.7         0.42%
 Water
Enhancements--  70           $1.5         0.26%  99           $5.2         0.19%  95          $6.6         0.21%
 Salads/
 Spreads
Asian Soy       71           $1.5         0.26%  64          $10.3         0.39%  66         $11.7         0.36%
 Sauce
Central         72           $1.4         0.25%  94           $5.5         0.21%  90          $6.9         0.21%
 American
 Foods
Misc Dairy      73           $1.4         0.25%  70           $9.1         0.34%  71         $10.5         0.32%
 Refigerated
Diet Cntrl      74           $1.4         0.24%  35          $19.9         0.74%  41         $21.3         0.66%
 Bars
 Nutritional
Tea Bags/Green  75           $1.2         0.22%  61          $11.2         0.42%  63         $12.5         0.38%
Flours/Grains/  76           $1.2         0.22%  49          $14.6         0.55%  54         $15.9         0.49%
 Sugar
Specialty       77           $1.2         0.22%  77           $7.7         0.29%  81          $8.9         0.27%
 Instant
 Coffee W/Swe
Misc Hispanic   78           $1.2         0.21%  65          $10.2         0.38%  67         $11.4         0.35%
 Grocery
Baking Powder   79           $1.1         0.20%  75           $8.2         0.31%  77          $9.4         0.29%
 & Soda
Isotonic        80           $1.1         0.19%  103          $4.7         0.18%  103         $5.7         0.18%
 Drinks Multi-
 Serve
Juices          81           $1.0         0.19%  76           $8.1         0.30%  78          $9.2         0.28%
 Antioxidant/
 Wellness
Spices &        82           $1.0         0.19%  104          $4.6         0.17%  104         $5.7         0.17%
 Seasonings
Infant Formula  83           $1.0         0.18%  119          $3.0         0.11%  117         $4.1         0.13%
 Up Age
Oils/Vinegar    84           $1.0         0.18%  67          $10.0         0.37%  69         $11.0         0.34%
Miscellaneous   85           $1.0         0.18%  80           $7.2         0.27%  84          $8.2         0.25%
 Package Mixes
Sal: Olives/    86           $1.0         0.18%  45          $15.5         0.58%  50         $16.5         0.51%
 Pickles--Bulk
Cooking Bags    87           $1.0         0.17%  132          $2.4         0.09%  124         $3.4         0.10%
 With Spices/
 Seaso
Cooking         88           $0.9         0.16%  63          $10.3         0.39%  68         $11.2         0.35%
 Chocolate
 (Ex: Smi-Swt)
Tea Bags        89           $0.9         0.15%  69           $9.2         0.34%  74         $10.0         0.31%
 (Supplement)
Specialty       90           $0.8         0.15%  53          $12.9         0.48%  60         $13.7         0.42%
 Vinegar
Traditional     91           $0.8         0.14%  74           $8.3         0.31%  80          $9.1         0.28%
 Thai Foods
Pickld Veg/     92           $0.8         0.14%  91           $5.9         0.22%  94          $6.7         0.21%
 Peppers/Etc.
Specialty       93           $0.8         0.14%  62          $11.0         0.41%  65         $11.7         0.36%
 Olives
Authentic       94           $0.8         0.14%  81           $7.1         0.27%  86          $7.9         0.24%
 Japanese
 Foods
Chili Sauce/    95           $0.7         0.13%  89           $6.0         0.22%  93          $6.7         0.21%
 Cocktail
 Sauce
Flavored Can    96           $0.7         0.13%  92           $5.8         0.22%  96          $6.5         0.20%
 Coffee
Fortified/      97           $0.7         0.13%  108          $4.4         0.17%  107         $5.1         0.16%
 Water
Sparkling       98           $0.7         0.12%  58          $12.1         0.45%  62         $12.8         0.40%
 Water--Unflav
 ored
Fitness &       99           $0.7         0.12%  78           $7.3         0.27%  85          $8.0         0.25%
 Diet--Powder
 Ntrtnl
Imitation       100          $0.7         0.12%  115          $3.5         0.13%  116         $4.2         0.13%
 Extracts
                       -------------------------        --------------------------------------------------------
  Top 100                  $540.1        95.68%           $2,453.1        91.80%          $2,993.1        92.48%
   Other
   Expenditure
   s *
                       -------------------------        --------------------------------------------------------
  Total Other              $550.7        97.56%           $2,533.2        94.80%          $3,083.9        95.28%
   Expenditure
   s Among Top
   1,000
   Subcommodit
   ies
                       =========================        ========================================================
    Total                  $564.5          100%           $2,672.1          100%          $3,236.6          100%
     Other
     Expenditu
     res Among
     1,792
     Subcommod
     ities
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.

Appendix E. Top 100 Subcommodities for SNAP Households by Expenditure 
        by Demographic and Store Characteristics

   Exhibit E-1: Top 100 Subcommodities for SNAP Households by Expenditure: Household Head Age 19-44 Year Olds
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $30.7         0.47%  1          $143.7         0.46%  1          $174.3         0.46%
 White Only
Soft Drinks 12/ 2          $25.1         0.38%  2           $95.9         0.30%  2          $121.0         0.32%
 18 & 15pk Can
 Car
Lean [Beef]     3          $17.2         0.26%  8           $42.7         0.14%  5           $59.9         0.16%
Kids Cereal     4          $13.8         0.21%  5           $44.6         0.14%  6           $58.4         0.15%
Shredded        5          $13.0         0.20%  3           $67.1         0.21%  3           $80.1         0.21%
 Cheese
Sft Drnk 2      6          $11.3         0.17%  13          $39.1         0.12%  8           $50.5         0.13%
 Liter Btl
 Carb Incl
Potato Chips    7          $10.1         0.15%  11          $39.4         0.13%  9           $49.5         0.13%
Primal [Beef]   8          $10.0         0.15%  16          $35.6         0.11%  14          $45.5         0.12%
Infant Formula  9           $9.8         0.15%  150          $9.2         0.03%  73          $19.0         0.05%
 Starter/
 Solutio
Lunchment--Del  10          $8.9         0.14%  6           $43.0         0.14%  7           $51.9         0.14%
 i Fresh
Chicken Breast  11          $8.4         0.13%  4           $54.2         0.17%  4           $62.5         0.16%
 Boneless
Tortilla/Nacho  12          $8.2         0.13%  10          $41.1         0.13%  10          $49.3         0.13%
 Chips
Eggs--Large     13          $7.8         0.12%  12          $39.4         0.13%  12          $47.2         0.12%
Snacks/         14          $7.7         0.12%  45          $20.6         0.07%  32          $28.3         0.07%
 Appetizers
Still Water     15          $7.6         0.12%  20          $30.5         0.10%  18          $38.1         0.10%
 Drnking/Mnrl
 Water
Mainstream      16          $7.4         0.11%  31          $23.4         0.07%  25          $30.8         0.08%
 White Bread
American        17          $7.0         0.11%  34          $22.8         0.07%  26          $29.8         0.08%
 Single Cheese
Dairy Case      18          $6.8         0.10%  9           $41.4         0.13%  11          $48.2         0.13%
 100% Pure
 Juice--O
Enhanced [Pork  19          $6.6         0.10%  24          $27.1         0.09%  23          $33.6         0.09%
 Boneless Loin/
 Rib]
Pizza/Premium   20          $6.5         0.10%  22          $28.2         0.09%  20          $34.8         0.09%
Snack Cake--    21          $6.5         0.10%  57          $18.9         0.06%  40          $25.5         0.07%
 Multi Pack
Fz Ss Economy   22          $6.3         0.10%  90          $13.6         0.04%  72          $19.9         0.05%
 Meals All
Convenient      23          $6.2         0.09%  48          $20.3         0.06%  38          $26.6         0.07%
 Meals--Kids
 Meal C
All Family      24          $6.2         0.09%  14          $37.6         0.12%  15          $43.8         0.11%
 Cereal
Fz Ss Prem      25          $6.1         0.09%  52          $19.7         0.06%  39          $25.8         0.07%
 Traditional
 Meals
Sandwiches &    26          $6.0         0.09%  77          $14.9         0.05%  64          $20.9         0.05%
 Handhelds
Soft Drinks     27          $6.0         0.09%  61          $17.9         0.06%  48          $23.9         0.06%
 20pk & 24pk
 Can Carb
Bacon--Trad     28          $6.0         0.09%  30          $23.5         0.07%  29          $29.4         0.08%
 16oz Or Less
Mainstream      29          $5.8         0.09%  23          $28.0         0.09%  22          $33.8         0.09%
 Variety
 Breads
Sugar           30          $5.6         0.09%  62          $17.9         0.06%  50          $23.5         0.06%
Natural Cheese  31          $5.6         0.08%  17          $34.5         0.11%  17          $40.1         0.11%
 Chunks
Unflavored Can  32          $5.5         0.08%  32          $23.3         0.07%  30          $28.8         0.08%
 Coffee
Frzn Chicken--  33          $5.4         0.08%  51          $19.9         0.06%  42          $25.2         0.07%
 Wht Meat
Potatoes        34          $5.3         0.08%  37          $22.4         0.07%  35          $27.7         0.07%
 Russet (Bulk
 & Bag)
Bananas         35          $5.2         0.08%  15          $37.0         0.12%  16          $42.2         0.11%
Isotonic        36          $5.1         0.08%  33          $22.9         0.07%  34          $28.0         0.07%
 Drinks Single
 Serve
Ribs [Pork]     37          $5.1         0.08%  78          $14.8         0.05%  71          $19.9         0.05%
Sft Drnk Mlt-   38          $5.0         0.08%  35          $22.6         0.07%  36          $27.6         0.07%
 Pk Btl Carb
 (Excp)
Premium [Ice    39          $4.7         0.07%  18          $32.9         0.10%  19          $37.6         0.10%
 Cream &
 Sherbert]
Sft Drnk Sngl   40          $4.7         0.07%  89          $13.7         0.04%  77          $18.4         0.05%
 Srv Btl Carb
 (Ex)
Pourable Salad  41          $4.7         0.07%  36          $22.4         0.07%  37          $27.1         0.07%
 Dressings
Condensed Soup  42          $4.6         0.07%  29          $24.0         0.08%  31          $28.6         0.08%
Choice Beef     43          $4.5         0.07%  86          $14.0         0.04%  76          $18.5         0.05%
Fz Family       44          $4.5         0.07%  82          $14.3         0.05%  74          $18.8         0.05%
 Style Entrees
Aseptic Pack    45          $4.4         0.07%  66          $16.9         0.05%  61          $21.3         0.06%
 Juice And
 Drinks
Select Beef     46          $4.3         0.06%  46          $20.5         0.07%  45          $24.8         0.07%
Macaroni &      47          $4.2         0.06%  92          $13.5         0.04%  82          $17.7         0.05%
 Cheese Dnrs
Choice Beef     48          $4.1         0.06%  63          $17.8         0.06%  56          $21.9         0.06%
Mainstream      49          $4.0         0.06%  70          $16.1         0.05%  67          $20.1         0.05%
 [Pasta &
 Pizza Sauce]
Mayonnaise &    50          $4.0         0.06%  67          $16.8         0.05%  65          $20.8         0.05%
 Whipped
 Dressing
Fz Ss Prem      51          $4.0         0.06%  7           $42.9         0.14%  13          $46.9         0.12%
 Nutritional
 Meals
Refrigerated    52          $4.0         0.06%  26          $25.8         0.08%  27          $29.7         0.08%
 Coffee
 Creamers
Fz Bag          53          $3.9         0.06%  54          $19.4         0.06%  51          $23.3         0.06%
 Vegetables--P
 lain
Hot Dogs--Base  54          $3.9         0.06%  137          $9.8         0.03%  113         $13.6         0.04%
 Meat
Strawberries    55          $3.8         0.06%  19          $30.7         0.10%  21          $34.5         0.09%
Adult Cereal    56          $3.8         0.06%  25          $25.8         0.08%  28          $29.6         0.08%
Can Pasta       57          $3.8         0.06%  119         $10.8         0.03%  102         $14.6         0.04%
Mexican Soft    58          $3.8         0.06%  39          $21.7         0.07%  41          $25.4         0.07%
 Tortillas And
 Wra
Traditional     59          $3.8         0.06%  69          $16.2         0.05%  70          $19.9         0.05%
 [Ice Cream &
 Sherbert]
Choice Beef     60          $3.7         0.06%  124         $10.6         0.03%  104         $14.3         0.04%
Mult Pk Bag     61          $3.6         0.05%  132         $10.0         0.03%  114         $13.6         0.04%
 Snacks
Pizza/Economy   62          $3.5         0.05%  128         $10.3         0.03%  111         $13.7         0.04%
Margarine:      63          $3.5         0.05%  88          $13.8         0.04%  84          $17.3         0.05%
 Tubs And
 Bowls
Frzn Chicken--  64          $3.4         0.05%  441          $3.0         0.01%  269          $6.4         0.02%
 Wings
Frzn French     65          $3.4         0.05%  143          $9.6         0.03%  119         $13.0         0.03%
 Fries
Peanut Butter   66          $3.4         0.05%  40          $21.4         0.07%  44          $24.8         0.07%
Candy Bags--    67          $3.4         0.05%  42          $20.8         0.07%  47          $24.2         0.06%
 Chocolate
Value Forms/    68          $3.3         0.05%  120         $10.7         0.03%  108         $13.9         0.04%
 18oz And
 Larger
 [Chicken]
Fruit Snacks    69          $3.3         0.05%  104         $12.1         0.04%  94          $15.4         0.04%
Sw Gds: Donuts  70          $3.2         0.05%  98          $12.5         0.04%  92          $15.7         0.04%
Meat: Turkey    71          $3.2         0.05%  21          $28.5         0.09%  24          $31.8         0.08%
 Bulk
Frzn Meat--     72          $3.2         0.05%  161          $8.8         0.03%  139         $12.0         0.03%
 Beef
Chicken Wings   73          $3.1         0.05%  350          $4.0         0.01%  247          $7.2         0.02%
Frzn Breakfast  74          $3.1         0.05%  125         $10.5         0.03%  115         $13.6         0.04%
 Sandwiches
Tuna            75          $3.1         0.05%  74          $15.6         0.05%  75          $18.8         0.05%
Waffles/        76          $3.1         0.05%  59          $18.2         0.06%  62          $21.3         0.06%
 Pancakes/
 French Toast
Cakes:          77          $3.1         0.05%  152          $9.2         0.03%  136         $12.2         0.03%
 Birthday/
 Celebration
 Sh
Sour Creams     78          $3.0         0.05%  64          $17.5         0.06%  66          $20.5         0.05%
Cheese          79          $3.0         0.05%  44          $20.7         0.07%  49          $23.7         0.06%
 Crackers
Fz Skillet      80          $3.0         0.05%  97          $12.6         0.04%  93          $15.6         0.04%
 Meals
Vegetable Oil   81          $3.0         0.05%  253          $5.7         0.02%  196          $8.7         0.02%
Lunchment--Bol  82          $3.0         0.05%  177          $8.1         0.03%  149         $11.1         0.03%
 ogna/Sausage
Pizza/          83          $3.0         0.05%  101         $12.3         0.04%  97          $15.3         0.04%
 Traditional
Cream Cheese    84          $3.0         0.04%  49          $20.3         0.06%  53          $23.2         0.06%
Sandwich        85          $2.9         0.04%  100         $12.4         0.04%  95          $15.4         0.04%
 Cookies
Butter          86          $2.9         0.04%  27          $25.1         0.08%  33          $28.0         0.07%
Ramen Noodles/  87          $2.9         0.04%  258          $5.6         0.02%  208          $8.5         0.02%
 Ramen Cups
String Cheese   88          $2.8         0.04%  38          $22.0         0.07%  46          $24.7         0.06%
Bagged Cheese   89          $2.7         0.04%  153          $9.0         0.03%  142         $11.7         0.03%
 Snacks
Salsa & Dips    90          $2.7         0.04%  136          $9.8         0.03%  129         $12.5         0.03%
Toaster         91          $2.7         0.04%  107         $11.8         0.04%  103         $14.5         0.04%
 Pastries
Hot Dog Buns    92          $2.7         0.04%  110         $11.2         0.04%  109         $13.9         0.04%
Hamburger Buns  93          $2.7         0.04%  103         $12.2         0.04%  100         $14.9         0.04%
Rts Soup:       94          $2.7         0.04%  65          $17.4         0.06%  68          $20.0         0.05%
 Chunky/
 Homestyle/Et
Flavored Milk   95          $2.6         0.04%  118         $10.8         0.03%  116         $13.4         0.04%
Candy Bars      96          $2.6         0.04%  158          $8.9         0.03%  146         $11.5         0.03%
 (Singles)
 (Including)
Yogurt/Kids     97          $2.6         0.04%  80          $14.4         0.05%  85          $17.0         0.04%
Angus [Beef]    98          $2.6         0.04%  75          $15.3         0.05%  80          $17.9         0.05%
Chicken Drums   99          $2.5         0.04%  297          $4.8         0.02%  241          $7.3         0.02%
Sweet Goods--   100         $2.5         0.04%  145          $9.5         0.03%  137         $12.0         0.03%
 Full Size
                      -------------------------       ----------------------------------------------------------
  Top 100                 $537.8         8.17%           $2,251.0         7.14%           $2,788.8         7.32%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


   Exhibit E-2: Top 100 Subcommodities for SNAP Households by Expenditure: Household Head Age 45-64 Year Olds
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $41.3         0.63%  1          $258.9         0.82%  1          $300.1         0.79%
 White Only
Soft Drinks 12/ 2          $36.6         0.56%  2          $197.3         0.63%  2          $233.9         0.61%
 18 & 15pk Can
 Car
Lean [Beef]     3          $22.4         0.34%  8           $77.3         0.25%  5           $99.7         0.26%
Shredded        4          $16.7         0.25%  3          $112.7         0.36%  6          $129.4         0.34%
 Cheese
Sft Drnk 2      5          $15.6         0.24%  14          $70.8         0.22%  3           $86.4         0.23%
 Liter Btl
 Carb Incl
Kids Cereal     6          $15.0         0.23%  27          $52.7         0.17%  8           $67.7         0.18%
Primal [Beef]   7          $14.6         0.22%  11          $74.6         0.24%  9           $89.2         0.23%
Potato Chips    8          $14.6         0.22%  6           $85.6         0.27%  14         $100.2         0.26%
Lunchment--Del  9          $12.2         0.19%  9           $76.8         0.24%  73          $89.1         0.23%
 i Fresh
Eggs--Large     10         $11.3         0.17%  10          $75.4         0.24%  7           $86.7         0.23%
Chicken Breast  11         $11.1         0.17%  4           $95.0         0.30%  4          $106.1         0.28%
 Boneless
Unflavored Can  12         $10.2         0.16%  18          $64.2         0.20%  10          $74.4         0.20%
 Coffee
Mainstream      13         $10.2         0.15%  44          $40.6         0.13%  12          $50.8         0.13%
 White Bread
Fz Ss Prem      14         $10.1         0.15%  26          $53.5         0.17%  32          $63.7         0.17%
 Traditional
 Meals
Tortilla/Nacho  15         $10.0         0.15%  17          $67.1         0.21%  18          $77.1         0.20%
 Chips
Still Water     16          $9.9         0.15%  22          $56.0         0.18%  25          $65.9         0.17%
 Drnking/Mnrl
 Water
Infant Formula  17          $9.8         0.15%  363          $7.7         0.02%  26          $17.4         0.05%
 Starter/
 Solutio
Dairy Case      18          $9.7         0.15%  7           $80.7         0.26%  11          $90.4         0.24%
 100% Pure
 Juice--O
American        19          $9.4         0.14%  42          $41.5         0.13%  23          $50.9         0.13%
 Single Cheese
Bacon--Trad     20          $9.1         0.14%  30          $50.1         0.16%  20          $59.2         0.16%
 16oz Or Less
Enhanced [Pork  21          $9.0         0.14%  24          $54.8         0.17%  40          $63.9         0.17%
 Boneless Loin/
 Rib]
Snacks/         22          $8.9         0.14%  64          $32.2         0.10%  72          $41.1         0.11%
 Appetizers
Snack Cake--    23          $8.8         0.13%  66          $31.8         0.10%  38          $40.5         0.11%
 Multi Pack
Sft Drnk Mlt-   24          $8.6         0.13%  19          $61.3         0.19%  15          $69.9         0.18%
 Pk Btl Carb
 (Excp)
Mainstream      25          $8.4         0.13%  29          $50.8         0.16%  39          $59.2         0.16%
 Variety
 Breads
Fz Ss Economy   26          $8.3         0.13%  104         $22.2         0.07%  64          $30.6         0.08%
 Meals All
Pizza/Premium   27          $8.3         0.13%  34          $48.7         0.15%  48          $57.0         0.15%
Natural Cheese  28          $8.3         0.13%  15          $69.9         0.22%  29          $78.2         0.21%
 Chunks
All Family      29          $8.1         0.12%  16          $68.0         0.22%  22          $76.1         0.20%
 Cereal
Soft Drinks     30          $8.1         0.12%  62          $33.3         0.11%  50          $41.5         0.11%
 20pk & 24pk
 Can Carb
Potatoes        31          $8.1         0.12%  31          $49.4         0.16%  17          $57.5         0.15%
 Russet (Bulk
 & Bag)
Bananas         32          $7.9         0.12%  12          $74.3         0.24%  30          $82.3         0.22%
Sugar           33          $7.7         0.12%  57          $35.2         0.11%  42          $42.9         0.11%
Ribs [Pork]     34          $7.7         0.12%  59          $34.9         0.11%  35          $42.6         0.11%
Premium [Ice    35          $7.4         0.11%  13          $73.2         0.23%  16          $80.6         0.21%
 Cream &
 Sherbert]
Condensed Soup  36          $7.2         0.11%  33          $49.0         0.16%  34          $56.2         0.15%
Sandwiches &    37          $7.1         0.11%  100         $22.5         0.07%  71          $29.5         0.08%
 Handhelds
Fz Ss Prem      38          $6.7         0.10%  5           $91.3         0.29%  36          $98.0         0.26%
 Nutritional
 Meals
Convenient      39          $6.6         0.10%  143         $18.0         0.06%  19          $24.6         0.06%
 Meals--Kids
 Meal C
Isotonic        40          $6.6         0.10%  54          $36.0         0.11%  77          $42.6         0.11%
 Drinks Single
 Serve
Select Beef     41          $6.6         0.10%  32          $49.3         0.16%  37          $55.9         0.15%
Frzn Chicken--  42          $6.5         0.10%  65          $32.0         0.10%  31          $38.5         0.10%
 Wht Meat
Choice Beef     43          $6.5         0.10%  70          $30.7         0.10%  76          $37.2         0.10%
Choice Beef     44          $6.5         0.10%  39          $45.3         0.14%  74          $51.8         0.14%
Pourable Salad  45          $6.5         0.10%  37          $46.3         0.15%  61          $52.7         0.14%
 Dressings
Traditional     46          $6.2         0.09%  52          $37.1         0.12%  45          $43.3         0.11%
 [Ice Cream &
 Sherbert]
Fz Bag          47          $6.2         0.09%  40          $42.0         0.13%  82          $48.2         0.13%
 Vegetables--P
 lain
Mayonnaise &    48          $6.0         0.09%  49          $38.0         0.12%  56          $44.0         0.12%
 Whipped
 Dressing
Refrigerated    49          $5.9         0.09%  35          $48.1         0.15%  67          $54.0         0.14%
 Coffee
 Creamers
Fz Family       50          $5.8         0.09%  80          $26.5         0.08%  65          $32.3         0.08%
 Style Entrees
Sft Drnk Sngl   51          $5.7         0.09%  111         $21.2         0.07%  13          $26.9         0.07%
 Srv Btl Carb
 (Ex)
Adult Cereal    52          $5.6         0.08%  21          $57.0         0.18%  27          $62.6         0.16%
Butter          53          $5.4         0.08%  20          $60.1         0.19%  51          $65.5         0.17%
Strawberries    54          $5.4         0.08%  25          $54.8         0.17%  113         $60.1         0.16%
Candy Bags--    55          $5.2         0.08%  28          $50.9         0.16%  21          $56.1         0.15%
 Chocolate
Hot Dogs--Base  56          $5.1         0.08%  161         $16.6         0.05%  28          $21.7         0.06%
 Meat
Margarine:      57          $5.1         0.08%  71          $30.5         0.10%  102         $35.6         0.09%
 Tubs And
 Bowls
Choice Beef     58          $5.1         0.08%  99          $22.6         0.07%  41          $27.7         0.07%
Mainstream      59          $4.9         0.07%  87          $25.0         0.08%  70          $29.9         0.08%
 [Pasta &
 Pizza Sauce]
Tuna            60          $4.8         0.07%  58          $35.1         0.11%  104         $39.9         0.10%
Lunchment--Bol  61          $4.7         0.07%  138         $18.5         0.06%  114         $23.2         0.06%
 ogna/Sausage
Meat: Turkey    62          $4.7         0.07%  23          $55.8         0.18%  111         $60.5         0.16%
 Bulk
Macaroni &      63          $4.7         0.07%  154         $17.1         0.05%  84          $21.8         0.06%
 Cheese Dnrs
Peanut Butter   64          $4.7         0.07%  45          $40.5         0.13%  269         $45.1         0.12%
Aseptic Pack    65          $4.5         0.07%  194         $14.2         0.04%  119         $18.7         0.05%
 Juice And
 Drinks
Chicken Wings   66          $4.5         0.07%  346          $8.1         0.03%  44          $12.6         0.03%
Mexican Soft    67          $4.5         0.07%  63          $33.0         0.10%  47          $37.5         0.10%
 Tortillas And
 Wra
Can Pasta       68          $4.4         0.07%  206         $13.4         0.04%  108         $17.9         0.05%
Sw Gds: Donuts  69          $4.4         0.07%  91          $23.6         0.07%  94          $27.9         0.07%
Frzn French     70          $4.3         0.07%  166         $16.2         0.05%  92          $20.5         0.05%
 Fries
Angus [Beef]    71          $4.3         0.07%  53          $36.2         0.11%  24          $40.5         0.11%
Rts Soup:       72          $4.2         0.06%  48          $38.2         0.12%  139         $42.4         0.11%
 Chunky/
 Homestyle/Et
Fz Skillet      73          $4.1         0.06%  85          $25.2         0.08%  247         $29.4         0.08%
 Meals
Cream Cheese    74          $4.1         0.06%  51          $37.6         0.12%  115         $41.7         0.11%
Frzn Chicken--  75          $4.1         0.06%  514          $4.8         0.02%  75           $8.9         0.02%
 Wings
Mult Pk Bag     76          $4.1         0.06%  208         $13.4         0.04%  62          $17.5         0.05%
 Snacks
Frzn Breakfast  77          $4.0         0.06%  147         $17.7         0.06%  136         $21.6         0.06%
 Sandwiches
Sandwich        78          $3.9         0.06%  94          $23.3         0.07%  66          $27.2         0.07%
 Cookies
Vegetable Oil   79          $3.9         0.06%  279          $9.8         0.03%  49          $13.7         0.04%
Sour Creams     80          $3.9         0.06%  67          $31.0         0.10%  93          $34.9         0.09%
Frzn Meat--     81          $3.9         0.06%  180         $15.2         0.05%  196         $19.1         0.05%
 Beef
Meat: Ham Bulk  82          $3.9         0.06%  46          $40.3         0.13%  149         $44.1         0.12%
Pizza/          83          $3.8         0.06%  125         $19.6         0.06%  97          $23.4         0.06%
 Traditional
Hamburger Buns  84          $3.8         0.06%  93          $23.5         0.07%  53          $27.2         0.07%
Pizza/Economy   85          $3.8         0.06%  238         $11.7         0.04%  95          $15.5         0.04%
Flavored Milk   86          $3.7         0.06%  116         $20.3         0.06%  33          $24.0         0.06%
Cheese          87          $3.7         0.06%  74          $29.0         0.09%  46          $32.7         0.09%
 Crackers
Candy Bars      88          $3.6         0.05%  96          $22.9         0.07%  142         $26.5         0.07%
 (Multi Pack)
Value Forms/    89          $3.6         0.05%  240         $11.6         0.04%  129         $15.2         0.04%
 18oz And
 Larger
 [Chicken]
Grapes Red      90          $3.6         0.05%  50          $37.6         0.12%  103         $41.2         0.11%
Hot Dog Buns    91          $3.6         0.05%  122         $19.7         0.06%  109         $23.3         0.06%
Waffles/        92          $3.6         0.05%  105         $22.1         0.07%  100         $25.6         0.07%
 Pancakes/
 French Toast
Spring Water    93          $3.6         0.05%  73          $29.4         0.09%  68          $32.9         0.09%
Sweet Goods--   94          $3.6         0.05%  144         $18.0         0.06%  116         $21.5         0.06%
 Full Size
Cottage Cheese  95          $3.5         0.05%  56          $35.4         0.11%  146         $38.9         0.10%
Cakes:          96          $3.5         0.05%  190         $14.6         0.05%  85          $18.2         0.05%
 Birthday/
 Celebration
 Sh
Bkfst Sausage-- 97          $3.5         0.05%  117         $20.2         0.06%  80          $23.7         0.06%
 Fresh Rolls
Dnr Sausage--   98          $3.5         0.05%  242         $11.5         0.04%  241         $15.0         0.04%
 Links Pork
 Ckd/S
Candy Bars      99          $3.5         0.05%  155         $17.1         0.05%  137         $20.5         0.05%
 (Singles)
 (Including)
Fruit Snacks    100         $3.5         0.05%  224         $12.2         0.04%  203         $15.6         0.04%
                      -------------------------       ----------------------------------------------------------
  Top 100                 $731.2        11.09%           $4,237.7        13.52%           $5,004.7        13.17%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


  Exhibit E-3: Top 100 Subcommodities for SNAP Households by Expenditure: Household Head Age 65 Years or Older
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $12.6         0.19%  1          $109.6         0.35%  1          $122.2         0.32%
 White Only
Soft Drinks 12/ 2          $10.9         0.17%  2           $69.4         0.22%  2           $80.3         0.21%
 18 & 15pk Can
 Car
Lean [Beef]     3           $6.3         0.10%  18          $26.1         0.08%  12          $32.4         0.09%
Sft Drnk 2      4           $4.2         0.06%  29          $21.4         0.07%  24          $25.6         0.07%
 Liter Btl
 Carb Incl
Primal [Beef]   5           $4.2         0.06%  15          $27.5         0.09%  13          $31.7         0.08%
Shredded        6           $4.2         0.06%  10          $29.8         0.09%  10          $34.0         0.09%
 Cheese
Potato Chips    7           $4.0         0.06%  13          $28.8         0.09%  11          $32.7         0.09%
Kids Cereal     8           $3.8         0.06%  72          $10.7         0.03%  59          $14.5         0.04%
Eggs--Large     9           $3.6         0.06%  8           $32.7         0.10%  8           $36.4         0.10%
Unflavored Can  10          $3.5         0.05%  6           $35.6         0.11%  5           $39.1         0.10%
 Coffee
Fz Ss Prem      11          $3.4         0.05%  9           $31.9         0.10%  9           $35.3         0.09%
 Traditional
 Meals
Lunchment--Del  12          $3.4         0.05%  19          $24.6         0.08%  19          $28.0         0.07%
 i Fresh
Mainstream      13          $3.2         0.05%  40          $16.9         0.05%  36          $20.1         0.05%
 White Bread
Dairy Case      14          $3.1         0.05%  3           $38.6         0.12%  3           $41.7         0.11%
 100% Pure
 Juice--O
Bacon--Trad     15          $2.9         0.04%  24          $23.1         0.07%  23          $26.0         0.07%
 16oz Or Less
Chicken Breast  16          $2.8         0.04%  17          $26.2         0.08%  18          $29.0         0.08%
 Boneless
Bananas         17          $2.7         0.04%  4           $37.1         0.12%  4           $39.8         0.10%
American        18          $2.7         0.04%  38          $17.4         0.06%  35          $20.1         0.05%
 Single Cheese
Enhanced [Pork  19          $2.7         0.04%  26          $22.9         0.07%  25          $25.6         0.07%
 Boneless Loin/
 Rib]
Mainstream      20          $2.7         0.04%  27          $22.6         0.07%  28          $25.3         0.07%
 Variety
 Breads
Sft Drnk Mlt-   21          $2.6         0.04%  20          $24.5         0.08%  20          $27.1         0.07%
 Pk Btl Carb
 (Excp)
Still Water     22          $2.6         0.04%  49          $15.2         0.05%  43          $17.8         0.05%
 Drnking/Mnrl
 Water
Potatoes        23          $2.6         0.04%  25          $22.9         0.07%  27          $25.5         0.07%
 Russet (Bulk
 & Bag)
Snack Cake--    24          $2.6         0.04%  68          $11.4         0.04%  62          $14.0         0.04%
 Multi Pack
Natural Cheese  25          $2.5         0.04%  14          $28.3         0.09%  16          $30.8         0.08%
 Chunks
All Family      26          $2.5         0.04%  12          $29.0         0.09%  14          $31.5         0.08%
 Cereal
Fz Ss Economy   27          $2.5         0.04%  87           $9.3         0.03%  73          $11.8         0.03%
 Meals All
Premium [Ice    28          $2.5         0.04%  7           $35.5         0.11%  6           $38.0         0.10%
 Cream &
 Sherbert]
Tortilla/Nacho  29          $2.5         0.04%  48          $15.6         0.05%  41          $18.0         0.05%
 Chips
Condensed Soup  30          $2.4         0.04%  22          $24.5         0.08%  21          $26.8         0.07%
Soft Drinks     31          $2.3         0.04%  82           $9.7         0.03%  70          $12.1         0.03%
 20pk & 24pk
 Can Carb
Sugar           32          $2.3         0.04%  51          $15.1         0.05%  47          $17.5         0.05%
Traditional     33          $2.3         0.03%  23          $23.2         0.07%  26          $25.5         0.07%
 [Ice Cream &
 Sherbert]
Ribs [Pork]     34          $2.3         0.03%  57          $13.4         0.04%  53          $15.6         0.04%
Snacks/         35          $2.2         0.03%  144          $6.6         0.02%  112          $8.9         0.02%
 Appetizers
Infant Formula  36          $2.2         0.03%  583          $1.4         0.00%  336          $3.6         0.01%
 Starter/
 Solutio
Pizza/Premium   37          $2.2         0.03%  59          $12.7         0.04%  57          $14.9         0.04%
Select Beef     38          $2.1         0.03%  35          $17.9         0.06%  37          $19.9         0.05%
Fz Ss Prem      39          $2.0         0.03%  5           $35.8         0.11%  7           $37.8         0.10%
 Nutritional
 Meals
Fz Bag          40          $2.0         0.03%  32          $19.9         0.06%  31          $21.9         0.06%
 Vegetables--P
 lain
Choice Beef     41          $1.9         0.03%  60          $12.7         0.04%  58          $14.6         0.04%
Mayonnaise &    42          $1.9         0.03%  34          $18.2         0.06%  34          $20.1         0.05%
 Whipped
 Dressing
Choice Beef     43          $1.9         0.03%  36          $17.7         0.06%  38          $19.6         0.05%
Adult Cereal    44          $1.9         0.03%  11          $29.4         0.09%  15          $31.2         0.08%
Butter          45          $1.9         0.03%  16          $27.4         0.09%  17          $29.3         0.08%
Margarine:      46          $1.8         0.03%  33          $18.5         0.06%  33          $20.4         0.05%
 Tubs And
 Bowls
Pourable Salad  47          $1.8         0.03%  39          $16.9         0.05%  39          $18.7         0.05%
 Dressings
Sandwiches &    48          $1.8         0.03%  219          $4.9         0.02%  165          $6.7         0.02%
 Handhelds
Strawberries    49          $1.7         0.03%  21          $24.5         0.08%  22          $26.1         0.07%
Candy Bags--    50          $1.6         0.02%  28          $22.4         0.07%  29          $24.1         0.06%
 Chocolate
Convenient      51          $1.6         0.02%  324          $3.4         0.01%  240          $5.0         0.01%
 Meals--Kids
 Meal C
Refrigerated    52          $1.6         0.02%  45          $16.1         0.05%  44          $17.7         0.05%
 Coffee
 Creamers
Frzn Chicken--  53          $1.6         0.02%  96           $8.8         0.03%  86          $10.4         0.03%
 Wht Meat
Lunchment--Bol  54          $1.6         0.02%  84           $9.5         0.03%  78          $11.1         0.03%
 ogna/Sausage
Fz Family       55          $1.6         0.02%  90           $9.0         0.03%  85          $10.6         0.03%
 Style Entrees
Isotonic        56          $1.6         0.02%  123          $7.4         0.02%  108          $9.0         0.02%
 Drinks Single
 Serve
Choice Beef     57          $1.5         0.02%  80           $9.8         0.03%  76          $11.3         0.03%
Sw Gds: Donuts  58          $1.5         0.02%  62          $12.5         0.04%  61          $14.1         0.04%
Hot Dogs--Base  59          $1.5         0.02%  146          $6.6         0.02%  125          $8.1         0.02%
 Meat
Peanut Butter   60          $1.4         0.02%  44          $16.1         0.05%  45          $17.6         0.05%
Sft Drnk Sngl   61          $1.4         0.02%  237          $4.5         0.01%  195          $6.0         0.02%
 Srv Btl Carb
 (Ex)
Tuna            62          $1.4         0.02%  54          $13.9         0.04%  55          $15.3         0.04%
Angus [Beef]    63          $1.4         0.02%  50          $15.2         0.05%  51          $16.6         0.04%
Cottage Cheese  64          $1.3         0.02%  31          $20.3         0.06%  32          $21.6         0.06%
Rts Soup:       65          $1.3         0.02%  41          $16.6         0.05%  42          $17.9         0.05%
 Chunky/
 Homestyle/Et
Chicken Wings   66          $1.3         0.02%  405          $2.6         0.01%  310          $3.9         0.01%
Meat: Turkey    67          $1.2         0.02%  47          $15.9         0.05%  48          $17.1         0.04%
 Bulk
Mainstream      68          $1.2         0.02%  142          $6.9         0.02%  126          $8.1         0.02%
 [Pasta &
 Pizza Sauce]
Grapes Red      69          $1.2         0.02%  37          $17.4         0.06%  40          $18.6         0.05%
Macaroni &      70          $1.2         0.02%  277          $4.0         0.01%  231          $5.2         0.01%
 Cheese Dnrs
Mexican Soft    71          $1.2         0.02%  115          $7.9         0.03%  106          $9.1         0.02%
 Tortillas And
 Wra
Frzn Breakfast  72          $1.2         0.02%  165          $6.1         0.02%  150          $7.2         0.02%
 Sandwiches
Cream Cheese    73          $1.1         0.02%  55          $13.9         0.04%  56          $15.0         0.04%
Can Pasta       74          $1.1         0.02%  321          $3.4         0.01%  268          $4.6         0.01%
Sweet Goods--   75          $1.1         0.02%  93           $8.9         0.03%  90          $10.1         0.03%
 Full Size
Meat: Ham Bulk  76          $1.1         0.02%  46          $15.9         0.05%  49          $17.0         0.04%
Bkfst Sausage-- 77          $1.1         0.02%  105          $8.3         0.03%  97           $9.5         0.02%
 Fresh Rolls
Fz Skillet      78          $1.1         0.02%  83           $9.6         0.03%  82          $10.8         0.03%
 Meals
Vegetable Oil   79          $1.1         0.02%  305          $3.6         0.01%  258          $4.7         0.01%
Frzn French     80          $1.1         0.02%  234          $4.6         0.01%  212          $5.7         0.01%
 Fries
Sandwich        81          $1.1         0.02%  102          $8.4         0.03%  96           $9.5         0.03%
 Cookies
Candy Bars      82          $1.1         0.02%  78           $9.9         0.03%  79          $11.0         0.03%
 (Multi Pack)
Butter Spray    83          $1.1         0.02%  69          $10.9         0.03%  71          $12.0         0.03%
 Cracker
Premium Bread   84          $1.1         0.02%  30          $21.2         0.07%  30          $22.3         0.06%
Aseptic Pack    85          $1.1         0.02%  420          $2.5         0.01%  343          $3.6         0.01%
 Juice And
 Drinks
Sticks/Enrobed  86          $1.1         0.02%  76          $10.2         0.03%  77          $11.3         0.03%
 [Frozen
 Novelties]
Sour Creams     87          $1.1         0.02%  71          $10.7         0.03%  72          $11.8         0.03%
Waffles/        88          $1.1         0.02%  111          $8.1         0.03%  102          $9.2         0.02%
 Pancakes/
 French Toast
Spring Water    89          $1.1         0.02%  73          $10.3         0.03%  75          $11.3         0.03%
Hamburger Buns  90          $1.1         0.02%  116          $7.9         0.02%  110          $8.9         0.02%
Mult Pk Bag     91          $1.0         0.02%  408          $2.6         0.01%  341          $3.6         0.01%
 Snacks
Frzn Chicken--  92          $1.0         0.02%  654          $1.2         0.00%  479          $2.2         0.01%
 Wings
Flavored Milk   93          $1.0         0.02%  178          $5.8         0.02%  161          $6.8         0.02%
Refrigerated    94          $1.0         0.02%  164          $6.2         0.02%  151          $7.2         0.02%
 Biscuits
Grapes White    95          $1.0         0.02%  70          $10.8         0.03%  74          $11.8         0.03%
Dnr Sausage--   96          $1.0         0.02%  284          $3.9         0.01%  249          $4.9         0.01%
 Links Pork
 Ckd/S
Pizza/Economy   97          $1.0         0.02%  357          $3.0         0.01%  305          $4.0         0.01%
Frzn Meat--     98          $1.0         0.01%  279          $3.9         0.01%  248          $4.9         0.01%
 Beef
Pizza/          99          $1.0         0.01%  211          $5.1         0.02%  184          $6.1         0.02%
 Traditional
Candy Bars      100         $1.0         0.01%  167          $6.0         0.02%  154          $7.0         0.02%
 (Singles)
                      -------------------------       ----------------------------------------------------------
  Top 100                 $213.1         3.29%           $1,664.6         5.23%           $1,877.6         4.94%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


    Exhibit E-4: Top 100 Subcommodities for SNAP Households by Expenditure: Households with Children Present
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $33.9         0.52%  1          $190.0         0.60%  1          $223.9         0.59%
 White Only
Soft Drinks 12/ 2          $28.4         0.43%  2          $128.5         0.41%  2          $156.9         0.41%
 18 & 15pk Can
 Car
Lean [Beef]     3          $17.5         0.27%  10          $51.4         0.16%  5           $68.9         0.18%
Kids Cereal     4          $14.0         0.21%  7           $53.4         0.17%  6           $67.4         0.18%
Shredded        5          $13.9         0.21%  3           $82.7         0.26%  3           $96.7         0.25%
 Cheese
Sft Drnk 2      6          $12.4         0.19%  12          $49.7         0.16%  9           $62.2         0.16%
 Liter Btl
 Carb Incl
Primal [Beef]   7          $11.4         0.17%  13          $49.7         0.16%  10          $61.0         0.16%
Potato Chips    8          $11.3         0.17%  5           $55.3         0.18%  7           $66.6         0.17%
Lunchment--Del  9           $9.6         0.15%  8           $53.4         0.17%  8           $63.0         0.17%
 i Fresh
Chicken Breast  10          $8.9         0.14%  4           $65.2         0.21%  4           $74.1         0.19%
 Boneless
Infant Formula  11          $8.7         0.13%  258          $7.1         0.02%  127         $15.8         0.04%
 Starter/
 Solutio
Tortilla/Nacho  12          $8.5         0.13%  11          $50.4         0.16%  12          $58.9         0.15%
 Chips
Eggs--Large     13          $8.5         0.13%  14          $49.1         0.16%  13          $57.6         0.15%
Mainstream      14          $8.3         0.13%  32          $31.1         0.10%  28          $39.4         0.10%
 White Bread
Snacks/         15          $8.2         0.12%  41          $27.4         0.09%  34          $35.6         0.09%
 Appetizers
Still Water     16          $7.8         0.12%  21          $37.7         0.12%  19          $45.5         0.12%
 Drnking/Mnrl
 Water
American        17          $7.5         0.11%  36          $28.9         0.09%  33          $36.4         0.10%
 Single Cheese
Dairy Case      18          $7.5         0.11%  6           $53.5         0.17%  11          $61.0         0.16%
 100% Pure
 Juice--O
Snack Cake--    19          $7.2         0.11%  47          $25.7         0.08%  41          $32.9         0.09%
 Multi Pack
Enhanced [Pork  20          $7.2         0.11%  22          $36.4         0.12%  21          $43.6         0.11%
 Boneless Loin/
 Rib]
Fz Ss Prem      21          $7.1         0.11%  39          $27.9         0.09%  36          $35.0         0.09%
 Traditional
 Meals
Pizza/Premium   22          $6.9         0.11%  27          $34.2         0.11%  24          $41.1         0.11%
Fz Ss Economy   23          $6.9         0.10%  90          $16.7         0.05%  73          $23.5         0.06%
 Meals All
All Family      24          $6.8         0.10%  15          $48.9         0.16%  15          $55.7         0.15%
 Cereal
Unflavored Can  25          $6.8         0.10%  26          $34.3         0.11%  25          $41.0         0.11%
 Coffee
Bacon--Trad     26          $6.8         0.10%  30          $32.1         0.10%  30          $38.8         0.10%
 16oz Or Less
Convenient      27          $6.7         0.10%  58          $23.7         0.08%  43          $30.3         0.08%
 Meals--Kids
 Meal C
Soft Drinks     28          $6.5         0.10%  63          $22.3         0.07%  53          $28.7         0.08%
 20pk & 24pk
 Can Carb
Mainstream      29          $6.3         0.10%  24          $35.3         0.11%  22          $41.6         0.11%
 Variety
 Breads
Sandwiches &    30          $6.2         0.09%  79          $18.6         0.06%  67          $24.8         0.07%
 Handhelds
Sft Drnk Mlt-   31          $6.2         0.09%  28          $33.7         0.11%  26          $39.9         0.10%
 Pk Btl Carb
 (Excp)
Natural Cheese  32          $6.2         0.09%  18          $42.9         0.14%  18          $49.1         0.13%
 Chunks
Sugar           33          $6.1         0.09%  60          $23.3         0.07%  52          $29.4         0.08%
Potatoes        34          $6.0         0.09%  33          $30.7         0.10%  32          $36.7         0.10%
 Russet (Bulk
 & Bag)
Bananas         35          $6.0         0.09%  16          $48.2         0.15%  16          $54.2         0.14%
Frzn Chicken--  36          $5.6         0.09%  54          $24.6         0.08%  45          $30.2         0.08%
 Wht Meat
Ribs [Pork]     37          $5.6         0.08%  70          $20.7         0.07%  61          $26.3         0.07%
Premium [Ice    38          $5.5         0.08%  17          $46.9         0.15%  17          $52.4         0.14%
 Cream &
 Sherbert]
Isotonic        39          $5.5         0.08%  37          $28.3         0.09%  39          $33.8         0.09%
 Drinks Single
 Serve
Condensed Soup  40          $5.4         0.08%  29          $32.7         0.10%  31          $38.2         0.10%
Pourable Salad  41          $5.1         0.08%  35          $29.1         0.09%  37          $34.2         0.09%
 Dressings
Sft Drnk Sngl   42          $4.9         0.07%  104         $15.3         0.05%  85          $20.2         0.05%
 Srv Btl Carb
 (Ex)
Choice Beef     43          $4.9         0.07%  77          $19.0         0.06%  71          $23.9         0.06%
Fz Family       44          $4.8         0.07%  80          $18.6         0.06%  74          $23.4         0.06%
 Style Entrees
Select Beef     45          $4.8         0.07%  38          $28.3         0.09%  40          $33.0         0.09%
Fz Ss Prem      46          $4.7         0.07%  9           $52.3         0.17%  14          $57.0         0.15%
 Nutritional
 Meals
Traditional     47          $4.6         0.07%  50          $24.9         0.08%  50          $29.6         0.08%
 [Ice Cream &
 Sherbert]
Aseptic Pack    48          $4.6         0.07%  74          $19.4         0.06%  69          $24.0         0.06%
 Juice And
 Drinks
Choice Beef     49          $4.6         0.07%  49          $25.1         0.08%  49          $29.7         0.08%
Fz Bag          50          $4.5         0.07%  48          $25.4         0.08%  48          $29.9         0.08%
 Vegetables--P
 lain
Mayonnaise &    51          $4.4         0.07%  66          $22.0         0.07%  60          $26.5         0.07%
 Whipped
 Dressing
Refrigerated    52          $4.4         0.07%  31          $31.1         0.10%  35          $35.5         0.09%
 Coffee
 Creamers
Strawberries    53          $4.4         0.07%  19          $40.0         0.13%  20          $44.4         0.12%
Adult Cereal    54          $4.2         0.06%  25          $35.0         0.11%  29          $39.2         0.10%
Macaroni &      55          $4.2         0.06%  101         $15.5         0.05%  88          $19.7         0.05%
 Cheese Dnrs
Mainstream      56          $4.2         0.06%  72          $19.8         0.06%  70          $24.0         0.06%
 [Pasta &
 Pizza Sauce]
Hot Dogs--Base  57          $4.2         0.06%  134         $12.6         0.04%  115         $16.8         0.04%
 Meat
Choice Beef     58          $4.0         0.06%  114         $14.4         0.05%  99          $18.5         0.05%
Can Pasta       59          $4.0         0.06%  133         $12.8         0.04%  113         $16.8         0.04%
Candy Bags--    60          $4.0         0.06%  34          $29.9         0.09%  38          $33.8         0.09%
 Chocolate
Margarine:      61          $3.9         0.06%  78          $18.9         0.06%  78          $22.8         0.06%
 Tubs And
 Bowls
Peanut Butter   62          $3.8         0.06%  40          $27.8         0.09%  42          $31.6         0.08%
Butter          63          $3.7         0.06%  23          $35.8         0.11%  27          $39.5         0.10%
Meat: Turkey    64          $3.7         0.06%  20          $37.8         0.12%  23          $41.5         0.11%
 Bulk
Mult Pk Bag     65          $3.7         0.06%  132         $12.9         0.04%  118         $16.6         0.04%
 Snacks
Frzn French     66          $3.6         0.06%  138         $12.5         0.04%  123         $16.1         0.04%
 Fries
Mexican Soft    67          $3.6         0.06%  59          $23.4         0.07%  58          $27.0         0.07%
 Tortillas And
 Wra
Sw Gds: Donuts  68          $3.6         0.05%  91          $16.7         0.05%  84          $20.2         0.05%
Pizza/Economy   69          $3.5         0.05%  158         $11.4         0.04%  136         $14.9         0.04%
Fruit Snacks    70          $3.5         0.05%  111         $14.5         0.05%  102         $18.0         0.05%
Tuna            71          $3.4         0.05%  73          $19.6         0.06%  77          $23.1         0.06%
Lunchment--Bol  72          $3.4         0.05%  156         $11.5         0.04%  135         $14.9         0.04%
 ogna/Sausage
Value Forms/    73          $3.4         0.05%  139         $12.4         0.04%  128         $15.8         0.04%
 18oz And
 Larger
 [Chicken]
Frzn Breakfast  74          $3.4         0.05%  122         $13.6         0.04%  110         $17.0         0.04%
 Sandwiches
Cheese          75          $3.4         0.05%  44          $26.8         0.09%  46          $30.2         0.08%
 Crackers
Frzn Meat--     76          $3.3         0.05%  151         $11.7         0.04%  133         $15.1         0.04%
 Beef
Waffles/        77          $3.3         0.05%  62          $22.5         0.07%  65          $25.9         0.07%
 Pancakes/
 French Toast
Frzn Chicken--  78          $3.3         0.05%  470          $3.4         0.01%  308          $6.8         0.02%
 Wings
Cream Cheese    79          $3.3         0.05%  45          $26.1         0.08%  51          $29.4         0.08%
Sandwich        80          $3.2         0.05%  83          $17.6         0.06%  83          $20.8         0.05%
 Cookies
Pizza/          81          $3.2         0.05%  100         $15.7         0.05%  94          $18.9         0.05%
 Traditional
Fz Skillet      82          $3.2         0.05%  103         $15.4         0.05%  97          $18.6         0.05%
 Meals
Sour Creams     83          $3.2         0.05%  69          $21.3         0.07%  68          $24.5         0.06%
Cakes:          84          $3.2         0.05%  160         $11.3         0.04%  143         $14.6         0.04%
 Birthday/
 Celebration
 Sh
Angus [Beef]    85          $3.2         0.05%  61          $22.8         0.07%  64          $25.9         0.07%
Flavored Milk   86          $3.2         0.05%  93          $16.4         0.05%  90          $19.6         0.05%
Chicken Wings   87          $3.2         0.05%  372          $4.7         0.01%  276          $7.8         0.02%
Hamburger Buns  88          $3.0         0.05%  92          $16.6         0.05%  89          $19.6         0.05%
Rts Soup:       89          $3.0         0.05%  65          $22.0         0.07%  66          $25.1         0.07%
 Chunky/
 Homestyle/Et
Vegetable Oil   90          $3.0         0.05%  269          $6.7         0.02%  221          $9.7         0.03%
Meat: Ham Bulk  91          $3.0         0.05%  43          $27.2         0.09%  44          $30.2         0.08%
String Cheese   92          $3.0         0.05%  51          $24.8         0.08%  55          $27.8         0.07%
Hot Dog Buns    93          $2.9         0.04%  115         $14.4         0.05%  106         $17.3         0.05%
Sweet Goods--   94          $2.9         0.04%  123         $13.5         0.04%  119         $16.4         0.04%
 Full Size
Bagged Cheese   95          $2.9         0.04%  149         $11.9         0.04%  138         $14.8         0.04%
 Snacks
Toaster         96          $2.9         0.04%  95          $16.1         0.05%  93          $19.0         0.05%
 Pastries
Grapes Red      97          $2.8         0.04%  42          $27.3         0.09%  47          $30.2         0.08%
Candy Bars      98          $2.8         0.04%  159         $11.4         0.04%  148         $14.2         0.04%
 (Singles)
 (Including)
Salsa & Dips    99          $2.8         0.04%  150         $11.8         0.04%  142         $14.6         0.04%
Ramen Noodles/  100         $2.8         0.04%  274          $6.5         0.02%  229          $9.3         0.02%
 Ramen Cups
                      -------------------------       ----------------------------------------------------------
  Top 100                 $585.8         8.90%           $2,937.8         9.32%           $3,523.7         9.25%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


   Exhibit E-5: Top 100 Subcommodities for SNAP Households by Expenditure: Households Without Children Present
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $50.6         0.77%  1          $322.1         1.02%  1          $372.7         0.98%
 White Only
Soft Drinks 12/ 2          $44.1         0.67%  2          $234.1         0.74%  2          $278.3         0.73%
 18 & 15pk Can
 Car
Lean [Beef]     3          $28.4         0.43%  10          $94.8         0.30%  6          $123.1         0.32%
Shredded        4          $19.9         0.30%  3          $126.8         0.40%  3          $146.7         0.39%
 Cheese
Sft Drnk 2      5          $18.7         0.28%  17          $81.5         0.26%  15         $100.2         0.26%
 Liter Btl
 Carb Incl
Kids Cereal     6          $18.6         0.28%  40          $54.6         0.17%  30          $73.2         0.19%
Primal [Beef]   7          $17.4         0.26%  15          $88.0         0.28%  12         $105.4         0.28%
Potato Chips    8          $17.3         0.26%  8           $98.4         0.31%  8          $115.8         0.30%
Lunchment--Del  9          $14.9         0.23%  12          $91.0         0.29%  11         $105.9         0.28%
 i Fresh
Eggs--Large     10         $14.2         0.22%  9           $98.4         0.31%  9          $112.7         0.30%
Chicken Breast  11         $13.3         0.20%  5          $110.1         0.35%  5          $123.5         0.32%
 Boneless
Infant Formula  12         $13.1         0.20%  314         $11.2         0.04%  157         $24.3         0.06%
 Starter/
 Solutio
Fz Ss Prem      13         $12.6         0.19%  19          $77.2         0.24%  18          $89.7         0.24%
 Traditional
 Meals
Unflavored Can  14         $12.5         0.19%  14          $88.7         0.28%  14         $101.2         0.27%
 Coffee
Mainstream      15         $12.5         0.19%  49          $49.8         0.16%  41          $62.3         0.16%
 White Bread
Still Water     16         $12.3         0.19%  29          $64.1         0.20%  25          $76.4         0.20%
 Drnking/Mnrl
 Water
Tortilla/Nacho  17         $12.1         0.18%  22          $73.4         0.23%  19          $85.6         0.22%
 Chips
Dairy Case      18         $12.1         0.18%  6          $107.2         0.34%  7          $119.3         0.31%
 100% Pure
 Juice--O
American        19         $11.6         0.18%  42          $52.8         0.17%  38          $64.4         0.17%
 Single Cheese
Bacon--Trad     20         $11.2         0.17%  27          $64.6         0.20%  27          $75.8         0.20%
 16oz Or Less
Enhanced [Pork  21         $11.1         0.17%  24          $68.3         0.22%  23          $79.4         0.21%
 Boneless Loin/
 Rib]
Snacks/         22         $10.7         0.16%  81          $32.0         0.10%  69          $42.7         0.11%
 Appetizers
Snack Cake--    23         $10.6         0.16%  68          $36.4         0.12%  61          $47.1         0.12%
 Multi Pack
Mainstream      24         $10.5         0.16%  25          $66.1         0.21%  24          $76.6         0.20%
 Variety
 Breads
Fz Ss Economy   25         $10.3         0.16%  94          $28.4         0.09%  75          $38.7         0.10%
 Meals All
Natural Cheese  26         $10.2         0.15%  13          $89.8         0.28%  16         $100.0         0.26%
 Chunks
Pizza/Premium   27         $10.1         0.15%  39          $55.5         0.18%  36          $65.6         0.17%
Soft Drinks     28         $10.0         0.15%  64          $38.7         0.12%  59          $48.7         0.13%
 20pk & 24pk
 Can Carb
All Family      29         $10.0         0.15%  16          $85.8         0.27%  17          $95.7         0.25%
 Cereal
Sft Drnk Mlt-   30         $10.0         0.15%  21          $74.7         0.24%  20          $84.7         0.22%
 Pk Btl Carb
 (Excp)
Potatoes        31          $9.9         0.15%  30          $64.0         0.20%  28          $73.9         0.19%
 Russet (Bulk
 & Bag)
Bananas         32          $9.9         0.15%  7          $100.3         0.32%  10         $110.1         0.29%
Sugar           33          $9.6         0.15%  55          $44.8         0.14%  50          $54.4         0.14%
Ribs [Pork]     34          $9.4         0.14%  60          $42.4         0.13%  53          $51.8         0.14%
Premium [Ice    35          $9.1         0.14%  11          $94.7         0.30%  13         $103.8         0.27%
 Cream &
 Sherbert]
Condensed Soup  36          $8.7         0.13%  26          $64.7         0.21%  29          $73.4         0.19%
Sandwiches &    37          $8.7         0.13%  128         $23.7         0.08%  94          $32.4         0.08%
 Handhelds
Select Beef     38          $8.1         0.12%  33          $59.5         0.19%  33          $67.6         0.18%
Choice Beef     39          $8.1         0.12%  65          $38.3         0.12%  63          $46.4         0.12%
Fz Ss Prem      40          $8.0         0.12%  4          $117.8         0.37%  4          $125.7         0.33%
 Nutritional
 Meals
Choice Beef     41          $7.9         0.12%  38          $55.7         0.18%  39          $63.6         0.17%
Frzn Chicken--  42          $7.9         0.12%  70          $36.1         0.11%  66          $44.0         0.12%
 Wht Meat
Pourable Salad  43          $7.9         0.12%  36          $56.5         0.18%  37          $64.4         0.17%
 Dressings
Isotonic        44          $7.8         0.12%  66          $37.9         0.12%  64          $45.7         0.12%
 Drinks Single
 Serve
Convenient      45          $7.8         0.12%  186         $18.0         0.06%  139         $25.8         0.07%
 Meals--Kids
 Meal C
Traditional     46          $7.7         0.12%  44          $51.5         0.16%  43          $59.2         0.16%
 [Ice Cream &
 Sherbert]
Fz Bag          47          $7.6         0.12%  37          $55.9         0.18%  40          $63.5         0.17%
 Vegetables--P
 lain
Mayonnaise &    48          $7.5         0.11%  45          $50.9         0.16%  44          $58.4         0.15%
 Whipped
 Dressing
Refrigerated    49          $7.1         0.11%  34          $58.8         0.19%  35          $65.9         0.17%
 Coffee
 Creamers
Fz Family       50          $7.0         0.11%  85          $31.3         0.10%  76          $38.3         0.10%
 Style Entrees
Adult Cereal    51          $7.0         0.11%  18          $77.2         0.24%  21          $84.2         0.22%
Sft Drnk Sngl   52          $6.9         0.11%  122         $24.2         0.08%  101         $31.1         0.08%
 Srv Btl Carb
 (Ex)
Margarine:      53          $6.5         0.10%  57          $44.0         0.14%  56          $50.5         0.13%
 Tubs And
 Bowls
Strawberries    54          $6.5         0.10%  23          $69.9         0.22%  26          $76.4         0.20%
Butter          55          $6.5         0.10%  20          $76.9         0.24%  22          $83.3         0.22%
Hot Dogs--Base  56          $6.3         0.10%  164         $20.4         0.06%  125         $26.7         0.07%
 Meat
Choice Beef     57          $6.3         0.10%  93          $28.5         0.09%  86          $34.8         0.09%
Candy Bags--    58          $6.2         0.09%  28          $64.3         0.20%  31          $70.5         0.19%
 Chocolate
Mainstream      59          $5.9         0.09%  96          $28.2         0.09%  88          $34.1         0.09%
 [Pasta &
 Pizza Sauce]
Lunchment--Bol  60          $5.9         0.09%  117         $24.6         0.08%  102         $30.5         0.08%
 ogna/Sausage
Tuna            61          $5.9         0.09%  54          $45.0         0.14%  54          $50.9         0.13%
Macaroni &      62          $5.8         0.09%  175         $19.1         0.06%  148         $24.9         0.07%
 Cheese Dnrs
Mexican Soft    63          $5.8         0.09%  63          $39.2         0.12%  65          $45.0         0.12%
 Tortillas And
 Wra
Chicken Wings   64          $5.8         0.09%  355         $10.0         0.03%  253         $15.8         0.04%
Peanut Butter   65          $5.7         0.09%  47          $50.3         0.16%  46          $55.9         0.15%
Sw Gds: Donuts  66          $5.6         0.09%  83          $31.9         0.10%  77          $37.5         0.10%
Meat: Turkey    67          $5.6         0.08%  31          $62.3         0.20%  32          $67.9         0.18%
 Bulk
Aseptic Pack    68          $5.4         0.08%  242         $14.1         0.04%  202         $19.5         0.05%
 Juice And
 Drinks
Can Pasta       69          $5.4         0.08%  232         $14.8         0.05%  191         $20.2         0.05%
Frzn Chicken--  70          $5.2         0.08%  547          $5.6         0.02%  372         $10.8         0.03%
 Wings
Frzn French     71          $5.2         0.08%  190         $17.8         0.06%  162         $23.0         0.06%
 Fries
Rts Soup:       72          $5.2         0.08%  48          $50.1         0.16%  48          $55.3         0.15%
 Chunky/
 Homestyle/Et
Angus [Beef]    73          $5.1         0.08%  58          $43.9         0.14%  58          $49.0         0.13%
Fz Skillet      74          $5.0         0.08%  80          $32.0         0.10%  79          $37.1         0.10%
 Meals
Mult Pk Bag     75          $5.0         0.08%  263         $13.1         0.04%  220         $18.1         0.05%
 Snacks
Vegetable Oil   76          $5.0         0.08%  278         $12.5         0.04%  226         $17.5         0.05%
Frzn Breakfast  77          $4.9         0.07%  159         $20.6         0.07%  143         $25.5         0.07%
 Sandwiches
Cream Cheese    78          $4.9         0.07%  52          $45.6         0.14%  55          $50.5         0.13%
Sour Creams     79          $4.8         0.07%  67          $37.9         0.12%  70          $42.7         0.11%
Pizza/Economy   80          $4.8         0.07%  256         $13.5         0.04%  217         $18.3         0.05%
Sandwich        81          $4.7         0.07%  105         $26.5         0.08%  100         $31.2         0.08%
 Cookies
Frzn Meat--     82          $4.7         0.07%  209         $16.2         0.05%  184         $20.9         0.05%
 Beef
Pizza/          83          $4.5         0.07%  150         $21.4         0.07%  138         $25.9         0.07%
 Traditional
Chix: Frd 8pc/  84          $4.5         0.07%  73          $35.1         0.11%  73          $39.6         0.10%
 Cut Up (Hot)
Meat: Ham Bulk  85          $4.5         0.07%  51          $47.9         0.15%  52          $52.4         0.14%
Hamburger Buns  86          $4.4         0.07%  101         $26.9         0.09%  97          $31.4         0.08%
Grapes Red      87          $4.4         0.07%  50          $48.5         0.15%  51          $52.9         0.14%
Spring Water    88          $4.4         0.07%  71          $36.1         0.11%  71          $40.5         0.11%
Cottage Cheese  89          $4.4         0.07%  46          $50.7         0.16%  49          $55.1         0.14%
Waffles/        90          $4.4         0.07%  109         $25.8         0.08%  105         $30.2         0.08%
 Pancakes/
 French Toast
Value Forms/    91          $4.4         0.07%  271         $12.7         0.04%  232         $17.1         0.04%
 18oz And
 Larger
 [Chicken]
Candy Bars      92          $4.3         0.07%  97          $28.1         0.09%  93          $32.5         0.09%
 (Multi Pack)
Cakes:          93          $4.3         0.07%  204         $16.7         0.05%  183         $21.0         0.06%
 Birthday/
 Celebration
 Sh
Hot Dog Buns    94          $4.3         0.07%  137         $22.9         0.07%  120         $27.2         0.07%
Salsa & Dips    95          $4.3         0.07%  163         $20.5         0.06%  151         $24.7         0.06%
Sweet Goods--   96          $4.3         0.07%  139         $22.9         0.07%  121         $27.2         0.07%
 Full Size
Dnr Sausage--   97          $4.3         0.07%  248         $13.9         0.04%  219         $18.2         0.05%
 Links Pork
 Ckd/S
Bkfst Sausage-- 98          $4.3         0.06%  113         $25.2         0.08%  111         $29.4         0.08%
 Fresh Rolls
Cheese          99          $4.2         0.06%  87          $30.0         0.10%  87          $34.2         0.09%
 Crackers
Bagged Cheese   100         $4.2         0.06%  177         $18.8         0.06%  161         $23.1         0.06%
 Snacks
                      -------------------------       ----------------------------------------------------------
  Top 100                 $894.8        13.60%           $5,251.7        16.66%           $6,146.5        16.13%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


          Exhibit E-6: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in the Midwest
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $64.3         0.98%  1          $237.1         0.75%  1          $301.4         0.79%
 White Only
Soft Drinks 12/ 2          $60.9         0.93%  2          $175.6         0.56%  2          $236.5         0.62%
 18 & 15pk Can
 Car
Primal [Beef]   3          $34.5         0.52%  4          $101.5         0.32%  3          $136.0         0.36%
Lean [Beef]     4          $32.9         0.50%  28          $43.8         0.14%  12          $76.7         0.20%
Shredded        5          $28.5         0.43%  3          $102.0         0.32%  4          $130.4         0.34%
 Cheese
Kids Cereal     6          $26.3         0.40%  18          $51.4         0.16%  11          $77.7         0.20%
Sft Drnk 2      7          $26.3         0.40%  8           $67.4         0.21%  6           $93.7         0.25%
 Liter Btl
 Carb Incl
Potato Chips    8          $23.0         0.35%  5           $76.5         0.24%  5           $99.5         0.26%
Snacks/         9          $19.5         0.30%  43          $33.6         0.11%  31          $53.0         0.14%
 Appetizers
Infant Formula  10         $18.9         0.29%  180         $12.1         0.04%  68          $31.1         0.08%
 Starter/
 Solutio
Lunchment--Del  11         $17.9         0.27%  10          $60.7         0.19%  10          $78.6         0.21%
 i Fresh
Mainstream      12         $17.4         0.26%  35          $38.8         0.12%  28          $56.1         0.15%
 White Bread
Enhanced [Pork  13         $17.2         0.26%  16          $54.2         0.17%  16          $71.4         0.19%
 Boneless Loin/
 Rib]
American        14         $17.1         0.26%  30          $43.2         0.14%  22          $60.3         0.16%
 Single Cheese
Tortilla/Nacho  15         $16.2         0.25%  14          $56.2         0.18%  15          $72.4         0.19%
 Chips
Unflavored Can  16         $16.1         0.24%  12          $60.0         0.19%  13          $76.1         0.20%
 Coffee
Fz Ss Economy   17         $15.7         0.24%  68          $25.0         0.08%  45          $40.7         0.11%
 Meals All
Soft Drinks     18         $15.5         0.24%  38          $36.7         0.12%  34          $52.3         0.14%
 20pk & 24pk
 Can Carb
Snack Cake--    19         $15.4         0.23%  42          $33.6         0.11%  38          $49.0         0.13%
 Multi Pack
Chicken Breast  20         $15.4         0.23%  7           $68.8         0.22%  7           $84.2         0.22%
 Boneless
Fz Ss Prem      21         $15.2         0.23%  22          $46.5         0.15%  21          $61.7         0.16%
 Traditional
 Meals
Bacon--Trad     22         $14.5         0.22%  32          $42.7         0.14%  25          $57.2         0.15%
 16oz Or Less
Eggs--Large     23         $14.2         0.22%  15          $55.8         0.18%  18          $70.0         0.18%
Dairy Case      24         $13.6         0.21%  9           $65.7         0.21%  9           $79.3         0.21%
 100% Pure
 Juice--O
Still Water     25         $13.5         0.20%  29          $43.5         0.14%  27          $57.0         0.15%
 Drnking/Mnrl
 Water
Convenient      26         $13.0         0.20%  82          $20.7         0.07%  61          $33.7         0.09%
 Meals--Kids
 Meal C
Potatoes        27         $13.0         0.20%  31          $42.9         0.14%  29          $55.9         0.15%
 Russet (Bulk
 & Bag)
Pizza/Premium   28         $12.9         0.20%  37          $37.1         0.12%  36          $50.0         0.13%
All Family      29         $12.6         0.19%  11          $60.1         0.19%  14          $72.7         0.19%
 Cereal
Sft Drnk Mlt-   30         $12.5         0.19%  19          $50.1         0.16%  19          $62.6         0.16%
 Pk Btl Carb
 (Excp)
Sandwiches &    31         $12.4         0.19%  88          $20.2         0.06%  65          $32.6         0.09%
 Handhelds
Frzn Chicken--  32         $12.4         0.19%  48          $31.9         0.10%  41          $44.3         0.12%
 Wht Meat
Ribs [Pork]     33         $12.3         0.19%  58          $27.8         0.09%  47          $40.1         0.11%
Mainstream      34         $11.8         0.18%  23          $45.3         0.14%  26          $57.1         0.15%
 Variety
 Breads
Sugar           35         $11.7         0.18%  56          $27.9         0.09%  49          $39.6         0.10%
Choice Beef     36         $11.3         0.17%  57          $27.9         0.09%  50          $39.2         0.10%
Condensed Soup  37         $11.2         0.17%  21          $46.8         0.15%  23          $58.0         0.15%
Traditional     38         $10.8         0.16%  26          $44.2         0.14%  30          $55.0         0.14%
 [Ice Cream &
 Sherbert]
Bananas         39         $10.7         0.16%  13          $59.9         0.19%  17          $70.6         0.19%
Pourable Salad  40         $10.6         0.16%  36          $38.6         0.12%  37          $49.2         0.13%
 Dressings
Fz Family       41          $9.7         0.15%  74          $22.9         0.07%  66          $32.6         0.09%
 Style Entrees
Macaroni &      42          $9.7         0.15%  97          $19.0         0.06%  74          $28.7         0.08%
 Cheese Dnrs
Choice Beef     43          $9.6         0.15%  44          $33.0         0.10%  43          $42.5         0.11%
Natural Cheese  44          $9.5         0.14%  20          $48.3         0.15%  24          $57.7         0.15%
 Chunks
Mainstream      45          $9.4         0.14%  60          $27.2         0.09%  56          $36.6         0.10%
 [Pasta &
 Pizza Sauce]
Margarine:      46          $9.1         0.14%  51          $29.9         0.09%  51          $39.0         0.10%
 Tubs And
 Bowls
Hot Dogs--Base  47          $9.1         0.14%  95          $19.5         0.06%  75          $28.6         0.08%
 Meat
Can Pasta       48          $9.0         0.14%  117         $16.1         0.05%  95          $25.1         0.07%
Mayonnaise &    49          $9.0         0.14%  54          $28.7         0.09%  54          $37.7         0.10%
 Whipped
 Dressing
Fz Ss Prem      50          $8.6         0.13%  6           $72.5         0.23%  8           $81.1         0.21%
 Nutritional
 Meals
Strawberries    51          $8.6         0.13%  17          $53.1         0.17%  20          $61.7         0.16%
Sft Drnk Sngl   52          $8.3         0.13%  127         $15.4         0.05%  100         $23.7         0.06%
 Srv Btl Carb
 (Ex)
Meat: Turkey    53          $8.1         0.12%  27          $43.9         0.14%  35          $52.0         0.14%
 Bulk
Lunchment--Bol  54          $8.1         0.12%  93          $19.7         0.06%  78          $27.8         0.07%
 ogna/Sausage
Aseptic Pack    55          $7.9         0.12%  124         $15.6         0.05%  101         $23.6         0.06%
 Juice And
 Drinks
Isotonic        56          $7.9         0.12%  59          $27.6         0.09%  58          $35.4         0.09%
 Drinks Single
 Serve
Fz Bag          57          $7.8         0.12%  45          $32.7         0.10%  46          $40.6         0.11%
 Vegetables--P
 lain
Select Beef     58          $7.7         0.12%  100         $18.5         0.06%  89          $26.2         0.07%
Frzn French     59          $7.6         0.12%  128         $15.3         0.05%  104         $23.0         0.06%
 Fries
Adult Cereal    60          $7.6         0.12%  24          $45.1         0.14%  32          $52.7         0.14%
Pizza/Economy   61          $7.6         0.12%  113         $16.6         0.05%  96          $24.2         0.06%
Sw Gds: Donuts  62          $7.6         0.11%  66          $25.4         0.08%  64          $32.9         0.09%
Frzn Chicken--  63          $7.5         0.11%  467          $4.2         0.01%  248         $11.7         0.03%
 Wings
Flavored Milk   64          $7.5         0.11%  75          $22.7         0.07%  72          $30.3         0.08%
Premium [Ice    65          $7.5         0.11%  25          $45.1         0.14%  33          $52.6         0.14%
 Cream &
 Sherbert]
Candy Bags--    66          $7.3         0.11%  34          $39.3         0.12%  40          $46.6         0.12%
 Chocolate
Peanut Butter   67          $7.1         0.11%  40          $34.5         0.11%  44          $41.6         0.11%
Sweet Goods--   68          $7.1         0.11%  81          $20.9         0.07%  77          $28.0         0.07%
 Full Size
Meat: Ham Bulk  69          $7.0         0.11%  39          $36.5         0.12%  42          $43.4         0.11%
Refrigerated    70          $7.0         0.11%  49          $31.2         0.10%  53          $38.2         0.10%
 Coffee
 Creamers
Bkfst Sausage-- 71          $6.6         0.10%  92          $19.7         0.06%  86          $26.4         0.07%
 Fresh Rolls
Tuna            72          $6.6         0.10%  62          $26.4         0.08%  63          $33.0         0.09%
Value Forms     73          $6.6         0.10%  157         $13.3         0.04%  126         $19.9         0.05%
 Frz Chick/
 18oz & Larger
Cakes:          74          $6.5         0.10%  147         $14.1         0.04%  119         $20.6         0.05%
 Birthday/
 Celebration
 Sh
Pizza/          75          $6.5         0.10%  96          $19.2         0.06%  93          $25.7         0.07%
 Traditional
Cream Cheese    76          $6.4         0.10%  47          $32.0         0.10%  52          $38.4         0.10%
Fruit Snacks    77          $6.4         0.10%  167         $13.0         0.04%  129         $19.4         0.05%
Vegetable Oil   78          $6.4         0.10%  265          $8.5         0.03%  189         $14.9         0.04%
Frzn Breakfast  79          $6.4         0.10%  145         $14.3         0.05%  118         $20.7         0.05%
 Sandwiches
Frzn Meat--     80          $6.3         0.10%  164         $13.1         0.04%  130         $19.4         0.05%
 Beef
Sandwich        81          $6.2         0.09%  89          $20.1         0.06%  85          $26.4         0.07%
 Cookies
Hamburger Buns  82          $6.2         0.09%  76          $22.4         0.07%  76          $28.6         0.08%
Fz Skillet      83          $6.2         0.09%  83          $20.7         0.07%  82          $26.9         0.07%
 Meals
Chicken Wings   84          $6.1         0.09%  368          $5.9         0.02%  240         $12.0         0.03%
Sour Creams     85          $6.1         0.09%  71          $24.3         0.08%  71          $30.4         0.08%
Cottage Cheese  86          $6.1         0.09%  41          $33.8         0.11%  48          $39.9         0.10%
Butter          87          $6.0         0.09%  33          $41.9         0.13%  39          $47.9         0.13%
Dnr Sausage--   88          $6.0         0.09%  103         $17.8         0.06%  99          $23.8         0.06%
 Links Fresh
Cheese          89          $5.9         0.09%  65          $25.5         0.08%  67          $31.4         0.08%
 Crackers
Rts Soup:       90          $5.8         0.09%  50          $30.3         0.10%  57          $36.1         0.09%
 Chunky/
 Homestyle/Et
Hot Dog Buns    91          $5.7         0.09%  102         $17.9         0.06%  102         $23.5         0.06%
Waffles/        92          $5.6         0.09%  85          $20.5         0.07%  90          $26.1         0.07%
 Pancakes/
 French Toast
Mult Pk Bag     93          $5.6         0.09%  234          $9.9         0.03%  178         $15.5         0.04%
 Snacks
Candy Bars      94          $5.6         0.08%  91          $20.0         0.06%  94          $25.6         0.07%
 (Multi Pack)
Toaster         95          $5.5         0.08%  121         $15.8         0.05%  113         $21.3         0.06%
 Pastries
Salsa & Dips    96          $5.4         0.08%  151         $13.9         0.04%  131         $19.2         0.05%
Angus [Beef]    97          $5.3         0.08%  55          $28.0         0.09%  62          $33.4         0.09%
Dnr Sausage--   98          $5.3         0.08%  182         $12.0         0.04%  155         $17.4         0.05%
 Links Pork
 Ckd/S
Tray Pack/Choc  99          $5.2         0.08%  125         $15.6         0.05%  116         $20.8         0.05%
 Chip Cookies
Grapes White    100         $5.2         0.08%  80          $21.3         0.07%  84          $26.5         0.07%
                      -------------------------       ----------------------------------------------------------
  Top 100               $1,174.1        17.84%           $3,685.6        11.70%           $4,859.7        12.76%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


           Exhibit E-7: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in the South
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $66.4         1.01%  1          $305.9         0.97%  1          $372.3         0.98%
 White Only
Soft Drinks 12/ 2          $63.3         0.96%  2          $229.6         0.73%  2          $292.8         0.77%
 18 & 15pk Can
 Car
Lean [Beef]     3          $38.6         0.59%  15          $75.2         0.24%  8          $113.8         0.30%
Kids Cereal     4          $29.8         0.45%  23          $63.5         0.20%  15          $93.3         0.24%
Sft Drnk 2      5          $26.2         0.40%  9           $91.0         0.29%  7          $117.2         0.31%
 Liter Btl
 Carb Incl
Primal [Beef]   6          $25.7         0.39%  6          $100.9         0.32%  5          $126.6         0.33%
Shredded        7          $25.6         0.39%  3          $121.8         0.39%  3          $147.4         0.39%
 Cheese
Potato Chips    8          $23.5         0.36%  12          $87.7         0.28%  10         $111.2         0.29%
Lunchment--Del  9          $22.8         0.35%  7           $95.8         0.30%  6          $118.6         0.31%
 i Fresh
Mainstream      10         $21.3         0.32%  24          $62.7         0.20%  21          $84.0         0.22%
 White Bread
Still Water     11         $20.1         0.31%  16          $74.1         0.24%  14          $94.2         0.25%
 Drnking/Mnrl
 Water
Snack Cake--    12         $19.8         0.30%  37          $48.3         0.15%  32          $68.1         0.18%
 Multi Pack
Eggs--Large     13         $18.8         0.29%  11          $88.4         0.28%  12         $107.2         0.28%
American        14         $17.9         0.27%  32          $56.0         0.18%  27          $73.9         0.19%
 Single Cheese
Chicken Breast  15         $17.5         0.27%  4          $109.1         0.35%  4          $126.6         0.33%
 Boneless
Sugar           16         $17.4         0.26%  41          $46.5         0.15%  35          $63.9         0.17%
Sft Drnk Mlt-   17         $17.2         0.26%  10          $89.0         0.28%  13         $106.2         0.28%
 Pk Btl Carb
 (Excp)
Fz Ss Prem      18         $16.7         0.25%  27          $59.9         0.19%  24          $76.6         0.20%
 Traditional
 Meals
Infant Formula  19         $16.5         0.25%  247         $13.1         0.04%  108         $29.5         0.08%
 Starter/
 Solutio
Tortilla/Nacho  20         $16.1         0.24%  19          $71.5         0.23%  18          $87.6         0.23%
 Chips
Dairy Case      21         $15.9         0.24%  8           $92.7         0.29%  11         $108.6         0.29%
 100% Pure
 Juice--O
Pizza/Premium   22         $15.9         0.24%  29          $59.0         0.19%  26          $74.9         0.20%
Fz Ss Economy   23         $15.2         0.23%  84          $27.9         0.09%  59          $43.1         0.11%
 Meals All
Snacks/         24         $15.2         0.23%  59          $35.7         0.11%  47          $50.9         0.13%
 Appetizers
Soft Drinks     25         $15.2         0.23%  58          $36.1         0.11%  46          $51.2         0.13%
 20pk & 24pk
 Can Carb
Bacon--Trad     26         $14.8         0.23%  30          $58.3         0.18%  29          $73.1         0.19%
 16oz Or Less
Mainstream      27         $14.6         0.22%  18          $72.1         0.23%  19          $86.8         0.23%
 Variety
 Breads
Sandwiches &    28         $14.6         0.22%  87          $27.1         0.09%  63          $41.7         0.11%
 Handhelds
Ribs [Pork]     29         $14.1         0.21%  51          $40.4         0.13%  41          $54.5         0.14%
Convenient      30         $14.1         0.21%  80          $28.6         0.09%  60          $42.7         0.11%
 Meals--Kids
 Meal C
Enhanced [Pork  31         $14.0         0.21%  21          $66.0         0.21%  23          $80.0         0.21%
 Boneless Loin/
 Rib]
Potatoes        32         $13.8         0.21%  26          $61.4         0.19%  25          $75.3         0.20%
 Russet (Bulk
 & Bag)
Unflavored Can  33         $13.4         0.20%  17          $73.0         0.23%  20          $86.3         0.23%
 Coffee
Chicken Wings   34         $13.4         0.20%  224         $14.2         0.05%  119         $27.6         0.07%
Mult Pk Bag     35         $12.2         0.19%  137         $20.4         0.06%  87          $32.6         0.09%
 Snacks
Fz Bag          36         $12.2         0.19%  33          $54.9         0.17%  33          $67.1         0.18%
 Vegetables--P
 lain
Sft Drnk Sngl   37         $12.2         0.18%  85          $27.5         0.09%  66          $39.7         0.10%
 Srv Btl Carb
 (Ex)
Premium [Ice    38         $12.1         0.18%  13          $79.1         0.25%  16          $91.3         0.24%
 Cream &
 Sherbert]
Frzn Chicken--  39         $12.1         0.18%  338          $9.0         0.03%  173         $21.1         0.06%
 Wings
Bananas         40         $11.6         0.18%  14          $78.9         0.25%  17          $90.5         0.24%
All Family      41         $11.3         0.17%  20          $70.1         0.22%  22          $81.4         0.21%
 Cereal
Pourable Salad  42         $11.1         0.17%  38          $48.1         0.15%  36          $59.2         0.16%
 Dressings
Hot Dogs--Base  43         $11.0         0.17%  106         $23.9         0.08%  80          $34.9         0.09%
 Meat
Condensed Soup  44         $10.9         0.17%  31          $56.2         0.18%  34          $67.1         0.18%
Fz Family       45         $10.5         0.16%  69          $32.1         0.10%  61          $42.6         0.11%
 Style Entrees
Isotonic        46         $10.2         0.16%  49          $40.6         0.13%  48          $50.8         0.13%
 Drinks Single
 Serve
Frzn Chicken--  47         $10.2         0.16%  55          $37.3         0.12%  53          $47.5         0.12%
 Wht Meat
Vegetable Oil   48         $10.1         0.15%  204         $15.4         0.05%  132         $25.5         0.07%
Mayonnaise &    49         $10.1         0.15%  46          $43.1         0.14%  43          $53.2         0.14%
 Whipped
 Dressing
Aseptic Pack    50          $9.9         0.15%  115         $22.7         0.07%  88          $32.5         0.09%
 Juice And
 Drinks
Frzn Breakfast  51          $9.5         0.14%  83          $27.9         0.09%  70          $37.4         0.10%
 Sandwiches
Macaroni &      52          $9.4         0.14%  121         $21.8         0.07%  98          $31.3         0.08%
 Cheese Dnrs
Fz Ss Prem      53          $9.2         0.14%  5          $102.2         0.32%  9          $111.5         0.29%
 Nutritional
 Meals
Frzn French     54          $9.2         0.14%  127         $21.2         0.07%  103         $30.4         0.08%
 Fries
Choice Beef     55          $8.9         0.14%  56          $37.2         0.12%  55          $46.1         0.12%
Lunchment--Bol  56          $8.9         0.14%  110         $23.5         0.07%  89          $32.4         0.09%
 ogna/Sausage
Natural Cheese  57          $8.9         0.14%  28          $59.2         0.19%  31          $68.1         0.18%
 Chunks
Can Pasta       58          $8.8         0.13%  156         $18.7         0.06%  121         $27.5         0.07%
Adult Cereal    59          $8.5         0.13%  22          $64.7         0.21%  28          $73.2         0.19%
Traditional     60          $8.5         0.13%  50          $40.5         0.13%  49          $49.0         0.13%
 [Ice Cream &
 Sherbert]
Mainstream      61          $8.4         0.13%  81          $28.5         0.09%  74          $36.9         0.10%
 [Pasta &
 Pizza Sauce]
Dnr Sausage--   62          $8.3         0.13%  199         $15.7         0.05%  144         $24.1         0.06%
 Links Pork
 Ckd/S
Chicken Drums   63          $8.3         0.13%  249         $12.9         0.04%  172         $21.2         0.06%
Margarine:      64          $8.1         0.12%  63          $33.4         0.11%  64          $41.5         0.11%
 Tubs And
 Bowls
Tuna            65          $8.0         0.12%  48          $40.9         0.13%  50          $48.9         0.13%
Pizza/Economy   66          $7.9         0.12%  181         $16.4         0.05%  142         $24.3         0.06%
Strawberries    67          $7.8         0.12%  25          $62.0         0.20%  30          $69.9         0.18%
Angus [Beef]    68          $7.8         0.12%  40          $46.9         0.15%  40          $54.7         0.14%
Shrimp--Raw     69          $7.6         0.12%  70          $31.8         0.10%  68          $39.4         0.10%
Value Forms/    70          $7.5         0.11%  179         $16.5         0.05%  145 $        24.0         0.06%
 18oz And
 Larger
 [Chicken]
Select Beef     71          $7.5         0.11%  36          $51.3         0.16%  37          $58.8         0.15%
Fz Skillet      72          $7.4         0.11%  76          $29.7         0.09%  72          $37.1         0.10%
 Meals
Cakes:          73          $7.3         0.11%  142         $19.7         0.06%  122         $27.1         0.07%
 Birthday/
 Celebration
 Sh
Bacon--Trad     74          $7.2         0.11%  108         $23.7         0.08%  100         $30.9         0.08%
 Greater Than
 16oz
Pizza/          75          $7.2         0.11%  91          $26.2         0.08%  84          $33.4         0.09%
 Traditional
Refrigerated    76          $7.1         0.11%  114         $22.8         0.07%  106         $29.9         0.08%
 Biscuits
Sw Gds: Donuts  77          $7.0         0.11%  107         $23.8         0.08%  101         $30.8         0.08%
Frzn Meat--     78          $7.0         0.11%  185         $16.3         0.05%  151         $23.3         0.06%
 Beef
Salsa & Dips    79          $7.0         0.11%  122         $21.7         0.07%  114         $28.7         0.08%
Fruit Snacks    80          $7.0         0.11%  194         $16.0         0.05%  154         $23.0         0.06%
Candy Bags--    81          $6.9         0.11%  42          $46.5         0.15%  42          $53.4         0.14%
 Chocolate
Peanut Butter   82          $6.7         0.10%  43          $45.2         0.14%  45          $51.9         0.14%
Sandwich        83          $6.7         0.10%  100         $24.9         0.08%  93          $31.6         0.08%
 Cookies
Ramen Noodles/  84          $6.6         0.10%  327          $9.5         0.03%  243         $16.2         0.04%
 Ramen Cups
Waffles/        85          $6.6         0.10%  82          $27.9         0.09%  81          $34.5         0.09%
 Pancakes/
 French Toast
Hot Dog Buns    86          $6.3         0.10%  116         $22.5         0.07%  113         $28.9         0.08%
Candy Bars      87          $6.2         0.09%  96          $25.4         0.08%  95          $31.6         0.08%
 (Multi Pack)
Bagged Cheese   88          $6.2         0.09%  147         $19.4         0.06%  133         $25.5         0.07%
 Snacks
Prepared        89          $6.1         0.09%  125         $21.5         0.07%  118         $27.6         0.07%
 Beans--Baked
 W/Pork
Loaf Cheese     90          $6.1         0.09%  145         $19.5         0.06%  130         $25.6         0.07%
Meat: Turkey    91          $6.0         0.09%  34          $52.7         0.17%  38          $58.8         0.15%
 Bulk
Tray Pack/Choc  92          $6.0         0.09%  141         $19.9         0.06%  129         $26.0         0.07%
 Chip Cookies
Hamburger Buns  93          $6.0         0.09%  99          $25.1         0.08%  99          $31.1         0.08%
Green Beans:    94          $6.0         0.09%  102         $24.8         0.08%  102         $30.8         0.08%
 Fs/Whl/Cut
Grapes White    95          $6.0         0.09%  75          $29.7         0.09%  79          $35.6         0.09%
Spring Water    96          $6.0         0.09%  64          $32.9         0.10%  69          $38.8         0.10%
Rts Soup:       97          $5.9         0.09%  54          $38.6         0.12%  57          $44.5         0.12%
 Chunky/
 Homestyle/Et
Butter Spray    98          $5.9         0.09%  88          $26.2         0.08%  91          $32.1         0.08%
 Cracker
Instore Cut     99          $5.9         0.09%  57          $36.6         0.12%  62          $42.5         0.11%
 Fruit
Toaster         100         $5.8         0.09%  134         $20.5         0.07%  125         $26.4         0.07%
 Pastries
                      -------------------------       ----------------------------------------------------------
  Top 100               $1,268.9        19.28%           $4,783.8        15.18%           $6,052.7        15.89%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


           Exhibit E-8: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in the West
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $60.4         0.92%  1          $310.8         0.99%  1          $371.2         0.97%
 White Only
Lean [Beef]     2          $40.9         0.62%  3          $138.9         0.44%  3          $179.8         0.47%
Soft Drinks 12/ 3          $40.5         0.62%  2          $196.0         0.62%  2          $236.5         0.62%
 18 & 15pk Can
 Car
Kids Cereal     4          $22.0         0.33%  22          $71.5         0.23%  17          $93.5         0.25%
Shredded        5          $20.7         0.31%  4          $118.2         0.38%  4          $138.9         0.36%
 Cheese
Eggs--Large     6          $19.1         0.29%  8          $107.4         0.34%  6          $126.5         0.33%
Infant Formula  7          $18.8         0.29%  167         $20.1         0.06%  75          $38.9         0.10%
 Starter/
 Solutio
Sft Drnk 2      8          $18.4         0.28%  21          $71.8         0.23%  18          $90.2         0.24%
 Liter Btl
 Carb Incl
Potato Chips    9          $17.9         0.27%  13          $89.0         0.28%  11         $106.9         0.28%
Natural Cheese  10         $16.9         0.26%  7          $108.6         0.34%  7          $125.6         0.33%
 Chunks
Chicken Breast  11         $16.7         0.25%  5          $115.0         0.36%  5          $131.7         0.35%
 Boneless
Still Water     12         $15.2         0.23%  24          $70.1         0.22%  23          $85.3         0.22%
 Drnking/Mnrl
 Water
Lunchment--Del  13         $15.2         0.23%  14          $86.0         0.27%  13         $101.2         0.27%
 i Fresh
Tortilla/Nacho  14         $15.1         0.23%  17          $81.3         0.26%  16          $96.4         0.25%
 Chips
Mexican Soft    15         $15.1         0.23%  23          $71.5         0.23%  21          $86.6         0.23%
 Tortillas And
 Wra
Dairy Case      16         $14.0         0.21%  6          $110.7         0.35%  8          $124.7         0.33%
 100% Pure
 Juice--O
Select Beef     17         $12.6         0.19%  19          $73.9         0.23%  22          $86.5         0.23%
Isotonic        18         $12.4         0.19%  39          $51.4         0.16%  38          $63.7         0.17%
 Drinks Single
 Serve
All Family      19         $12.3         0.19%  15          $84.7         0.27%  15          $97.0         0.25%
 Cereal
Mainstream      20         $12.0         0.18%  37          $55.8         0.18%  36          $67.8         0.18%
 Variety
 Breads
Fz Ss Prem      21         $11.9         0.18%  27          $69.1         0.22%  25          $81.0         0.21%
 Traditional
 Meals
Bananas         22         $11.9         0.18%  9          $103.9         0.33%  9          $115.8         0.30%
Unflavored Can  23         $11.9         0.18%  29          $65.0         0.21%  27          $76.9         0.20%
 Coffee
Premium [Ice    24         $11.6         0.18%  10         $101.7         0.32%  10         $113.3         0.30%
 Cream &
 Sherbert]
Refrigerated    25         $11.5         0.17%  18          $75.9         0.24%  20          $87.4         0.23%
 Coffee
 Creamers
Bacon--Trad     26         $11.4         0.17%  36          $56.6         0.18%  34          $68.1         0.18%
 16oz Or Less
Pizza/Premium   27         $10.9         0.17%  35          $57.2         0.18%  35          $68.1         0.18%
Enhanced [Pork  28         $10.3         0.16%  49          $47.8         0.15%  42          $58.1         0.15%
 Boneless Loin/
 Rib]
Fz Ss Economy   29         $10.0         0.15%  104         $27.8         0.09%  83          $37.8         0.10%
 Meals All
Snacks/         30         $10.0         0.15%  85          $31.2         0.10%  70          $41.1         0.11%
 Appetizers
Choice Beef     31          $9.9         0.15%  28          $66.5         0.21%  28          $76.5         0.20%
Mainstream      32          $9.3         0.14%  71          $35.3         0.11%  64          $44.6         0.12%
 White Bread
American        33          $9.0         0.14%  66          $37.4         0.12%  62          $46.5         0.12%
 Single Cheese
Soft Drinks     34          $9.0         0.14%  77          $33.6         0.11%  67          $42.6         0.11%
 20pk & 24pk
 Can Carb
Potatoes        35          $9.0         0.14%  44          $50.1         0.16%  40          $59.1         0.16%
 Russet (Bulk
 & Bag)
Adult Cereal    36          $8.8         0.13%  20          $72.8         0.23%  24          $81.6         0.21%
Sandwiches &    37          $8.8         0.13%  113         $26.3         0.08%  92          $35.1         0.09%
 Handhelds
Ribs [Pork]     38          $8.6         0.13%  62          $38.5         0.12%  59          $47.1         0.12%
Avocado         39          $8.4         0.13%  26          $69.5         0.22%  26          $77.9         0.20%
Choice Beef     40          $8.2         0.13%  102         $28.4         0.09%  85          $36.6         0.10%
Mayonnaise &    41          $8.2         0.12%  50          $47.2         0.15%  45          $55.4         0.15%
 Whipped
 Dressing
Sandwiches--(C  42          $8.1         0.12%  54          $44.1         0.14%  51          $52.2         0.14%
 old)
Butter          43          $8.0         0.12%  16          $81.6         0.26%  19          $89.6         0.24%
Premium Bread   44          $7.9         0.12%  12          $89.1         0.28%  14          $97.0         0.25%
Sugar           45          $7.8         0.12%  64          $38.3         0.12%  63          $46.1         0.12%
Condensed Soup  46          $7.6         0.12%  42          $50.6         0.16%  41          $58.2         0.15%
Frzn Chicken--  47          $7.4         0.11%  90          $30.6         0.10%  81          $38.0         0.10%
 Wht Meat
Fz Family       48          $7.4         0.11%  100         $28.5         0.09%  87          $35.9         0.09%
 Style Entrees
Sft Drnk Sngl   49          $7.3         0.11%  101         $28.5         0.09%  88          $35.8         0.09%
 Srv Btl Carb
 (Ex)
Candy Bags--    50          $7.3         0.11%  33          $61.8         0.20%  32          $69.0         0.18%
 Chocolate
Pourable Salad  51          $7.3         0.11%  38          $52.8         0.17%  39          $60.1         0.16%
 Dressings
Convenient      52          $7.1         0.11%  160         $20.5         0.06%  126         $27.6         0.07%
 Meals--Kids
 Meal C
Strawberries    53          $7.0         0.11%  31          $63.3         0.20%  31          $70.3         0.18%
Fz Ss Prem      54          $6.9         0.10%  11          $96.9         0.31%  12         $103.7         0.27%
 Nutritional
 Meals
Sw Gds: Donuts  55          $6.7         0.10%  79          $33.1         0.11%  74          $39.8         0.10%
Peanut Butter   56          $6.6         0.10%  48          $48.1         0.15%  46          $54.7         0.14%
Tuna            57          $6.5         0.10%  59          $42.6         0.14%  57          $49.2         0.13%
Snack Cake--    58          $6.5         0.10%  168         $19.8         0.06%  141         $26.3         0.07%
 Multi Pack
Aseptic Pack    59          $6.4         0.10%  174         $18.8         0.06%  152         $25.3         0.07%
 Juice And
 Drinks
Traditional     60          $6.3         0.10%  75          $34.1         0.11%  73          $40.4         0.11%
 [Ice Cream &
 Sherbert]
Margarine:      61          $6.2         0.09%  65          $37.5         0.12%  65          $43.8         0.11%
 Tubs And
 Bowls
Sour Creams     62          $6.2         0.09%  60          $41.7         0.13%  58          $47.9         0.13%
String Cheese   63          $6.2         0.09%  55          $43.8         0.14%  54          $50.0         0.13%
Candy Bars      64          $6.2         0.09%  103         $28.1         0.09%  95          $34.2         0.09%
 (Singles)
 (Including)
Bagged Cheese   65          $6.1         0.09%  166         $20.2         0.06%  139         $26.4         0.07%
 Snacks
Cream Cheese    66          $6.1         0.09%  46          $48.4         0.15%  47          $54.5         0.14%
Dairy Case      67          $6.0         0.09%  132         $23.5         0.07%  115         $29.5         0.08%
 Juice Drnk
 Under 10
Rts Soup:       68          $5.9         0.09%  40          $51.0         0.16%  43          $56.9         0.15%
 Chunky/
 Homestyle/Et
Fz Bag          69          $5.7         0.09%  53          $44.3         0.14%  55          $50.0         0.13%
 Vegetables--P
 lain
Frzn Meat--     70          $5.7         0.09%  199         $16.9         0.05%  168         $22.6         0.06%
 Beef
Tea Sweetened   71          $5.7         0.09%  89          $30.6         0.10%  86          $36.3         0.10%
Chix:           72          $5.6         0.09%  30          $64.7         0.21%  30          $70.3         0.18%
 Rotisserie
 (Hot)
Burritos        73          $5.4         0.08%  286         $12.2         0.04%  220         $17.6         0.05%
Spring Water    74          $5.3         0.08%  52          $44.9         0.14%  53          $50.3         0.13%
Ramen Noodles/  75          $5.3         0.08%  268         $12.8         0.04%  217         $18.1         0.05%
 Ramen Cups
Macaroni &      76          $5.2         0.08%  173         $18.8         0.06%  156         $24.0         0.06%
 Cheese Dnrs
Natural Cheese  77          $5.2         0.08%  41          $51.0         0.16%  44          $56.2         0.15%
 Slices
Fz Skillet      78          $5.2         0.08%  94          $29.0         0.09%  96          $34.1         0.09%
 Meals
Waffles/        79          $5.2         0.08%  95          $28.9         0.09%  97          $34.1         0.09%
 Pancakes/
 French Toast
Mainstream      80          $5.1         0.08%  117         $25.3         0.08%  113         $30.4         0.08%
 [Pasta &
 Pizza Sauce]
Meat: Turkey    81          $5.1         0.08%  32          $63.0         0.20%  33          $68.1         0.18%
 Bulk
Cheese          82          $5.1         0.08%  78          $33.1         0.11%  79          $38.2         0.10%
 Crackers
Grapes Red      83          $5.1         0.08%  51          $46.6         0.15%  52          $51.6         0.14%
Sandwich        84          $5.1         0.08%  110         $26.7         0.08%  107         $31.8         0.08%
 Cookies
Shrimp--Cooked  85          $5.1         0.08%  124         $24.5         0.08%  114         $29.5         0.08%
Whole Chicken   86          $5.0         0.08%  107         $27.3         0.09%  104         $32.3         0.08%
 (Roasters/
 Fryer)
Shrimp--Raw     87          $5.0         0.08%  109         $27.2         0.09%  106         $32.2         0.08%
Hot Dogs--Base  88          $4.9         0.08%  255         $13.5         0.04%  213         $18.4         0.05%
 Meat
Cottage Cheese  89          $4.9         0.07%  45          $48.8         0.15%  49          $53.7         0.14%
Oranges Navels  90          $4.9         0.07%  68          $36.8         0.12%  69          $41.6         0.11%
 All
Chewing Gum     91          $4.8         0.07%  80          $33.0         0.10%  84          $37.8         0.10%
Lunchment--Bol  92          $4.8         0.07%  190         $17.7         0.06%  170         $22.5         0.06%
 ogna/Sausage
Apple Juice &   93          $4.7         0.07%  188         $18.0         0.06%  167         $22.7         0.06%
 Cider (Over
 50%)
Super Premium   94          $4.7         0.07%  47          $48.3         0.15%  50          $53.1         0.14%
 Pints [Ice
 Cream &
 Sherbert]
Salsa & Dips    95          $4.7         0.07%  152         $21.4         0.07%  143         $26.2         0.07%
Cakes:          96          $4.7         0.07%  206         $16.5         0.05%  184         $21.2         0.06%
 Birthday/
 Celebration
 Sh
Yogurt/Ss       97          $4.7         0.07%  70          $36.3         0.12%  71          $41.0         0.11%
 Regular
Value Forms/    98          $4.6         0.07%  270         $12.8         0.04%  226         $17.3         0.05%
 18oz And
 Larger
 [Chicken]
Energy Drink--  99          $4.5         0.07%  108         $27.3         0.09%  108         $31.8         0.08%
 Single Serve
 (N)
Non-Carb Water  100         $4.5         0.07%  88          $30.7         0.09%  90          $35.1         0.09%
 Flvr--Drnk/
 Mnr
                      -------------------------       ----------------------------------------------------------
  Top 100                 $971.3        14.76%           $5,340.7        16.93%           $6,312.0        16.56%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


  Exhibit E-9: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in Large Metropolitan Counties
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1         $102.1         1.55%  1          $484.1         1.54%  1          $586.2         1.54%
 White Only
Soft Drinks 12/ 2          $84.7         1.29%  2          $346.6         1.10%  2          $431.3         1.13%
 18 & 15pk Can
 Car
Lean [Beef]     3          $58.3         0.89%  11         $142.4         0.45%  5          $200.7         0.53%
Kids Cereal     4          $44.8         0.68%  18         $110.5         0.35%  14         $155.3         0.41%
Shredded        5          $41.0         0.62%  3          $197.3         0.63%  3          $238.2         0.63%
 Cheese
Sft Drnk 2      6          $39.6         0.60%  13         $135.9         0.43%  10         $175.5         0.46%
 Liter Btl
 Carb Incl
Potato Chips    7          $35.3         0.54%  9          $145.9         0.46%  8          $181.2         0.48%
Lunchment--Del  8          $30.4         0.46%  12         $140.6         0.45%  11         $171.0         0.45%
 i Fresh
Eggs--Large     9          $29.6         0.45%  8          $147.8         0.47%  9          $177.3         0.47%
Primal [Beef]   10         $29.6         0.45%  19         $109.9         0.35%  18         $139.5         0.37%
Infant Formula  11         $29.1         0.44%  198         $26.5         0.08%  88          $55.6         0.15%
 Starter/
 Solution
Still Water     12         $28.9         0.44%  17         $119.0         0.38%  16         $147.9         0.39%
 Drnking/Mnrl
 Water
Chicken Breast  13         $27.5         0.42%  4          $178.4         0.57%  4          $205.9         0.54%
 Boneless
Dairy Case      14         $26.7         0.41%  6          $168.2         0.53%  6          $194.9         0.51%
 100% Pure
 Juice--O
Tortilla/Nacho  15         $25.7         0.39%  15         $122.3         0.39%  15         $148.0         0.39%
 Chips
Fz Ss Prem      16         $25.6         0.39%  23         $108.0         0.34%  20         $133.5         0.35%
 Traditional
 Meals
Snacks/         17         $24.7         0.38%  65          $61.0         0.19%  45          $85.7         0.22%
 Appetizers
Mainstream      18         $24.3         0.37%  49          $73.5         0.23%  39          $97.8         0.26%
 White Bread
American        19         $23.7         0.36%  43          $77.3         0.25%  34         $101.0         0.27%
 Single Cheese
Mainstream      20         $23.2         0.35%  25         $102.4         0.32%  22         $125.7         0.33%
 Variety
 Breads
Fz Ss Economy   21         $22.6         0.34%  91          $46.0         0.15%  70          $68.7         0.18%
 Meals All
Bacon--Trad     22         $22.5         0.34%  31          $90.3         0.29%  28         $112.9         0.30%
 16oz Or Less
Snack Cake--    23         $22.3         0.34%  72          $55.8         0.18%  59          $78.1         0.21%
 Multi Pack
Pizza/Premium   24         $21.7         0.33%  29          $91.8         0.29%  26         $113.5         0.30%
Unflavored Can  25         $20.3         0.31%  22         $108.3         0.34%  21         $128.7         0.34%
 Coffee
Sugar           26         $20.1         0.31%  62          $62.1         0.20%  54          $82.1         0.22%
Bananas         27         $19.9         0.30%  7          $148.3         0.47%  12         $168.2         0.44%
Enhanced [Pork  28         $19.8         0.30%  33          $86.6         0.27%  31         $106.5         0.28%
 Boneless Loin/
 Rib]
All Family      29         $19.8         0.30%  14         $124.8         0.40%  17         $144.6         0.38%
 Cereal
Premium [Ice    30         $19.3         0.29%  10         $144.6         0.46%  13         $163.9         0.43%
 Cream &
 Sherbert]
Sandwiches &    31         $19.2         0.29%  95          $43.3         0.14%  78          $62.5         0.16%
 Handhelds
Ribs [Pork]     32         $19.1         0.29%  64          $61.4         0.19%  56          $80.6         0.21%
Convenient      33         $18.7         0.28%  103         $41.8         0.13%  82          $60.5         0.16%
 Meals--Kids
 Meal C
Natural Cheese  34         $18.6         0.28%  16         $120.3         0.38%  19         $138.9         0.36%
 Chunks
Potatoes        35         $18.5         0.28%  36          $85.2         0.27%  32         $103.7         0.27%
 Russet (Bulk
 & Bag)
Isotonic        36         $17.7         0.27%  47          $73.7         0.23%  43          $91.4         0.24%
 Drinks Single
 Serve
Soft Drinks     37         $17.5         0.27%  75          $54.2         0.17%  64          $71.6         0.19%
 20pk & 24pk
 Can Carb
Frzn Chicken--  38         $16.9         0.26%  73          $55.6         0.18%  63          $72.5         0.19%
 Wht Meat
Sft Drnk Mlt-   39         $16.3         0.25%  30          $90.4         0.29%  29         $106.7         0.28%
 Pk Btl Carb
 (Excp)
Pourable Salad  40         $16.2         0.25%  39          $82.7         0.26%  37          $98.9         0.26%
 Dressings
Choice Beef     41         $16.1         0.24%  40          $81.9         0.26%  38          $98.0         0.26%
Fz Family       42         $15.5         0.24%  82          $49.6         0.16%  74          $65.1         0.17%
 Style Entrees
Condensed Soup  43         $15.4         0.23%  38          $84.7         0.27%  35         $100.2         0.26%
Fz Bag          44         $15.1         0.23%  42          $77.6         0.25%  42          $92.7         0.24%
 Vegetables--P
 lain
Frzn Chicken--  45         $15.1         0.23%  444         $11.1         0.04%  242         $26.3         0.07%
 Wings
Mayonnaise &    46         $14.9         0.23%  55          $68.0         0.22%  50          $82.9         0.22%
 Whipped
 Dressing
Select Beef     47         $14.9         0.23%  34          $86.5         0.27%  33         $101.4         0.27%
Fz Ss Prem      48         $14.6         0.22%  5          $172.2         0.55%  7          $186.7         0.49%
 Nutritional
 Meals
Adult Cereal    49         $14.4         0.22%  20         $109.6         0.35%  23         $124.0         0.33%
Sft Drnk Sngl   50         $14.4         0.22%  107         $40.1         0.13%  92          $54.5         0.14%
 Srv Btl Carb
 (Ex)
Aseptic Pack    51         $14.3         0.22%  122         $36.3         0.12%  100         $50.6         0.13%
 Juice And
 Drinks
Chicken Wings   52         $14.0         0.21%  282         $18.6         0.06%  190         $32.6         0.09%
Traditional     53         $13.6         0.21%  58          $63.3         0.20%  62          $76.9         0.20%
 [Ice Cream &
 Sherbert]
Mult Pk Bag     54         $13.5         0.21%  182         $28.3         0.09%  134         $41.8         0.11%
 Snacks
Refrigerated    55         $13.5         0.20%  27          $93.2         0.30%  30         $106.6         0.28%
 Coffee
 Creamers
Mexican Soft    56         $13.4         0.20%  53          $69.5         0.22%  51          $82.9         0.22%
 Tortillas And
 Wra
Strawberries    57         $13.4         0.20%  21         $109.1         0.35%  24         $122.5         0.32%
Hot Dogs--Base  58         $13.1         0.20%  174         $29.5         0.09%  130         $42.5         0.11%
 Meat
Mainstream      59         $13.0         0.20%  86          $48.2         0.15%  80          $61.2         0.16%
 [Pasta &
 Pizza Sauce]
Macaroni &      60         $12.8         0.19%  136         $34.4         0.11%  109         $47.1         0.12%
 Cheese Dnrs
Choice Beef     61         $12.6         0.19%  114         $38.4         0.12%  99          $51.0         0.13%
Margarine:      62         $12.6         0.19%  68          $58.4         0.19%  65          $71.0         0.19%
 Tubs And
 Bowls
Tuna            63         $12.2         0.19%  56          $68.0         0.22%  57          $80.2         0.21%
Meat: Turkey    64         $12.1         0.18%  24         $105.2         0.33%  25         $117.4         0.31%
 Bulk
Vegetable Oil   65         $11.7         0.18%  256         $20.5         0.06%  194         $32.2         0.08%
Frzn French     66         $11.4         0.17%  180         $28.5         0.09%  147         $39.8         0.10%
 Fries
Lunchment--Bol  67         $11.3         0.17%  152         $32.9         0.10%  121         $44.2         0.12%
 ogna/Sausage
Candy Bags--    68         $11.3         0.17%  37          $84.8         0.27%  41          $96.0         0.25%
 Chocolate
Can Pasta       69         $11.3         0.17%  204         $26.0         0.08%  163         $37.3         0.10%
Fz Skillet      70         $11.2         0.17%  84          $48.9         0.16%  85          $60.1         0.16%
 Meals
Sw Gds: Donuts  71         $11.1         0.17%  99          $43.0         0.14%  93          $54.1         0.14%
Butter          72         $11.1         0.17%  26         $102.0         0.32%  27         $113.1         0.30%
Peanut Butter   73         $11.0         0.17%  45          $74.1         0.23%  46          $85.0         0.22%
Frzn Meat--     74         $10.7         0.16%  196         $26.6         0.08%  162         $37.3         0.10%
 Beef
Frzn Breakfast  75         $10.7         0.16%  143         $33.6         0.11%  120         $44.3         0.12%
 Sandwiches
Cakes:          76         $10.7         0.16%  169         $30.1         0.10%  140         $40.8         0.11%
 Birthday/
 Celebration
 Sh
Waffles/        77         $10.4         0.16%  81          $50.0         0.16%  83          $60.5         0.16%
 Pancakes/
 French Toast
Spring Water    78         $10.4         0.16%  57          $67.7         0.21%  60          $78.0         0.20%
Value Forms/    79         $10.2         0.16%  212         $24.9         0.08%  177         $35.1         0.09%
 18oz And
 Larger
 [Chicken]
Sandwiches--(C  80         $10.2         0.16%  92          $46.0         0.15%  87          $56.2         0.15%
 old)
Dairy Case      81         $10.2         0.15%  158         $31.8         0.10%  131         $42.0         0.11%
 Juice Drnk
 Under 10
Dnr Sausage--   82         $10.2         0.15%  232         $23.0         0.07%  186         $33.2         0.09%
 Links Pork
 Ckd/S
Sandwich        83         $10.1         0.15%  102         $42.0         0.13%  97          $52.1         0.14%
 Cookies
Pizza/Economy   84         $10.0         0.15%  234         $22.9         0.07%  188         $32.9         0.09%
Chicken Drums   85         $10.0         0.15%  276         $18.9         0.06%  225         $28.9         0.08%
Rts Soup:       86          $9.9         0.15%  50          $73.4         0.23%  48          $83.4         0.22%
 Chunky/
 Homestyle/Et
Ramen Noodles/  87          $9.8         0.15%  302         $17.2         0.05%  237         $27.0         0.07%
 Ramen Cups
Cream Cheese    88          $9.8         0.15%  54          $68.9         0.22%  58          $78.7         0.21%
Sour Creams     89          $9.7         0.15%  70          $56.7         0.18%  72          $66.4         0.17%
Bagged Cheese   90          $9.6         0.15%  167         $30.8         0.10%  144         $40.4         0.11%
 Snacks
Fruit Snacks    91          $9.6         0.15%  211         $25.1         0.08%  181         $34.6         0.09%
Salsa & Dips    92          $9.5         0.14%  139         $34.0         0.11%  124         $43.5         0.11%
Ground Turkey   93          $9.4         0.14%  74          $55.3         0.18%  75          $64.7         0.17%
Pizza/          94          $9.3         0.14%  128         $35.3         0.11%  117         $44.7         0.12%
 Traditional
Sweet Goods--   95          $9.3         0.14%  119         $36.5         0.12%  113         $45.7         0.12%
 Full Size
Candy Bars      96          $9.2         0.14%  155         $32.3         0.10%  136         $41.5         0.11%
 (Singles)
 (Including)
Hot Dog Buns    97          $9.2         0.14%  118         $36.7         0.12%  112         $46.0         0.12%
Cheese          98          $9.2         0.14%  71          $55.9         0.18%  73          $65.1         0.17%
 Crackers
Shrimp--Raw     99          $9.2         0.14%  104         $41.3         0.13%  101         $50.5         0.13%
Grapes Red      100         $9.2         0.14%  51          $72.9         0.23%  55          $82.1         0.22%
                      -------------------------       ----------------------------------------------------------
  Top 100               $1,843.6        28.02%           $7,796.5        24.74%           $9,640.1        25.31%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


Exhibit E-10: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in Smaller Metropolitan Counties
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $62.4         0.95%  1          $264.0         0.84%  1          $326.5         0.86%
 White Only
Soft Drinks 12/ 2          $52.7         0.80%  2          $176.7         0.56%  2          $229.4         0.60%
 18 & 15pk Can
 Car
Lean [Beef]     3          $38.9         0.59%  5           $80.9         0.26%  4          $119.7         0.31%
Kids Cereal     4          $24.8         0.38%  20          $55.9         0.18%  13          $80.7         0.21%
Shredded        5          $24.6         0.37%  3          $104.4         0.33%  3          $129.1         0.34%
 Cheese
Primal [Beef]   6          $23.2         0.35%  8           $76.1         0.24%  6           $99.3         0.26%
Sft Drnk 2      7          $23.2         0.35%  12          $70.0         0.22%  8           $93.1         0.24%
 Liter Btl
 Carb Incl
Potato Chips    8          $20.9         0.32%  7           $76.3         0.24%  7           $97.3         0.26%
Infant Formula  9          $18.7         0.28%  180         $13.8         0.04%  73          $32.5         0.09%
 Starter/
 Solutio
Lunchment--Del  10         $18.4         0.28%  11          $74.4         0.24%  9           $92.8         0.24%
 i Fresh
Eggs--Large     11         $16.4         0.25%  9           $74.8         0.24%  10          $91.2         0.24%
Mainstream      12         $16.1         0.24%  33          $42.8         0.14%  29          $58.9         0.15%
 White Bread
Chicken Breast  13         $15.9         0.24%  4           $84.6         0.27%  5          $100.5         0.26%
 Boneless
Tortilla/Nacho  14         $15.8         0.24%  16          $63.2         0.20%  16          $79.0         0.21%
 Chips
Enhanced [Pork  15         $14.7         0.22%  21          $54.7         0.17%  20          $69.4         0.18%
 Boneless Loin/
 Rib]
American        16         $14.5         0.22%  35          $41.3         0.13%  33          $55.8         0.15%
 Single Cheese
Snacks/         17         $14.2         0.22%  66          $28.6         0.09%  48          $42.8         0.11%
 Appetizers
Unflavored Can  18         $14.2         0.22%  17          $61.8         0.20%  18          $75.9         0.20%
 Coffee
Soft Drinks     19         $14.0         0.21%  49          $35.1         0.11%  38          $49.1         0.13%
 20pk & 24pk
 Can Carb
Still Water     20         $13.9         0.21%  28          $47.9         0.15%  24          $61.8         0.16%
 Drnking/Mnrl
 Water
Fz Ss Prem      21         $13.6         0.21%  25          $50.3         0.16%  22          $64.0         0.17%
 Traditional
 Meals
Fz Ss Economy   22         $13.4         0.20%  76          $25.0         0.08%  59          $38.3         0.10%
 Meals All
Bacon--Trad     23         $13.2         0.20%  30          $46.6         0.15%  26          $59.8         0.16%
 16oz Or Less
Snack Cake--    24         $13.0         0.20%  61          $30.5         0.10%  46          $43.5         0.11%
 Multi Pack
Pizza/Premium   25         $12.8         0.19%  32          $44.8         0.14%  31          $57.6         0.15%
Dairy Case      26         $12.7         0.19%  10          $74.5         0.24%  11          $87.2         0.23%
 100% Pure
 Juice--O
Potatoes        27         $12.0         0.18%  29          $47.4         0.15%  28          $59.4         0.16%
 Russet (Bulk
 & Bag)
Sugar           28         $11.9         0.18%  50          $35.0         0.11%  42          $47.0         0.12%
Natural Cheese  29         $11.9         0.18%  14          $68.4         0.22%  14          $80.3         0.21%
 Chunks
All Family      30         $11.8         0.18%  15          $66.4         0.21%  17          $78.2         0.21%
 Cereal
Sandwiches &    31         $11.7         0.18%  89          $21.8         0.07%  70          $33.5         0.09%
 Handhelds
Sft Drnk Mlt-   32         $11.7         0.18%  19          $57.3         0.18%  21          $68.9         0.18%
 Pk Btl Carb
 (Excp)
Ribs [Pork]     33         $11.4         0.17%  57          $31.2         0.10%  50          $42.6         0.11%
Mainstream      34         $11.2         0.17%  24          $50.9         0.16%  23          $62.2         0.16%
 Variety
 Breads
Convenient      35         $11.1         0.17%  103         $20.1         0.06%  77          $31.2         0.08%
 Meals--Kids
 Meal C
Bananas         36         $10.4         0.16%  13          $69.3         0.22%  15          $79.7         0.21%
Condensed Soup  37         $10.0         0.15%  27          $48.8         0.15%  30          $58.7         0.15%
Frzn Chicken--  38          $9.6         0.15%  58          $31.1         0.10%  51          $40.7         0.11%
 Wht Meat
Choice Beef     39          $9.5         0.14%  36          $40.9         0.13%  36          $50.4         0.13%
Pourable Salad  40          $9.3         0.14%  37          $40.9         0.13%  37          $50.2         0.13%
 Dressings
Select Beef     41          $9.3         0.14%  34          $41.5         0.13%  35          $50.8         0.13%
Sft Drnk Sngl   42          $9.3         0.14%  87          $22.6         0.07%  76          $31.9         0.08%
 Srv Btl Carb
 (Ex)
Isotonic        43          $9.2         0.14%  53          $33.6         0.11%  49          $42.7         0.11%
 Drinks Single
 Serve
Premium [Ice    44          $8.9         0.14%  18          $61.5         0.19%  19          $70.4         0.18%
 Cream &
 Sherbert]
Fz Family       45          $8.8         0.13%  77          $24.8         0.08%  69          $33.6         0.09%
 Style Entrees
Mayonnaise &    46          $8.8         0.13%  45          $36.0         0.11%  45          $44.8         0.12%
 Whipped
 Dressing
Traditional     47          $8.7         0.13%  41          $39.7         0.13%  39          $48.4         0.13%
 [Ice Cream &
 Sherbert]
Hot Dogs--Base  48          $8.3         0.13%  121         $18.0         0.06%  92          $26.3         0.07%
 Meat
Choice Beef     49          $8.2         0.13%  79          $23.8         0.08%  74          $32.1         0.08%
Macaroni &      50          $8.2         0.12%  118         $18.1         0.06%  93          $26.3         0.07%
 Cheese Dnrs
Fz Bag          51          $7.8         0.12%  42          $39.6         0.13%  41          $47.4         0.12%
 Vegetables--P
 lain
Refrigerated    52          $7.7         0.12%  39          $40.6         0.13%  40          $48.3         0.13%
 Coffee
 Creamers
Margarine:      53          $7.7         0.12%  63          $30.0         0.10%  61          $37.6         0.10%
 Tubs And
 Bowls
Adult Cereal    54          $7.7         0.12%  22          $54.1         0.17%  25          $61.7         0.16%
Can Pasta       55          $7.6         0.12%  157         $15.3         0.05%  114         $22.9         0.06%
Mexican Soft    56          $7.6         0.12%  56          $31.9         0.10%  56          $39.5         0.10%
 Tortillas And
 Wra
Fz Ss Prem      57          $7.6         0.12%  6           $76.8         0.24%  12          $84.4         0.22%
 Nutritional
 Meals
Aseptic Pack    58          $7.3         0.11%  155         $15.3         0.05%  118         $22.6         0.06%
 Juice And
 Drinks
Mainstream      59          $7.3         0.11%  80          $23.8         0.08%  78          $31.1         0.08%
 [Pasta &
 Pizza Sauce]
Candy Bags--    60          $7.3         0.11%  31          $46.3         0.15%  34          $53.5         0.14%
 Chocolate
Strawberries    61          $7.2         0.11%  26          $50.2         0.16%  32          $57.4         0.15%
Lunchment--Bol  62          $7.2         0.11%  115         $18.6         0.06%  97          $25.8         0.07%
 ogna/Sausage
Sw Gds: Donuts  63          $7.1         0.11%  70          $27.0         0.09%  66          $34.1         0.09%
Pizza/Economy   64          $7.0         0.11%  151         $15.7         0.05%  117         $22.7         0.06%
Peanut Butter   65          $6.6         0.10%  43          $39.0         0.12%  44          $45.7         0.12%
Frzn French     66          $6.5         0.10%  159         $15.2         0.05%  125         $21.7         0.06%
 Fries
Vegetable Oil   67          $6.5         0.10%  246         $10.4         0.03%  184         $16.9         0.04%
Tuna            68          $6.5         0.10%  60          $30.7         0.10%  63          $37.2         0.10%
Chicken Wings   69          $6.4         0.10%  338          $7.6         0.02%  223         $14.1         0.04%
Butter          70          $6.3         0.09%  23          $53.3         0.17%  27          $59.5         0.16%
Frzn Meat--     71          $6.1         0.09%  177         $14.2         0.04%  142         $20.3         0.05%
 Beef
Mult Pk Bag     72          $6.1         0.09%  231         $11.1         0.04%  177         $17.1         0.04%
 Snacks
Value Forms/    73          $6.0         0.09%  197         $12.7         0.04%  158         $18.7         0.05%
 18oz And
 Larger
 [Chicken]
Frzn Breakfast  74          $6.0         0.09%  147         $15.8         0.05%  123         $21.8         0.06%
 Sandwiches
Pizza/          75          $5.9         0.09%  101         $20.2         0.06%  94          $26.1         0.07%
 Traditional
Fruit Snacks    76          $5.9         0.09%  189         $13.3         0.04%  154         $19.2         0.05%
Frzn Chicken--  77          $5.9         0.09%  479          $4.7         0.01%  289         $10.6         0.03%
 Wings
Fz Skillet      78          $5.7         0.09%  85          $23.0         0.07%  83          $28.7         0.08%
 Meals
Sandwich        79          $5.7         0.09%  93          $21.4         0.07%  86          $27.1         0.07%
 Cookies
Sour Creams     80          $5.7         0.09%  69          $28.0         0.09%  68          $33.7         0.09%
Cakes:          81          $5.7         0.09%  178         $14.1         0.04%  147         $19.8         0.05%
 Birthday/
 Celebration
 Sh
Rts Soup:       82          $5.6         0.09%  51          $34.7         0.11%  53          $40.3         0.11%
 Chunky/
 Homestyle/Et
Chicken Drums   83          $5.5         0.08%  277          $9.0         0.03%  215         $14.6         0.04%
Bagged Cheese   84          $5.4         0.08%  161         $15.0         0.05%  141         $20.5         0.05%
 Snacks
Cream Cheese    85          $5.4         0.08%  52          $33.8         0.11%  57          $39.2         0.10%
Salsa & Dips    86          $5.4         0.08%  139         $16.5         0.05%  121         $21.9         0.06%
Flavored Milk   87          $5.4         0.08%  116         $18.5         0.06%  107         $23.9         0.06%
Ramen Noodles/  88          $5.3         0.08%  312          $8.1         0.03%  233         $13.5         0.04%
 Ramen Cups
Cheese          89          $5.3         0.08%  74          $25.8         0.08%  79          $31.0         0.08%
 Crackers
Hamburger Buns  90          $5.3         0.08%  92          $21.5         0.07%  90          $26.8         0.07%
Meat: Turkey    91          $5.3         0.08%  38          $40.9         0.13%  43          $46.1         0.12%
 Bulk
Waffles/        92          $5.2         0.08%  99          $20.7         0.07%  96          $25.9         0.07%
 Pancakes/
 French Toast
Candy Bars      93          $5.2         0.08%  90          $21.7         0.07%  89          $26.9         0.07%
 (Multi Pack)
Candy Bars      94          $5.1         0.08%  140         $16.5         0.05%  127         $21.6         0.06%
 (Singles)
 (Including)
Bkfst Sausage-- 95          $5.1         0.08%  105         $19.4         0.06%  103         $24.5         0.06%
 Fresh Rolls
Angus [Beef]    96          $5.0         0.08%  65          $28.7         0.09%  67          $33.7         0.09%
Hot Dog Buns    97          $5.0         0.08%  119         $18.1         0.06%  112         $23.1         0.06%
Cottage Cheese  98          $5.0         0.08%  55          $33.0         0.10%  60          $38.0         0.10%
String Cheese   99          $4.9         0.07%  68          $28.1         0.09%  71          $33.0         0.09%
Sandwiches--(C  100         $4.9         0.07%  145         $16.0         0.05%  135       $20.9 0          .05%
 old)
                      -------------------------       ----------------------------------------------------------
  Top 100               $1,084.4        16.48%           $3,993.9        12.67%           $5,078.3        13.33%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


     Exhibit E-11: Top 100 Subcommodities for SNAP Households by Expenditure: Smaller Micropolitan Counties
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Soft Drinks 12/ 1          $20.5         0.31%  2           $61.5         0.20%  2           $82.0         0.22%
 18 & 15pk Can
 Car
Fluid Milk/     2          $20.2         0.31%  1           $82.6         0.26%  1          $102.9         0.27%
 White Only
Lean [Beef]     3          $12.0         0.18%  4           $27.1         0.09%  4           $39.0         0.10%
Primal [Beef]   4           $7.5         0.11%  5           $27.0         0.09%  5           $34.5         0.09%
Shredded        5           $7.2         0.11%  3           $31.9         0.10%  3           $39.1         0.10%
 Cheese
Kids Cereal     6           $6.8         0.10%  23          $16.0         0.05%  17          $22.8         0.06%
Sft Drnk 2      7           $6.4         0.10%  15          $19.6         0.06%  12          $26.0         0.07%
 Liter Btl
 Carb Incl
Soft Drinks     8           $6.3         0.10%  33          $13.7         0.04%  24          $20.0         0.05%
 20pk & 24pk
 Can Carb
Potato Chips    9           $6.3         0.10%  6           $24.3         0.08%  6           $30.5         0.08%
Mainstream      10          $5.6         0.08%  27          $15.7         0.05%  20          $21.3         0.06%
 White Bread
Lunchment--Del  11          $5.4         0.08%  10          $21.7         0.07%  8           $27.2         0.07%
 i Fresh
Enhanced [Pork  12          $5.4         0.08%  11          $21.1         0.07%  11          $26.5         0.07%
 Boneless Loin/
 Rib]
Unflavored Can  13          $5.1         0.08%  9           $21.8         0.07%  10          $26.9         0.07%
 Coffee
Infant Formula  14          $5.0         0.08%  190          $4.0         0.01%  78           $9.0         0.02%
 Starter/
 Solutio
Chicken Breast  15          $4.8         0.07%  7           $23.8         0.08%  7           $28.7         0.08%
 Boneless
Snack Cake--    16          $4.8         0.07%  41          $11.9         0.04%  36          $16.6         0.04%
 Multi Pack
Eggs--Large     17          $4.7         0.07%  8           $22.4         0.07%  9           $27.1         0.07%
Still Water     18          $4.7         0.07%  21          $16.4         0.05%  21          $21.0         0.06%
 Drnking/Mnrl
 Water
Tortilla/Nacho  19          $4.6         0.07%  19          $18.4         0.06%  16          $23.0         0.06%
 Chips
American        20          $4.5         0.07%  31          $14.0         0.04%  28          $18.5         0.05%
 Single Cheese
Sft Drnk Mlt-   21          $4.5         0.07%  14          $20.1         0.06%  13          $24.5         0.06%
 Pk Btl Carb
 (Excp)
Snacks/         22          $4.4         0.07%  65           $8.6         0.03%  47          $13.0         0.03%
 Appetizers
Potatoes        23          $4.0         0.06%  20          $16.9         0.05%  22          $20.9         0.05%
 Russet (Bulk
 & Bag)
Pizza/Premium   24          $4.0         0.06%  35          $13.0         0.04%  34          $17.0         0.04%
Fz Ss Economy   25          $3.9         0.06%  71           $7.8         0.02%  56          $11.7         0.03%
 Meals All
Sandwiches &    26          $3.8         0.06%  85           $6.8         0.02%  65          $10.7         0.03%
 Handhelds
Bacon--Trad     27          $3.8         0.06%  24          $15.9         0.05%  25          $19.7         0.05%
 16oz Or Less
Sugar           28          $3.8         0.06%  39          $12.0         0.04%  37          $15.8         0.04%
Fz Ss Prem      29          $3.7         0.06%  32          $13.7         0.04%  31          $17.4         0.05%
 Traditional
 Meals
Natural Cheese  30          $3.6         0.06%  12          $20.8         0.07%  14          $24.5         0.06%
 Chunks
Ribs [Pork]     31          $3.6         0.06%  45          $11.3         0.04%  41          $14.9         0.04%
Convenient      32          $3.5         0.05%  95           $6.3         0.02%  74           $9.8         0.03%
 Meals--Kids
 Meal C
All Family      33          $3.5         0.05%  17          $18.8         0.06%  19          $22.3         0.06%
 Cereal
Condensed Soup  34          $3.3         0.05%  22          $16.1         0.05%  26          $19.4         0.05%
Dairy Case      35          $3.2         0.05%  13          $20.7         0.07%  15          $23.9         0.06%
 100% Pure
 Juice--O
Select Beef     36          $3.2         0.05%  34          $13.6         0.04%  35          $16.8         0.04%
Sft Drnk Sngl   37          $3.2         0.05%  86           $6.7         0.02%  73           $9.8         0.03%
 Srv Btl Carb
 (Ex)
Mainstream      38          $3.1         0.05%  28          $15.7         0.05%  27          $18.8         0.05%
 Variety
 Breads
Bananas         39          $3.0         0.05%  16          $19.6         0.06%  18          $22.6         0.06%
Isotonic        40          $2.9         0.04%  53          $10.0         0.03%  50          $12.9         0.03%
 Drinks Single
 Serve
Hot Dogs--Base  41          $2.8         0.04%  78           $7.2         0.02%  68          $10.1         0.03%
 Meat
Frzn Chicken--  42          $2.8         0.04%  50          $10.5         0.03%  46          $13.3         0.04%
 Wht Meat
Pourable Salad  43          $2.8         0.04%  37          $12.4         0.04%  38          $15.2         0.04%
 Dressings
Mayonnaise &    44          $2.7         0.04%  42          $11.8         0.04%  42          $14.5         0.04%
 Whipped
 Dressing
Macaroni &      45          $2.7         0.04%  107          $5.8         0.02%  88           $8.4         0.02%
 Cheese Dnrs
Can Pasta       46          $2.7         0.04%  129          $5.1         0.02%  94           $7.8         0.02%
Fz Family       47          $2.7         0.04%  77           $7.2         0.02%  71           $9.9         0.03%
 Style Entrees
Traditional     48          $2.6         0.04%  38          $12.3         0.04%  40          $14.9         0.04%
 [Ice Cream &
 Sherbert]
Lunchment--Bol  49          $2.5         0.04%  80           $7.2         0.02%  75           $9.7         0.03%
 ogna/Sausage
Margarine:      50          $2.5         0.04%  57           $9.8         0.03%  51          $12.2         0.03%
 Tubs And
 Bowls
Sw Gds: Donuts  51          $2.4         0.04%  59           $9.4         0.03%  55          $11.8         0.03%
Premium [Ice    52          $2.4         0.04%  25          $15.8         0.05%  29          $18.2         0.05%
 Cream &
 Sherbert]
Angus [Beef]    53          $2.4         0.04%  40          $12.0         0.04%  43          $14.3         0.04%
Choice Beef     54          $2.3         0.03%  72           $7.6         0.02%  72           $9.9         0.03%
Fz Bag          55          $2.3         0.03%  43          $11.8         0.04%  44          $14.0         0.04%
 Vegetables--P
 lain
Refrigerated    56          $2.3         0.03%  46          $10.7         0.03%  48          $13.0         0.03%
 Coffee
 Creamers
Pizza/Economy   57          $2.3         0.03%  124          $5.2         0.02%  97           $7.5         0.02%
Choice Beef     58          $2.3         0.03%  48          $10.6         0.03%  49          $12.9         0.03%
Candy Bags--    59          $2.3         0.03%  36          $12.9         0.04%  39          $15.1         0.04%
 Chocolate
Adult Cereal    60          $2.2         0.03%  30          $15.0         0.05%  33          $17.1         0.05%
Strawberries    61          $2.2         0.03%  29          $15.0         0.05%  32          $17.1         0.05%
Peanut Butter   62          $2.2         0.03%  44          $11.6         0.04%  45          $13.7         0.04%
Mexican Soft    63          $2.1         0.03%  64           $8.9         0.03%  59          $11.0         0.03%
 Tortillas And
 Wra
Mainstream      64          $2.1         0.03%  81           $7.1         0.02%  77           $9.2         0.02%
 [Pasta &
 Pizza Sauce]
Fz Ss Prem      65          $2.1         0.03%  18          $18.6         0.06%  23          $20.7         0.05%
 Nutritional
 Meals
Aseptic Pack    66          $2.0         0.03%  163          $4.5         0.01%  121          $6.5         0.02%
 Juice And
 Drinks
Frzn French     67          $2.0         0.03%  128          $5.1         0.02%  108          $7.2         0.02%
 Fries
Flavored Milk   68          $2.0         0.03%  96           $6.2         0.02%  91           $8.2         0.02%
Pizza/          69          $2.0         0.03%  89           $6.6         0.02%  86           $8.6         0.02%
 Traditional
Tuna            70          $2.0         0.03%  62           $8.9         0.03%  64          $10.9         0.03%
Frzn Breakfast  71          $1.9         0.03%  132          $5.1         0.02%  112          $7.0         0.02%
 Sandwiches
Hamburger Buns  72          $1.9         0.03%  68           $8.1         0.03%  69          $10.1         0.03%
Value Forms/    73          $1.9         0.03%  187          $4.0         0.01%  146          $5.9         0.02%
 18oz And
 Larger
 [Chicken]
Vegetable Oil   74          $1.8         0.03%  214          $3.5         0.01%  168          $5.3         0.01%
Pails [Ice      75          $1.8         0.03%  131          $5.1         0.02%  114          $6.9         0.02%
 Cream &
 Sherbert]
Butter          76          $1.8         0.03%  26          $15.8         0.05%  30          $17.6         0.05%
Candy Bars      77          $1.7         0.03%  83           $6.9         0.02%  83           $8.7         0.02%
 (Multi Pack)
Cakes:          78          $1.7         0.03%  154          $4.7         0.01%  126          $6.4         0.02%
 Birthday/
 Celebration
 Sh
Fruit Snacks    79          $1.7         0.03%  198          $3.9         0.01%  159          $5.6         0.01%
Cottage Cheese  80          $1.7         0.03%  52          $10.2         0.03%  54          $11.9         0.03%
Sandwich        81          $1.7         0.03%  91           $6.5         0.02%  90           $8.2         0.02%
 Cookies
Salsa & Dips    82          $1.7         0.03%  133          $5.0         0.02%  116          $6.7         0.02%
Frzn Meat--     83          $1.7         0.03%  174          $4.3         0.01%  144          $6.0         0.02%
 Beef
Mult Pk Bag     84          $1.7         0.03%  230          $3.2         0.01%  186          $4.9         0.01%
 Snacks
Bkfst Sausage-- 85          $1.7         0.03%  76           $7.3         0.02%  80           $8.9         0.02%
 Fresh Rolls
Refrigerated    86          $1.6         0.03%  116          $5.4         0.02%  111          $7.0         0.02%
 Biscuits
Sour Creams     87          $1.6         0.02%  66           $8.3         0.03%  70          $10.0         0.03%
Rts Soup:       88          $1.6         0.02%  60           $9.4         0.03%  61          $11.0         0.03%
 Chunky/
 Homestyle/Et
Bagged Cheese   89          $1.6         0.02%  143          $4.8         0.02%  129          $6.4         0.02%
 Snacks
Cream Cheese    90          $1.6         0.02%  54          $10.0         0.03%  57          $11.6         0.03%
Skillet         91          $1.6         0.02%  245          $3.1         0.01%  198          $4.7         0.01%
 Dinners
Cheese          92          $1.6         0.02%  84           $6.8         0.02%  89           $8.4         0.02%
 Crackers
Chicken Wings   93          $1.5         0.02%  374          $2.0         0.01%  258          $3.5         0.01%
Angus [Beef]    94          $1.5         0.02%  148          $4.8         0.02%  133          $6.3         0.02%
String Cheese   95          $1.5         0.02%  75           $7.3         0.02%  81           $8.9         0.02%
Fz Skillet      96          $1.5         0.02%  99           $6.0         0.02%  98           $7.5         0.02%
 Meals
Hot Dog Buns    97          $1.5         0.02%  110          $5.7         0.02%  104          $7.2         0.02%
Sweet Goods--   98          $1.5         0.02%  135          $5.0         0.02%  123          $6.5         0.02%
 Full Size
Candy Bars      99          $1.5         0.02%  153          $4.7         0.01%  135          $6.2         0.02%
 (Singles)
 (Including)
Toaster         100         $1.5         0.02%  155          $4.7         0.01%  136          $6.2         0.02%
 Pastries
                      -------------------------       ----------------------------------------------------------
  Top 100                 $339.6        $5.16%           $1,243.8        $3.95%           $1,583.4        $4.16%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5         $100%          $31,513.8         $100%          $38,094.2         $100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


       Exhibit E-12: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in Noncore Counties
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Soft Drinks 12/ 1           $6.7         0.10%  2           $16.3         0.05%  2           $23.1         0.06%
 18 & 15pk Can
 Car
Fluid Milk/     2           $6.4         0.10%  1           $23.0         0.07%  1           $29.4         0.08%
 White Only
Lean [Beef]     3           $3.2         0.05%  4            $7.6         0.02%  3           $10.8         0.03%
Primal [Beef]   4           $2.1         0.03%  5            $6.8         0.02%  5            $8.9         0.02%
Shredded        5           $2.0         0.03%  3            $8.4         0.03%  4           $10.3         0.03%
 Cheese
Soft Drinks     6           $2.0         0.03%  34           $3.5         0.01%  24           $5.5         0.01%
 20pk & 24pk
 Can Carb
Mainstream      7           $1.9         0.03%  20           $4.8         0.02%  14           $6.7         0.02%
 White Bread
Potato Chips    8           $1.9         0.03%  6            $6.7         0.02%  6            $8.6         0.02%
Kids Cereal     9           $1.8         0.03%  27           $4.0         0.01%  22           $5.8         0.02%
Sft Drnk 2      10          $1.7         0.03%  21           $4.7         0.01%  16           $6.4         0.02%
 Liter Btl
 Carb Incl
Unflavored Can  11          $1.7         0.03%  9            $6.1         0.02%  8            $7.8         0.02%
 Coffee
Sft Drnk Mlt-   12          $1.6         0.02%  11           $5.8         0.02%  10           $7.5         0.02%
 Pk Btl Carb
 (Excp)
Lunchment--Del  13          $1.6         0.02%  12           $5.8         0.02%  11           $7.4         0.02%
 i Fresh
Snack Cake--    14          $1.6         0.02%  36           $3.5         0.01%  27           $5.0         0.01%
 Multi Pack
Enhanced [Pork  15          $1.5         0.02%  14           $5.5         0.02%  13           $7.1         0.02%
 Boneless Loin/
 Rib]
Eggs--Large     16          $1.4         0.02%  7            $6.6         0.02%  7            $8.0         0.02%
Infant Formula  17          $1.4         0.02%  186          $1.1         0.00%  81           $2.5         0.01%
 Starter/
 Solutio
American        18          $1.4         0.02%  29           $4.0         0.01%  25           $5.4         0.01%
 Single Cheese
Chicken Breast  19          $1.3         0.02%  10           $6.1         0.02%  12           $7.4         0.02%
 Boneless
Tortilla/Nacho  20          $1.3         0.02%  16           $5.1         0.02%  18           $6.4         0.02%
 Chips
Potatoes        21          $1.3         0.02%  17           $5.0         0.02%  19           $6.2         0.02%
 Russet (Bulk
 & Bag)
Still Water     22          $1.3         0.02%  23           $4.5         0.01%  23           $5.7         0.02%
 Drnking/Mnrl
 Water
Snacks/         23          $1.2         0.02%  67           $2.3         0.01%  49           $3.5         0.01%
 Appetizers
Pizza/Premium   24          $1.2         0.02%  32           $3.7         0.01%  30           $4.9         0.01%
Bacon--Trad     25          $1.2         0.02%  19           $4.8         0.02%  20           $6.0         0.02%
 16oz Or Less
Natural Cheese  26          $1.1         0.02%  8            $6.5         0.02%  9            $7.7         0.02%
 Chunks
Sugar           27          $1.1         0.02%  35           $3.5         0.01%  34           $4.6         0.01%
Sandwiches &    28          $1.0         0.02%  96           $1.7         0.01%  71           $2.8         0.01%
 Handhelds
All Family      29          $1.0         0.02%  18           $4.9         0.02%  21           $5.9         0.02%
 Cereal
Fz Ss Economy   30          $1.0         0.02%  80           $2.0         0.01%  65           $3.0         0.01%
 Meals All
Fz Ss Prem      31          $1.0         0.01%  38           $3.4         0.01%  36           $4.4         0.01%
 Traditional
 Meals
Convenient      32          $1.0         0.01%  111          $1.6         0.00%  79           $2.5         0.01%
 Meals--Kids
 Meal C
Sft Drnk Sngl   33          $0.9         0.01%  77           $2.0         0.01%  67           $2.9         0.01%
 Srv Btl Carb
 (Ex)
Condensed Soup  34          $0.9         0.01%  28           $4.0         0.01%  29           $5.0         0.01%
Bananas         35          $0.9         0.01%  15           $5.5         0.02%  17           $6.4         0.02%
Dairy Case      36          $0.9         0.01%  13           $5.7         0.02%  15           $6.6         0.02%
 100% Pure
 Juice--O
Mainstream      37          $0.9         0.01%  24           $4.2         0.01%  26           $5.1         0.01%
 Variety
 Breads
Choice Beef     38          $0.9         0.01%  59           $2.7         0.01%  48           $3.5         0.01%
Hot Dogs--Base  39          $0.8         0.01%  74           $2.1         0.01%  66           $2.9         0.01%
 Meat
Ribs [Pork]     40          $0.8         0.01%  48           $2.9         0.01%  43           $3.7         0.01%
Lunchment--Bol  41          $0.8         0.01%  71           $2.2         0.01%  62           $3.0         0.01%
 ogna/Sausage
Mayonnaise &    42          $0.8         0.01%  41           $3.3         0.01%  40           $4.1         0.01%
 Whipped
 Dressing
Sw Gds: Donuts  43          $0.8         0.01%  49           $2.9         0.01%  45           $3.7         0.01%
Traditional     44          $0.8         0.01%  39           $3.4         0.01%  38           $4.2         0.01%
 [Ice Cream &
 Sherbert]
Pourable Salad  45          $0.8         0.01%  40           $3.4         0.01%  39           $4.1         0.01%
 Dressings
Frzn Chicken--  46          $0.7         0.01%  60           $2.5         0.01%  56           $3.3         0.01%
 Wht Meat
Margarine:      47          $0.7         0.01%  58           $2.7         0.01%  51           $3.4         0.01%
 Tubs And
 Bowls
Can Pasta       48          $0.7         0.01%  159          $1.3         0.00%  108          $2.0         0.01%
Candy Bags--    49          $0.7         0.01%  33           $3.6         0.01%  37           $4.3         0.01%
 Chocolate
Macaroni &      50          $0.7         0.01%  121          $1.5         0.00%  93           $2.2         0.01%
 Cheese Dnrs
Isotonic        51          $0.7         0.01%  66           $2.3         0.01%  64           $3.0         0.01%
 Drinks Single
 Serve
Fz Family       52          $0.7         0.01%  89           $1.8         0.01%  77           $2.5         0.01%
 Style Entrees
Peanut Butter   53          $0.7         0.01%  44           $3.1         0.01%  42           $3.8         0.01%
Strawberries    54          $0.7         0.01%  25           $4.2         0.01%  31           $4.8         0.01%
Adult Cereal    55          $0.6         0.01%  31           $4.0         0.01%  33           $4.6         0.01%
Hamburger Buns  56          $0.6         0.01%  64           $2.4         0.01%  63           $3.0         0.01%
Pizza/          57          $0.6         0.01%  79           $2.0         0.01%  76           $2.6         0.01%
 Traditional
Choice Beef     58          $0.6         0.01%  42           $3.2         0.01%  41           $3.9         0.01%
Premium [Ice    59          $0.6         0.01%  26           $4.1         0.01%  32           $4.7         0.01%
 Cream &
 Sherbert]
Flavored Milk   60          $0.6         0.01%  107          $1.6         0.01%  91           $2.2         0.01%
Refrigerated    61          $0.6         0.01%  56           $2.8         0.01%  53           $3.4         0.01%
 Coffee
 Creamers
Angus [Beef]    62          $0.6         0.01%  57           $2.7         0.01%  54           $3.3         0.01%
Pails [Ice      63          $0.6         0.01%  110          $1.6         0.00%  95           $2.2         0.01%
 Cream &
 Sherbert]
Mexican Soft    64          $0.6         0.01%  52           $2.8         0.01%  52           $3.4         0.01%
 Tortillas And
 Wra
Pizza/Economy   65          $0.6         0.01%  162          $1.3         0.00%  117          $1.9         0.00%
Cottage Cheese  66          $0.6         0.01%  45           $3.1         0.01%  46           $3.6         0.01%
Mainstream      67          $0.6         0.01%  84           $1.9         0.01%  83           $2.4         0.01%
 [Pasta &
 Pizza Sauce]
Frzn French     68          $0.6         0.01%  123          $1.5         0.00%  107          $2.0         0.01%
 Fries
Fz Bag          69          $0.5         0.01%  46           $3.0         0.01%  47           $3.5         0.01%
 Vegetables--P
 lain
Candy Bars      70          $0.5         0.01%  78           $2.0         0.01%  78           $2.5         0.01%
 (Multi Pack)
Cakes:          71          $0.5         0.01%  149          $1.3         0.00%  116          $1.9         0.00%
 Birthday/
 Celebration
 Sh
Aseptic Pack    72          $0.5         0.01%  183          $1.1         0.00%  146          $1.6         0.00%
 Juice And
 Drinks
Refrigerated    73          $0.5         0.01%  104          $1.6         0.01%  99           $2.1         0.01%
 Biscuits
Salsa & Dips    74          $0.5         0.01%  130          $1.4         0.00%  111          $1.9         0.01%
Value Forms/    75          $0.5         0.01%  192          $1.1         0.00%  158          $1.6         0.00%
 18oz And
 Larger
 [Chicken]
Fz Ss Prem      76          $0.5         0.01%  30           $4.0         0.01%  35           $4.5         0.01%
 Nutritional
 Meals
Tuna            77          $0.5         0.01%  70           $2.2         0.01%  72           $2.8         0.01%
Sandwich        78          $0.5         0.01%  83           $1.9         0.01%  85           $2.4         0.01%
 Cookies
Bkfst Sausage-- 79          $0.5         0.01%  73           $2.1         0.01%  75           $2.6         0.01%
 Fresh Rolls
Butter          80          $0.5         0.01%  22           $4.5         0.01%  28           $5.0         0.01%
Frzn Breakfast  81          $0.5         0.01%  172          $1.2         0.00%  139          $1.7         0.00%
 Sandwiches
Vegetable Oil   82          $0.5         0.01%  203          $1.0         0.00%  166          $1.5         0.00%
Sweet Goods--   83          $0.5         0.01%  129          $1.4         0.00%  114          $1.9         0.00%
 Full Size
Hot Dog Buns    84          $0.5         0.01%  98           $1.7         0.01%  94           $2.2         0.01%
Candy Bars      85          $0.5         0.01%  119          $1.5         0.00%  110          $2.0         0.01%
 (Singles)
 (Including)
Bagged Cheese   86          $0.5         0.01%  147          $1.3         0.00%  127          $1.8         0.00%
 Snacks
Sandwiches--(C  87          $0.5         0.01%  102          $1.6         0.01%  103          $2.1         0.01%
 old)
Cream Cheese    88          $0.5         0.01%  54           $2.8         0.01%  57           $3.3         0.01%
Sour Creams     89          $0.5         0.01%  69           $2.3         0.01%  73           $2.7         0.01%
Select Beef     90          $0.5         0.01%  75           $2.0         0.01%  80           $2.5         0.01%
Frzn Meat--     91          $0.5         0.01%  166          $1.2         0.00%  136          $1.7         0.00%
 Beef
Sticks/Enrobed  92          $0.5         0.01%  124          $1.5         0.00%  113          $1.9         0.01%
 [Frozen
 Novelties]
String Cheese   93          $0.4         0.01%  76           $2.0         0.01%  82           $2.5         0.01%
Fruit Snacks    94          $0.4         0.01%  222          $0.9         0.00%  185          $1.4         0.00%
Rts Soup:       95          $0.4         0.01%  63           $2.4         0.01%  68           $2.8         0.01%
 Chunky/
 Homestyle/Et
Angus [Beef]    96          $0.4         0.01%  177          $1.1         0.00%  156          $1.6         0.00%
Cheese          97          $0.4         0.01%  93           $1.8         0.01%  92           $2.2         0.01%
 Crackers
Meat: Ham Bulk  98          $0.4         0.01%  62           $2.4         0.01%  69           $2.8         0.01%
Meat: Turkey    99          $0.4         0.01%  51           $2.8         0.01%  58           $3.3         0.01%
 Bulk
Tray Pack/Choc  100         $0.4         0.01%  133          $1.4         0.00%  119          $1.8         0.00%
 Chip Cookies
                      -------------------------       ----------------------------------------------------------
  Top 100                  $99.1         1.57%             $341.8         1.08%             $440.9         1.23%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


  Exhibit E-13: Top 100 Subcommodities for SNAP Households by Expenditure: Stores with more than $12 Million in
                                                      Sales
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $38.9         0.59%  1          $229.9         0.73%  1          $268.8         0.71%
 White Only
Soft Drinks 12/ 2          $32.4         0.49%  2          $162.4         0.52%  2          $194.8         0.51%
 18 & 15pk Can
 Car
Lean [Beef]     3          $22.2         0.34%  8           $74.1         0.24%  5           $96.4         0.25%
Shredded        4          $16.2         0.25%  3          $103.2         0.33%  3          $119.4         0.31%
 Cheese
Kids Cereal     5          $15.5         0.23%  23          $52.1         0.17%  17          $67.5         0.18%
Sft Drnk 2      6          $13.3         0.20%  18          $56.1         0.18%  16          $69.4         0.18%
 Liter Btl
 Carb Incl
Potato Chips    7          $13.0         0.20%  10          $70.8         0.22%  9           $83.8         0.22%
Lunchment--Del  8          $11.6         0.18%  13          $69.9         0.22%  11          $81.5         0.21%
 i Fresh
Chicken Breast  9          $11.4         0.17%  4           $89.3         0.28%  4          $100.7         0.26%
 Boneless
Infant Formula  10         $11.1         0.17%  259         $10.4         0.03%  119         $21.5         0.06%
 Starter/
 Solutio
Eggs--Large     11         $10.8         0.16%  9           $73.1         0.23%  8           $83.9         0.22%
Primal [Beef]   12         $10.8         0.16%  24          $49.1         0.16%  23          $59.9         0.16%
Snacks/         13         $10.4         0.16%  63          $31.6         0.10%  47          $42.1         0.11%
 Appetizers
Tortilla/Nacho  14          $9.9         0.15%  15          $62.4         0.20%  15          $72.3         0.19%
 Chips
Dairy Case      15          $9.4         0.14%  6           $80.1         0.25%  6           $89.5         0.23%
 100% Pure
 Juice--O
Fz Ss Prem      16          $9.1         0.14%  26          $47.5         0.15%  25          $56.6         0.15%
 Traditional
 Meals
Unflavored Can  17          $9.1         0.14%  21          $54.4         0.17%  19          $63.4         0.17%
 Coffee
Natural Cheese  18          $9.0         0.14%  12          $70.0         0.22%  12          $79.1         0.21%
 Chunks
Still Water     19          $8.8         0.13%  30          $46.5         0.15%  28          $55.3         0.15%
 Drnking/Mnrl
 Water
Mainstream      20          $8.6         0.13%  56          $33.6         0.11%  46          $42.3         0.11%
 White Bread
Enhanced [Pork  21          $8.6         0.13%  28          $47.3         0.15%  26          $55.9         0.15%
 Boneless Loin/
 Rib]
Bacon--Trad     22          $8.4         0.13%  34          $44.1         0.14%  29          $52.6         0.14%
 16oz Or Less
All Family      23          $8.4         0.13%  14          $66.3         0.21%  14          $74.7         0.20%
 Cereal
Pizza/Premium   24          $8.4         0.13%  29          $47.0         0.15%  27          $55.4         0.15%
American        25          $8.3         0.13%  51          $35.4         0.11%  44          $43.7         0.11%
 Single Cheese
Fz Ss Economy   26          $8.1         0.12%  105         $21.1         0.07%  81          $29.2         0.08%
 Meals All
Soft Drinks     27          $7.9         0.12%  67          $30.2         0.10%  58          $38.1         0.10%
 20pk & 24pk
 Can Carb
Bananas         28          $7.8         0.12%  7           $74.4         0.24%  10          $82.2         0.22%
Snack Cake--    29          $7.4         0.11%  81          $25.3         0.08%  73          $32.7         0.09%
 Multi Pack
Premium [Ice    30          $7.4         0.11%  11          $70.2         0.22%  13          $77.6         0.20%
 Cream &
 Sherbert]
Mainstream      31          $7.3         0.11%  32          $44.6         0.14%  32          $51.8         0.14%
 Variety
 Breads
Select Beef     32          $7.2         0.11%  37          $41.6         0.13%  36          $48.8         0.13%
Sandwiches &    33          $7.2         0.11%  107         $20.6         0.07%  89          $27.8         0.07%
 Handhelds
Frzn Chicken--  34          $7.2         0.11%  65          $31.2         0.10%  57          $38.4         0.10%
 Wht Meat
Potatoes        35          $7.2         0.11%  35          $42.4         0.13%  35          $49.6         0.13%
 Russet (Bulk
 & Bag)
Ribs [Pork]     36          $6.8         0.10%  69          $29.4         0.09%  65          $36.2         0.10%
Sugar           37          $6.8         0.10%  64          $31.3         0.10%  59          $38.1         0.10%
Choice Beef     38          $6.7         0.10%  40          $41.1         0.13%  38          $47.8         0.13%
Convenient      39          $6.7         0.10%  114         $19.5         0.06%  98          $26.2         0.07%
 Meals--Kids
 Meal C
Condensed Soup  40          $6.5         0.10%  33          $44.1         0.14%  34          $50.6         0.13%
Refrigerated    41          $6.4         0.10%  31          $46.0         0.15%  31          $52.3         0.14%
 Coffee
 Creamers
Isotonic        42          $6.2         0.09%  66          $30.9         0.10%  62          $37.1         0.10%
 Drinks Single
 Serve
Fz Family       43          $6.1         0.09%  85          $24.7         0.08%  77          $30.8         0.08%
 Style Entrees
Pourable Salad  44          $6.0         0.09%  38          $41.5         0.13%  39          $47.6         0.12%
 Dressings
Sft Drnk Mlt-   45          $5.9         0.09%  36          $42.2         0.13%  37          $48.1         0.13%
 Pk Btl Carb
 (Excp)
Fz Ss Prem      46          $5.9         0.09%  5           $82.0         0.26%  7           $87.9         0.23%
 Nutritional
 Meals
Sft Drnk Sngl   47          $5.8         0.09%  103         $21.3         0.07%  93          $27.1         0.07%
 Srv Btl Carb
 (Ex)
Mayonnaise &    48          $5.7         0.09%  54          $34.5         0.11%  54          $40.2         0.11%
 Whipped
 Dressing
Choice Beef     49          $5.7         0.09%  97          $22.6         0.07%  85          $28.3         0.07%
Adult Cereal    50          $5.6         0.08%  20          $55.1         0.17%  22          $60.7         0.16%
Strawberries    51          $5.4         0.08%  19          $55.9         0.18%  21          $61.3         0.16%
Meat: Turkey    52          $5.4         0.08%  17          $57.3         0.18%  20          $62.7         0.16%
 Bulk
Mexican Soft    53          $5.4         0.08%  53          $35.2         0.11%  53          $40.6         0.11%
 Tortillas And
 Wra
Butter          54          $5.4         0.08%  16          $58.3         0.19%  18          $63.7         0.17%
Fz Bag          55          $5.2         0.08%  49          $36.6         0.12%  48          $41.8         0.11%
 Vegetables--P
 lain
Candy Bags--    56          $5.0         0.08%  27          $47.4         0.15%  30          $52.4         0.14%
 Chocolate
Traditional     57          $5.0         0.08%  68          $29.4         0.09%  69          $34.4         0.09%
 [Ice Cream &
 Sherbert]
Margarine:      58          $5.0         0.08%  71          $29.2         0.09%  70          $34.2         0.09%
 Tubs And
 Bowls
Macaroni &      59          $4.9         0.07%  139         $17.4         0.06%  113         $22.3         0.06%
 Cheese Dnrs
Peanut Butter   60          $4.8         0.07%  44          $39.1         0.12%  43          $43.9         0.12%
Aseptic Pack    61          $4.7         0.07%  168         $15.3         0.05%  136         $20.0         0.05%
 Juice And
 Drinks
Tuna            62          $4.7         0.07%  60          $33.0         0.10%  61          $37.6         0.10%
Mainstream      63          $4.6         0.07%  96          $22.9         0.07%  91          $27.5         0.07%
 [Pasta &
 Pizza Sauce]
Hot Dogs--Base  64          $4.6         0.07%  188         $13.8         0.04%  159         $18.3         0.05%
 Meat
Cream Cheese    65          $4.5         0.07%  48          $37.3         0.12%  49          $41.7         0.11%
Sw Gds: Donuts  66          $4.4         0.07%  92          $23.3         0.07%  90          $27.7         0.07%
Sushi--In       67          $4.3         0.07%  42          $40.4         0.13%  40          $44.7         0.12%
 Store
 Prepared
Premium Bread   68          $4.3         0.06%  22          $53.9         0.17%  24          $58.1         0.15%
Can Pasta       69          $4.3         0.06%  216         $12.4         0.04%  179         $16.7         0.04%
Frzn Meat--     70          $4.2         0.06%  182         $14.1         0.04%  160         $18.3         0.05%
 Beef
Fz Skillet      71          $4.2         0.06%  87          $24.4         0.08%  84          $28.6         0.08%
 Meals
Meat: Ham Bulk  72          $4.1         0.06%  43          $40.2         0.13%  41          $44.3         0.12%
Angus [Beef]    73          $4.1         0.06%  62          $31.9         0.10%  66          $35.9         0.09%
Cakes:          74          $4.0         0.06%  170         $15.1         0.05%  151         $19.1         0.05%
 Birthday/
 Celebration
 Sh
Sour Creams     75          $4.0         0.06%  72          $29.2         0.09%  71          $33.2         0.09%
Cheese          76          $4.0         0.06%  73          $29.0         0.09%  72          $33.0         0.09%
 Crackers
Value Forms/    77          $4.0         0.06%  218         $12.3         0.04%  188         $16.3         0.04%
 18oz And
 Larger
 [Chicken]
Frzn French     78          $4.0         0.06%  187         $13.8         0.04%  165         $17.8         0.05%
 Fries
Rts Soup:       79          $3.9         0.06%  52          $35.2         0.11%  56          $39.2         0.10%
 Chunky/
 Homestyle/Et
String Cheese   80          $3.9         0.06%  58          $33.2         0.11%  63          $37.1         0.10%
Sandwiches--(C  81          $3.9         0.06%  98          $22.2         0.07%  99          $26.1         0.07%
 old)
Instore Cut     82          $3.9         0.06%  55          $33.8         0.11%  60          $37.6         0.10%
 Fruit
Lunchment--Bol  83          $3.9         0.06%  175         $14.6         0.05%  156         $18.5         0.05%
 ogna/Sausage
Frzn Chicken--  84          $3.8         0.06%  585          $3.9         0.01%  395          $7.7         0.02%
 Wings
Frzn Breakfast  85          $3.8         0.06%  161         $15.8         0.05%  142         $19.6         0.05%
 Sandwiches
Waffles/        86          $3.8         0.06%  91          $23.3         0.07%  92          $27.1         0.07%
 Pancakes/
 French Toast
Pizza/Economy   87          $3.8         0.06%  226         $11.9         0.04%  200         $15.6         0.04%
Spring Water    88          $3.7         0.06%  77          $27.7         0.09%  75          $31.4         0.08%
Mult Pk Bag     89          $3.7         0.06%  222         $12.0         0.04%  198         $15.7         0.04%
 Snacks
Grapes Red      90          $3.6         0.05%  46          $37.7         0.12%  51          $41.3         0.11%
Sandwich        91          $3.6         0.05%  110         $20.3         0.06%  107         $23.9         0.06%
 Cookies
Candy Bars      92          $3.6         0.05%  144         $17.1         0.05%  131         $20.6         0.05%
 (Singles)
 (Including)
Fruit Snacks    93          $3.5         0.05%  209         $12.6         0.04%  189         $16.2         0.04%
Pizza/          94          $3.5         0.05%  134         $17.9         0.06%  120         $21.4         0.06%
 Traditional
Flavored Milk   95          $3.5         0.05%  148         $16.8         0.05%  133         $20.3         0.05%
Sweet Goods--   96          $3.5         0.05%  162         $15.7         0.05%  150         $19.2         0.05%
 Full Size
Vegetable Oil   97          $3.4         0.05%  306          $8.8         0.03%  248         $12.2         0.03%
Natural Cheese  98          $3.4         0.05%  50          $36.0         0.11%  55          $39.4         0.10%
 Slices
Salsa & Dips    99          $3.4         0.05%  152         $16.5         0.05%  139         $19.9         0.05%
Avocado         100         $3.4         0.05%  47          $37.5         0.12%  52          $40.9         0.11%
                      -------------------------       ----------------------------------------------------------
  Top 100                 $699.9        10.64%           $4,012.7        12.73%           $4,712.5        12.37%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


 Exhibit E-14: Top 100 Subcommodities for SNAP Households by Expenditure: Stores with $2 to $12 Million in Sales
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1         $151.9         2.31%  1          $622.5         1.98%  1          $774.4         2.03%
 White Only
Soft Drinks 12/ 2         $131.9         2.00%  2          $437.9         1.39%  2          $569.9         1.50%
 18 & 15pk Can
 Car
Lean [Beef]     3          $90.0         1.37%  7          $183.4         0.58%  4          $273.4         0.72%
Kids Cereal     4          $62.6         0.95%  20         $134.2         0.43%  13         $196.7         0.52%
Shredded        5          $58.4         0.89%  3          $238.3         0.76%  3          $296.8         0.78%
 Cheese
Sft Drnk 2      6          $57.5         0.87%  10         $173.7         0.55%  7          $231.2         0.61%
 Liter Btl
 Carb Incl
Primal [Beef]   7          $51.5         0.78%  12         $169.9         0.54%  9          $221.4         0.58%
Potato Chips    8          $51.3         0.78%  8          $182.1         0.58%  6          $233.4         0.61%
Lunchment--Del  9          $44.1         0.67%  11         $172.4         0.55%  11         $216.5         0.57%
 i Fresh
Infant Formula  10         $43.0         0.65%  169         $34.9         0.11%  71          $77.9         0.20%
 Starter/
 Solutio
Eggs--Large     11         $41.3         0.63%  9          $178.2         0.57%  10         $219.5         0.58%
Still Water     12         $39.9         0.61%  19         $141.1         0.45%  16         $180.9         0.48%
 Drnking/Mnrl
 Water
Mainstream      13         $39.2         0.60%  32         $102.9         0.33%  27         $142.1         0.37%
 White Bread
Chicken Breast  14         $38.1         0.58%  4          $203.4         0.65%  5          $241.5         0.63%
 Boneless
Tortilla/Nacho  15         $37.4         0.57%  16         $146.3         0.46%  15         $183.7         0.48%
 Chips
American        16         $35.7         0.54%  36         $101.0         0.32%  31         $136.7         0.36%
 Single Cheese
Fz Ss Prem      17         $34.7         0.53%  23         $127.8         0.41%  21         $162.5         0.43%
 Traditional
 Meals
Snack Cake--    18         $34.1         0.52%  57          $76.2         0.24%  43         $110.4         0.29%
 Multi Pack
Dairy Case      19         $34.1         0.52%  6          $188.7         0.60%  8          $222.9         0.58%
 100% Pure
 Juice--O
Snacks/         20         $34.1         0.52%  66          $68.7         0.22%  50         $102.8         0.27%
 Appetizers
Enhanced [Pork  21         $32.9         0.50%  26         $120.4         0.38%  24         $153.2         0.40%
 Boneless Loin/
 Rib]
Fz Ss Economy   22         $32.8         0.50%  76          $59.5         0.19%  58          $92.3         0.24%
 Meals All
Bacon--Trad     23         $32.2         0.49%  28         $113.2         0.36%  26         $145.4         0.38%
 16oz Or Less
Unflavored Can  24         $32.2         0.49%  18         $143.4         0.46%  19         $175.6         0.46%
 Coffee
Soft Drinks     25         $31.7         0.48%  58          $76.0         0.24%  46         $107.7         0.28%
 20pk & 24pk
 Can Carb
Pizza/Premium   26         $31.2         0.47%  31         $106.2         0.34%  30         $137.4         0.36%
Mainstream      27         $31.1         0.47%  22         $128.4         0.41%  22         $159.5         0.42%
 Variety
 Breads
Sugar           28         $30.1         0.46%  51          $81.2         0.26%  42         $111.3         0.29%
Sandwiches &    29         $28.6         0.43%  88          $52.9         0.17%  67          $81.5         0.21%
 Handhelds
Potatoes        30         $28.5         0.43%  29         $111.8         0.35%  28         $140.3         0.37%
 Russet (Bulk
 & Bag)
Ribs [Pork]     31         $28.2         0.43%  54          $77.3         0.25%  48         $105.4         0.28%
Sft Drnk Mlt-   32         $28.0         0.43%  21         $131.2         0.42%  23         $159.2         0.42%
 Pk Btl Carb
 (Excp)
All Family      33         $27.7         0.42%  15         $148.4         0.47%  18         $176.1         0.46%
 Cereal
Convenient      34         $27.5         0.42%  95          $50.1         0.16%  72          $77.6         0.20%
 Meals--Kids
 Meal C
Bananas         35         $26.3         0.40%  13         $168.0         0.53%  14         $194.4         0.51%
Natural Cheese  36         $26.2         0.40%  17         $145.8         0.46%  20         $172.0         0.45%
 Chunks
Isotonic        37         $24.2         0.37%  45          $88.5         0.28%  41         $112.7         0.30%
 Drinks Single
 Serve
Premium [Ice    38         $23.9         0.36%  14         $155.6         0.49%  17         $179.5         0.47%
 Cream &
 Sherbert]
Condensed Soup  39         $23.2         0.35%  30         $109.2         0.35%  32         $132.4         0.35%
Pourable Salad  40         $22.9         0.35%  39          $97.8         0.31%  35         $120.7         0.32%
 Dressings
Frzn Chicken--  41         $22.8         0.35%  67          $68.4         0.22%  59          $91.2         0.24%
 Wht Meat
Sft Drnk Sngl   42         $22.0         0.33%  96          $49.9         0.16%  81          $71.9         0.19%
 Srv Btl Carb
 (Ex)
Choice Beef     43         $21.7         0.33%  40          $95.4         0.30%  37         $117.1         0.31%
Fz Family       44         $21.5         0.33%  79          $58.8         0.19%  69          $80.3         0.21%
 Style Entrees
Mayonnaise &    45         $21.5         0.33%  48          $84.4         0.27%  47         $105.9         0.28%
 Whipped
 Dressing
Select Beef     46         $20.6         0.31%  34         $102.0         0.32%  34         $122.6         0.32%
Traditional     47         $20.6         0.31%  43          $89.1         0.28%  44         $109.7         0.29%
 [Ice Cream &
 Sherbert]
Fz Bag          48         $20.5         0.31%  41          $95.2         0.30%  40         $115.7         0.30%
 Vegetables--P
 lain
Hot Dogs--Base  49         $20.5         0.31%  121         $42.9         0.14%  93          $63.3         0.17%
 Meat
Aseptic Pack    50         $19.5         0.30%  131         $41.7         0.13%  99          $61.3         0.16%
 Juice And
 Drinks
Macaroni &      51         $19.4         0.29%  127         $42.2         0.13%  97          $61.6         0.16%
 Cheese Dnrs
Adult Cereal    52         $19.3         0.29%  24         $127.3         0.40%  25         $146.7         0.38%
Chicken Wings   53         $18.9         0.29%  274         $22.1         0.07%  176         $41.0         0.11%
Fz Ss Prem      54         $18.8         0.29%  5          $189.5         0.60%  12         $208.2         0.55%
 Nutritional
 Meals
Margarine:      55         $18.4         0.28%  64          $71.5         0.23%  61          $89.9         0.24%
 Tubs And
 Bowls
Frzn Chicken--  56         $18.3         0.28%  425         $13.4         0.04%  240         $31.8         0.08%
 Wings
Mainstream      57         $18.3         0.28%  80          $58.0         0.18%  76          $76.3         0.20%
 [Pasta &
 Pizza Sauce]
Choice Beef     58         $18.3         0.28%  97          $49.7         0.16%  86          $68.0         0.18%
Mexican Soft    59         $18.3         0.28%  53          $77.8         0.25%  53          $96.1         0.25%
 Tortillas And
 Wra
Strawberries    60         $18.0         0.27%  25         $122.4         0.39%  29         $140.3         0.37%
Mult Pk Bag     61         $17.9         0.27%  194         $31.3         0.10%  143         $49.3         0.13%
 Snacks
Can Pasta       62         $17.9         0.27%  165         $35.2         0.11%  120         $53.1         0.14%
Lunchment--Bol  63         $17.9         0.27%  105         $46.2         0.15%  91          $64.1         0.17%
 ogna/Sausage
Refrigerated    64         $17.7         0.27%  35         $101.2         0.32%  36         $118.9         0.31%
 Coffee
 Creamers
Vegetable Oil   65         $17.1         0.26%  237         $26.5         0.08%  167         $43.6         0.11%
Sw Gds: Donuts  66         $16.9         0.26%  78          $58.9         0.19%  78          $75.8         0.20%
Frzn French     67         $16.5         0.25%  157         $36.4         0.12%  121         $52.9         0.14%
 Fries
Tuna            68         $16.5         0.25%  56          $76.8         0.24%  56          $93.3         0.24%
Candy Bags--    69         $16.4         0.25%  37         $100.0         0.32%  38         $116.5         0.31%
 Chocolate
Pizza/Economy   70         $16.0         0.24%  180         $33.1         0.11%  144         $49.2         0.13%
Peanut Butter   71         $15.6         0.24%  44          $88.6         0.28%  49         $104.2         0.27%
Frzn Breakfast  72         $15.3         0.23%  139         $39.9         0.13%  112         $55.2         0.14%
 Sandwiches
Frzn Meat--     73         $14.7         0.22%  190         $32.1         0.10%  154         $46.8         0.12%
 Beef
Value Forms/    74         $14.7         0.22%  201         $30.2         0.10%  160         $44.9         0.12%
 18oz And
 Larger
 [Chicken]
Cakes:          75         $14.6         0.22%  167         $35.1         0.11%  139         $49.8         0.13%
 Birthday/
 Celebration
 Sh
Fz Skillet      76         $14.5         0.22%  82          $54.9         0.17%  85          $69.4         0.18%
 Meals
Sandwich        77         $14.4         0.22%  92          $51.4         0.16%  88          $65.8         0.17%
 Cookies
Chicken Drums   78         $14.3         0.22%  251         $23.7         0.08%  197         $38.1         0.10%
Pizza/          79         $14.3         0.22%  106         $46.1         0.15%  101         $60.4         0.16%
 Traditional
Butter          80         $14.2         0.22%  27         $117.1         0.37%  33         $131.3         0.34%
Fruit Snacks    81         $14.1         0.21%  200         $30.5         0.10%  163         $44.6         0.12%
Meat: Turkey    82         $13.9         0.21%  33         $102.3         0.32%  39         $116.1         0.30%
 Bulk
Bagged Cheese   83         $13.8         0.21%  146         $38.3         0.12%  125         $52.1         0.14%
 Snacks
Salsa & Dips    84         $13.7         0.21%  136         $40.4         0.13%  118         $54.0         0.14%
Ramen Noodles/  85         $13.7         0.21%  293         $20.5         0.07%  225         $34.2         0.09%
 Ramen Cups
Rts Soup:       86         $13.7         0.21%  47          $84.6         0.27%  52          $98.2         0.26%
 Chunky/
 Homestyle/Et
Waffles/        87         $13.5         0.21%  85          $54.0         0.17%  87          $67.5         0.18%
 Pancakes/
 French Toast
Sour Creams     88         $13.5         0.20%  69          $65.9         0.21%  70          $79.4         0.21%
Dnr Sausage--   89         $13.3         0.20%  233         $26.7         0.08%  184         $40.0         0.11%
 Links Pork
 Ckd/S
Angus [Beef]    90         $13.1         0.20%  63          $71.9         0.23%  66          $84.9         0.22%
Hot Dog Buns    91         $13.0         0.20%  111         $45.1         0.14%  105         $58.1         0.15%
Sandwiches--(C  92         $13.0         0.20%  108         $45.4         0.14%  104         $58.4         0.15%
 old)
Dairy Case      93         $12.9         0.20%  170         $34.8         0.11%  151         $47.6         0.13%
 Juice Drnk
 Under 10
Hamburger Buns  94         $12.8         0.20%  94          $50.1         0.16%  94          $63.0         0.17%
Candy Bars      95         $12.8         0.19%  149         $37.8         0.12%  132         $50.6         0.13%
 (Singles)
 (Including)
Cream Cheese    96         $12.8         0.19%  52          $78.1         0.25%  60          $90.9         0.24%
Candy Bars      97         $12.5         0.19%  93          $50.4         0.16%  95          $62.9         0.17%
 (Multi Pack)
Cheese          98         $12.5         0.19%  74          $61.2         0.19%  79          $73.7         0.19%
 Crackers
Spring Water    99         $12.5         0.19%  68          $67.9         0.22%  68          $80.3         0.21%
Flavored Milk   100        $12.4         0.19%  124         $42.5         0.13%  114         $54.9         0.14%
                      -------------------------       ----------------------------------------------------------
  Top 100               $2,658.3        40.40%           $9,463.7        30.03%          $12,122.1        31.82%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


  Exhibit E-15: Top 100 Subcommodities for SNAP Households by Expenditure: Stores with less than $2 Million in
                                                      Sales
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1           $0.4         0.01%  1            $1.4         0.00%  1            $1.8         0.00%
 White Only
Soft Drinks 12/ 2           $0.3         0.01%  2            $0.8         0.00%  2            $1.2         0.00%
 18 & 15pk Can
 Car
Primal [Beef]   3           $0.2         0.00%  3            $0.7         0.00%  3            $0.9         0.00%
Lean [Beef]     4           $0.2         0.00%  6            $0.4         0.00%  5            $0.5         0.00%
Sft Drnk 2      5           $0.1         0.00%  7            $0.3         0.00%  7            $0.5         0.00%
 Liter Btl
 Carb Incl
Mainstream      6           $0.1         0.00%  11           $0.3         0.00%  9            $0.4         0.00%
 White Bread
Soft Drinks     7           $0.1         0.00%  19           $0.2         0.00%  13           $0.3         0.00%
 20pk & 24pk
 Can Carb
Potato Chips    8           $0.1         0.00%  5            $0.4         0.00%  6            $0.5         0.00%
Shredded        9           $0.1         0.00%  4            $0.4         0.00%  4            $0.5         0.00%
 Cheese
Kids Cereal     10          $0.1         0.00%  28           $0.2         0.00%  20           $0.3         0.00%
Lunchment--Del  11          $0.1         0.00%  8            $0.3         0.00%  8            $0.4         0.00%
 i Fresh
Snack Cake--    12          $0.1         0.00%  31           $0.2         0.00%  26           $0.3         0.00%
 Multi Pack
American        13          $0.1         0.00%  16           $0.2         0.00%  14           $0.3         0.00%
 Single Cheese
Enhanced [Pork  14          $0.1         0.00%  10           $0.3         0.00%  11           $0.3         0.00%
 Boneless Loin/
 Rib]
Tortilla/Nacho  15          $0.1         0.00%  12           $0.3         0.00%  12           $0.3         0.00%
 Chips
Unflavored Can  16          $0.1         0.00%  15           $0.2         0.00%  16           $0.3         0.00%
 Coffee
Eggs--Large     17          $0.1         0.00%  9            $0.3         0.00%  10           $0.3         0.00%
Potatoes        18          $0.1         0.00%  18           $0.2         0.00%  17           $0.3         0.00%
 Russet (Bulk
 & Bag)
Still Water     19          $0.1         0.00%  20           $0.2         0.00%  19           $0.3         0.00%
 Drnking/Mnrl
 Water
Fz Ss Economy   20          $0.1         0.00%  57           $0.1         0.00%  45           $0.2         0.00%
 Meals All
Sugar           21          $0.1         0.00%  32           $0.2         0.00%  31           $0.2         0.00%
Bacon--Trad     22          $0.1         0.00%  21           $0.2         0.00%  21           $0.3         0.00%
 16oz Or Less
Convenient      23          $0.1         0.00%  66           $0.1         0.00%  52           $0.2         0.00%
 Meals--Kids
 Meal C
Mainstream      24          $0.1         0.00%  13           $0.3         0.00%  15           $0.3         0.00%
 Variety
 Breads
Infant Formula  25          $0.1         0.00%  143          $0.1         0.00%  78           $0.1         0.00%
 Starter/
 Solutio
Sft Drnk Sngl   26          $0.1         0.00%  51           $0.1         0.00%  44           $0.2         0.00%
 Srv Btl Carb
 (Ex)
Sft Drnk Mlt-   27          $0.1         0.00%  27           $0.2         0.00%  27           $0.3         0.00%
 Pk Btl Carb
 (Excp)
Chicken Breast  28          $0.1         0.00%  14           $0.2         0.00%  18           $0.3         0.00%
 Boneless
Hot Dogs--Base  29          $0.0         0.00%  46           $0.1         0.00%  36           $0.2         0.00%
 Meat
Snacks/         30          $0.0         0.00%  70           $0.1         0.00%  60           $0.1         0.00%
 Appetizers
Traditional     31          $0.0         0.00%  23           $0.2         0.00%  24           $0.3         0.00%
 [Ice Cream &
 Sherbert]
Pizza/Economy   32          $0.0         0.00%  55           $0.1         0.00%  49           $0.2         0.00%
Pizza/Premium   33          $0.0         0.00%  43           $0.1         0.00%  38           $0.2         0.00%
Condensed Soup  34          $0.0         0.00%  25           $0.2         0.00%  25           $0.3         0.00%
Lunchment--Bol  35          $0.0         0.00%  45           $0.1         0.00%  43           $0.2         0.00%
 ogna/Sausage
Flavored Milk   36          $0.0         0.00%  64           $0.1         0.00%  57           $0.1         0.00%
All Family      37          $0.0         0.00%  22           $0.2         0.00%  23           $0.3         0.00%
 Cereal
Sandwiches &    38          $0.0         0.00%  75           $0.1         0.00%  66           $0.1         0.00%
 Handhelds
Hamburger Buns  39          $0.0         0.00%  38           $0.1         0.00%  34           $0.2         0.00%
Bananas         40          $0.0         0.00%  17           $0.2         0.00%  22           $0.3         0.00%
Pizza/          41          $0.0         0.00%  47           $0.1         0.00%  46           $0.2         0.00%
 Traditional
Pails [Ice      42          $0.0         0.00%  59           $0.1         0.00%  55           $0.2         0.00%
 Cream &
 Sherbert]
Margarine:      43          $0.0         0.00%  42           $0.1         0.00%  39           $0.2         0.00%
 Tubs And
 Bowls
Natural Cheese  44          $0.0         0.00%  26           $0.2         0.00%  29           $0.2         0.00%
 Chunks
Fz Ss Prem      45          $0.0         0.00%  41           $0.1         0.00%  41           $0.2         0.00%
 Traditional
 Meals
Macaroni &      46          $0.0         0.00%  88           $0.1         0.00%  74           $0.1         0.00%
 Cheese Dnrs
Pourable Salad  47          $0.0         0.00%  35           $0.1         0.00%  35           $0.2         0.00%
 Dressings
Choice Beef     48          $0.0         0.00%  53           $0.1         0.00%  54           $0.2         0.00%
Isotonic        49          $0.0         0.00%  44           $0.1         0.00%  48           $0.2         0.00%
 Drinks Single
 Serve
Strawberries    50          $0.0         0.00%  29           $0.2         0.00%  30           $0.2         0.00%
Can Pasta       51          $0.0         0.00%  118          $0.1         0.00%  97           $0.1         0.00%
Mayonnaise &    52          $0.0         0.00%  48           $0.1         0.00%  50           $0.2         0.00%
 Whipped
 Dressing
Ribs [Pork]     53          $0.0         0.00%  52           $0.1         0.00%  53           $0.2         0.00%
Candy Bags--    54          $0.0         0.00%  36           $0.1         0.00%  37           $0.2         0.00%
 Chocolate
Cottage Cheese  55          $0.0         0.00%  37           $0.1         0.00%  42           $0.2         0.00%
Dairy Case      56          $0.0         0.00%  24           $0.2         0.00%  28           $0.2         0.00%
 100% Pure
 Juice--O
Mexican Soft    57          $0.0         0.00%  56           $0.1         0.00%  58           $0.1         0.00%
 Tortillas And
 Wra
Frzn French     58          $0.0         0.00%  93           $0.1         0.00%  80           $0.1         0.00%
 Fries
Candy Bars      59          $0.0         0.00%  71           $0.1         0.00%  70           $0.1         0.00%
 (Multi Pack)
Sweet Goods--   60          $0.0         0.00%  95           $0.1         0.00%  85           $0.1         0.00%
 Full Size
Butts [Pork     61          $0.0         0.00%  80           $0.1         0.00%  76           $0.1         0.00%
 Shoulder]
Frzn Chicken--  62          $0.0         0.00%  54           $0.1         0.00%  59           $0.1         0.00%
 Wht Meat
Sandwich        63          $0.0         0.00%  63           $0.1         0.00%  63           $0.1         0.00%
 Cookies
Mainstream      64          $0.0         0.00%  73           $0.1         0.00%  71           $0.1         0.00%
 [Pasta &
 Pizza Sauce]
Fz Bag          65          $0.0         0.00%  34           $0.2         0.00%  40           $0.2         0.00%
 Vegetables--P
 lain
Bagged Cheese   66          $0.0         0.00%  90           $0.1         0.00%  79           $0.1         0.00%
 Snacks
Choice Beef     67          $0.0         0.00%  40           $0.1         0.00%  47           $0.2         0.00%
Peanut Butter   68          $0.0         0.00%  50           $0.1         0.00%  56           $0.2         0.00%
Bkfst Sausage-- 69          $0.0         0.00%  61           $0.1         0.00%  62           $0.1         0.00%
 Fresh Rolls
Adult Cereal    70          $0.0         0.00%  33           $0.2         0.00%  33           $0.2         0.00%
Loaf Cheese     71          $0.0         0.00%  67           $0.1         0.00%  67           $0.1         0.00%
Refrigerated    72          $0.0         0.00%  86           $0.1         0.00%  82           $0.1         0.00%
 Biscuits
Vegetable Oil   73          $0.0         0.00%  131          $0.1         0.00%  108          $0.1         0.00%
Hot Dog Buns    74          $0.0         0.00%  79           $0.1         0.00%  77           $0.1         0.00%
Candy Bars      75          $0.0         0.00%  84           $0.1         0.00%  83           $0.1         0.00%
 (Singles)
 (Including)
Sour Creams     76          $0.0         0.00%  62           $0.1         0.00%  65           $0.1         0.00%
Sticks/Enrobed  77          $0.0         0.00%  99           $0.1         0.00%  92           $0.1         0.00%
 [Frozen
 Novelties]
Angus [Beef]    78          $0.0         0.00%  83           $0.1         0.00%  81           $0.1         0.00%
Tray Pack/Choc  79          $0.0         0.00%  85           $0.1         0.00%  84           $0.1         0.00%
 Chip Cookies
Salsa & Dips    80          $0.0         0.00%  106          $0.1         0.00%  99           $0.1         0.00%
Skillet         81          $0.0         0.00%  142          $0.1         0.00%  120          $0.1         0.00%
 Dinners
Aseptic Pack    82          $0.0         0.00%  154          $0.1         0.00%  126          $0.1         0.00%
 Juice And
 Drinks
Tuna            83          $0.0         0.00%  72           $0.1         0.00%  75           $0.1         0.00%
Sw Gds: Donuts  84          $0.0         0.00%  89           $0.1         0.00%  89           $0.1         0.00%
Head Lettuce    85          $0.0         0.00%  65           $0.1         0.00%  69           $0.1         0.00%
Fz Family       86          $0.0         0.00%  170          $0.0         0.00%  138          $0.1         0.00%
 Style Entrees
Cubed Meats     87          $0.0         0.00%  97           $0.1         0.00%  94           $0.1         0.00%
 [Beef]
Select Beef     88          $0.0         0.00%  91           $0.1         0.00%  91           $0.1         0.00%
Value Forms/    89          $0.0         0.00%  166          $0.0         0.00%  139          $0.1         0.00%
 18oz And
 Larger
 [Chicken]
Fz Ss Prem      90          $0.0         0.00%  30           $0.2         0.00%  32           $0.2         0.00%
 Nutritional
 Meals
Variety Beans-- 91          $0.0         0.00%  77           $0.1         0.00%  87           $0.1         0.00%
 Kidney/Pinto/
 E
Cream Cheese    92          $0.0         0.00%  58           $0.1         0.00%  64           $0.1         0.00%
Dnr Sausage--   93          $0.0         0.00%  129          $0.1         0.00%  122          $0.1         0.00%
 Links Pork
 Ckd/S
Lunchmeat--Cho  94          $0.0         0.00%  186          $0.0         0.00%  155          $0.1         0.00%
 p/Form Pltry
 & Ha
Frzn Meat--     95          $0.0         0.00%  194          $0.0         0.00%  162          $0.1         0.00%
 Beef
Toaster         96          $0.0         0.00%  121          $0.1         0.00%  116          $0.1         0.00%
 Pastries
Bacon--Trad     97          $0.0         0.00%  76           $0.1         0.00%  88           $0.1         0.00%
 Greater Than
 16oz
Corn Chips      98          $0.0         0.00%  108          $0.1         0.00%  105          $0.1         0.00%
Water Ice       99          $0.0         0.00%  220          $0.0         0.00%  182          $0.1         0.00%
 [Frozen
 Novelties]
Eggs--Medium    100         $0.0         0.00%  164          $0.0         0.00%  144          $0.1         0.00%
                      -------------------------       ----------------------------------------------------------
  Top 100                   $4.9         0.07%              $16.8         0.05%              $21.7         0.06%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


 Exhibit E-16: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in Counties with Poverty Rates
                                                  Less than 10%
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $12.2         0.18%  1          $105.5         0.33%  1          $117.6         0.31%
 White Only
Soft Drinks 12/ 2          $10.3         0.16%  2           $74.1         0.24%  2           $84.4         0.22%
 18 & 15pk Can
 Car
Lean [Beef]     3           $6.3         0.10%  7           $32.5         0.10%  5           $38.9         0.10%
Shredded        4           $4.8         0.07%  3           $47.5         0.15%  3           $52.3         0.14%
 Cheese
Kids Cereal     5           $4.3         0.06%  20          $24.1         0.08%  18          $28.3         0.07%
Sft Drnk 2      6           $3.9         0.06%  18          $25.3         0.08%  17          $29.2         0.08%
 Liter Btl
 Carb Incl
Potato Chips    7           $3.8         0.06%  9           $31.6         0.10%  7           $35.4         0.09%
Primal [Beef]   8           $3.6         0.05%  16          $27.7         0.09%  14          $31.3         0.08%
Chicken Breast  9           $3.4         0.05%  4           $39.9         0.13%  4           $43.3         0.11%
 Boneless
Lunchment--Del  10          $3.3         0.05%  11          $29.7         0.09%  10          $33.0         0.09%
 i Fresh
Eggs--Large     11          $3.1         0.05%  8           $31.8         0.10%  9           $34.9         0.09%
Infant Formula  12          $3.1         0.05%  268          $4.3         0.01%  169          $7.4         0.02%
 Starter/
 Solutio
Snacks/         13          $3.0         0.05%  54          $14.2         0.05%  48          $17.3         0.05%
 Appetizers
Tortilla/Nacho  14          $3.0         0.05%  13          $28.8         0.09%  12          $31.8         0.08%
 Chips
Enhanced [Pork  15          $2.8         0.04%  21          $23.6         0.07%  20          $26.4         0.07%
 Boneless Loin/
 Rib]
Mainstream      16          $2.8         0.04%  40          $17.3         0.05%  36          $20.1         0.05%
 White Bread
Unflavored Can  17          $2.8         0.04%  22          $23.4         0.07%  21          $26.1         0.07%
 Coffee
Still Water     18          $2.7         0.04%  27          $21.6         0.07%  26          $24.2         0.06%
 Drnking/Mnrl
 Water
Soft Drinks     19          $2.6         0.04%  59          $13.8         0.04%  53          $16.3         0.04%
 20pk & 24pk
 Can Carb
Pizza/Premium   20          $2.5         0.04%  28          $21.3         0.07%  27          $23.9         0.06%
Fz Ss Prem      21          $2.5         0.04%  32          $19.3         0.06%  30          $21.8         0.06%
 Traditional
 Meals
Dairy Case      22          $2.5         0.04%  6           $33.2         0.11%  6           $35.7         0.09%
 100% Pure
 Juice--O
Natural Cheese  23          $2.4         0.04%  15          $28.1         0.09%  15          $30.6         0.08%
 Chunks
American        24          $2.4         0.04%  46          $16.3         0.05%  41          $18.7         0.05%
 Single Cheese
All Family      25          $2.3         0.04%  14          $28.2         0.09%  16          $30.5         0.08%
 Cereal
Bacon--Trad     26          $2.3         0.03%  35          $19.0         0.06%  35          $21.3         0.06%
 16oz Or Less
Snack Cake--    27          $2.2         0.03%  70          $12.5         0.04%  64          $14.7         0.04%
 Multi Pack
Select Beef     28          $2.2         0.03%  34          $19.2         0.06%  33          $21.4         0.06%
Bananas         29          $2.2         0.03%  10          $30.5         0.10%  11          $32.7         0.09%
Potatoes        30          $2.2         0.03%  33          $19.3         0.06%  32          $21.5         0.06%
 Russet (Bulk
 & Bag)
Sft Drnk Mlt-   31          $2.2         0.03%  25          $22.5         0.07%  24          $24.6         0.06%
 Pk Btl Carb
 (Excp)
Fz Ss Economy   32          $2.2         0.03%  112          $8.7         0.03%  94          $10.8         0.03%
 Meals All
Premium [Ice    33          $2.1         0.03%  12          $29.6         0.09%  13          $31.7         0.08%
 Cream &
 Sherbert]
Mainstream      34          $2.1         0.03%  26          $21.8         0.07%  28          $23.8         0.06%
 Variety
 Breads
Sft Drnk Sngl   35          $2.1         0.03%  90          $10.1         0.03%  81          $12.2         0.03%
 Srv Btl Carb
 (Ex)
Convenient      36          $2.1         0.03%  94           $9.7         0.03%  86          $11.8         0.03%
 Meals--Kids
 Meal C
Sandwiches &    37          $2.0         0.03%  104          $9.0         0.03%  91          $11.0         0.03%
 Handhelds
Sugar           38          $1.9         0.03%  61          $13.6         0.04%  55          $15.5         0.04%
Condensed Soup  39          $1.9         0.03%  31          $19.6         0.06%  31          $21.5         0.06%
Fz Family       40          $1.8         0.03%  83          $11.0         0.03%  77          $12.8         0.03%
 Style Entrees
Ribs [Pork]     41          $1.8         0.03%  68          $12.9         0.04%  63          $14.7         0.04%
Isotonic        42          $1.7         0.03%  60          $13.8         0.04%  56          $15.5         0.04%
 Drinks Single
 Serve
Refrigerated    43          $1.7         0.03%  38          $18.3         0.06%  37          $20.0         0.05%
 Coffee
 Creamers
Pourable Salad  44          $1.7         0.03%  39          $18.0         0.06%  38          $19.7         0.05%
 Dressings
Fz Ss Prem      45          $1.7         0.03%  5           $33.6         0.11%  8           $35.3         0.09%
 Nutritional
 Meals
Frzn Chicken--  46          $1.7         0.03%  74          $12.2         0.04%  69          $13.9         0.04%
 Wht Meat
Strawberries    47          $1.7         0.03%  17          $26.3         0.08%  19          $27.9         0.07%
Mayonnaise &    48          $1.6         0.02%  52          $14.6         0.05%  54          $16.1         0.04%
 Whipped
 Dressing
Mexican Soft    49          $1.6         0.02%  51          $14.8         0.05%  51          $16.4         0.04%
 Tortillas And
 Wra
Candy Bags--    50          $1.5         0.02%  30          $20.3         0.06%  29          $21.9         0.06%
 Chocolate
Adult Cereal    51          $1.5         0.02%  24          $22.8         0.07%  25          $24.3         0.06%
Choice Beef     52          $1.5         0.02%  63          $13.5         0.04%  60          $15.1         0.04%
Sw Gds: Donuts  53          $1.5         0.02%  77          $11.7         0.04%  76          $13.2         0.03%
Traditional     54          $1.5         0.02%  56          $13.9         0.04%  58          $15.3         0.04%
 [Ice Cream &
 Sherbert]
Meat: Turkey    55          $1.4         0.02%  19          $24.3         0.08%  22          $25.7         0.07%
 Bulk
Aseptic Pack    56          $1.4         0.02%  136          $7.8         0.02%  115          $9.2         0.02%
 Juice And
 Drinks
Fz Bag          57          $1.4         0.02%  47          $16.0         0.05%  46          $17.4         0.05%
 Vegetables--P
 lain
Butter          58          $1.4         0.02%  23          $23.3         0.07%  23          $24.7         0.06%
Margarine:      59          $1.4         0.02%  75          $12.1         0.04%  72          $13.5         0.04%
 Tubs And
 Bowls
Hot Dogs--Base  60          $1.4         0.02%  174          $6.5         0.02%  149          $7.9         0.02%
 Meat
Can Pasta       61          $1.4         0.02%  193          $6.1         0.02%  166          $7.4         0.02%
Macaroni &      62          $1.4         0.02%  133          $7.9         0.02%  114          $9.2         0.02%
 Cheese Dnrs
Choice Beef     63          $1.4         0.02%  107          $8.9         0.03%  100         $10.2         0.03%
Pizza/Economy   64          $1.4         0.02%  191          $6.1         0.02%  164          $7.5         0.02%
Peanut Butter   65          $1.3         0.02%  45          $16.4         0.05%  45          $17.7         0.05%
Mainstream      66          $1.3         0.02%  88          $10.4         0.03%  88          $11.7         0.03%
 [Pasta &
 Pizza Sauce]
Pizza/          67          $1.3         0.02%  98           $9.3         0.03%  95          $10.6         0.03%
 Traditional
Tuna            68          $1.3         0.02%  64          $13.3         0.04%  65          $14.6         0.04%
Value Forms/    69          $1.2         0.02%  209          $5.8         0.02%  181          $7.0         0.02%
 18oz And
 Larger
 [Chicken]
Angus           70          $1.2         0.02%  62          $13.6         0.04%  62          $14.8         0.04%
Meat: Ham Bulk  71          $1.2         0.02%  36          $18.4         0.06%  39          $19.6         0.05%
Frzn Breakfast  72          $1.2         0.02%  135          $7.8         0.02%  122          $9.0         0.02%
 Sandwiches
Cream Cheese    73          $1.2         0.02%  49          $15.5         0.05%  50          $16.7         0.04%
Cheese          74          $1.2         0.02%  66          $13.1         0.04%  67          $14.2         0.04%
 Crackers
Fz Skillet      75          $1.2         0.02%  89          $10.3         0.03%  90          $11.5         0.03%
 Meals
String Cheese   76          $1.2         0.02%  53          $14.3         0.05%  57          $15.4         0.04%
Fruit Snacks    77          $1.2         0.02%  170          $6.6         0.02%  152          $7.8         0.02%
Frzn Meat--     78          $1.1         0.02%  184          $6.3         0.02%  168          $7.4         0.02%
 Beef
Frzn French     79          $1.1         0.02%  173          $6.5         0.02%  159          $7.7         0.02%
 Fries
Instore Cut     80          $1.1         0.02%  57          $13.8         0.04%  61          $14.9         0.04%
 Fruit
Waffles/        81          $1.1         0.02%  84          $10.9         0.03%  83          $12.0         0.03%
 Pancakes/
 French Toast
Sandwiches--(C  82          $1.1         0.02%  140          $7.7         0.02%  130          $8.8         0.02%
 old)
Sour Creams     83          $1.1         0.02%  73          $12.4         0.04%  73          $13.5         0.04%
Cakes:          84          $1.1         0.02%  164          $6.7         0.02%  150          $7.8         0.02%
 Birthday/
 Celebration
 Sh
Avocado         85          $1.1         0.02%  48          $15.7         0.05%  49          $16.8         0.04%
Rts Soup:       86          $1.1         0.02%  55          $14.2         0.05%  59          $15.3         0.04%
 Chunky/
 Homestyle/Et
Salsa & Dips    87          $1.1         0.02%  132          $7.9         0.02%  124          $9.0         0.02%
Flavored Milk   88          $1.1         0.02%  145          $7.5         0.02%  137          $8.5         0.02%
Grapes Red      89          $1.1         0.02%  42          $17.0         0.05%  43          $18.0         0.05%
Candy Bars      90          $1.1         0.02%  152          $7.1         0.02%  142          $8.2         0.02%
 (Singles)
 (Including)
Lunchment--Bol  91          $1.1         0.02%  179          $6.4         0.02%  167          $7.4         0.02%
 ogna/Sausage
Sandwich        92          $1.0         0.02%  99           $9.3         0.03%  98          $10.4         0.03%
 Cookies
Bkfst Sausage-- 93          $1.0         0.02%  109          $8.8         0.03%  105          $9.9         0.03%
 Fresh Rolls
Spring Water    94          $1.0         0.02%  82          $11.0         0.03%  82          $12.0         0.03%
Chix: Frd 8pc/  95          $1.0         0.02%  85          $10.8         0.03%  84          $11.8         0.03%
 Cut Up (Hot)
Bagged Cheese   96          $1.0         0.02%  176          $6.4         0.02%  165          $7.4         0.02%
 Snacks
Natural Cheese  97          $1.0         0.02%  50          $15.3         0.05%  52          $16.4         0.04%
 Slices
Hamburger Buns  98          $1.0         0.02%  102          $9.1         0.03%  103         $10.1         0.03%
Sweet Goods--   99          $1.0         0.01%  175          $6.5         0.02%  163          $7.5         0.02%
 Full Size
Yogurt/Kids     100         $1.0         0.01%  165          $6.7         0.02%  155          $7.7         0.02%
                      -------------------------       ----------------------------------------------------------
  Top 100                 $204.3         3.10%           $1,763.9         5.60%           $1,968.2         5.17%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


 Exhibit E-17: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in Counties with Poverty Rates
                                                  of 10% to 20%
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1         $147.5         2.24%  1          $651.2         2.07%  1          $798.7         2.10%
 White Only
Soft Drinks 12/ 2         $123.8         1.88%  2          $456.0         1.45%  2          $579.8         1.52%
 18 & 15pk Can
 Car
Lean [Beef]     3          $85.1         1.29%  7          $199.9         0.63%  4          $285.0         0.75%
Kids Cereal     4          $59.3         0.90%  20         $141.9         0.45%  13         $201.2         0.53%
Shredded        5          $57.3         0.87%  3          $255.8         0.81%  3          $313.1         0.82%
 Cheese
Sft Drnk 2      6          $54.3         0.83%  13         $175.5         0.56%  9          $229.8         0.60%
 Liter Btl
 Carb Incl
Potato Chips    7          $49.2         0.75%  8          $192.5         0.61%  6          $241.8         0.63%
Primal [Beef]   8          $44.4         0.68%  17         $156.1         0.50%  15         $200.6         0.53%
Infant Formula  9          $42.1         0.64%  179         $35.8         0.11%  79          $77.9         0.20%
 Starter/
 Solutio
Lunchment--Del  10         $42.1         0.64%  11         $183.1         0.58%  11         $225.2         0.59%
 i Fresh
Eggs--Large     11         $40.0         0.61%  9          $191.2         0.61%  8          $231.2         0.61%
Chicken Breast  12         $38.5         0.58%  4          $221.7         0.70%  5          $260.2         0.68%
 Boneless
Still Water     13         $37.9         0.58%  19         $146.8         0.47%  19         $184.8         0.48%
 Drnking/Mnrl
 Water
Tortilla/Nacho  14         $36.3         0.55%  16         $157.8         0.50%  17         $194.1         0.51%
 Chips
Mainstream      15         $35.0         0.53%  42         $100.2         0.32%  35         $135.3         0.36%
 White Bread
Snacks/         16         $34.2         0.52%  67          $75.2         0.24%  49         $109.4         0.29%
 Appetizers
Fz Ss Prem      17         $33.7         0.51%  22         $136.9         0.43%  21         $170.6         0.45%
 Traditional
 Meals
Dairy Case      18         $33.7         0.51%  6          $206.7         0.66%  7          $240.4         0.63%
 100% Pure
 Juice--O
American        19         $32.8         0.50%  41         $102.4         0.32%  36         $135.2         0.35%
 Single Cheese
Unflavored Can  20         $31.4         0.48%  18         $149.8         0.48%  20         $181.2         0.48%
 Coffee
Enhanced [Pork  21         $31.1         0.47%  27         $122.2         0.39%  24         $153.3         0.40%
 Boneless Loin/
 Rib]
Fz Ss Economy   22         $31.1         0.47%  80          $62.1         0.20%  65          $93.1         0.24%
 Meals All
Bacon--Trad     23         $31.0         0.47%  29         $119.4         0.38%  26         $150.3         0.39%
 16oz Or Less
Pizza/Premium   24         $30.2         0.46%  34         $115.3         0.37%  29         $145.5         0.38%
Snack Cake--    25         $30.2         0.46%  70          $74.2         0.24%  54         $104.4         0.27%
 Multi Pack
Mainstream      26         $29.7         0.45%  25         $130.8         0.42%  22         $160.5         0.42%
 Variety
 Breads
Soft Drinks     27         $29.0         0.44%  62          $79.6         0.25%  50         $108.6         0.29%
 20pk & 24pk
 Can Carb
Natural Cheese  28         $28.2         0.43%  14         $167.0         0.53%  16         $195.1         0.51%
 Chunks
All Family      29         $28.0         0.43%  15         $163.5         0.52%  18         $191.6         0.50%
 Cereal
Sugar           30         $27.3         0.42%  58          $84.4         0.27%  46         $111.8         0.29%
Sandwiches &    31         $27.0         0.41%  93          $56.0         0.18%  73          $83.0         0.22%
 Handhelds
Potatoes        32         $26.8         0.41%  32         $116.0         0.37%  30         $142.8         0.37%
 Russet (Bulk
 & Bag)
Bananas         33         $26.6         0.40%  10         $187.2         0.59%  12         $213.7         0.56%
Ribs [Pork]     34         $25.8         0.39%  60          $80.9         0.26%  53         $106.7         0.28%
Convenient      35         $25.2         0.38%  106         $51.5         0.16%  82          $76.7         0.20%
 Meals--Kids
 Meal C
Premium [Ice    36         $24.8         0.38%  12         $176.1         0.56%  14         $200.9         0.53%
 Cream &
 Sherbert]
Isotonic        37         $24.2         0.37%  45          $93.9         0.30%  42         $118.1         0.31%
 Drinks Single
 Serve
Sft Drnk Mlt-   38         $24.0         0.36%  26         $123.5         0.39%  28         $147.5         0.39%
 Pk Btl Carb
 (Excp)
Select Beef     39         $23.8         0.36%  30         $117.5         0.37%  31         $141.3         0.37%
Frzn Chicken--  40         $22.7         0.35%  69          $74.8         0.24%  61          $97.5         0.26%
 Wht Meat
Condensed Soup  41         $22.5         0.34%  33         $115.5         0.37%  32         $138.0         0.36%
Pourable Salad  42         $21.7         0.33%  39         $105.6         0.34%  39         $127.3         0.33%
 Dressings
Choice Beef     43         $21.3         0.32%  38         $106.3         0.34%  38         $127.6         0.33%
Fz Family       44         $21.2         0.32%  78          $63.1         0.20%  72          $84.3         0.22%
 Style Entrees
Sft Drnk Sngl   45         $20.9         0.32%  99          $53.5         0.17%  85          $74.4         0.20%
 Srv Btl Carb
 (Ex)
Mayonnaise &    46         $20.9         0.32%  49          $90.9         0.29%  45         $111.8         0.29%
 Whipped
 Dressing
Mexican Soft    47         $19.8         0.30%  50          $90.3         0.29%  48         $110.1         0.29%
 Tortillas And
 Wra
Refrigerated    48         $19.5         0.30%  31         $116.6         0.37%  33         $136.1         0.36%
 Coffee
 Creamers
Adult Cereal    49         $19.3         0.29%  21         $139.5         0.44%  23         $158.8         0.42%
Traditional     50         $19.2         0.29%  52          $88.6         0.28%  51         $107.8         0.28%
 [Ice Cream &
 Sherbert]
Fz Ss Prem      51         $19.1         0.29%  5          $208.6         0.66%  10         $227.7         0.60%
 Nutritional
 Meals
Fz Bag          52         $19.0         0.29%  43          $98.9         0.31%  43         $117.9         0.31%
 Vegetables--P
 lain
Aseptic Pack    53         $18.6         0.28%  137         $43.3         0.14%  107         $61.9         0.16%
 Juice And
 Drinks
Choice Beef     54         $18.4         0.28%  97          $53.6         0.17%  89          $72.1         0.19%
Hot Dogs--Base  55         $18.4         0.28%  145         $42.1         0.13%  111         $60.5         0.16%
 Meat
Macaroni &      56         $18.2         0.28%  129         $44.6         0.14%  103         $62.8         0.16%
 Cheese Dnrs
Margarine:      57         $18.1         0.27%  63          $77.4         0.25%  64          $95.5         0.25%
 Tubs And
 Bowls
Strawberries    58         $17.8         0.27%  24         $132.8         0.42%  25         $150.6         0.40%
Mainstream      59         $17.4         0.26%  85          $60.8         0.19%  78          $78.2         0.21%
 [Pasta &
 Pizza Sauce]
Candy Bags--    60         $16.7         0.25%  36         $112.6         0.36%  37         $129.3         0.34%
 Chocolate
Can Pasta       61         $16.5         0.25%  185         $35.3         0.11%  144         $51.8         0.14%
Frzn Chicken--  62         $16.4         0.25%  469         $13.0         0.04%  268         $29.4         0.08%
 Wings
Tuna            63         $16.4         0.25%  59          $84.4         0.27%  58         $100.8         0.26%
Sw Gds: Donuts  64         $16.2         0.25%  84          $61.0         0.19%  80          $77.2         0.20%
Peanut Butter   65         $15.8         0.24%  44          $96.9         0.31%  44         $112.7         0.30%
Lunchment--Bol  66         $15.7         0.24%  124         $45.6         0.14%  108         $61.3         0.16%
 ogna/Sausage
Mult Pk Bag     67         $15.4         0.23%  205         $32.4         0.10%  161         $47.8         0.13%
 Snacks
Butter          68         $15.3         0.23%  23         $134.9         0.43%  27         $150.1         0.39%
Meat: Turkey    69         $15.1         0.23%  28         $120.3         0.38%  34         $135.4         0.36%
 Bulk
Frzn French     70         $15.1         0.23%  177         $37.0         0.12%  141         $52.1         0.14%
 Fries
Vegetable Oil   71         $14.9         0.23%  250         $26.7         0.08%  193         $41.6         0.11%
Pizza/Economy   72         $14.6         0.22%  195         $33.3         0.11%  159         $48.0         0.13%
Frzn Meat--     73         $14.6         0.22%  188         $35.0         0.11%  154         $49.6         0.13%
 Beef
Fz Skillet      74         $14.5         0.22%  87          $60.4         0.19%  84          $74.9         0.20%
 Meals
Value Forms/    75         $14.2         0.22%  214         $31.9         0.10%  168         $46.2         0.12%
 18oz And
 Larger
 [Chicken]
Frzn Breakfast  76         $14.1         0.21%  154         $41.0         0.13%  128         $55.0         0.14%
 Sandwiches
Cakes:          77         $14.1         0.21%  172         $37.9         0.12%  143         $52.0         0.14%
 Birthday/
 Celebration
 Sh
Chicken Wings   78         $14.0         0.21%  319         $20.8         0.07%  238         $34.8         0.09%
Sandwiches--(C  79         $13.9         0.21%  94          $56.0         0.18%  92          $69.9         0.18%
 old)
Sandwich        80         $13.8         0.21%  95          $54.6         0.17%  94          $68.4         0.18%
 Cookies
Sour Creams     81         $13.7         0.21%  71          $73.2         0.23%  71          $86.9         0.23%
Rts Soup:       82         $13.7         0.21%  47          $93.1         0.30%  52         $106.8         0.28%
 Chunky/
 Homestyle/Et
Pizza/          83         $13.6         0.21%  118         $47.2         0.15%  109         $60.8         0.16%
 Traditional
Cream Cheese    84         $13.5         0.21%  53          $88.0         0.28%  57         $101.6         0.27%
Waffles/        85         $13.4         0.20%  89          $58.6         0.19%  88          $72.1         0.19%
 Pancakes/
 French Toast
Fruit Snacks    86         $13.4         0.20%  209         $32.1         0.10%  172         $45.5         0.12%
Bagged Cheese   87         $13.3         0.20%  158         $40.0         0.13%  136         $53.2         0.14%
 Snacks
Angus [Beef]    88         $13.1         0.20%  64          $77.0         0.24%  67          $90.2         0.24%
Ramen Noodles/  89         $12.9         0.20%  298         $22.0         0.07%  237         $34.8         0.09%
 Ramen Cups
Salsa & Dips    90         $12.8         0.20%  140         $42.7         0.14%  124         $55.5         0.15%
Cheese          91         $12.8         0.19%  74          $67.9         0.22%  77          $80.7         0.21%
 Crackers
Candy Bars      92         $12.8         0.19%  139         $42.9         0.14%  123         $55.7         0.15%
 (Singles)
 (Including)
Dairy Case      93         $12.6         0.19%  170         $38.2         0.12%  149         $50.7         0.13%
 Juice Drnk
 Under 10
Spring Water    94         $12.5         0.19%  65          $76.3         0.24%  68          $88.8         0.23%
Chicken Drums   95         $12.4         0.19%  276         $23.9         0.08%  226         $36.3         0.10%
Hot Dog Buns    96         $12.3         0.19%  119         $47.0         0.15%  113         $59.3         0.16%
Sweet Goods--   97         $12.3         0.19%  128         $44.9         0.14%  118         $57.2         0.15%
 Full Size
Hamburger Buns  98         $12.2         0.19%  104         $52.5         0.17%  98          $64.8         0.17%
Grapes Red      99         $12.1         0.18%  48          $91.9         0.29%  55         $104.0         0.27%
Flavored Milk   100        $12.1         0.18%  130         $44.6         0.14%  120         $56.7         0.15%
                      -------------------------       ----------------------------------------------------------
  Top 100               $2,551.7        38.78%          $10,139.2        32.17%          $12,690.9        33.31%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.


 Exhibit E-18: Top 100 Subcommodities for SNAP Households by Expenditure: Stores in Counties with Poverty Rates
                                                Greater than 20%
----------------------------------------------------------------------------------------------------------------
                 SNAP Household  Expenditures          Non-SNAP Household         Total Household  Expenditures
               --------------------------------           Expenditures          --------------------------------
 Subcommodity                                  ---------------------------------
                 Rank     $ in        % of                $ in         % of       Rank     $ in         % of
                        millions  Expenditures   Rank   millions   Expenditures          millions   Expenditures
----------------------------------------------------------------------------------------------------------------
Fluid Milk/     1          $31.5         0.48%  1           $97.0         0.31%  1          $128.5         0.34%
 White Only
Soft Drinks 12/ 2          $30.5         0.46%  2           $71.0         0.23%  2          $101.6         0.27%
 18 & 15pk Can
 Car
Lean [Beef]     3          $21.0         0.32%  13          $25.4         0.08%  5           $46.4         0.12%
Kids Cereal     4          $14.6         0.22%  21          $20.4         0.06%  13          $35.0         0.09%
Primal [Beef]   5          $14.4         0.22%  4           $35.9         0.11%  4           $50.3         0.13%
Shredded        6          $12.7         0.19%  3           $38.6         0.12%  3           $51.3         0.13%
 Cheese
Sft Drnk 2      7          $12.6         0.19%  8           $29.3         0.09%  6           $42.0         0.11%
 Liter Btl
 Carb Incl
Potato Chips    8          $11.3         0.17%  10          $29.1         0.09%  7           $40.4         0.11%
Lunchment--Del  9          $10.5         0.16%  6           $29.8         0.09%  8           $40.2         0.11%
 i Fresh
Mainstream      10         $10.1         0.15%  26          $19.3         0.06%  19          $29.4         0.08%
 White Bread
Snack Cake--    11          $9.2         0.14%  38          $15.1         0.05%  30          $24.2         0.06%
 Multi Pack
Eggs--Large     12          $9.0         0.14%  11          $28.6         0.09%  10          $37.6         0.10%
Infant Formula  13          $9.0         0.14%  172          $5.2         0.02%  61          $14.2         0.04%
 Starter/
 Solutio
American        14          $8.8         0.13%  31          $17.9         0.06%  24          $26.8         0.07%
 Single Cheese
Still Water     15          $8.1         0.12%  24          $19.3         0.06%  21          $27.5         0.07%
 Drnking/Mnrl
 Water
Soft Drinks     16          $8.1         0.12%  46          $13.1         0.04%  39          $21.2         0.06%
 20pk & 24pk
 Can Carb
Tortilla/Nacho  17          $8.1         0.12%  17          $22.4         0.07%  16          $30.5         0.08%
 Chips
Sft Drnk Mlt-   18          $7.9         0.12%  12          $27.7         0.09%  12          $35.6         0.09%
 Pk Btl Carb
 (Excp)
Fz Ss Economy   19          $7.7         0.12%  64          $10.0         0.03%  48          $17.7         0.05%
 Meals All
Sugar           20          $7.7         0.12%  41          $14.6         0.05%  36          $22.3         0.06%
Fz Ss Prem      21          $7.7         0.12%  27          $19.3         0.06%  23          $26.9         0.07%
 Traditional
 Meals
Chicken Breast  22          $7.6         0.12%  5           $31.3         0.10%  9           $39.0         0.10%
 Boneless
Chicken Wings   23          $7.6         0.12%  181          $5.1         0.02%  72          $12.7         0.03%
Enhanced [Pork  24          $7.6         0.11%  18          $22.2         0.07%  18          $29.7         0.08%
 Boneless Loin/
 Rib]
Bacon--Trad     25          $7.5         0.11%  28          $19.2         0.06%  25          $26.7         0.07%
 16oz Or Less
Ribs [Pork]     26          $7.4         0.11%  47          $12.9         0.04%  41          $20.3         0.05%
Dairy Case      27          $7.4         0.11%  9           $29.1         0.09%  11          $36.5         0.10%
 100% Pure
 Juice--O
Snacks/         28          $7.4         0.11%  60          $11.0         0.03%  44          $18.4         0.05%
 Appetizers
Unflavored Can  29          $7.2         0.11%  15          $24.9         0.08%  15          $32.1         0.08%
 Coffee
Convenient      30          $7.0         0.11%  86           $8.5         0.03%  53          $15.5         0.04%
 Meals--Kids
 Meal C
Pizza/Premium   31          $6.9         0.10%  35          $16.7         0.05%  32          $23.6         0.06%
Sandwiches &    32          $6.9         0.10%  82           $8.6         0.03%  56          $15.4         0.04%
 Handhelds
Potatoes        33          $6.7         0.10%  29          $19.2         0.06%  26          $25.9         0.07%
 Russet (Bulk
 & Bag)
Mainstream      34          $6.6         0.10%  20          $20.7         0.07%  22          $27.3         0.07%
 Variety
 Breads
All Family      35          $5.8         0.09%  16          $23.2         0.07%  20          $29.0         0.08%
 Cereal
Frzn Chicken--  36          $5.6         0.09%  49          $12.8         0.04%  42          $18.4         0.05%
 Wht Meat
Choice Beef     37          $5.6         0.09%  34          $16.8         0.05%  34          $22.5         0.06%
Pourable Salad  38          $5.6         0.09%  37          $15.8         0.05%  37          $21.4         0.06%
 Dressings
Bananas         39          $5.5         0.08%  14          $24.9         0.08%  17          $30.4         0.08%
Fz Bag          40          $5.3         0.08%  33          $17.0         0.05%  35          $22.3         0.06%
 Vegetables--P
 lain
Hot Dogs--Base  41          $5.3         0.08%  89           $8.2         0.03%  67          $13.5         0.04%
 Meat
Mult Pk Bag     42          $5.3         0.08%  178          $5.1         0.02%  101         $10.4         0.03%
 Snacks
Condensed Soup  43          $5.3         0.08%  30          $18.5         0.06%  31          $23.8         0.06%
Frzn Chicken--  44          $5.2         0.08%  356          $2.6         0.01%  156          $7.8         0.02%
 Wings
Lunchment--Bol  45          $5.0         0.08%  79           $8.9         0.03%  65          $14.0         0.04%
 ogna/Sausage
Traditional     46          $5.0         0.08%  36          $16.3         0.05%  38          $21.3         0.06%
 [Ice Cream &
 Sherbert]
Sft Drnk Sngl   47          $4.8         0.07%  99           $7.8         0.02%  73          $12.6         0.03%
 Srv Btl Carb
 (Ex)
Vegetable Oil   48          $4.8         0.07%  193          $4.9         0.02%  113          $9.7         0.03%
Macaroni &      49          $4.8         0.07%  110          $7.2         0.02%  77          $11.9         0.03%
 Cheese Dnrs
Mayonnaise &    50          $4.7         0.07%  43          $13.6         0.04%  43          $18.4         0.05%
 Whipped
 Dressing
Natural Cheese  51          $4.7         0.07%  19          $21.0         0.07%  27          $25.7         0.07%
 Chunks
Fz Family       52          $4.6         0.07%  70           $9.4         0.03%  64          $14.0         0.04%
 Style Entrees
Isotonic        53          $4.6         0.07%  56          $11.9         0.04%  49          $16.4         0.04%
 Drinks Single
 Serve
Can Pasta       54          $4.4         0.07%  135          $6.3         0.02%  96          $10.7         0.03%
Mainstream      55          $4.3         0.07%  67           $9.7         0.03%  63          $14.0         0.04%
 [Pasta &
 Pizza Sauce]
Premium [Ice    56          $4.3         0.07%  22          $20.3         0.06%  28          $24.6         0.06%
 Cream &
 Sherbert]
Frzn French     57          $4.3         0.06%  118          $6.8         0.02%  90          $11.0         0.03%
 Fries
Choice Beef     58          $4.2         0.06%  65          $10.0         0.03%  62          $14.2         0.04%
Aseptic Pack    59          $4.2         0.06%  144          $6.1         0.02%  102         $10.3         0.03%
 Juice And
 Drinks
Chicken Drums   60          $4.1         0.06%  231          $4.2         0.01%  140          $8.4         0.02%
Dnr Sausage--   61          $4.1         0.06%  209          $4.7         0.01%  130          $8.8         0.02%
 Links Pork
 Ckd/S
Adult Cereal    62          $4.0         0.06%  23          $20.3         0.06%  29          $24.3         0.06%
Strawberries    63          $4.0         0.06%  25          $19.3         0.06%  33          $23.3         0.06%
Margarine:      64          $4.0         0.06%  57          $11.3         0.04%  57          $15.3         0.04%
 Tubs And
 Bowls
Fz Ss Prem      65          $4.0         0.06%  7           $29.4         0.09%  14          $33.4         0.09%
 Nutritional
 Meals
Frzn Breakfast  66          $3.9         0.06%  116          $6.9         0.02%  95          $10.8         0.03%
 Sandwiches
Pizza/Economy   67          $3.8         0.06%  160          $5.7         0.02%  119          $9.5         0.02%
Sw Gds: Donuts  68          $3.7         0.06%  69           $9.5         0.03%  68          $13.2         0.03%
Tuna            69          $3.5         0.05%  54          $12.2         0.04%  51          $15.7         0.04%
Cakes:          70          $3.4         0.05%  162          $5.6         0.02%  125          $9.1         0.02%
 Birthday/
 Celebration
 Sh
Bacon--Trad     71          $3.4         0.05%  117          $6.8         0.02%  103         $10.3         0.03%
 Greater Than
 16oz
Peanut Butter   72          $3.3         0.05%  42          $14.5         0.05%  46          $17.8         0.05%
Candy Bags--    73          $3.3         0.05%  40          $14.6         0.05%  45          $17.9         0.05%
 Chocolate
Sandwich        74          $3.2         0.05%  98           $7.9         0.02%  89          $11.0         0.03%
 Cookies
Salsa & Dips    75          $3.2         0.05%  130          $6.4         0.02%  115          $9.6         0.03%
Frzn Meat--     76          $3.2         0.05%  185          $5.0         0.02%  143          $8.2         0.02%
 Beef
Bkfst Sausage-- 77          $3.2         0.05%  87           $8.5         0.03%  81          $11.7         0.03%
 Fresh Rolls
Value Forms/    78          $3.2         0.05%  192          $4.9         0.02%  145          $8.1         0.02%
 18oz And
 Larger
 [Chicken]
Fz Skillet      79          $3.1         0.05%  81           $8.6         0.03%  80          $11.7         0.03%
 Meals
Refrigerated    80          $3.1         0.05%  121          $6.7         0.02%  109          $9.8         0.03%
 Biscuits
Fruit Snacks    81          $3.1         0.05%  218          $4.5         0.01%  162          $7.5         0.02%
Hot Dog Buns    82          $3.0         0.05%  104          $7.5         0.02%  100         $10.5         0.03%
Ramen Noodles/  83          $3.0         0.05%  330          $2.9         0.01%  213          $5.9         0.02%
 Ramen Cups
Hamburger Buns  84          $3.0         0.05%  83           $8.5         0.03%  82          $11.5         0.03%
Tray Pack/Choc  85          $3.0         0.05%  124          $6.6         0.02%  116          $9.6         0.03%
 Chip Cookies
Pizza/          86          $3.0         0.05%  101          $7.6         0.02%  99          $10.6         0.03%
 Traditional
Candy Bars      87          $2.9         0.04%  91           $8.1         0.03%  88          $11.1         0.03%
 (Multi Pack)
Pails [Ice      88          $2.9         0.04%  194          $4.9         0.02%  153          $7.9         0.02%
 Cream &
 Sherbert]
Grapes White    89          $2.9         0.04%  72           $9.3         0.03%  76          $12.2         0.03%
Refrigerated    90          $2.9         0.04%  53          $12.3         0.04%  58          $15.2         0.04%
 Coffee
 Creamers
Butter          91          $2.9         0.04%  32          $17.5         0.06%  40          $20.4         0.05%
Shrimp--Cooked  92          $2.9         0.04%  161          $5.6         0.02%  135          $8.5         0.02%
Rts Soup:       93          $2.9         0.04%  51          $12.6         0.04%  55          $15.5         0.04%
 Chunky/
 Homestyle/Et
Bagged Cheese   94          $2.8         0.04%  163          $5.6         0.02%  138          $8.4         0.02%
 Snacks
Butter Spray    95          $2.8         0.04%  85           $8.5         0.03%  83          $11.4         0.03%
 Cracker
Angus [Beef]    96          $2.8         0.04%  45          $13.1         0.04%  50          $15.9         0.04%
Flavored Milk   97          $2.8         0.04%  107          $7.4         0.02%  105         $10.2         0.03%
Waffles/        98          $2.8         0.04%  97           $7.9         0.03%  97          $10.7         0.03%
 Pancakes/
 French Toast
Dnr Sausage--   99          $2.8         0.04%  150          $5.9         0.02%  133          $8.7         0.02%
 Pork Rope Ckd/
 Sm
Traditional     100         $2.8         0.04%  109          $7.2         0.02%  107         $10.0         0.03%
 Spices
                      -------------------------       ----------------------------------------------------------
  Top 100                 $610.2         9.27%           $1,500.2         4.76%           $2,110.3         5.54%
   Subcommodit
   ies
                      =========================       ==========================================================
    Total               $6,580.5          100%          $31,513.8          100%          $38,094.2          100%
     Expenditu
     res
----------------------------------------------------------------------------------------------------------------
Source: Foods Typically Purchased by SNAP Households, IMPAQ International, LLC, 2016.
Note: Columns may not sum to total shown due to rounding.
* Top 100 subcommodities based on SNAP household expenditures.

                                 ______
                                 
                Submitted Policy Brief by Feeding Texas
Policy Brief: Maintaining Choices for SNAP Recipients
Feeding Texas
          Our View: SNAP restrictions are an ineffective and costly 
        strategy to improve recipient health. Our nation would be 
        better served by educating and empowering recipients to make 
        better choices, not restricting those choices.
Obesity: A Problem for All, but Improving
    Obesity and diet-related disease affect Americans of all income 
levels and backgrounds. SNAP consumers face additional barriers to 
healthy eating, including limited geographic access to affordable, 
healthy food; tight food budgets overall; and inadequate SNAP 
allotments. SNAP recipients sometimes manage this shortfall by buying 
less-nutritious foods that can adversely affect their health.
    Despite these challenges, the most recent USDA report on SNAP 
purchases found no major differences in the expenditures of SNAP and 
non-SNAP households. Put simply, SNAP consumers shop like Americans do 
as a whole.
    And Americans as a whole are eating better. Soda consumption, the 
behavior most often targeted for SNAP restrictions, is at a thirty-year 
low in America. And while dietary quality remains poor, American diets 
have steadily improved in recent years.
SNAP Restrictions Can Not Force Dietary Change
    A recent, peer-reviewed study (https://www.ncbi.nlm.nih.gov/pubmed/
27653735) in the medical journal JAMA demonstrated how simply 
restricting SNAP purchases would not improve recipients' diets. 
Participants in this study reported a slight reduction in calories 
consumed but no change in overall diet quality.
    An associated meta-study (https://www.ncbi.nlm.nih.gov/pubmed/
26647851) concluded that restricting SNAP participants from spending 
their benefits on soda only had a ``small to moderate'' impact, because 
recipients substituted their own money to purchase soda.
SNAP Restrictions Are Neither Free, nor Freeing
    There are significant costs to SNAP purchase restrictions that 
would be borne by participants, businesses and the program itself.
Participants
    Americans of all income levels view the government restricting food 
choices as an intrusion into their autonomy to decide what is best for 
their families. Because SNAP restrictions unfairly single out low-
income Americans for a problem that affects all Americans, they 
increase the stigma associated with SNAP participation. Increased 
stigma could actually reduce health outcomes, as it would lead some 
families to forgo nutrition assistance rather than put their dinner 
table under Federal scrutiny.
Businesses
    Restricting SNAP purchases would constitute an unfunded Federal 
mandate on business. SNAP retailers would likely bear the cost of re-
training cashiers, creating signage, reprogramming computers and 
implementing rules associated with this broad change.
    Because SNAP serves a diverse group of Americans with a wide range 
of dietary needs, it would be impossible to restrict SNAP benefits to 
an easy-to-control, ``affirmative list'' of approved foods like that 
found in the WIC program. More likely, restrictions would be 
implemented as a short list of restricted foods, forcing retailers to 
evaluate each product on their shelves, as well as thousands of new 
products each year against rules made in Washington.
Program Efficiency & Effectiveness
    Implementation of EBT technology has made SNAP efficient and cost-
effective for retailers and government. The introduction of purchase 
restrictions at checkout would complicate SNAP transactions and 
undermine these gains.
    Unless SNAP restrictions were accompanied by an increase in overall 
benefits, they would also result in a de facto benefit cut by forcing 
recipients to purchase alternative foods that cost more. In this way, 
restrictions could result in decreased purchasing power for SNAP 
recipients, resulting in less food on the family table and a less 
effective hunger-fighting program.
There is a Better Way
    Our nation would be better served pursuing policies that seek to 
educate and empower clients to make better choices, not restrict those 
choices.
    Congress could achieve these aims in two ways:

  1.  Make SNAP benefits reflect the actual costs of eating healthy. 
            The Institute of Medicine has recommended (https://
            www.nap.edu/catalog/13485/supplemental-nutrition-
            assistance-program-examining-the-evidence-to-define-
            benefit) increasing SNAP benefit levels to more accurately 
            reflect the costs involved in eating a healthy diet. Absent 
            a broad increase in benefits, research suggests that 
            funding ``double-dollar incentive'' programs may also 
            improve participants' consumption patterns

  2.  Promote well-evaluated, outcomes-driven nutrition education. 
            Programming directed by Feeding Texas and our local food 
            banks has demonstrated that health interventions and 
            nutrition education strategies funded through SNAP-Ed can 
            effectively promote healthy eating and improve dietary 
            health. These strategies are especially effective when 
            paired with the distribution of free produce, which helps 
            participants to bridge the transition to healthier habits. 
            We call this combined approach ``Feeding with Impact 
            (https://www.feedingtexas.org/product/2017/02/Feeding-with-
            Impact-Factsheet/).''
                                 ______
                                 
          Submitted Statement by Secretaries' Innovation Group
    The Secretaries' Innovation Group (SIG) is a network of state human 
services secretaries who have program responsibility for the state SNAP 
program, among many others. These SIG member secretaries serve under 
Republican governors from states which make up 46% of the country. In 
November 2014 the members of the Secretaries' Innovation Group issued a 
statement from which these recommendations derive.
    The Supplemental Nutrition Assistance Program (SNAP), which is 
known as Food Stamps, has quadrupled in cost since 2001. A common sense 
approach is needed to allow states the ability to ensure welfare 
benefits are being used appropriately. Despite intense opposition, 
states have made significant strides in some areas to tackle wasteful 
expenditures, fraud and abuse in the system, and with the help of 
reform-minded voices in Congress and a new Administration, states will 
be able to go much further.
Recommendations
    The program which is intended as a nutritional supplement should 
restrict the purchase of soda, candy and other unhealthy products.

    The Supplemental Nutrition Assistance Program is intended to 
subsidize nutrition for needy families. Too many recipients are 
utilizing their benefit to purchase items that are \1/3\ of adults and 
17% of youth in the United States are obese, according to the Journal 
of the American Medical Association.\1\ According to a Health Affairs 
study, the medical costs associated with obesity are an estimated $147 
billion in 2008.\2\
---------------------------------------------------------------------------
    \1\ http://jama.jamanetwork.com/article.aspx?articleid=1832542.
    \2\ http://content.healthaffairs.org/content/28/5/
w822.full.pdf+html.
---------------------------------------------------------------------------
    One option to balance SNAP purchases toward healthier choices is to 
allow SNAP purchases to mirror allowable purchases in the Women, 
Infants and Children (WIC) program. A second alternative is to restrict 
the purchase of products with zero nutritional value such as candy, 
energy drinks and other sugar-sweetened drinks. A third alternative is 
to establish a pilot project with up to ten states for a one-time 
waiver that would allow for some nutrition controls on SNAP purchases. 
These pilot waivers would require an evaluation of measurable outcomes.

    Make key SNAP purchase data available to states.

    Micro-level transaction data which shows how SNAP benefits are 
being spent is not available to the states. However this data would 
provide an objective, measurable picture of where reforms are needed to 
ensure the program is effective in providing essential nutrition for 
those in need. SIG recommends FNS and SNAP-EBT vendors (i.e., Xerox) to 
capture all SNAP transaction-level data and make it available to 
states. Transparency is important to inform program officials, 
legislators and the public on what changes are needed in the program to 
ensure its effectiveness as a supplementary nutrition program.

    Convenience stores need more stringent requirements to participate 
in SNAP.

    The ``convenience store'' category of EBT retailers is of 
particular concern (e.g., gas stations, food marts, party stores). The 
majority of EBT trafficking occurs in these venues. These 
establishments typically do not stock the type of eligible food 
products that satisfy the original intent of the SNAP program. EBT 
redemptions often exceed eligible food inventory at these locations. We 
recommend increasing the minimum eligible food inventory requirements 
of the four major food groups to be stocked for sale at convenience 
store category retailers. An alternative option is to require EBT 
retailers to submit food inventory records on a frequency basis 
(quarterly or semi-annually) in order to reconcile with EBT redemptions 
which could serve as a deterrent to trafficking redemptions.
                                 ______
                                 
  Submitted Letter by David B. Allison, Ph.D., Distinguished Quetelet
  Endowed Professor; Associate Dean for Research & Science; Director,
  Office of Energetics; Director, Nutrition & Obesity Research Center,
    Department of Nutrition Sciences, School of Health Professions,
                  University of Alabama at Birmingham
Tuesday, February 14, 2017

  Hon. K. Michael Conaway,
  Chairman,
  House Committee on Agriculture,
  Washington, D.C.

    Thank you for inviting me to testify before the House Committee on 
Agriculture for your February 16, 2017 meeting.
    I regret that I will be unable to join you at that meeting, but 
instead wanted to offer you some thoughts, information, and materials 
that may be helpful to you and the Committee in your deliberations. I 
reference several articles below and include them, as well as my 
current CV,* as enclosed attachments to this e-mail.
---------------------------------------------------------------------------
    * The document referred to is retained in Committee file.
---------------------------------------------------------------------------
    Before proceeding further, I wish to emphasize that the opinions 
below are my own and I am not speaking on behalf of my university or 
any other organization.
I. The Challenge in Predicting Intervention Effects
    Some individuals may assert that if society implements a particular 
policy, scientists can predict that it will have a particular effect on 
obesity levels. In the vast majority of cases, at present, such 
statements are unwarranted. This is so for two reasons.
    First, human physiology and even more so human behavior are complex 
and insufficiently understood to permit confident conclusions about how 
even the average person will respond to some intervention, let alone to 
predict with confidence how any one individual will respond, without 
performing an experiment to actually observe the effects. That is why 
scientists do randomized controlled trials (RCTs) to test the effects 
of things. If you look at this website (http://
www.obesityandenergetics.org/) under the category ``Contrary or Null 
Findings,'' in each weekly entry, you will see many examples of this 
unpredictability of intervention effects. That does not mean that 
scientists have no ability to predict effects, but rather that our 
ability is rather limited.
    Second, some will posit that if it is known that an intervention 
affects energy (calorie) intake or expenditure by a particular amount, 
then one can calculate the expected weight or obesity change that will 
result from such an intervention using validated mathematical models 
(for such a claim, see: http://www.ajpmonline.org/article/S0749-
3797(13)00269-9/abstract). The problem with such reasoning is that 
these calculations assume that people take no compensatory action, 
i.e., that they do not change their food intake, physical patterns, or 
any other factors that influence weight in response to the proposed 
intervention. However, much evidence indicates that people do take such 
compensatory actions (see: https://www.ncbi.nlm.nih.gov/pmc/articles/
PMC4516704/). As a result, interventions generally have far lesser 
impact on body weight than one might initially predict.
II. Myths & Presumptions in Nutrition and Obesity.
    Many academics or nutrition or obesity experts may assert that a 
particular thing is known to be true about nutrition or obesity. In 
some cases, they will be correct. However, experience shows that in 
many cases, propositions asserted to be true by such experts turn out 
to be either false or unsupported presumptions. Therefore, when any 
assertions are made, the complete scientific evidence supporting those 
assertions should be requested. Two papers which discuss the commonness 
of mistaken beliefs about nutrition or obesity are these:

   Casazza, K., Fontaine, K.R., Astrup, A., Birch, L., Brown, 
        A.W., Bohan Brown, M.M., Durant, N., Dutton, G., Foster, E.M., 
        Heymsfield, S.B., McIver, K., Mehta, T., Menachemi, N., Newby, 
        P.K., Pate, R., Rolls, B. J., Sen, B., Smith, D. L., Thomas, 
        D., & Allison, D. B. (2013). Myths, Presumptions, and Facts 
        about Obesity. New England Journal of Medicine, Jan. 31; 
        368(5): 446-54. doi: 10.1056/NEJMsa1208051. https://
        www.ncbi.nlm.nih.gov/pubmed/23363498.

   Allison D.B., Assaganya-Riera J., Burlingame B., Brown A., 
        Le Coutre J., Dickson S.L., Van Eden W., Garssen J., 
        Hontecillas R., Khoo C.S., Knorr D., Kussmann M., Magiestretti 
        P.J., Mehta T., Meule Adrian, Rychlik M., & Vogele C. (2015). 
        Goals in Nutrition Science 2015-2020. Frontiers in Nutrition, 
        Sep 2015 2:26. doi: 10.3389/fnut.2015.00026. http://
        journal.frontiersin.org/article/10.3389/fnut.2015.00026/
        abstract.
III. Separating the Moral, Social, and Legal Issues from the Scientific 
        Issues
    It is important not to conflate the moral, social, and legal issues 
with the scientific issues in policy questions around nutrition and 
weight. The scientific information can inform the policy decision, but 
generally cannot determine the best policy decision, because moral, 
social, and legal factors are also involved. In some cases, moral, 
social, or legal factors may be overwhelming and may appropriately 
drive a decision largely independently of data.
    You have asked me about the wisdom of restriction on purchases of 
certain food items with SNAP benefits.
    Some persons might offer reasonable arguments for such restriction 
which rely minimally on data. Here the values of beneficence (wanting 
to help people) and responsible stewardship of taxpayer dollars 
predominate. Such persons could argue that certain foods (e.g., 
confections, pastries, sugar-sweetened beverages) are luxuries which 
are unnecessary for life or health and without which most persons' 
health would be no worse and possibly better. Given that, it can be 
argued that: (a) It is in the best interests of SNAP participants 
(i.e., beneficence) to not consume these items; and (b) It is 
questionable for the government to spend tax-payer money on items which 
are at best unnecessary and at worst harmful. By these arguments, one 
could, with little need to rely on specific data, argue for such 
exclusions.
    Alternatively, other persons might offer reasonable arguments 
against such restriction which rely minimally on data. Here the values 
of autonomy (allowing people to make their own choices about their 
lives) and equity (not disadvantaging lower-income persons further and 
unduly hampering their access to goods others can partake of) 
predominate. Some might argue that these are important values and 
people should have a right to decide how to spend their resources on 
food and which food choices to make, however nutritionally sound or 
unsound those choices are.
    The choice between the two perspectives above is largely not one 
that hinges on data, but rather on the differential value one places on 
beneficence and responsible stewardship of taxpayer dollars vs autonomy 
and equity. These are, of course, not the only values or factors that 
can be brought to bear on these questions. See:

   Brown, A. & Allison, D.B. (2013). Unintended consequences of 
        obesity-targeted health policy. Virtual Mentor. 2013 Apr. 1; 
        15(4):339-46. doi: 10.1001/virtualmentor.2013.15.4.pfor2-1304. 
        http://journalofethics.ama-assn.org/2013/04/pfor2-1304.html.
IV. Standards of Evidence for Scientific Conclusions vs. Policy 
        Decisions
    A frequent question is ``what is the standard of evidence for 
effectiveness of a policy needed to justify a decision to enact a 
policy?'' The answer is that there is no single standard that applies 
in all contexts and this is a matter of social and legal judgment, not 
scientific judgement. In contrast, there are standards (albeit with 
some judgement still involved) for drawing scientific conclusions about 
the effects of interventions or policies. I raise this important 
distinction because this distinction is sometimes blurred by those who 
feel strongly that it is reasonable to move forward with a decision to 
take some action. Such individuals sometimes seem to feel compelled to 
dispute a data-based conclusion that evidence is insufficient to show 
the proposed action will have its desired effects. However, 
definitiveness in a decision to act despite uncertainty about drawing a 
conclusion, poses no contradiction. These ideas are discussed more 
fully in these two papers.

   Allison, D.B. (2011). Evidence, Discourse, and Values in 
        Obesity-Oriented Policy: Menu-Labeling as a Conversation 
        Starter. International Journal of Obesity, Apr.; 35(4): 464-71. 
        http://www.nature.com/ijo/journal/v35/n4/full/ijo201128a.html.

   Richardson, M.B. Williams, M.S., Fontaine, K.R., & Allison, 
        D.B. (in press). The development of scientific evidence for 
        health policies for obesity: why and how. International Journal 
        of Obesity.
V. Information on Sugar Sweetened Beverages and Weight
    You have specifically asked me about the effects of sugar-sweetened 
beverages (SSBs) on weight. Two papers I have written on this topic 
are:

   Kaiser, K.A., Shikany, J.M., Keating, K.D. & Allison, D.B. 
        (2013). Will reducing sugar-sweetened beverage consumption 
        reduce obesity? Evidence supporting conjecture is strong, but 
        evidence when testing effect is weak. Obesity Reviews, Aug.; 
        14(8): 620-33. doi: 10.1111/obr.12048. https://
        www.ncbi.nlm.nih.gov/pmc/articles/PMC3929296/.

   Allison, D.B. (2014). Liquid calories, energy compensation, 
        and weight: what we know and what we still need to learn. 
        Invited Commentary. British Journal of Nutrition, Feb.; 
        111(3):384-6. doi: 10.1017/S0007114513003309. https://
        www.ncbi.nlm.nih.gov/pmc/articles/PMC4973863/.
VI. Biases and Emotion
    The topics you are addressing are ones where many strong interests 
are at play. These interests include selfless interests in benefitting 
members of our country, economic interests, and personal interests. 
Consideration of this fact is important for at least two reasons:

    A. Some will try to discredit the statements of individuals who 
have some connection to commerce involving food or agriculture,\1\ 
based on claims that they are biased. In considering this, persons 
interested in reason and rationality should:
---------------------------------------------------------------------------
    \1\ For the record, I disclose that I have received funds from 
multiple for-profit, not-for-profit, and government organizations with 
interests in nutrition and obesity, including commodity groups and 
food, beverage, and restaurant companies.

  1.  First and foremost note that in Science, three things matter: (a) 
            The data; (b) The methods by which the data were collected 
            which give them their probative value; and (c) The logic by 
            which the data are connected to conclusions. Everything 
---------------------------------------------------------------------------
            else is a distraction.

  2.  The claim that research produced by those with financial 
            connections to food and agricultural commerce are biased 
            has not been demonstrated. See:

       http://jamanetwork.com/journals/jamainternalmedicine/
            articleabstract/
              2517951.

       https://www.theatlantic.com/health/archive/2017/01/the-
            limits-of-
              sugarguidelines/512045/.

       http://journals.sagepub.com/doi/abs/10.1177/
            0162243912456271.

  3.  Trying to overturn arguments or discredit individuals based on 
            their personal characteristics is argumentum ad hominem. It 
            is logically invalid, uncivil, and unethical. See:

       http://www.nature.com/ijo/journal/v38/n5/full/
            ijo201432a.html.

       http://www.prnewswire.com/news-releases/the-obesity-
            society-encourages-
              science-industry-collaborations-to-support-obesity-
            science-public-health-
              252453321.html.

       http://utminers.utep.edu/omwilliamson/ENGL1311/
            fallacies.htm.

    B. Interests other than financial connections to for-profit groups 
can create biases. Therefore,the scientific bases of everyone's 
statements need to be scrutinized. See the articles below.

   Cope, M., Allison, D.B. (2010). White Hat Bias: A Threat to 
        the Integrity of Scientific Reporting. Acta Paediatrica, Nov.; 
        99(11): 1615-7. https://www.ncbi.nlm.nih.gov/pubmed/21039822

   Cope, M. B. & Allison, D. B. (2010). White Hat Bias: 
        Examples of its Presence in Obesity Research and a Call for 
        Renewed Commitment to Faithfulness in Research Reporting. 
        International Journal of Obesity, 34(1): 84-8. https://
        www.ncbi.nlm.nih.gov/pubmed/19949416.
VII. Things You Can Do to Enhance The Science
    Finally, there are things your Committee can do to enhance what 
society knows on questions about the effects of interventions. For 
questions such as ``What is the effect of some intervention on health 
or weight,'' the best way to answer that question, if feasible, is with 
randomized controlled trials (RCTs).

   When such trials exist, your Committee could request the raw 
        data from all investigators who have conducted these RCTs and 
        commission a statistician to analyze all the data together in 
        an open and transparent manner and issue a public report to 
        you.

   When such trials do not exist or are insufficient to 
        generate confident conclusions, your Committee could take steps 
        to have a large, statistically powerful, well-designed RCT 
        commissioned and executed.

    In doing so, you would add substantially to our objective knowledge 
about outcomes.
    I hope this information is helpful to you in your deliberations.
            Sincerely,
            
            
David B. Allison, Ph.D.
                              attachment 1
The Caloric Calculator: Average Caloric Impact of Childhood Obesity 
        Interventions
August 2013
Y. Claire Wang, M.D., Sc.D., Amber Hsiao, M.P.H., C. Tracy Orleans, 
Ph.D., Steven L. Gortmaker, Ph.D.*
---------------------------------------------------------------------------
    * From the Department of Health Policy & Management (Wang, Hsiao), 
Mailman School of Public Health, Columbia University, New York, New 
York; the Robert Wood Johnson Foundation (Orleans), Princeton, New 
Jersey; and Department of Society, Health, and Human Development 
(Gortmaker), Harvard School of Public Health, Cambridge, Massachusetts
    Address correspondence to: Y. Claire Wang, M.D., Sc.D., Department 
of Health Policy and Management, Mailman School of Public Health, 
Columbia University, 600 W 168th St, Rm 602 New York NY 10032. E-mail: 
[email protected].
    0749-3797/$36.00
    http://dx.doi.org/10.1016/j.amepre.2013.03.012
---------------------------------------------------------------------------
This activity is available for CME credit. See page A4 for information.

          Background: The childhood obesity epidemic reflects the daily 
        accumulation of an ``energy gap''--excess calories consumed 
        over calories expended. Population-level interventions to 
        reverse the epidemic can be assessed by the degree to which 
        they increase energy expenditure and/or reduce caloric intake. 
        However, no common metric exists for such comparative 
        assessment.
          Purpose: To develop a common metric, the Average Caloric 
        Impact (ACI), for estimating and comparing population-level 
        effect sizes of a range of childhood obesity interventions.
          Methods: An iterative, collaborative process was used to 
        review literature from 1996 to 2012 and select illustrative 
        interventions showing effects on youth diet and/or activity 
        levels, energy balance, and weight. The ACIs of physical 
        activity interventions were estimated based on program reach, 
        frequency, duration, and intensity and mean body weight of the 
        targeted age and gender group from the 2009-2010 National 
        Health and Nutrition Examination Survey. ACIs of dietary 
        interventions were based on reach and changes in foods and/or 
        beverages consumed.
          Results: Fifteen interventions informed by 29 studies were 
        included, ranging from individual behavioral to population-
        level policies. A web tool, the Caloric Calculator, was 
        developed to allow researchers and policymakers to estimate the 
        ACIs of interventions on target populations with reference to 
        energy gap reductions required to reach the nation's Healthy 
        People childhood obesity goals.
          Conclusions: The Caloric Calculator and ACIs provide 
        researchers and policymakers with a common metric for 
        estimating the potential effect sizes of various interventions 
        for reducing childhood obesity, providing a platform for 
        evidence-based dialogues on new program or policy approaches as 
        data emerge.
          (Am. J. Prev. Med. 2013; 45(2): e3-e13) 
        2013 American Journal of Preventive 
        Medicine.
Background
    The obesity epidemic costs the U.S. $147-$210 billion in annual 
healthcare costs.\1\ Although the trends have shown some signs of 
leveling, more than \1/3\ of U.S. adults and nearly 17% of children and 
adolescents are obese.\2\ As a result, it was predicted that one in 
three children born in 2000 would be diagnosed with type 2 diabetes in 
his or her lifetime.\3\
    The rise in childhood obesity since the early 1970s reflects the 
accumulation of the small daily ``energy gap''--the excess of calories 
consumed over calories expended.4-5 Previous analyses 
estimated that an average surplus of 110-165 kcal/day in energy 
accounted for the excess weight gain seen in U.S. children and youth 
over a 10 year period.\4\ Thus, effective interventions would have to 
bring about a net reduction in this energy gap to reverse the epidemic. 
A recent study estimated that among U.S. children aged 2-19 years, a 
net reduction of 64 kcal/day per capita in energy surplus would be 
needed to achieve the Healthy People 2020 childhood obesity goals, with 
a range from 22 kcal/day for those aged 2-5 years, to 77 kcal/day for 
those aged 6-11 years, 98 kcal/day for those aged 12-19 years, and much 
higher levels among those who are already overweight or obese.\5\
    The evidence base for population-level interventions to reduce 
childhood obesity levels has grown rapidly, ranging from strategies to 
change individual behaviors to those that seek to alter policies, 
environments, and social norms. In most cases, however, these policies 
or programs are evaluated independently. No common metric exists to 
allow comparative assessments of effects across interventions with 
varied configurations for a target population.6-7
    In the current paper, the Average Caloric Impact (ACI) is proposed 
as a metric to gauge the population-level average effect on daily 
calories expended/consumed. This metric was applied to an illustrative 
set of interventions evaluated in the literature. Greater emphasis was 
placed on population-, school-, or state-level programs than on medical 
treatments of overweight/obese youth. The results are presented using a 
user-friendly web tool, the Caloric Calculator.
Methods
Selection of Interventions
    Using recently published reviews, a set of obesity prevention 
interventions targeting U.S. children and adolescents aged 2-5 years 
(preschool); 6-11 years (primary school); 12-14 years (middle school); 
and/or 15-18 years (high school) was selected. Target populations were 
defined by grade level based on the divisions within the typical K-12 
system. Mean height and weight for each age group (by gender) were 
based on the nationally representative 2009-2010 National Health and 
Nutrition Examination Survey (NHANES).
    From an initial list of 67 studies published between 2000 and 2009, 
as reviewed by Brennan, et al.,\8\ only seven physical activity 
interventions were included that lasted >6 months and reported outcome 
measures that were sufficient to have an influence on calories. For 
example, several studies of school lunch programs or wellness policies 
were excluded because they reported consumption of only specific 
nutrients (e.g., % fat), and/or servings of fruits and vegetables, 
rather than changes in total calories consumed or body weight. 
Similarly, many evaluations of physical activity programs did not use 
objective measures of activity levels (e.g., accelerometers) and thus 
were unable to inform changes in energy expenditure.
    An iterative and collaborative process was used to identify an 
additional 22 studies published between 1996 and 2012; of these, 12 
were empirical studies that met the research design and measurement 
standards used in the Brennan, et al., review. The remaining studies 
provided inputs for the model-based estimates. For dietary 
interventions selected, the studies assessed changes in daily caloric 
intake before and after the intervention (e.g., California schools' 
competitive foods standards).\9\ For studies reporting changes in 
consumption of particular foods and/or beverages, published estimates 
on the average caloric contribution of these foods and beverages in the 
indicated setting (e.g., removing sugar-sweetened beverages from 
schools) \10\ were used. Strategies were categorized by implementation 
level (individual, school, state/national). Because empirical data were 
lacking for some strategies (e.g., promoting walking to schools), 
analytic models were used to incorporate available evidence to estimate 
the likely caloric effect of these strategies, if broadly implemented.
Caloric Impact Calculations
    Physical activity interventions. The physical activity 
interventions were placed into one of the following categories: (1) 
varied school physical education (PE) classes; (2) school PE 
interventions designed to increase moderate-to-vigorous physical 
activity (MVPA) levels to achieve more active PE; (3) afterschool 
physical activity programs; and (4) active commuting (e.g., walking) to 
school. When multiple high-quality studies were available within a 
category, the study with the largest effect size was typically used to 
represent the best-possible outcome and population-level 
implementation.
    The effect of the intervention on daily caloric impact was 
estimated based on the calculated basal metabolic rate (BMR, which is a 
function of age, gender, and body weight), as well as the frequency 
(e.g., twice a week); duration (e.g., 30 minutes); and the intensity of 
the physical activity (e.g., moderate/vigorous). BMR for an average-
weight child is calculated based on published equations.\11\ 
Intervention intensity was estimated in METs, representing the amount 
of energy expended from carrying out a specific activity relative to 
sitting quietly (MET value of 1.0) for a defined period of time. For 
instance, walking at a pace of 3 miles per hour represents an average 
intensity of 3.3 METs, which burns 3.3 times as many calories than 
sitting quietly for the same individual.\12\
    Pre-intervention activity levels were based on published baseline 
measures of study participants and/or national averages. When MET 
values were not reported, activity-specific MET values from the 
Ainsworth Compendium for adults \12\ were combined with calculated 
youth-specific BMR estimates, following recommendations by Ridley, et 
al.\13\ Table 1 provides examples of how various inputs affect the 
number of calories expended by different physical activity 
interventions.
    Dietary interventions. Dietary interventions were similarly 
reviewed and categorized. For example, a number of interventions only 
measured changes in fruit and vegetable intake, and were excluded 
because net impact on caloric intake could not be estimated. One study 
that empirically measured the caloric impact of competitive food 
policies in high schools was included.\9\ The other five dietary 
interventions (e.g., reducing intake of calories from chips) were 
estimated based on the authors' calculations.
    For policy interventions with limited direct, empirical data (e.g., 
removing sugar-sweetened beverages [SSBs] from schools, and a portion-
size cap on sugary drinks sold in New York City),\14\ dietary data from 
NHANES were used to inform the baseline consumption level among those 
who would be hypothetically affected by the policy. For example, NHANES 
1999-2004 showed that SSBs contributed an average of 224 kcal/day to 
the overall caloric intake of U.S. children and adolescents, and 7-15% 
of SSBs were consumed in schools.\10\ The estimated caloric impact of 
replacing all SSB intake from schools (in session 180 days a year) with 
water was averaged across the whole calendar year.
    Combined physical activity/dietary interventions. Sonneville and 
Gortmaker \15\ have estimated that every 1 hour increase in TV watching 
is associated with a 105.5-kcal increase in net total energy intake, or 
a 92-kcal increase in energy intake for video- or computer-game 
playing. Their findings are consistent with a previously published 
randomized trial, which found that reducing TV watching among children 
led to lower caloric intake.16 It was hypothesized that children who 
spend more time watching TV or playing video games may be more exposed 
and/or influenced by food advertising through characters present in 
commercials and interactive games that can shape food preferences and 
intake.17-19

         Table 1. Daily Caloric Effects of Physical Activity for Select Groups Using Schofield Equations
----------------------------------------------------------------------------------------------------------------
                                                                                      Inputs
                                                                ------------------------------------------------
                  Average   Schofield equation                                                         Caloric
  Population      weight         (BMR=) a         Intervention                Duration     School-      effect
                   (kg)                                            D METs    (minutes/    based? b    (kcal/day)
                                                                                day)                      c
----------------------------------------------------------------------------------------------------------------
Boys, age in
 years:
  2-5                   18  22.706 kg + 504.3   Add 30 minutes/        2.3           30         No            44
                                                 day of walking
  6-11                  34  22.706 kg + 504.3   Add 30 minutes/          7           30         No           186
                                                 day of jogging
  12-14                 59  17.686 kg + 658.2   Add 15 minutes/        2.6           15        Yes            23
                                                 day of PE
  15-18                 77  17.686 kg + 658.2   Implement SPARK        3.5           30        Yes            73
Girls, age in
 years:
  2-5                   17  20.315 kg + 485.9   Add afterschool        3.5         10.5        Yes            11
                                                 program
  6-11                  35  13.384 kg + 485.9   Make PE more      Varies d           60        Yes             9
                                                 active
  12-14                 57  13.384 kg + 692.6   Add 30 minutes/        2.6           30        Yes            39
                                                 day of PE
  15-18                 65  13.384 kg + 692.6   Add 10 minutes/          7           10         No            76
                                                 day of jogging
----------------------------------------------------------------------------------------------------------------
a The Schofield equations are grouped by gender and age groups (broken down as 0-3 years, 3-10 years, and 10-18
  years). Because of this, some age groups have the same equations.
b If the intervention is applied over a full school year, it multiples the caloric impact by 180 days. This is
  then averaged over 365 days to account for no change in activity on holidays, weekends, and summer vacation.
c Daily caloric impact = (BMR  D METs  duration in minutes)  1,440 minutes/day.
d The MET value for ``Make PE more active'' is a composite of MET values from five different activities, based
  on the Ainsworth Compendium: \12\ lying down, sitting, standing, walking, and running. The change in METs from
  the intervention depends on user input of baseline versus target % MVPA. BMR, basal metabolism rate; MVPA,
  moderate-to-vigorous physical activity; PE, physical education; SPARK, Sports, Play, and Active Recreation for
  Kids.

Online ``Caloric Calculator'' Tool
    Accompanying the current paper is a web-based tool 
(www.caloriccalculator.org) designed to help users visualize and query 
the estimated caloric effects of defined interventions within a defined 
target population. Programmed in PHP script for HTML, the tool allows 
users to choose one or more interventions and customize their 
configurations. For example, the user can select as the target ``Boys'' 
and ``Middle School (12-14)'' from the dropdown menu, and ``implement'' 
an intervention to increase PE intensity (e.g., moderate/vigorous) for 
a duration of time by specifying the baseline MVPA (default is 37%) and 
desired post-intervention level (e.g., 50% as recommended).\20\
    The resulting caloric effect is benchmarked against two ``energy 
gap'' goals: to return the prevalence of obesity to (1) the early 1970s 
and/or (2) the Year-2000 levels. The former more ambitious goal 
corresponds to the original goals set in Healthy People 2010; \21\ the 
latter provides a rough estimate of the current, more modest Healthy 
People 2020 goals.\22\ The methodology underlying the calculations of 
these targets for various population subgroups has been described 
previously.\5\ All interventions listed assume that no compensatory 
changes affecting daily energy balance occur, beyond any effects 
observed in the empirical studies cited. For example, the ACI of 
increasing MVPA from 37% to 50% during PE classes assumes that students 
will not consume additional calories to compensate for additional 
physical activity, or that removing a food item from one's diet does 
not result in increased consumption of other foods or beverages.
Results
    The estimated caloric effect of the 15 interventions in the tool, 
by gender and age group, are summarized in Tables 2 and 3. For 
instance, for high school boys and girls, adding 15 minutes of PE time 
per day for a full school year was estimated to increase mean energy 
expenditure by 25 kcal/day; replacing SSBs with water in schools for 
the same group would reduce mean energy intake by 15 kcal/day. For this 
group, however, an average per capita reduction of 82 kcal/day in 
energy surplus would be needed to meet the Healthy People 2020 obesity 
prevalence goal of reducing obesity rates from 20.8% to 14.8%. 
Returning to the early 1970s level of obesity prevalence--the target 
set by the more ambitious Healthy People 2010 goal--would require an 
average per capita reduction in energy gap of 217 kcal/day. These 
estimates suggest that although any single intervention may not be 
sufficient to achieve the Healthy People goals, substantial progress 
could be made through a combination of feasible, sustained policy and 
environmental interventions.

 Table 2. Caloric Impact of Physical Activity Interventions for Average
                          Student, By Age Group
------------------------------------------------------------------------
                            Inputs for caloric calculations
                          ----------------------------------
               Population                            Avg.
 Intervention     (age                             caloric   Assumptions
                 group,      Target   Avg.weight    impact
                 years)      METs a     (lbs) b     (kcal/
                                                     day)
------------------------------------------------------------------------
                            Modeled estimates
------------------------------------------------------------------------
Add walking    Both (2-5)        3.3          39         21  Same
 at a 3-mph    Both (6-          3.3          76         30   baseline
 pace, 15       11)              3.3         127         38   (1.0,
 minutes/day   Both (12-                                      sitting
                14)                                           quietly)
                                                              and target
                                                              METs for
                                                              all ages,
                                                              based on
                                                              Ainsworth,
                                                              et
                                                              al.,\12\
                                                              and
                                                              Ridley, et
                                                              al.\13\
               Both (15-         3.3         157         43
                18)
Add jogging    Both (2-5)        8.0          39         64  Same
 at a 5-mph    Both (6-          8.0          76         90   baseline
 pace, 15       11)              8.0         127        115   (1.0,
 minutes/day   Both (12-         8.0         157        130   sitting
                14)                                           quietly)
               Both (15-                                      and target
                18)                                           METs for
                                                              all ages,
                                                              based on
                                                              Ainsworth,
                                                              et
                                                              al.,\12\
                                                              and
                                                              Ridley, et
                                                              al.\13\
Walking to     Both (2-5)        3.3          39          9  Interventio
 and from      Both (6-          3.3          76         12   n model
 school         11)                                           estimates
 (roundtrip)                                                  based on
                                                              METs from
                                                              Ainsworth,
                                                              et
                                                              al.,\12\
                                                              and
                                                              Ridley, et
                                                              al.,\13\
               Both (12-         3.3         127         15    and
                14)              3.3         157         17   published
               Both (15-                                      data on
                18)                                           average
                                                              distances
                                                              from
                                                              schools
                                                              and
                                                              students
                                                              living
                                                              within 1
                                                              mile of
                                                              school.23	
                                                              24
                                                             Caloric
                                                              impact
                                                              estimate
                                                              uses METs
                                                              of 1.0 as
                                                              baseline
                                                              (i.e.,
                                                              sitting in
                                                              car).
                                                             Implemented
                                                              for a full
                                                              academic
                                                              year.b
------------------------------------------------------------------------
                           Empirical estimates
------------------------------------------------------------------------
Add school PE  Both (2-5)        3.4          39         11  McKenzie,
 time, 15      Both (6-          3.4          76         15   et
 minutes/day    11)                                           al.,\25\
                                                              estimate
                                                              3.4 METs
                                                              for
                                                              elementary
                                                              school PE.
                                                              Same value
                                                              used for
                                                              pre-
               Both (12-         3.6         127         21    school.
                14)              3.7         157         25   Nader, et
               Both (15-                                      al.,\26\
                18)                                           estimate
                                                              3.6 METs
                                                              for middle
                                                              school PE.
                                                              Smith, et
                                                              al.,\27\
                                                              estimate
                                                              3.7 METs
                                                              for high
                                                              school PE.
                                                              Implemente
                                                              d for a
                                                              full
                                                              academic
                                                              year.b
Make current   Both (2-5)        4.5          39          3  MET values
 PE more       Both (6-          4.5          76          4   used at
 active, 30     11)              4.5         127          6   baseline
 minutes/day   Both (12-                                      and target
                14)                                           is a
                                                              composite
                                                              of
                                                              estimated
                                                              MET
                                                              values,
                                                              based on
                                                              Wu, et
                                                              al.,\7\
                                                              and
                                                              Ainsworth,
                                                              et
                                                              al.,\12\
                                                              (4.5 METs)
               Both (15-         4.5         157          6    for MVPA,
                18)                                           1.8 METs
                                                              for non-
                                                              MVPA).
                                                             Because of
                                                              high
                                                              variance
                                                              in METs,
                                                              baseline
                                                              activity
                                                              levels,
                                                              and
                                                              population
                                                              characteri
                                                              stics
                                                              between
                                                              CATCH,20,
                                                              26, 28	29
                                                              MSPAN,\25\
                                                              and TAAG
                                                              30	35
                                                              interventi
                                                              ons, same
                                                              averaged
                                                              MVPA% used
                                                              for all
                                                              age
                                                              groups.
                                                             Changing
                                                              the
                                                              intensity
                                                              of current
                                                              PE time
                                                              (not
                                                              adding
                                                              additional
                                                              PE time).
                                                             Base case
                                                              increases
                                                              MVPA from
                                                              37% to
                                                              50%, based
                                                              on DHHS
                                                              national
                                                              recommenda
                                                              tion.\20\
                                                             Implemented
                                                              for a full
                                                              academic
                                                              year.b
Implement      Both (2-5)        7.2          39         34  7.2 METs
 SPARK using   Both (6-          7.2          76         48   for PE
 only PE        11)              7.2         127         58   specialist
 specialists   Both (12-         7.2         157         64   s for
 to teach PE,   14)                                           SPARK
 30 minutes/   Both (15-                                      interventi
 day            18)                                           on from
                                                              McKenzie,
                                                              et
                                                              al.,\36\
                                                              and
                                                              Sallis, et
                                                              al.,\37\
                                                              used in
                                                              calculatio
                                                              n to
                                                              demonstrat
                                                              e maximum
                                                              potential
                                                              of
                                                              interventi
                                                              on
                                                              (compared
                                                              to 5.8
                                                              METs for
                                                              trained
                                                              classroom
                                                              teachers).
                                                             Adding PE
                                                              time to
                                                              existing
                                                              PE time.
                                                             Baseline
                                                              METs
                                                              assumed to
                                                              be 3.4 for
                                                              preschool
                                                              and
                                                              elementary
                                                              ,\25\ 3.6
                                                              for
                                                              middle,\26
                                                              \ and 3.7
                                                              for high
                                                              school.\27
                                                              \
Add            Both (2-5)        4.5          39         11  Gortmaker,
 afterschool   Both (6-          4.5          76         16   et
 physical       11)              4.5         127         20   al.,\38\
 activity      Both (12-                                      estimate
 program        14)                                           %4.0 METs
                                                              in
                                                              interventi
                                                              on. 4.5
                                                              METs is
                                                              used here
                                                              as a
                                                              conservati
                                                              ve
                                                              composite
                                                              target
                                                              based on
                                                              Wu, et
                                                              al.\7\
               Both (15-         4.5         157         22  Same
                18)                                           baseline
                                                              (1.0,
                                                              sitting
                                                              quietly)
                                                              and target
                                                              METs for
                                                              all ages,
                                                              based on
                                                              Ainsworth,
                                                              et
                                                              al.,\12\
                                                              and
                                                              Ridley, et
                                                              al.\13\
                                                             Implemented
                                                              for a full
                                                              academic
                                                              year.b
------------------------------------------------------------------------
a METs expresses how much energy is needed for physical activities.
  Caloric impacts expressed in this table are calculated assuming the
  physical activity is above a baseline of 1.0 METs (except where noted,
  as with implementing SPARK), which is the baseline resting metabolic
  rate when sitting quietly.
b Intervention is applied over a full school year (on average, 180
  days). The total caloric impact is averaged over 365 days to account
  for no change in activity on holidays, weekends, and summer vacation.
  CATCH, The Child and Adolescent Trial for Cardiovascular Health;
  MSPAN, The Middle-School Physical Activity and Nutrition intervention;
  MVPA, moderate-to-vigorous physical activity; PE, physical education;
  SPARK, Sports, Play, and Active Recreation for Kids; TAAG, The Trial
  of Activity for Adolescent Girls.


             Table 3. Caloric Impact of Dietary and Other Interventions for Average Student By Group
----------------------------------------------------------------------------------------------------------------
                                                     Inputs for caloric calculations
                                               ------------------------------------------
                            Population (age                                     Avg.
      Intervention           group, years)                      Affected       caloric          Assumptions
                                                  Amount a      pop., % b   impact (kcal/
                                                                                day)
----------------------------------------------------------------------------------------------------------------
                                                Modeled estimates
----------------------------------------------------------------------------------------------------------------
Reduce unhealthy food    All                     1-oz bag of           100           154  Intervention models
 intake                  All                       chips per                               estimates based on
                                                         day           100            55   published caloric
                                                1 cookie per                               values of average bag
                                                         day                               of regular potato
                                                                                           chips and single Oreo
                                                                                           cookie.
Reduce SSB intake        All                       12-oz can           100           136  Intervention models
                         All                         per day           100           240   estimates based on
                                                20-oz bottle                               published caloric
                                                     per day                               values of average can
                                                                                           or bottle of regular
                                                                                           caffeinated cola.
Replace SSBs with water  Both (2-5)                      124           5.5             3  Affected population
 in schools              Both (6-11)                     184           6.5             6   and amounts based on
                         Both (12-14)                    301          10.3            15   published analysis
                         Both (15-18)                    301          10.3            15   from Wang, et al.\10\
                                                                                           Implemented for a
                                                                                           full academic year.c
Switch from 1 cup of     Both (2-5)                0.64 cups          48.4             7  Averaged grams/cup and
 sugary cereals to       Boys (2-5)                0.64 cups          47.3             7   standardized serving
 cereals scored highest  Girls (2-5)               0.64 cups          49.6             7   sizes of top ten \39\
 in nutritional quality  Both (6-11)               0.93 cups          39.5             6   and bottom ten \40\
                         Boys (6-11)               0.93 cups          40.2             6   cereals by nutrition
                         Girls (6-11)              0.94 cups          38.8             6   score, as determined
                         Both (12-14)              1.16 cups          34.5             5   by CerealFACTS.
                         Boys (12-14)              1.32 cups          35.5             5   org.\41\
                         Girls (12-14)              1.0 cups          33.5             5  Affected population
                         Both (15-18)              1.15 cups          26.6             4   and average grams/
                         Boys (15-18)              1.25 cups          26.1             4   serving consumed
                         Girls (15-18)             1.06 cups          27.0             4   based on analysis of
                                                                                           NHANES 2007-2010 data
                                                                                           on 24-hour dietary
                                                                                           recall.
                                                                                          Proportion of cups
                                                                                           consumed in Amount
                                                                                           column based on
                                                                                           standardized 39.2
                                                                                           grams/cup (as
                                                                                           described above), and
                                                                                           grams/serving from
                                                                                           NHANES.
Pass NYC's proposed      Both (2-5)                     24.2           0.6             0  Amount is average
 sugary drink size       Boys (2-5)                     21.1           0.9             0   kilocalorie reduction
 limit                   Girls (2-5)                    32.3           0.4             0   per day if limited
                         Both (6-11)                    67.9           5.1             3   consumption to 16 oz/
                         Boys (6-11)                    70.0           6.1             4   day as in Elbel, et
                         Girls (6-11)                   64.9           4.2             3   al.,\42\ and Wang, et
                         Both (12-14)                   93.6           9.4             9   al.\14\
                         Boys (12-14)                  109.3          10.1            11  Affected population
                         Girls (12-14)                  77.7           8.7             7   and average
                         Both (15-18)                  111.8          13.3            15   kilocalorie reduction
                         Boys (15-18)                  120.3          15.3            18   based on analysis of
                         Girls (15-18)                 100.1          11.2            11   NHANES 2007-2010 data
                                                                                           on 24-hour dietary
                                                                                           recall.
                                                                                          Those consuming >16 oz
                                                                                           limit consumption to
                                                                                           maximum of 16 oz/day
                                                                                          No ``upsizing'' occurs
                                                                                           (i.e., individuals
                                                                                           purchase more than
                                                                                           one 16-oz beverage to
                                                                                           compensate for size
                                                                                           limit).
                                                                                          SSB definition
                                                                                           includes sodas,
                                                                                           sports drinks, fruit
                                                                                           drinks and punches,
                                                                                           low-calorie drinks,
                                                                                           sweetened tea, and
                                                                                           other sweetened
                                                                                           beverages consumed in
                                                                                           food service
                                                                                           establishments.
                                                                                          Implemented
                                                                                           nationally.
----------------------------------------------------------------------------------------------------------------
                                               Empirical estimates
----------------------------------------------------------------------------------------------------------------
Pass California's        Both (15-18)                  157.8           100            78  Taber, et al.,\9\
 competitive food                                                                          estimate 157.9 kcal
 nutrition standards in                                                                    per weekday fewer
 high schools                                                                              calories consumed in
 nationally                                                                                California high
                                                                                           schools, compared to
                                                                                           14 other states with
                                                                                           weaker competitive
                                                                                           food laws states.
                                                                                          The intervention only
                                                                                           applies to high
                                                                                           school students.
                                                                                          Implemented for a full
                                                                                           academic year.c
Reduce TV viewing, 60    All                             106           100           106  Sonneville and
 minutes/day                                                                               Gortmaker \38\
                                                                                           estimate TV watching
                                                                                           and video/computer
                                                                                           game playing
                                                                                           associated with 105.5-
                                                                                           kcal/hour and 91.8-
                                                                                           kcal/hour increase in
                                                                                           total energy intake
                                                                                           in boys aged 13-15
                                                                                           years and girls aged
                                                                                           12-14 years. Epstein,
                                                                                           et al.,\16\ and
                                                                                           Miller, et al.,\18\
                                                                                           report similar
                                                                                           changes in energy
                                                                                           intake.
Reduce video- or         All                              92           100            92  Same calorie change
 computer-game playing                                                                     for other age groups
 time, 60 minutes/day
----------------------------------------------------------------------------------------------------------------
a The amount designates the current pre-intervention consumption level of the item by the selected population;
  amounts are kilocalories unless otherwise specified.
b The impact designates the percentage of the selected eligible population that is affected by the intervention.
c Intervention is applied over a full school year (on average, 180 days). The total caloric impact is averaged
  over 365 days to account for no change in activity on holidays, weekends, and summervacation.
NHANES, National Health and Nutrition Examination Survey; NYC, New York City; SSB, sugar-sweetened beverage.

    Many of the ACI estimates built into the Caloric Calculator require 
stipulated assumptions, which are shown in detail in Tables 2 and 3, as 
well as within the web tool. For example, the calculations of energy 
expended through increased MVPA during PE involved the following 
assumptions: a national baseline of 37% MVPA during PE time,\28\ a 
target level of 50% recommended by the CDC,\20\ and 180 school days a 
year for school-based interventions. The assumed MET level for non-MVPA 
PE time was estimated as 1.8 METs, using an average of lying down, 
sitting, and standing.\12\
    The time spent on MVPA was estimated to be 4.5 METs based on the 
average of moderate physical activity (3 METs) and vigorous physical 
activity (6 METs).\7\ For example, for a typical high school adolescent 
(average weight: 157 lbs), increasing MVPA from 37% to 50% during a 
daily 30 minute PE class for a school year was estimated to produce an 
average increase in energy expenditure of 6 kcal/day--clearly 
insufficient on its own to reverse the childhood obesity epidemic. 
Further, even this small effect could potentially be diminished if 
compensation occurred for this additional caloric expenditure with 
increased food or beverage consumption.
    It is important to note that all estimates used in creating the 
Caloric Calculator were population-based. In addition, for 
interventions designed to remove a particular food or beverage from the 
diet, caloric benefits were accrued only from the population affected 
(e.g., the population affected by the NYC sugary drink portion-size cap 
was presumed to include those consuming sugary beverages of >16 ounces 
per serving, estimated to include only 12% of adolescents aged 12-19 
years).\14\
Discussion
    Reversing the nation's current childhood obesity epidemic will 
require multiple individual, behavioral, policy, environmental, and 
normative changes--through public health and clinical strategies--to 
reverse the daily accumulation of a positive ``energy gap'' that 
brought us to this point. New evidence from New York City,\43\ 
Philadelphia,\44\ California,9, 45 and Mississippi \46\ 
demonstrates that broad approaches involving multifaceted policies and 
environmental strategies have the power to halt and reverse the 
trend.\47\ However, what has been missing is a metric for estimating 
the individual and combined effects of specific interventions to 
increase children's activity levels and reduce their intake of energy-
dense, low-nutrient foods and beverages.
    This paper expands on the previously published ``energy gap'' 
framework--which estimated the magnitude of energy surplus underlying 
the obesity epidemic among U.S. youth 4-5--to examine the 
effects of various interventions, alone or in combination, to favorably 
tip the energy balance. The lack of a common metric for comparing the 
effectiveness of strategies with differing behavioral targets (i.e., 
reducing excess caloric intake and/or increasing physical activity) has 
stymied past efforts to apply analytic tools to rank existing 
strategies on their contribution to reversing the childhood obesity 
trend. The development and application of the Average Caloric Impact 
(ACI) metric and the Caloric Calculator tool offer an opportunity to 
fill this gap.
    Although the Caloric Calculator begins to address these issues, 
there are nuances in the obesity reduction equation that will require 
further research and discussion. The evidence used to estimate ACIs is 
still in many ways limited and dependent on the rigor of existing 
intervention studies and on the availability and reliability of 
intervention outcome measures (e.g., the use of objectively measured, 
versus self-reported, outcomes or ecologic associations that can be 
examined across studies). In addition, many studies focus narrowly on 
specific populations, such as middle school girls30 or a specific age 
range.29, 36, 37
    Most challenging at this stage in childhood obesity prevention 
research is the lack of high-quality studies with a sufficiently long 
follow-up. A 2011 Cochrane review of obesity prevention efforts found 
that only 14 of the 55 included studies had interventions lasting more 
than 12 months, most of which focused only on children aged 6-12 years. 
There is virtually no evidence from studies aimed at younger children 
to determine whether intervention benefits can be sustained into later 
adolescence or adulthood.\6\ Therefore, it would be inaccurate to make 
predictions of weight change from fixed caloric changes using these 
estimates, particularly given the multitude of factors that drive 
weight change over time \48\ and the large changes seen from childhood 
to adolescence.\49\
    Study populations also have varied widely with respect to racial/
ethnic composition, SES, and prevalence of obesity at baseline, 
limiting the generalizability and comparability of intervention 
effects. Thus, the tool represents the authors' best effort to assess 
the average impact if these programs were broadly implemented. Local 
contexts and subpopulation characteristics are likely to modify the 
actual outcomes. The estimates will continue to be refined and updated 
as new data emerge from periodic scans of newly published data and 
feedback from collaborators in the field of childhood obesity 
prevention. Going forward, the Calculator will be further developed to 
address specific subsets of the population or allow more user inputs to 
facilitate broader dissemination and policy discussions. For example, a 
principal of a disproportionately low-income school could use the tool 
based on the school's demographics, or parents could use the tool by 
entering their child's age, gender, and body weight.
    Despite these limitations, there is value in the Caloric 
Calculator's ability to translate evidence into practice by generating 
caloric impact estimates and projecting the potential cumulative 
effects of multicomponent interventions addressing one or both sides of 
the energy balance equation. The ACI is a summary measure of several 
dimensions of the program or policy evaluated: reach, effectiveness/
efficacy, adoption, implementation, and maintenance.\50\ These 
dimensions also convey why the net caloric impact of the same program 
will vary from population to population when implemented in the real 
world. As such, the tool is expected to offer a starting point to 
support policymakers and practitioners in using existing evidence to 
drive decision making in a more straightforward manner.
    The development of a common metric can lay the groundwork for more 
evidence-based resource allocation decisions, both in program 
implementation and in further evidence gathering. Future expansion of 
this framework may include finer granularity in the population 
targeted, such as overweight status, race/ethnicity, and urban/rural 
locations as well as concerns for equity, cost effectiveness, and other 
long-term outcomes.\47\ Further, the current review underscored the 
need to encourage the evaluations of programs and policies to use and 
report objective and comparable outcome measures, such as changes in 
activity levels (e.g., MET values); duration (e.g., minutes of MVPA 
added); net changes in calories consumed in addition to key nutrients 
or diet quality; and measured BMI whenever possible.
    Because the Caloric Calculator uses national data with the aim of 
estimating mean population-level effect sizes, the effect of an 
intervention is averaged across those who received and benefited from 
the program and those who did not. Therefore, an intervention that has 
a large effect but reaches only a small number of children may appear 
to have less of an impact at the population level. For example, an 
active transport program may target children who live within 1 mile of 
their school, which will reach at most 31% of children in Grades K-
8.\23\ The daily caloric impact, when averaged across all children, is 
therefore a fraction of the net caloric impact for those who 
participate in walking to school. Although not evaluated in the current 
study, the same consideration applies to interventions specifically 
targeted at overweight adolescents (who have an average energy gap of 
700-1,000 kcal/day).\4\
    It is important to note that although the analyses presented in 
this paper focus on intervention effects on daily energy gaps and 
obesity levels in youth, there are important health and nonhealth 
benefits gained from improving physical activity and diet that are not 
captured by the ACI measure. For instance, there is growing evidence 
that physical activity has beneficial effects on mental health outcomes 
and academic performance.\51\ Similarly, an intervention to improve the 
nutritional quality of a la carte foods and beverages improves the 
overall nutritional profile of foods consumed at school despite having 
no significant effect on the total number of calories 
sold.52-53
    Some investments in childhood obesity prevention have been 
projected to be cost effective.\54\ But without knowing what types of 
interventions to invest in, efforts may fail to produce the expected 
results. There have been many controversial, yet noteworthy, recent 
policy recommendations that will be scaled up to the national level 
(e.g., menu labeling). Without experimental evidence, however, it can 
be difficult to convince the public and policymakers of the 
implications and demonstrate the possible impact of implementation. The 
Caloric Calculator provides a novel tool for appraising these policies 
and interventions based on their potential efficacy, alone or combined, 
providing an evidence-based platform to inform practice and policy.

          The authors acknowledge the contribution of Dr. Laura K. 
        Brennan, Ph.D., M.P.H., President and CEO of Transtria LLC (St. 
        Louis, MO), and her team in the evidence-review process. The 
        authors thank Shawn Nowicki, M.P.H., and Andrew Wang, M.P.H., 
        as graduate student assistants in literature review and the 
        early development of the tool. The authors also thank Michael 
        Slaven, MA, who designed and implemented the web tool, 
        www.caloriccalculator.org, as well as Kevin Hall, Ph.D., and 
        Carson Chow, Ph.D. (NIH/National Institute of Diabetes and 
        Digestive and Kidney Diseases), for their methodologic advice 
        on the analysis.
          This work was supported by the Robert Wood Johnson Foundation 
        (grant no. 68162). This work is solely the responsibility of 
        the authors and does not represent the official views of the 
        Robert Wood Johnson Foundation.
          No financial disclosures were reported by the authors of this 
        paper.

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                              attachment 2
Predicting Adult Weight Change in the Real World: A Systematic Review 
        and Meta-Analysis Accounting for Compensatory Changes in Energy 
        Intake or Expenditure *
---------------------------------------------------------------------------
    * Received 6 May 2014; revised 19 August 2014; accepted 8 September 
2014; accepted article preview online 17 October 2014; advance online 
publication, 23 December 2014.
---------------------------------------------------------------------------
Review
E.J. Dhurandhar,[1-3, 7] K.A. Kaiser,[1, 3-4, 7] 
J.A. Dawson,[3] A.S. Alcorn,[3] K.D. Keating 
[5-6] and D.B. Allison [1, 3-4
---------------------------------------------------------------------------
    \[1]\ Nutrition Obesity Research Center, University of Alabama at 
Birmingham, Birmingham, AL, USA; [2] Department of Health 
Behavior, University of Alabama at Birmingham, Birmingham, AL, USA; 
[3] Office of Energetics, University of Alabama at 
Birmingham, Birmingham, AL, USA; [4] School of Public 
Health, Dean's Office, University of Alabama at Birmingham, Birmingham, 
AL, USA; [5] Department of Biostatistics, School of Public 
Health, University of Alabama at Birmingham, Birmingham, AL, USA and 
[6] Department of Statistics, Kansas State University, 
Manhattan, KS, USA. Correspondence: Dr. Professor D.B. Allison, School 
of Public Health, Dean's Office, University of Alabama at Birmingham, 
1665 University Boulevard, RPHB 140J, Birmingham, AL 35294, USA.
    E-mail: [email protected].
    [7] These authors contributed equally to this work.

          Background: Public health and clinical interventions for 
        obesity in free-living adults may be diminished by individual 
        compensation for the intervention. Approaches to predict weight 
        outcomes do not account for all mechanisms of compensation, so 
        they are not well suited to predict outcomes in free-living 
        adults. Our objective was to quantify the range of compensation 
        in energy intake or expenditure observed in human randomized 
        controlled trials (RCTs).
          Methods: We searched multiple databases (PubMed, CINAHL, 
        SCOPUS, Cochrane, ProQuest, PsycInfo) up to 1 August 2012 for 
        RCTs evaluating the effect of dietary and/or physical activity 
        interventions on body weight/composition. Inclusion criteria: 
        subjects per treatment arm %5; %1 week intervention; a reported 
        outcome of body weight/body composition; the intervention was 
        either a prescribed amount of over- or underfeeding and/or 
        supervised or monitored physical activity was prescribed; %80% 
        compliance; and an objective method was used to verify 
        compliance with the intervention (for example, observation and 
        electronic monitoring). Data were independently extracted and 
        analyzed by multiple reviewers with consensus reached by 
        discussion. We compared observed weight change with predicted 
        weight change using two models that predict weight change 
        accounting only for metabolic compensation.
          Findings: Twenty-eight studies met inclusion criteria. 
        Overfeeding studies indicate 96% less weight gain than expected 
        if no compensation occurred. Dietary restriction and exercise 
        studies may result in up to 12-44% and 55-64% less weight loss 
        than expected, respectively, under an assumption of no 
        behavioral compensation.
          Interpretation: Compensation is substantial even in high-
        compliance conditions, resulting in far less weight change than 
        would be expected. The simple algorithm we report allows for 
        more realistic predictions of intervention effects in free-
        living populations by accounting for the significant 
        compensation that occurs.
          International Journal of Obesity (2015) 39, 1181-1187; 
        doi:10.1038/ijo.2014.184.
Introduction
    Obesity is a serious and prevalent public health concern.\1\ New 
public health and clinical interventions to reduce obesity are 
frequently advocated or implemented based on hypothetical estimates of 
an outcome that may have little empirical support (for example, the 
3,500 kcal rule). For example, imagine an initiative from a large 
company that replaces its 250 kcal candy bars in its vending machines 
with 50 kcal protein bars to reduce energy intake (EI) from snacking 
among its employees. This initiative can be expected to produce (in 
those who consume at least 250 kcal per day from such snacks), on 
average, 5.7 kg of weight loss after 1 year (for example, for a 35 year 
old man who is 183 cm tall and weighs 100 kg at baseline, body mass 
index = 30). This estimate is based on one of the mathematically 
validated prediction models \2\ sometimes used to justify such 
interventions.\3\ But is this estimate realistic?
    On the basis of the evidence, this estimate is likely optimistic 
because current models for predicting weight change are not well suited 
for use in free-living subjects. A common rule of thumb used for 
decades to predict weight change outcomes is that losing or gaining 1 
pound of fat requires a deficit of 3,500 kcals of energy.\4\ This rule 
does not consider that human energy balance is a dynamic and adaptable 
system or that lean and fat mass is lost during negative energy 
balance, and this leads to an underestimation of the change in EI or 
energy expenditure (EE) needed to produce weight change.5-8 
Recently, more sophisticated models have been developed to predict 
weight changes, which consider the metabolic adaptations that occur 
during weight change.9-12 To accurately predict weight 
change in free-living individuals, however, both metabolic and 
behavioral compensatory mechanisms must be accounted for.
    Specifically, we define the modes of possible compensation as 
follows:
Metabolic Compensation
    It is a compensation for an energy balance intervention through 
physiological changes in metabolism. For example, current mathematical 
models account for changes in resting metabolic rate, fluid balance, 
the thermic effect of food and spontaneous physical activity resulting 
from an energy balance intervention.11-13
Behavioral Compensation
    It is a compensation for an energy balance intervention through 
behavior changes. For example, when a dietary or physical activity 
intervention attempts to create negative energy balance, an individual 
may respond by reducing voluntary EE and/or increasing EI if these 
avenues are not strictly controlled. Similarly, during an energy 
balance intervention of added energy, voluntary EE may increase and/or 
EI may decrease from other sources.
    Others have shown that behavioral compensation occurs for physical 
activity interventions.\14\ Behavioral compensation may also occur for 
interventions that reduce caloric intake or add calorie-containing 
foods to the diet.15-16 Current prediction models are 
intended for use where interventions are implemented with high fidelity 
(that is, intended intervention exposure was achieved) in isolation, 
and when metabolic compensation is the only route of compensation for 
the intervention possible. During interventions in free-living 
subjects, however, compensation can occur through metabolic 
compensation and through behavioral compensation. Behavioral 
compensation may diminish the effects of an intervention, making it 
important to quantify and account for when predicting outcomes in free-
living populations. It is imperative that more realistic models be used 
for predicting outcomes for the reasons stated recently:

          ``. . . to establish a less controversial legacy for this 
        important field, we should avoid past traps and be explicit 
        about reasonable expectations. Implausible results that are 
        `too good to be true' still threaten nutritional research on 
        many fronts, including survey measurements, observational 
        associations, treatment effects in randomized trials, and 
        estimates of the impact on populations.'' \17\

    We therefore set out to build an empirically based model to predict 
weight change outcomes in free-living subjects, and to quantify the 
extent to which observed weight change in free-living subjects differs 
from that predicted under the assumption of no behavioral compensation. 
The approach we took was to use systematic review techniques to collect 
study data and conduct meta-regression on studies meeting a priori 
inclusion criteria. These criteria guided identification of high-
fidelity interventions implemented in free-living adults. The subjects 
had some ability to behaviorally compensate for the intervention, yet 
the reported information about the intervention and compliance 
verification allowed for a high degree of confidence in treatment 
fidelity. For our main analysis, we compared the predictions from 
models that assume no active compensation 2, 18 with the 
observed outcomes as an estimate of the effects of behavioral 
compensation.
Materials and Methods
Systematic Review of the Literature and Study Selection
    Articles, abstracts and doctoral dissertations were retrieved using 
searches performed on the following electronic databases: PubMed, 
Cochrane Library, SCOPUS, PsycInfo, Cumulative Index to Nursing and 
Allied Health Literature (CINAHL) and Dissertation Abstracts. We 
searched PubMed without MeSH headings to identify publications for 
inclusion, using the following limits: dated 1 August 2012 back to 
earliest records of human studies. Detailed search methods are provided 
on the PROSPERO registry website (Registry #CRD42013002912). No ethics 
committee approval was required as the data used are published summary 
statistics.
    All studies were evaluated according to the following inclusion 
criteria: (1) the data were from adult human randomized controlled 
trials in free-living subjects, (2) the intervention was either a 
prescribed amount of over- or underfeeding given and reported (or could 
be converted) in kcal and/or supervised or monitored physical activity 
was prescribed and verified, (3) an objective verification method was 
used to verify the intervention at %80% (for example, observation, 
electronic monitoring and provision of food with returned unused 
portions), (4) the study had a total sample size of at least five 
participants at enrollment, (5) the study protocol included an 
intervention period of at least 7 days, (6) the publication was 
available in the English language and (7) the study was published and 
listed in the above databases on or before 1 August 2012.
    Our exclusion criteria are detailed in the online Supplementary 
Material. Briefly, we excluded studies on samples that were completely 
or predominantly made up of individuals younger than 18 years old or 
older than 60 years or having any health conditions that may affect 
weight. The filtering process of the initial search results is detailed 
in Figure 1 and also described in more detail in the online supplement.
Statistical Analysis
    Quantifying the effect of behavioral compensation-comparison with 
metabolic compensation models. We entered sample demographic and 
intervention data into each of the metabolic compensation model 
calculators to most closely represent each intervention as described in 
the published papers to estimate weight changes that would occur if 
only metabolic compensation occurred. As we included data that had 
samples of both men and women where separate baseline data and results 
were not reported (only combined summaries), we entered the data for 
both genders and mathematically adjusted the outputs for the relative 
proportions of men and women. For the NIDDK simulator,\2\ we assumed a 
baseline value (when not otherwise reported) of sedentary activity 
level (1.4 metabolic equivalents). The difference between the observed 
weight change for each study and the weight change predicted by these 
models is indicative of the degree of behavioral compensation that is 
observed for the interventions in free-living adults included in our 
review and meta-analysis.
    All model data were analyzed with R routines \19\ and descriptive 
summaries were generated with Microsoft Excel version 2010. Further 
details of statistical approaches used for the predictive model 
building are on the online supplement. Risk of bias was assessed by two 
authors (EJD and KAK) independently and discrepancies were discussed 
until consensus was reached.
Role of Funding Source
    The funding agency (International Life Science Institute--North 
America) had no role in the design, conduct, analysis, manuscript 
preparation or decision to publish the results of this study.
Results
Results of Publication Search
    We retrieved citations dated back to 1935, but more than \2/3\ of 
the initial publications retrieved were published after 2001. The final 
data set for building the predictive model consisted of 28 studies 
published between 1987 and 2012, including 15 exercise studies, nine 
studies with added energy, three dietary restriction studies and two 
studies that included both dietary restriction and exercise in the 
intervention (see Table 1 for a complete listing of included studies 
with selected summary data and intervention descriptions). The primary 
reasons for exclusion after full text review were studies not being 
truly randomized or not having a control group, followed by reliance 
only on self-report for EI or physical activity without any objective 
verification of compliance. Studies were all published journal 
articles, except for two dissertations.20-21 Eleven studies 
had samples that were either 100% men or 100% women. Three other 
studies reported results by gender separately if both males and females 
were included in the sample. Only six studies (21%) reported the racial 
makeup of the samples; therefore, this factor was excluded from further 
analysis. Mean ages of the samples ranged from 20.6 to 60 years. Mean 
baseline body mass index of the samples ranged from 22.6 to 35.1 
kgm^\2\.
Figure 1 


          PRISMA diagram-literature search and study selection process.

               Table 1. Master List and Summary of Included Studies Grouped By Treatment Type and Sorted in Ascending Year of Publication
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                      Sample studied
                                     (mean age-years,      Adjusted daily       Study                        N  randomized,     Method of
  Reference(s)      Intervention       pct  female,        dose(s) (kcal:      duration     Intervention       completed,     missing data  Overall mean
                                       baseline BMI     treatment- control)    (weeks)          notes           analyzed        handling      compliance
                                         kgm^\2\)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Johnstone, et     Diet                    38, 0%, 35.1               ^167.2            4  High protein,           20, 17, 17  Completers             100
 al.\22\                                                                                   ketogenic diet
Das, et al.\23\   Diet                 35, 76.3%, 27.6               ^285.6           26  Caloric                 46, 39, 39  Completers             100
                                                                                           restriction
Zachwieja, et     Diet and             24, 45.8%, 24.1                 ^675            2  Caloric                 24, 24, 24  No drops                90
 al.\24\           exercise                                                                restriction and
                                                                                           daily treadmill
                                                                                           exercise
Moreira, et       Diet and                 49, 68%, 30       ^556.0, ^753.3           11  25% caloric             36, 35, 36  ITT                     99
 al.\25\           exercise                                                                restriction
                   (separate                                                               (controlled
                   treatments)                                                             feeding) versus
                                                                                           aerobic
                                                                                           exercise
                                                                                           (individualized
                                                                                           and supervised
                                                                                           sessions 3 per
                                                                                           week)
Leon, et al.\26\  Exercise                32.6, 0%, 26               ^245.6           12  Walking and             22, 16, 16  Completers              86
                                                                                           stair climbing
Van Etten, et     Exercise              33.7, 0%, 23.7                ^31.6           18  Weight training         26, 26, 26  Completers              95
 al.\27\
Murphy, et        Exercise           44.4, 100%, 25.76         ^81.6, ^84.5           10  Long versus             47, 34, 34  Completers            86.5
 al.\28\                                                                                   short bouts of
                                                                                           walking
Crandall \21\     Exercise            51.75, 44%, 30.8                ^76.7           12  Recumbent cycle         13, 13, 13  No drops               100
                                                                                           ergometer
Shaw and Shaw     Exercise               41, 92%, 32.6                ^13.7            8  Resistance              28, 28, 28  Completers            91.1
 \29\                                                                                      training
Kirk, et al.\30\  Exercise              20.6, 0%, 28.2               ^104.7           24  High-intensity          25, 19, 19  Completers              96
                                                                                           resistance
                                                                                           training
Whybrow, et       Exercise             27.2, 50%, 23.6      ^455.6, ^513.6,            2  Progressive             12, 12, 12  No drops               100
 al.\31\                                                             ^907.1                exercise on
                                                                                           cycle ergometer
                                                                                           or treadmill
Guadalupe-Grau,   Exercise          23.7, 65.2%, 23.03                ^51.7            9  Strength                88, 72, 66  Completers              85
 et al.\32\                                                                                training and
                                                                                           plyometric
                                                                                           jumps
Alves, et         Exercise              38.2, 100%, 30               ^106.1           26  Group exercises      156, 146, 156  ITT, BOCF               96
 al.\33\
Turner, et        Exercise                  54, 0%, 28               ^187.3           24  Structured              54, 41, 29  Completers              94
 al.\34\                                                                                   exercise
Bell, et al.\35\  Exercise              49, 100%, 34.7       ^399.0, ^395.1           24  Pedometer-based      211, 128, 128  Completers           84.77
                                                                                           walking program
Vispute, et       Exercise          23.66, 41.7%, 24.6                ^41.9            6  Abdominal               24, 24, 24  No drops             95.71
 al.\36\                                                                                   exercises
Hornbuckle, et    Exercise             28.5, 0%, 25.42                ^57.7           12  Resistance              44, 32, 44  ITT                     96
 al.\37\                                                                                   training
Heydari, et       Exercise           37.7, 56.3%, 27.8               ^186.4           12  High-intensity          46, 38, 38  Completers             100
 al.\38\                                                                                   intermittent
                                                                                           exercise
Thompson, et      Exercise           49.7, 72.8%, 31.8               ^174.8           16  Supervised           162, 137, 162  ITT                     91
 al.,\39\ and                                                                              aerobic
 Church, et                                                                                exercise
 al.\40\
Addington \20\    Feeding                38.74, 63.8%,       2.9 (aspartame            4  Artificially         150, 111, 111  Completers             100
                                                 32.09   group), 142.9 (SSB                sweetened
                                                                     group)                beverage
                                                                                           (aspartame)
                                                                                           versus SSB
Lammert, et       Feeding              22.4, 0%, 22.61                  191            3  Overfeeding             20, 20, 20  No drops               100
 al.\41\                                                                                   carbohydrate or
                                                                                           fat
Martin, et        Feeding            37.7, 56.3%, 27.8                597.1            2  Low- versus high-       10, 10, 10  No drops               100
 al.\42\                                                                                   calorie
                                                                                           breakfast
Sabate, et        Feeding            42.6, 45.2%, 23.7                  219           26  Walnuts                 90, 90, 90  No drops                95
 al.\43\
Whybrow, et       Feeding              60, 26.7%, 27.7         122.8, 227.5            8  Added fruits and        90, 62, 62  Completers            92.6
 al.\44\                                                                                   vegetables
Whybrow, et       Feeding            35.05, 50%, 25.35         343.9, 687.9            2  Added snacks           100, 87, 72  Completers              96
 al.\45\
Sheridan, et      Feeding               24.9, 0%, 28.7                314.8            4  Pistachio nuts          15, 15, 15  No drops                99
 al.\46\
Casas-Agustench,  Feeding            54.4, 56.3%, 26.5                176.9           12  Mixed nuts              52, 50, 50  Completers              94
 et al.\47\
Maersk, et        Feeding                 28, 0%, 22.2    3.1, 365.2, 385.5           26  1 l per day of          60, 47, 47  Completers              85
 al.\48\                                                                                   diet soda, SSB
                                                                                           or milk versus
                                                                                           water
--------------------------------------------------------------------------------------------------------------------------------------------------------
Abbreviations: BOCF, baseline observation carried forward; ITT, intention-to-treat analysis reported; pct, percentage; SSB, sugar-sweetened beverage.

Building a Predictive Model
    We expected to find enough studies to build a robust regression 
model, incorporating mean participant characteristics and evaluating 
any significant interactions. However, the relatively low number and 
sparsely distributed data prevented reliable estimates from our final 
model. Details of the model and its estimations can be found in the 
online supplement, Supplementary Figure S1 and Supplementary Tables S1a 
and S1b.
Comparison with Metabolic Compensation Models--Estimating Behavioral 
        Compensation
    To address our main research question (What is the effect of 
behavioral compensation that occurs in free-living subjects who receive 
an energy balance intervention on weight outcomes?), we generated 
output for each study using the NIDDK and Pennington weight change 
prediction calculators 2, 18 to estimate weight changes that 
would occur if only metabolic compensation occurred. The difference 
between the observed weight loss for each study and the weight change 
predicted by these models is indicative of behavioral compensation 
occurring during the intervention. The NIDDK and Pennington models are 
highly correlated (Pearson's r = 0.98, P<0.0001) in predicted weight 
change (Supplementary Figure S2). In general, the Pennington calculator 
is slightly more conservative than the predictions made by the NIDDK 
calculator.
    The overall degree of behavioral compensation estimated by the gap 
between the observed and metabolic compensation--only predicted values 
is illustrated in Supplementary Figure S3, panels A and B. Both slopes 
being less than 1 (that is, 0.344 and 0.399 for the NIDDK and 
Pennington Models, respectively) indicate that the observed weight 
change is less than predicted after accounting for metabolic 
compensation. This quantifies the degree of behavioral compensation 
that is occurring (that is, the compensation that is in addition to the 
metabolic compensation, resulting in less weight change than expected).
    The degree of behavioral compensation appears to differ depending 
on intervention type. As shown in Supplementary Figure S3, panels A and 
B, all types of interventions demonstrated less weight change than 
either the Pennington or NIDDK calculators predicted. The plot of 
overfeeding trials has a slope (95% confidence interval) of 0.06 
(^0.04, 0.16) and 0.07 (^0.05, 0.18), plotted against the NIDDK and 
Pennington calculators, respectively (Figure 2, panels a and b). A 
slope of 1 would indicate that, on average, the interventions produced 
exactly as much weight change as expected from the mathematical models, 
which assume no behavioral compensation. As such, this suggests that 
behavioral compensation may result in as much as 96% less weight gain 
than predicted by metabolic calculators when adding energy to the diet. 
The slopes of the plots for dietary restriction and exercise studies 
are more similar to each other. Specifically, slopes (95% confidence 
interval) of 0.56 (0.17, 0.96) and 0.88 (0.36, 1.40) were plotted 
against the NIDDK and Pennington calculators, respectively, for dietary 
restriction studies (Figure 2). For exercise intervention studies, 
slopes (confidence interval) of 0.38 (0.16, 0.60) and 0.46 (0.19, 0.72) 
were plotted against the NIDDK and Pennington calculators, respectively 
(Figure 3). Thus, behavioral compensation may result in up to 12-44% 
less weight loss than predicted for dietary restriction studies and 55-
64% less weight loss than predicted for exercise intervention studies.
Risk of Bias Assessment for Included Studies
    See online supplement for risk of bias summary and detailed rating 
figure (Supplementary Figure S4) for each included study. The greatest 
proportions of study aspects with high risk of bias were judged to be 
due to the lack of analysis for incomplete data (attrition bias--for 
example, use of intention-to-treat analysis) and lack of attention 
placebo for control groups. Four studies reported results using 
intention-to-treat analysis.
Figure 2


          NIDDK and Pennington calculator predictions for caloric 
        restriction (D, squares) and overfeeding (F, triangles) 
        interventions. NIDDK (a) and Pennington (b) model predictions 
        (x axis) versus actual observed weight changes for all studies 
        (y axis). Each individual point represents a control versus 
        treatment comparison; the solid lines are lines of best fit for 
        slope and black dashed lines are 95% confidence intervals. Gray 
        dashes lines are axes and lines of identity. Overall, 
        predictions are an overestimate of observed weight change.
Figure 3


          NIDDK and Pennington calculator predictions for exercise 
        interventions (E). NIDDK (a) and Pennington (b) model 
        predictions (x axis) versus actual observed weight changes for 
        all studies (y axis). Each individual point represents a 
        treatment versus control comparison; the solid lines are lines 
        of best fit for slope and black dashed lines are 95% confidence 
        intervals. Gray dashes lines are axes and lines of identity. 
        Overall, predictions are an overestimate of observed weight 
        change.
Discussion
    We generated simple adjustment factors to predict weight change 
resulting from energy balance interventions in free-living adult 
populations, with the ability to compensate both behaviorally and 
metabolically, using 73 treatment and control arm group outcomes from 
28 studies. One of the notable findings was the small number of studies 
meeting our inclusion criteria (that is, where compliance was 
objectively measured), making it difficult to study the role of 
behavioral compensation in a free-living context beyond a very basic 
level. Although our estimates are the only ones for this purpose to 
date based on the currently available literature, this highlights a gap 
in the literature of studies designed to determine the impact of energy 
balance perturbations in humans in the context of a full range of 
compensation that prevents a more precise estimate. As these studies 
are crucial to understanding the effect of public health interventions, 
their limited quantity underscores a need for future research in this 
area.
    Perhaps, the most robust finding from our study most relevant to 
public health is that currently available predictions consistently 
overestimate weight change, which is evidence of significantly 
diminished weight change resulting from behavioral compensation. This 
is in spite of some instances where explicit instructions were given to 
make no other changes in routine habits, a form of compliance that is 
less commonly tracked or verified. In particular, the treatment effect 
of added calories was only, on average, 5% of the weight gain 
predicted from models assuming no behavioral compensation. Several 
included studies reported a mean weight loss effect from added energy. 
This indicates that even if a new food is introduced to the diet, for 
example, adding a daily snack or beverage, EI and/or EE can be adjusted 
reasonably well, resulting in very little weight gain relative to how 
much would be expected if this behavioral compensation did not occur. 
Behavioral compensation for negative energy balance interventions such 
as exercise or dietary restriction is also evident from our analysis, 
and results in 37-45% and 56-88% of the weight loss predicted from 
metabolic-only compensation models. In our initial example of reducing 
EI via snacks by 200 kcals per day for the hypothetical man, the 
adjusted estimate of weight change after 1 year would be closer to 3.2 
kg. This is lower than the 5.7 kg estimate given by the body weight 
simulator that predicts metabolic compensation only.
    Therefore, our results suggest that current public health 
interventions or clinical interventions that alter one aspect of energy 
balance, without holding other aspects constant, may result in more 
modest weight changes than predicted or desired. A similar approach has 
been reported in pediatric studies,\3\ but it did not attempt to 
account for both behavioral and metabolic compensation components. It 
is important to take all modes of compensation into consideration when 
planning an intervention with targeted amounts of weight change and 
when anticipating its outcomes. It is likely that increased doses of 
energy perturbations are required. Increased control over compliance 
and compensation is necessary to achieve target outcomes. Estimates of 
what is required to achieve a specific weight change may be made more 
accurate for the purposes of public health recommendations if the 
present estimations are considered.
    Our results suggest that there might be a differential effect of 
treatment type on the degree of behavioral compensation. However, an 
aspect of our data set needs to be considered in interpreting this 
result. Dietary restriction interventions are associated with greater 
treatment effects, and less behavioral compensation, than either 
exercise or overfeeding interventions. However, this finding may be 
because the dietary restriction interventions included in our analysis 
only allowed for behavioral compensation through EE changes, whereas 
all exercise and overfeeding interventions allowed for behavioral 
compensation through both dietary intake and EE changes.
    Our approach has strengths and limitations. First, our inclusion 
criteria were rigorous. All included studies have at least 80% 
compliance with the prescribed intervention, with compliance verified 
objectively (no reliance solely on self-report). In addition, the dose 
was corrected in our calculations for the level of compliance reported 
in the study. Further, included studies were randomized controlled 
trials, and our outcome for generating the predictive model and for 
comparing with metabolic compensation models was the control group-
adjusted weight change. Therefore, our models are built to assess true 
treatment effect, and are corrected for any weight change due to 
factors such as regression to the mean, maturation, historical factors 
and behaviors that result from simply participating in a study, rather 
than from the treatment itself.
    Several limitations should also be considered when interpreting our 
analysis. Weight was not always the primary outcome in studies that met 
our inclusion criteria. This is particularly true for those with added 
EI in the form of nuts. Differences in stated outcomes of interest, 
time with researchers and other factors may affect weight outcomes for 
individual studies. In addition, body composition may be an important 
outcome that we were not able to adequately analyze because of the 
limited number of studies including body composition measurements such 
as changes in fat mass and fat-free mass. Because of our rigorous 
inclusion criteria, our data set is small (28 studies). The types of 
studies we selected are necessary for making definitive conclusions 
about the impact of perturbations in one aspect of energy balance on 
body weight. Studies also tended to be shorter in duration, thus it is 
difficult to make conclusions about long-term effects. This is a large 
gap in the literature, and a more systematic approach to large, well-
controlled studies to answer these questions is warranted. In addition, 
16 of the 28 studies reported data only for those participants who 
completed the intervention period, and across all studies there was a 
17.8% dropout rate (Table 1), which may have biased our estimates of 
weight change toward overestimation. We used the intention to treat 
data when reported (four studies). Eight studies reported no dropouts.
    Future research is needed to understand potential differences in 
compensation between dietary interventions (added or reduced energy), 
different food forms and macronutrient compositions. Also, certain 
factors should be considered as potential confounders when quantifying 
the compensatory response to a specific intervention. For example, 
bioavailability of energy in food, efficiencies in physical activity 
and food utilization, seasonal effects and durations of interventions 
may all influence both the metabolic and behavioral compensatory 
response to an intervention. It is also unclear whether compensation 
would remain constant over time. Moreover, evaluating the influence of 
participant characteristics related to eating behavior (cognitive 
restraint, disinhibition and hunger) and compensation during 
interventions is needed as this may hold promise for optimizing 
treatment effectiveness.
    To conclude, we have presented the first empirically based, 
quantitative estimation for the range of behavioral compensation that 
may be observed for energy balance interventions. This information may 
assist in the estimation of weight outcomes of clinical health 
interventions. It may also inform public health projections for obesity 
interventions or public health initiatives.

 
 
 
Conflict of Interest
 
    DBA has received consulting fees and his university has received
 gifts, grants and donations from multiple nonprofit and for-profit
 organizations with interests in obesity including publishers,
 litigators and food and pharmaceutical companies. KAK has received a
 speaker honorarium from Coca-Cola Iberia. The remaining authors declare
 no conflict of interest.
 
Acknowledgements
 
    This project was sponsored by the International Life Sciences
 Institute--North America (EJD and KAK, co-PIs). We thank the following
 experts for their helpful comments on earlier versions of this
 manuscript: Steve Blair, Steve Heymsfield, Rick Mattes, Robert
 Matthews, Diana Thomas and Kevin Fontaine. Registry Information:
 PROSPERO (http://www.crd.york.ac.uk/prospero/search.asp)
 CRD42013002912.
 
Author Contributions
 
    EJD, KAK and DBA conceived the study and developed the design and
 selection criteria. KAK performed the literature searches. KAK and EJD
 reviewed the literature, selected studies, extracted data, evaluated
 risk of bias and wrote significant portions of the manuscript. ASA
 assisted with literature selection, data extraction and summary
 calculations. JAD and KDK performed the statistical analysis and wrote
 some portions of the manuscript. DBA directed the statistical analysis
 and wrote some portions of the manuscript.
 
        Supplementary Information accompanies this paper on
     International Journal of Obesity website (http://www.nature.com/
     ijo).
 


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                              attachment 3
Myths, Presumptions, and Facts About Obesity *
---------------------------------------------------------------------------
    * This article was updated on June 6, 2013, at NEJM.org.
    N. Engl. J. Med. 2013;368:446-54.
    DOI: 10.1056/NEJMsa1208051.
    Copyright  13 Massachusetts Medical Society.
---------------------------------------------------------------------------
Krista Casazza, Ph.D., R.D., Kevin R. Fontaine, Ph.D., Arne Astrup, 
M.D., Ph.D., Leann L. Birch, Ph.D., Andrew W. Brown, Ph.D., Michelle M. 
Bohan Brown, Ph.D., Nefertiti Durant, M.D., M.P.H., Gareth Dutton, 
Ph.D., E. Michael Foster, Ph.D., Steven B. Heymsfield, M.D., Kerry 
McIver, M.S., Tapan Mehta, M.S., Nir Menachemi, Ph.D., P.K. Newby, 
Sc.D., M.P.H., Russell Pate, Ph.D., Barbara J. Rolls, Ph.D., Bisakha 
Sen, Ph.D., Daniel L. Smith, Jr., Ph.D., Diana M. Thomas, Ph.D., and 
David B. Allison, Ph.D.**
---------------------------------------------------------------------------
    ** From the Departments of Nutrition Sciences (K.C., M.M.B.B., 
D.L.S., D.B.A.), Health Behavior (K.R.F.), Pediatrics (N.D.), Medicine 
(G.D.), Health Care Organization and Policy (E.M.F., N.M., B.S.), and 
Biostatistics (T.M., D.B.A.) and the School of Public Health, Office of 
Energetics, Nutrition Obesity Research Center (A.W.B., D.B.A.), 
University of Alabama at Birmingham, Birmingham; the OPUS Center and 
the Department of Nutrition, Exercise, and Sports, University of 
Copenhagen, Copenhagen (A.A.); the Departments of Development and 
Family Studies (L.L.B.) and Nutritional Sciences (B.J.R.), Pennsylvania 
State University, University Park; Pennington Biomedical Research 
Center, Baton Rouge, LA (S.B.H.); Children's Physical Activity Research 
Group, Department of Exercise Science, Arnold School of Public Health, 
University of South Carolina, Columbia (K.M., R.P.); the Departments of 
Pediatrics and Epidemiology, Program in Graduate Medical Nutrition 
Sciences, and Program in Gastronomy, Culinary Arts, and Wine Studies, 
Boston University, Boston (P.K.N.); and the Center for Quantitative 
Obesity Research, Montclair State University, Montclair, NJ (D.M.T.). 
Address reprint requests to Dr. Allison at the University of Alabama at 
Birmingham, Department of Biostatistics, Birmingham, AL 35294, or at 
[email protected].
---------------------------------------------------------------------------
Abstract
  Background
          Many beliefs about obesity persist in the absence of 
        supporting scientific evidence (presumptions); some persist 
        despite contradicting evidence (myths). The promulgation of 
        unsupported beliefs may yield poorly informed policy decisions, 
        inaccurate clinical and public health recommendations, and an 
        unproductive allocation of research resources and may divert 
        attention away from useful, evidence-based information.
    Methods
          Using Internet searches of popular media and scientific 
        literature, we identified, reviewed, and classified obesity-
        related myths and presumptions. We also examined facts that are 
        well supported by evidence, with an emphasis on those that have 
        practical implications for public health, policy, or clinical 
        recommendations.
    Results
          We identified seven obesity-related myths concerning the 
        effects of small sustained increases in energy intake or 
        expenditure, establishment of realistic goals for weight loss, 
        rapid weight loss, weight-loss readiness, physical-education 
        classes, breast-feeding, and energy expended during sexual 
        activity. We also identified six presumptions about the 
        purported effects of regularly eating breakfast, early 
        childhood experiences, eating fruits and vegetables, weight 
        cycling, snacking, and the built (i.e., human-made) 
        environment. Finally, we identified nine evidence-supported 
        facts that are relevant for the formulation of sound public 
        health, policy, or clinical recommendations.
    Conclusions
          False and scientifically unsupported beliefs about obesity 
        are pervasive in both scientific literature and the popular 
        press. (Funded by the National Institutes of Health.)

    Passionate interests, the human tendency to seek explanations for 
observed phenomena, and everyday experience appear to contribute to 
strong convictions about obesity, despite the absence of supporting 
data. When the public, mass media, government agencies, and even 
academic scientists espouse unsupported beliefs, the result may be 
ineffective policy, unhelpful or unsafe clinical and public health 
recommendations, and an unproductive allocation of resources. In this 
article, we review some common beliefs about obesity that are not 
supported by scientific evidence and also provide some useful evidence-
based concepts. We define myths as beliefs held to be true despite 
substantial refuting evidence, presumptions as beliefs held to be true 
for which convincing evidence does not yet confirm or disprove their 
truth, and facts as propositions backed by sufficient evidence to 
consider them empirically proved for practical purposes.
    When standards for evidence are considered, it is critical to 
distinguish between drawing conclusions from scientific evidence and 
making decisions about prudent actions. Stakeholders must sometimes 
take action in the absence of strong scientific evidence. Yet this 
principle of action should not be mistaken as justification for drawing 
conclusions. Regardless of the urgency of public health issues, 
scientific principles remain unchanged. We find the language of the 
Federal Trade Commission to be apt: its standard for making claims is 
``competent and reliable scientific evidence,'' defined as ``tests, 
analyses, research, studies, or other evidence . . . conducted and 
evaluated in an objective manner . . . using procedures generally 
accepted . . . to yield accurate and reliable results.'' \1\
    The scientific community recognizes that randomized experiments 
offer the strongest evidence for drawing causal inferences. 
Nevertheless, at least since the 1960s, when Sir Austin Bradford Hill 
spearheaded the scientific activities that led to the acceptance of the 
claim that smoking causes lung cancer and to his classic writing on 
association and causation,\2\ the scientific community has acknowledged 
that under some circumstances (i.e., when it is unethical or unfeasible 
to conduct a randomized study and when observed associations are not 
plausibly due to confounding), inferring causality in the absence of 
data from randomized, controlled trials is necessary and appropriate. 
However, the fact that the appropriateness of inferring causality holds 
only under certain circumstances is sometimes discounted by those who 
are eager to garner support for a proposal in the absence of strong 
data from randomized studies.
    Notably, the circumstances that justify drawing a conclusion of 
causation from nonexperimental data are rarely met in clinical and 
public proposals regarding obesity. It is possible to conduct 
randomized studies of even the most sensitive and invasive obesity 
procedures, as exemplified by recent articles in the Journal. Moreover, 
observational associations germane to the causes, treatment, and 
prevention of obesity are subject to substantial confounding, fraught 
with measurement problems, and typically small and inconsistent.\3\ 
Such observational associations are often found to differ from those 
later obtained by more rigorously designed studies.\4\ Hence, in the 
present discussion, we generally conclude that a proposition has been 
shown to be true only when it has been supported by confirmatory 
randomized studies. References to published studies are used sparingly 
herein, with a more comprehensive listing provided in the Supplementary 
Appendix, available with the full text of this article at NEJM.org.
Myths
    We review seven myths about obesity, along with the refuting 
evidence. Table 1 provides anecdotal support that the beliefs are 
widely held or stated, in addition to reasons that support conjecture.

                  Table 1. Seven Myths about Obesity *
------------------------------------------------------------------------
               Myth                         Basis of Conjecture
------------------------------------------------------------------------
Small sustained changes in energy  National health guidelines and
 intake or expenditure will         reputable websites advertise that
 produce large, long-term weight    large changes in weight accumulate
 changes                            indefinitely after small sustained
                                    daily lifestyle modifications (e.g.,
                                    walking for 20 minutes or eating two
                                    additional potato chips)
Setting realistic goals in         According to goal-setting theory,
 obesity treatment is important     unattainable goals impair
 because otherwise patients will    performance and discourage goal-
 become frustrated and lose less    attaining behavior; in obesity
 weight                             treatment, incongruence between
                                    desired and actual weight loss is
                                    thought to undermine the patient's
                                    perceived ability to attain goals,
                                    which may lead to the
                                    discontinuation of behaviors
                                    necessary for weight loss
Large, rapid weight loss is        This notion probably emerged in
 associated with poorer long-term   reaction to the adverse effects of
 weight outcomes than is slow,      nutritionally insufficient very-low-
 gradual weight loss                calorie diets (<800 kcal per day) in
                                    the 1960s; the belief has persisted,
                                    has been repeated in textbooks and
                                    recommendations from health
                                    authorities, and has been offered as
                                    a rule by dietitians
Assessing the stage of change or   Many believe that patients who feel
 diet readiness is important in     ready to lose weight are more likely
 helping patients who seek weight-  to make the required lifestyle
 loss treatment                     changes
Physical-education classes in      The health benefits of physical
 their current format play an       activity of sufficient duration,
 important role in preventing or    frequency, and intensity are well
 reducing childhood obesity         established and include reductions
                                    in adiposity
Breast-feeding is protective       The belief that breast-fed children
 against obesity                    are less likely to become obese has
                                    persisted for more than a century
                                    and is passionately defended
A bout of sexual activity burns    Many sources state that substantial
 100 to 300 kcal for each person    energy is expended in typical sexual
 involved                           activity between two adults
------------------------------------------------------------------------
* We define myths as beliefs held true despite substantial evidence
  refuting them. A list of articles in which these myths are espoused is
  provided in the Supplementary Appendix.

Small Sustained Changes in Energy Intake Or Expenditure
    Myth number 1: Small sustained changes in energy intake or 
expenditure will produce large, long-term weight changes.
    Predictions suggesting that large changes in weight will accumulate 
indefinitely in response to small sustained lifestyle modifications 
rely on the half-century-old 3,500-kcal rule, which equates a weight 
alteration of 1 lb (0.45 kg) to a 3,500-kcal cumulative deficit or 
increment.5-6 However, applying the 3,500-kcal rule to cases 
in which small modifications are made for long periods violates the 
assumptions of the original model, which were derived from short-term 
experiments predominantly performed in men on very-low-energy diets 
(<800 kcal per day).5, 7 Recent studies have shown that 
individual variability affects changes in body composition in response 
to changes in energy intake and expenditure,\7\ with analyses 
predicting substantially smaller changes in weight (often by an order 
of magnitude across extended periods) than the 3,500-kcal rule 
does.5, 7 For example, whereas the 3,500-kcal rule predicts 
that a person who increases daily energy expenditure by 100 kcal by 
walking 1 mile (1.6 km) per day will lose more than 50 lb (22.7 kg) 
over a period of 5 years, the true weight loss is only about 10 lb (4.5 
kg),\6\ assuming no compensatory increase in caloric intake, because 
changes in mass concomitantly alter the energy requirements of the 
body.
Setting Realistic Weight-Loss Goals
    Myth number 2: Setting realistic goals for weight loss is 
important, because otherwise patients will become frustrated and lose 
less weight.
    Although this is a reasonable hypothesis, empirical data indicate 
no consistent negative association between ambitious goals and program 
completion or weight loss.\8\ Indeed, several studies have shown that 
more ambitious goals are sometimes associated with better weight-loss 
outcomes (see the Supplementary Appendix).\8\ Furthermore, two studies 
showed that interventions designed to improve weight-loss outcomes by 
altering unrealistic goals resulted in more realistic weight-loss 
expectations but did not improve outcomes.
Rate of Weight Loss
    Myth number 3: Large, rapid weight loss is associated with poorer 
long-term weight-loss outcomes, as compared with slow, gradual weight 
loss.
    Within weight-loss trials, more rapid and greater initial weight 
loss has been associated with lower body weight at the end of long-term 
follow-up.9-10 A meta-analysis of randomized, controlled 
trials that compared rapid weight loss (achieved with very-low-energy 
diets) with slower weight loss (achieved with low-energy diets--i.e., 
800 to 1200 kcal per day) at the end of short-term follow-up (<1 yr) 
and long-term follow-up (%1 year) showed that, despite the association 
of very-low-energy diets with significantly greater weight loss at the 
end of short-term follow-up (16.1% of body weight lost, vs. 9.7% with 
low-energy diets), there was no significant difference between the 
very-low-energy diets and low-energy diets with respect to weight loss 
at the end of long-term follow-up.\10\ Although it is not clear why 
some obese persons have a greater initial weight loss than others do, a 
recommendation to lose weight more slowly might interfere with the 
ultimate success of weight-loss efforts.
Diet Readiness
    Myth number 4: It is important to assess the stage of change or 
diet readiness in order to help patients who request weight-loss 
treatment.
    Readiness does not predict the magnitude of weight loss or 
treatment adherence among persons who sign up for behavioral programs 
or who undergo obesity surgery.\11\ Five trials (involving 3,910 
participants; median study period, 9 months) specifically evaluated 
stages of change (not exclusively readiness) and showed an average 
weight loss of less than 1 kg and no conclusive evidence of sustained 
weight loss (see the Supplementary Appendix). The explanation may be 
simple--people voluntarily choosing to enter weight-loss programs are, 
by definition, at least minimally ready to engage in the behaviors 
required to lose weight.
Importance of Physical Education
    Myth number 5: Physical-education classes, in their current form, 
play an important role in reducing or preventing childhood obesity.
    Physical education, as typically provided, has not been shown to 
reduce or prevent obesity. Findings in three studies that focused on 
expanded time in physical education \12\ indicated that even though 
there was an increase in the number of days children attended physical-
education classes, the effects on body-mass index (BMI) were 
inconsistent across sexes and age groups. Two meta-analyses showed that 
even specialized school-based programs that promoted physical activity 
were ineffective in reducing BMI or the incidence or prevalence of 
obesity.\13\ There is almost certainly a level of physical activity (a 
specific combination of frequency, intensity, and duration) that would 
be effective in reducing or preventing obesity. Whether that level is 
plausibly achievable in conventional school settings is unknown, 
although the dose-response relationship between physical activity and 
weight warrants investigation in clinical trials.
Breast-Feeding and Obesity
    Myth number 6: Breast-feeding is protective against obesity.
    A World Health Organization (WHO) report states that persons who 
were breast-fed as infants are less likely to be obese later in life 
and that the association is ``not likely to be due to publication bias 
or confounding.'' \14\ Yet the WHO, using Egger's test and funnel 
plots, found clear evidence of publication bias in the published 
literature it synthesized.\15\ Moreover, studies with better control 
for confounding (e.g., studies including within-family sibling 
analyses) and a randomized, controlled trial involving more than 13,000 
children who were followed for more than 6 years \16\ provided no 
compelling evidence of an effect of breast-feeding on obesity. On the 
basis of these findings, one long-term proponent of breast-feeding for 
the prevention of obesity wrote that breast-feeding status ``no longer 
appears to be a major determinant'' of obesity risk; \17\ however, he 
speculated that breast-feeding may yet be shown to be modestly 
protective, current evidence to the contrary. Although existing data 
indicate that breast-feeding does not have important antiobesity 
effects in children, it has other important potential benefits for the 
infant and mother and should therefore be encouraged.
Sexual Activity and Energy Expenditure
    Myth number 7: A bout of sexual activity burns 100 to 300 kcal for 
each participant.
    The energy expenditure of sexual intercourse can be estimated by 
taking the product of activity intensity in metabolic equivalents 
(METs),\18\ the body weight in kilograms, and time spent. For example, 
a man weighing 154 lb (70 kg) would, at 3 METs, expend approximately 
3.5 kcal per minute (210 kcal per hour) during a stimulation and orgasm 
session. This level of expenditure is similar to that achieved by 
walking at a moderate pace (approximately 2.5 miles [4 km] per hour). 
Given that the average bout of sexual activity lasts about 6 
minutes,\19\ a man in his early-to-mid-30s might expend approximately 
21 kcal during sexual intercourse. Of course, he would have spent 
roughly \1/3\ that amount of energy just watching television, so the 
incremental benefit of one bout of sexual activity with respect to 
energy expended is plausibly on the order of 14 kcal.
Presumptions
    Just as it is important to recognize that some widely held beliefs 
are myths so that we may move beyond them, it is important to recognize 
presumptions, which are widely accepted beliefs that have neither been 
proved nor disproved, so that we may move forward to collect solid data 
to support or refute them. Instead of attempting to comprehensively 
describe all the data peripherally related to each of the six 
presumptions shown in Table 2, we describe the best evidence.

                  Table 2. Presumptions about Obesity *
------------------------------------------------------------------------
             Presumption                      Basis of Conjecture
------------------------------------------------------------------------
Regularly eating (vs. skipping)       Skipping breakfast purportedly
 breakfast is protective against       leads to overeating later in the
 obesity                               day
Early childhood is the period during  Weight-for-height indexes, eating
 which we learn exercise and eating    behaviors, and preferences that
 habits that influence our weight      are present in early childhood
 throughout life                       are correlated with those later
                                       in life
Eating more fruits and vegetables     By eating more fruits and
 will result in weight loss or less    vegetables, a person presumably
 weight gain, regardless of whether    spontaneously eats less of other
 one intentionally makes any other     foods, and the resulting
 behavioral or environmental changes   reduction in calories is greater
                                       than the increase in calories
                                       from the fruit and vegetables
Weight cycling (i.e., yo-yo dieting)  In observational studies,
 is associated with increased          mortality rates have been lower
 mortality                             among persons with stable weight
                                       than among those with unstable
                                       weight
Snacking contributes to weight gain   Snack foods are presumed to be
 and obesity                           incompletely compensated for at
                                       subsequent meals, leading to
                                       weight gain
The built environment, in terms of    Neighborhood-environment features
 sidewalk and park availability,       may promote or inhibit physical
 influences obesity                    activity, thereby affecting
                                       obesity
------------------------------------------------------------------------
* We define presumptions as unproved yet commonly espoused propositions.
  A list of articles in which these presumptions are implied is provided
  in the Supplementary Appendix.

Value of Breakfast
    Presumption number 1: Regularly eating (versus skipping) breakfast 
is protective against obesity.
    Two randomized, controlled trials that studied the outcome of 
eating versus skipping breakfast showed no effect on weight in the 
total sample.\20\ However, the findings in one study suggested that the 
effect on weight loss of being assigned to eat or skip breakfast was 
dependent on baseline breakfast habits.\20\
Early Childhood Habits and Weight
    Presumption number 2: Early childhood is the period in which we 
learn exercise and eating habits that influence our weight throughout 
life.
    Although a person's BMI typically tracks over time (i.e., tends to 
be in a similar percentile range as the person ages), longitudinal 
genetic studies suggest that such tracking may be primarily a function 
of genotype rather than a persistent effect of early learning.\21\ No 
randomized, controlled clinical trials provide evidence to the 
contrary.
Value of Fruits and Vegetables
    Presumption number 3: Eating more fruits and vegetables will result 
in weight loss or less weight gain, regardless of whether any other 
changes to one's behavior or environment are made.
    It is true that the consumption of fruits and vegetables has health 
benefits. However, when no other behavioral changes accompany increased 
consumption of fruits and vegetables, weight gain may occur or there 
may be no change in weight.\22\
Weight Cycling and Mortality
    Presumption number 4: Weight cycling (i.e., yo-yo dieting) is 
associated with increased mortality.
    Although observational epidemiologic studies show that weight 
instability or cycling is associated with increased mortality, such 
findings are probably due to confounding by health status. Studies of 
animal models do not support this epidemiologic association.\23\
Snacking and Weight Gain
    Presumption number 5: Snacking contributes to weight gain and 
obesity.
    Randomized, controlled trials do not support this presumption.\24\ 
Even observational studies have not shown a consistent association 
between snacking and obesity or increased BMI.
Built Environment and Obesity
    Presumption number 6: The built environment, in terms of sidewalk 
and park availability, influences the incidence or prevalence of 
obesity.
    According to a systematic review, virtually all studies showing 
associations between the risk of obesity and components of the built 
environment (e.g., parks, roads, and architecture) have been 
observational.\25\ Furthermore, these observational studies have not 
shown consistent associations, so no conclusions can be drawn.
Facts
    Our proposal that myths and presumptions be seen for what they are 
should not be mistaken as a call for nihilism. There are things we do 
know with reasonable confidence. Table 3 lists nine such facts and 
their practical implications for public health, policy, or clinical 
recommendations. The first two facts help establish a framework in 
which intervention and preventive techniques may work. The next four 
facts are more prescriptive, offering tools that can be conveyed to the 
public as well established. The last three facts are suited to clinical 
settings.

                     Table 3. Facts about Obesity *
------------------------------------------------------------------------
               Fact                             Implication
------------------------------------------------------------------------
Although genetic factors play a    If we can identify key environmental
 large role, heritability is not    factors and successfully influence
 destiny; calculations show that    them, we can achieve clinically
 moderate environmental changes     significant reductions in obesity
 can promote as much weight loss
 as the most efficacious
 pharmaceutical agents available
 \26\
Diets (i.e., reduced energy        This seemingly obvious distinction is
 intake) very effectively reduce    often missed, leading to erroneous
 weight, but trying to go on a      conceptions regarding possible
 diet or recommending that          treatments for obesity; recognizing
 someone go on a diet generally     this distinction helps our
 does not work well in the long-    understanding that energy reduction
 term \27\                          is the ultimate dietary intervention
                                    required and approaches such as
                                    eating more vegetables or eating
                                    breakfast daily are likely to help
                                    only if they are accompanied by an
                                    overall reduction in energy intake
Regardless of body weight or       Exercise offers a way to mitigate the
 weight loss, an increased level    health-damaging effects of obesity,
 of exercise increases health       even without weight loss
 \28\
Physical activity or exercise in   Physical-activity programs are
 a sufficient dose aids in long-    important, especially for children,
 term weight maintenance 28	29      but for physical activity to affect
                                    weight, there must be a substantial
                                    quantity of movement, not mere
                                    participation
Continuation of conditions that    Obesity is best conceptualized as a
 promote weight loss promotes       chronic condition, requiring ongoing
 maintenance of lower weight \30\   management to maintain long-term
                                    weight loss
For overweight children, programs  Programs provided only in schools or
 that involve the parents and the   other out-of-home structured
 home setting promote greater       settings may be convenient or
 weight loss or maintenance \31\    politically expedient, but programs
                                    including interventions that involve
                                    the parents and are provided at home
                                    are likely to yield better outcomes
Provision of meals and use of      More structure regarding meals is
 meal-replacement products          associated with greater weight loss,
 promote greater weight loss \32\   as compared with seemingly holistic
                                    programs that are based on concepts
                                    of balance, variety, and moderation
Some pharmaceutical agents can     While we learn how to alter the
 help patients achieve clinically   environment and individual behaviors
 meaningful weight loss and         to prevent obesity, we can offer
 maintain the reduction as long     moderately effective treatmentto
 as the agents continue to be       obese persons
 used \33\
In appropriate patients,           For severely obese persons, bariatric
 bariatric surgery results in       surgery can offer a life-changing,
 long-term weight loss and          and in some cases lifesaving,
 reductions in the rate of          treatment
 incident diabetes and mortality
 \34\
------------------------------------------------------------------------
* We classify the listed propositions as facts because there is
  sufficient evidence to consider them empirically proved.

Implications
    Myths and presumptions about obesity are common. Several 
presumptions appear to be testable, and some of them (e.g., effects of 
eating breakfast daily, eating more fruits and vegetables, and 
snacking) can be tested with standard study designs. Despite enormous 
efforts promoting these ideas, research often seems mired in the 
accrual of observational data. Many of the trials that have been 
completed or are in progress do not isolate the effect of the presumed 
influence and the findings are therefore not definitive.
    Many of the myths and presumptions about obesity reflect a failure 
to consider the diverse aspects of energy balance,\35\ especially 
physiological compensation for changes in intake or expenditure.\36\ 
Some myths and presumptions involve an implicit assumption that there 
is no physiological compensation whatsoever (i.e., the 3,500-kcal rule) 
or only minimal compensation (e.g., a reduction in snacking as a means 
of reducing weight). In other cases, there is an implicit assumption of 
overcompensation (e.g., eating breakfast daily or increasing the intake 
of fruits and vegetables as a means of reducing weight). Proponents of 
other unsupported ideas fail to consider that people burn some amount 
of energy even without engaging in the activity in question (e.g., 
increased sexual activity). In addition, interested parties do not 
regularly request the results from randomized, long-term studies that 
measure weight or adiposity as an outcome. Therefore, the presented 
data are rife with circumstantial evidence, and people are not informed 
that the existing evidence is not compelling (e.g., breakfast 
consumption). Furthermore, some suggested treatment or prevention 
strategies may work well (e.g., increasing the consumption of fruits 
and vegetables) but only as part of a multifaceted program for weight 
reduction. Yet such a strategy is often presented as though it will 
have effects in isolation and even among persons not participating in 
weight-loss programs. We must recognize that evidence that a technique 
is beneficial for the treatment of obesity is not necessarily evidence 
that it will be helpful in population-based approaches to the 
prevention of obesity, and vice versa.
Knowing and Not Knowing
    Why do we think or claim we know things that we actually do not 
know? Numerous cognitive biases lead to an unintentional retention of 
erroneous beliefs.37-38 When media coverage about obesity is 
extensive, many people appear to believe some myths (e.g., rapid weight 
loss facilitates weight regain) simply because of repeated exposure to 
the claims.\39\ Cognitive dissonance may prevent us from abandoning 
ideas that are important to us, despite contradictory evidence (e.g., 
the idea that breast-feeding prevents obesity in children). Similarly, 
confirmation bias may prevent us from seeking data that might refute 
propositions we have already intuitively accepted as true because they 
seem obvious (e.g., the value of realistic weight-loss goals). 
Moreover, we may be swayed by persuasive yet fallacious arguments 
(Whately provides a classic catalogue) \40\ unless we are prepared to 
identify them as spurious.
    Fortunately, the scientific method and logical thinking offer ways 
to detect erroneous statements, acknowledge our uncertainty, and 
increase our knowledge. When presented with an alleged truth, we can 
pause to ask simple questions, such as, ``How could someone actually 
know that?'' Such a simple question allows one to easily recognize some 
beliefs as spurious (e.g., 300 kcal is burned during sexual 
intercourse). Moreover, we often settle for data generated with the use 
of inadequate methods in situations in which inferentially stronger 
study designs, including quasi-experiments and true randomized 
experiments, are possible, as recently illustrated (see the 
Supplementary Appendix). In addition, eliminating the distortions of 
scientific information that sometimes occur with public health advocacy 
would reduce the propagation of misinformation.
    The myths and presumptions about obesity that we have discussed are 
just a sampling of the numerous unsupported beliefs held by many 
people, including academics, regulators, and journalists, as well as 
the general public. Yet there are facts about obesity of which we may 
be reasonably certain--facts that are useful today. While we work to 
generate additional useful knowledge, we may in some cases justifiably 
move forward with hypothesized, but not proved, strategies. However, as 
a scientific community, we must always be open and honest with the 
public about the state of our knowledge and should rigorously evaluate 
unproved strategies.

 
 
 
    The views expressed in this article are those of the authors and do
 not necessarily represent the official views of the National Institutes
 of Health.
    Supported in part by a grant (P30DK056336) from the National
 Institutes of Health.
    Dr. Astrup reports receiving payment for board membership from the
 Global Dairy Platform, Kraft Foods, Knowledge Institute for Beer,
 McDonald's Global Advisory Council, Arena Pharmaceuticals, Basic
 Research, Novo Nordisk, Pathway Genomics, Jenny Craig, and Vivus;
 receiving lecture fees from the Global Dairy Platform, Novo Nordisk,
 Danish Brewers Association, GlaxoSmithKline, Danish Dairy Association,
 International Dairy Foundation, European Dairy Foundation, and
 AstraZeneca; owning stock in Mobile Fitness; holding patents regarding
 the use of flaxseed mucilage or its active component for suppression of
 hunger and reduction of prospective consumption (patents EP1744772,
 WO2009033483-A1, EP2190303-A1, US2010261661-A1, and priority
 applications DK001319, DK001320, S971798P, and US971827P); holding
 patents regarding the use of an alginate for the preparation of an
 aqueous dietary product for the treatment or prevention of overweight
 and obesity (patent WO2011063809-A1 and priority application DK070227);
 and holding a patent regarding a method for regulating energy balance
 for body-weight management (patent WO2007062663-A1 and priority
 application DK001710). Drs. Brown and Bohan Brown report receiving
 grant support from the Coca-Cola Foundation through their institution.
 Dr. Mehta reports receiving grant support from Kraft Foods. Dr. Newby
 reports receiving grant support from General Mills Bell Institute of
 Health and Nutrition. Dr. Pate reports receiving consulting fees from
 Kraft Foods. Dr. Rolls reports having a licensing agreement for the
 Volumetrics trademark with Jenny Craig. Dr. Thomas reports receiving
 consulting fees from Jenny Craig. Dr. Allison reports serving as an
 unpaid board member for the International Life Sciences Institute of
 North America; receiving payment for board membership from Kraft Foods;
 receiving consulting fees from Vivus, Ulmer and Berne, Paul, Weiss,
 Rifkind, Wharton, Garrison, Chandler Chicco, Arena Pharmaceuticals,
 Pfizer, National Cattlemen's Association, Mead Johnson Nutrition,
 Frontiers Foundation, Orexigen Therapeutics, and Jason Pharmaceuticals;
 receiving lecture fees from Porter Novelli and the Almond Board of
 California; receiving payment for manuscript preparation from Vivus;
 receiving travel reimbursement from International Life Sciences
 Institute of North America; receiving other support from the United
 Soybean Board and the Northarvest Bean Growers Association; receiving
 grant support through his institution from Wrigley, Kraft Foods, Coca-
 Cola, Vivus, Jason Pharmaceuticals, Aetna Foundation, and McNeil
 Nutritionals; and receiving other funding through his institution from
 the Coca-Cola Foundation, Coca-Cola, PepsiCo, Red Bull, World Sugar
 Research Organisation, Archer Daniels Midland, Mars, Eli Lilly and
 Company, and Merck. No other potential conflict of interest relevant to
 this article was reported.
    Disclosure forms provided by the authors are available with the full
 text of this article at NEJM.org.
    We thank Drs. Kyle Grimes and S. Louis Bridges for their suggestions
 on an earlier version of the manuscript.
 


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Copyright 13 Massachusetts Medical Society.

                              attachment 4
Goals in Nutrition Science 2015-2020 *
---------------------------------------------------------------------------
    * Edited by: Steven H. Zeisel, University of North Carolina at 
Chapel Hill, USA; Reviewed by: Naima Moustaid-Moussa, Texas Tech 
University, USA Patrick John Stover, Cornell University, USA; Received: 
26 May 2015; Accepted: 14 August 2015; Published: 08 September 2015.
    Citation: Allison D.B., Bassaganya-Riera J., Burlingame B., Brown 
A.W., le Coutre J., Dickson S.L., van Eden W., Garssen J., Hontecillas 
R., Khoo C.S.H., Knorr D., Kussmann M., Magistretti P.J., Mehta T., 
Meule A., Rychlik M., and Vogele C. (2015) Goals in nutrition science 
2015-2020. Front. Nutr. 2:26. doi: 10.3389/fnut.2015.00026
---------------------------------------------------------------------------
David B. Allison,[1-4] Josep Bassaganya-Riera,[5] 
Barbara Burlingame,[6-7] Andrew W. Brown,[1] 
Johannes le Coutre,[8-10, *] Suzanne L. 
Dickson,[11] Willem van Eden,[12] Johan 
Garssen,[13] Raquel Hontecillas,[5] Chor San H. 
Khoo,[14] Dietrich Knorr,[15] Martin 
Kussmann,[10, 16] Pierre J. Magistretti,[17-18] 
Tapan Mehta,[19] Adrian Meule,[20] Michael 
Rychlik,[21] and Claus Vogele [22]
---------------------------------------------------------------------------
    \[1]\ Office of Energetics and Nutrition Obesity Research Center, 
School of Public Health, University of Alabama at Birmingham, 
Birmingham, AL, USA, [2] Section on Statistical Genetics, 
University of Alabama at Birmingham, Birmingham, AL, USA, 
[3] Department of Nutrition Sciences, University of Alabama 
at Birmingham, Birmingham, AL, USA, [4] Department of 
Biostatistics, University of Alabama at Birmingham, Birmingham, AL, 
USA, [5] Nutritional Immunology and Molecular Medicine 
Laboratory, Virginia Bioinformatics Institute, Virginia Tech, 
Blacksburg, VA, USA, [6] Deakin University, Melbourne, VIC, 
Australia, [7] American University of Rome, Rome, Italy, 
[8] Nestle Research Center, Lausanne, Switzerland, 
[9] Organization for Interdisciplinary Research Projects, 
The University of Tokyo, Tokyo, Japan, [10] Ecole 
Polytechnique Federale de Lausanne, Lausanne, Switzerland, 
[11] Institute of Neuroscience and Physiology, The 
Sahlgrenska Academy at the University of Gothenburg, Gothenburg, 
Sweden, [12] Department of Infectious Diseases and 
Immunology, Faculty of Veterinary Medicine, Utrecht University, 
Utrecht, Netherlands, [13] Faculty of Science, Utrecht 
Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, 
Netherlands, [14] North American Branch of International 
Life Sciences Institute, Washington, D.C., USA, 15 Technische 
Universitat Berlin, Berlin, Germany, [16] Nestle Institute 
of Health Sciences SA, Lausanne, Switzerland, [17] Division 
of Biological and Environmental Sciences and Engineering, King Abdullah 
University of Science and Technology, Thuwal, Saudi Arabia, 
[18] Laboratory of Neuroenergetics and Cellular Dynamics, 
Brain Mind Institute, Ecole Polytechnique Federale de Lausanne, 
Lausanne, Switzerland, [19] Department of Health Services 
Administration, Nutrition Obesity Research Center, University of 
Alabama at Birmingham, Birmingham, AL, USA, [20] Department 
of Psychology, University of Salzburg, Salzburg, Austria, 
[21] Analytical Food Chemistry, Technische Universitat   
Munchen, Freising, Germany, [22] Research Unit INSIDE, 
Institute for Health and Behaviour, University of Luxembourg, 
Luxembourg, Luxembourg.
    * Correspondence: Johannes le Coutre 
[email protected], [email protected].
---------------------------------------------------------------------------
          With the definition of goals in Nutrition Science, we are 
        taking a brave step and a leap of faith with regard to 
        predicting the scope and direction of nutrition science over 
        the next 5 years. The content of this editorial has been 
        discussed, refined, and evaluated with great care by the 
        Frontiers in Nutrition editorial board. We feel the topics 
        described represent the key opportunities, but also the biggest 
        challenges in our field. We took a clean-slate, bottom-up 
        approach to identify and address these topics and present them 
        in eight categories. For each category, the authors listed take 
        responsibility, and deliberately therefore this document is a 
        collection of thoughts from active minds, rather than a 
        complete integration or consensus.
          At Frontiers in Nutrition, we are excited to develop and 
        share a platform for this discussion. Healthy Nutrition for 
        all--an ambition too important to be handled by 
        detachedinterest groups.
        Johannes le Coutre, Field Chief Editor, Frontiers in Nutrition.
Sustainable Development Goals for Food and Nutrition
(Barbara Burlingame, Chor San H. Khoo, and Dietrich Knorr)

    To deliver successfully, nutrition research needs a bold dose of 
innovation. Moving forward from the Millennium Development Goals to the 
post-2015 sustainable development goals (SDG), global nutrition appears 
to require an improved model. Under current practices, feeding the 
exploding world population necessitates to close a gap of nearly 70% 
between the amount of food available today and the projected 
availability by 2050.(1) Today, globally, an estimated 805 
million people are undernourished or food-insecure,(2) yet 1 
out of 4 calories from food goes uneaten. Meanwhile, overweight and 
obesity affect approximately two billion people, including 42 million 
children under the age of 5. Human health notwithstanding environmental 
health is also at stake. Agriculture alone accounts for about 70% of 
our global water usage and 24% of our greenhouse gas emissions. As a 
result, our strategies to overcome issues of food sustainability, food 
waste, and food loss must be multifarious and include, at the very 
least: (i) Improving the global consumption of food. (ii) Increasing 
production efficiencies on existing agricultural land. (iii) Developing 
sustainable approaches that reduce the environmental impact of food 
production, and in particular greenhouse gas emissions. Certainly, the 
impact of agriculture on climate, ecosystems, and water will have to be 
reduced, while at the same time, we will need to ensure that it 
supports inclusive economic and social development.(1)
    Systems science, the interdisciplinary field that explores the 
nature of complex systems, is perhaps the best research model we have 
for addressing the urgent needs of a precariously unhealthy planet. For 
better or for worse, nutrition imparts a quintessential challenge, 
straddling many sectors and disciplines.
    In the past, at times, the agenda for mainstream nutrition has been 
pushing sectoral lines of reasoning by implementing policies that leave 
long-standing problems unresolved, while disrupting other sectors in 
the process. Of course, nutrition is not alone in this, but the history 
of unintended consequence is long and discouraging.(3-4)
    Agriculture and health have been the mainstay sectors at the United 
Nations level, in government ministries, and in academic departments. 
Increasingly, nutrition is being recognized as an important pillar for 
the environmental sector, with biodiversity for food and nutrition 
acknowledged by the Convention on Biological Diversity,(5) 
and the Commission on Genetic Resources for Food and Agriculture 
accepting whole diets, food, and nutrients for human nutrition as 
ecosystem services.(6)
    For all their embracing of nutrition, these sectors often work at 
cross-purposes, providing many useful illustrations of policies and 
programs that undermine each other's development efforts. We have 
policies and interventions in agriculture that contribute to diet-
related chronic disease, environmental degradation, and food 
insecurity; (4, 7) conversely, in the health sector we have 
policies and interventions that compromise agricultural 
development;(8) and in the environmental sector that lead to 
micronutrient malnutrition.(9) Agriculture in particular, 
while solving some of its own sector problems, has been associated with 
many of the environmental and human health crises we now face, which 
directly impact upon nutrition, including chemical contamination of 
food supplies, loss of agrobiodiversity, and severe environmental 
degradation.(10)
    In spite of the clear need to develop innovation for the future, 
``systematic attempts to explore existing methods and to develop new 
technologies of more sustainable food production systems have so far 
been scarce''.(11) Although this quote is from over 30 years 
ago, it still quite accurately describes the current situation 
regarding activities related to sustainable diets and sustainable food 
systems. A sustainable development lens with a systems science approach 
offers not only a new analytical model for nutrition, but also an 
ethical and inclusive framework. Within this framework, nutrition 
encompasses more than its traditional domains and takes on issues of 
climate change,(12) biodiversity and 
ecosystems,(13) water use/waste,(14) food losses 
and waste,(15-16) sustainable forests and 
seas,(17) chemical contamination of food and water 
supplies,(18) environmental regulatory issues and food law, 
risk and risk/benefit assessments,(19) and monitoring 
adherence to and compliance with a range of relevant treaties and 
signed declarations/commitments.(13)
    With this mindset of sensitive, cross-sectoral resolve, tangible 
and specific solutions will envisage a holistic food chain integration 
taking into account a total life cycle assessment. Food and nutrition 
security must be an intrinsic component of any solution for food 
sustainability. Forthcoming strategies will also have to explore the 
potential and utilization of new raw materials.
    Improvements of food safety, storage, packaging, and 
transportation--including the use of sensor technologies--can reduce 
food losses and waste. Innovation will have to equally encompass the 
re-evaluation of existing food processing, storage, and home 
preparation operations employing existing modern toolboxes. Moreover, 
low energy, waste-free or waste-reduced processing, and preparation 
operations need to be implemented to a larger extent, including 
alternative energy sources. In the same context, water decontamination, 
recycling, and preservation tools need to be applied.
    Unintended consequences must be considered with any sustainability 
program and global solutions are not necessarily applicable in local 
contexts. For example, reducing livestock production and consumption in 
one setting may benefit both human and environmental health, while in 
another setting it may reduce further already marginal intakes of high-
quality protein and micronutrients and marginalize grazing lands that 
are self-renewing, sustainable repositories of biodiversity. Finally, 
young engineers and scientists need to be encouraged, trained, and 
involved to tackle the challenges of the future.
    We have a planet in crisis on so many fronts. Regardless of how the 
SDGs evolve, this multi-sectoral vision of nutrition research and 
action has the potential to make meaningful, and sustainable, 
contributions.
Identifying and Mitigating Errors in Nutritional Science
(David B. Allison, Andrew W. Brown, and Tapan Mehta)

    ``Science,'' as Adam Smith famously said, ``is the great antidote 
to the poison of enthusiasm and superstition''.(20) 
Complementarily, Stephen Hawking has called scientists, ``the bearers 
of the torch of discovery in our quest for knowledge''.(21) 
Thus, science can be seen as having two key complementary roles--
dispelling false beliefs, and creating new knowledge. For science to 
fulfill this joint mission, its practice must be true to its principles 
and precepts, including objectivity, methodological rigor, 
transparency, and reproducibility. Yet, there are concerns that 
departures from these precepts are too common.(22-28) Some 
have speculated that deviations from good scientific practices have 
increased in recent years due to a number of social, institutional, and 
economic factors in science.(25, 29) Others have speculated 
that the problem may be especially severe in the related domains of 
nutrition research and obesity research, perhaps because of emotional, 
economic, and other factors involved in those topics or because the 
everyday familiarity with aspects of those topics is mistaken for 
expertise.(23, 26-28) It is difficult to quantify whether 
the situation is better or worse today than in the past, or whether 
this is especially true in nutrition and obesity research compared to 
other fields. Nevertheless, it is clear that the problem exists.

       Table 1: Common Errors Noted in the Published Literature a
------------------------------------------------------------------------
              Error                         Example(s) of error
------------------------------------------------------------------------
Errors involving or resulting       Self-reported energy intake
 from poor measurement              (33, 118, 119)b (34) c (32) d
                                    Self-reported weights (120)
                                    b (121, 122) d
Errors involving inappropriate      Cluster randomized trials
 choice of or incorrect study       with no degrees of freedom (123) c
 design                             Lack of control for non-
                                    specific factors, i.e., failure to
                                    isolate the independent variable of
                                    interest (124) c
                                    Non-random assignment in
                                    self-described RCTs (125) b
Errors involving replication        Not validating prediction
                                    models in fresh samples (126) d
                                    Gratuitous replication (35)
                                    d
Errors in statistical analyses      Inappropriate baseline
                                    testing in parallel groups RCTs
                                    (127) c (128) d
                                    Failure to appropriately
                                    manage missing data (129) c (130,
                                    131) d
                                    Not accounting for
                                    clustering in cluster randomized
                                    trials (132, 133) b (134, 135) c
                                    (136) d
Errors involving insufficient       Changing endpoints in a
 transparency in choices made       study (137) b (138) d
 about how to analyze and present   Excessive or unacknowledged
 the data                           multiple testing [called p-
                                    hacking,(139) d investigator degrees
                                    of freedom,(140) d or p-value
                                    fiddling,(141) d among other names]
                                    (142) c (143) b
Errors of misleadingly describing   Selectively citing only the
 past literature                    part of a study that supports a
                                    hypothesis (35) d
                                    Perpetuating citations from
                                    previous researchwithout confirming
                                    the original source (144) b
Errors that distort the             Publication bias (145) b
 scientific record by publishing    (23, 146) d
 studies as a function of study
 outcomes
Errors of interpretation or         Inappropriate use of causal
 communication                      language (24, 35) d
                                    Exaggerating or mis-
                                    describing results (35) d
                                    Highlighting benefits of
                                    treatment when the effects were non-
                                    significant (i.e., spin) (147) d
                                    Issuing misleading press-
                                    releases (148) d
Errors of logic and mathematics     Unreasonable linear
                                    extrapolations (e.g., 3,500 kcal
                                    rule) (149	150) b
------------------------------------------------------------------------
a Errors, examples, and references were identified in a manner neither
  systematic nor comprehensive.
b Denotes references correcting or commenting on specific errors.
c references in which the error in question occurred.
d Denotes references that provide tutorials on avoiding or overviews of
  the errors.

    Several initiatives are going to be important in the coming years 
to improve nutrition as a science. First is classifying errors that 
exist in the nutrition literature. Just as Mendeleev's Periodic Table 
of the Elements led to increased understanding of chemistry and 
Linnaeus' taxonomy of life led to a framework for the study of biology, 
if we can develop a ``pathology'' or classification of these errors, we 
may be better able to quantify the situation, identify patterns, 
develop an understanding of origins, and ultimately reduce the 
occurrence and severity of these errors. In our non-systematic study of 
these issues, we see a number of categories of common errors (Table 1). 
We refer to them as errors without making any inference that they are 
intentional or unintentional errors.
    Second, there is a general movement in science for ``Transparency 
and Openness Promotion,'' formalized in ``The TOP 
Guidelines''.(30) The guidelines recognize eight standards: 
citation, data transparency, analytic methods (code) transparency, 
research materials transparency, design and analysis transparency, 
preregistration of studies, preregistration of analysis plans, and 
replication. These standards aim to improve the communication of 
science, allowing improved understanding and replicability of results. 
Because the TOP Guidelines are being adopted across fields of science, 
the field of nutrition will not have to act in isolation to improve its 
scientific practices. Instead, we can build on and work with the minds 
and resources coming from a spectrum of scientific inquiry. Indeed, 
Frontiers in Nutrition was one of the initial signatories.
    Third, there is a need to develop sound methodology for evaluating 
nutrition and diet in free-living research participants. Issues are 
continually documented with self-report diet 
methodology,(31-33) and yet dietary recommendations depend 
heavily on dietary recall data.(34) Similarly, although 
existing nutrition-related health hypotheses can be investigated using 
randomized controlled trials (pragmatic or explanatory), the field 
often relies on ordinary association tests using observational data to 
quantify evidence (35-36) that policy-makers may then use to 
create policies or guidelines. The needs here are twofold: to develop 
and implement study designs that lie in the causality spectrum between 
ordinary association tests and randomized controlled trials 
(37-38) and to develop objective, reliable data on dietary 
patterns and nutrient status.(31-33)
    We believe that by recognizing and acknowledging these problems, we 
also recognize and acknowledge that our field can do better. This will 
pave the way toward constructive efforts to reduce such problems and to 
ultimately improve the scientific foundations of nutrition science.
Building the Foundation: Procurement of Relevant Measures and Big Data 
        Analysis
(Martin Kussmann, Josep Bassaganya-Riera, Raquel Hontecillas, Tapan 
Mehta, and Chor San H. Khoo)

    Diet is considered a key environmental factor for maintaining 
health and preventing disease. As such, we need to better understand 
the interactions of nutrition and lifestyle with an individual's 
genetic makeup in order to delay or prevent metabolic and cognitive 
decline. Nutrition science is therefore undergoing a paradigm shift to 
better leverage the potential of nutrigenomics, a discipline that is 
already transforming the field.(39) To achieve this, the 
field will need to transform its current approach to research and 
implementation actions, and to take advantage of emerging advances in 
other disciplines--research designs, methods, new technologies, big 
data analysis, and bioinformation sharing.
    The conceptual basis of gene--environmental interactions require 
not only research and technology, but also the cross-fertilization of 
disciplines: genomics will encompass other-omics, and nutrition 
research will need to take on a holistic or system biology approach 
rather than just nutrients, ingredients, or genes. Nutrition science 
now encompasses more than the classic reductionist and descriptive 
approaches to more quantitative and systems-level 
approaches.(40) Translational research to maintain health 
and prevent or delay disease onset requires a transdisciplinary 
approach that embraces the complexity of human individuality in a 
rapidly changing environment. Nutrigenomics fuels this research by 
investigating how genomic and epigenomic individuality predisposes 
dietary, health, and disease responses. It also influences how an 
individual's genome expresses itself at different omic levels 
(proteomics, metabolomics, lipidomics) in response to environmental 
factors, including nutrition. Molecular phenotyping of humans over time 
and across healthy and safe exposures and challenges have thus been 
proposed.(41)
    Both the ongoing prevalence of malnutrition and the increasing 
incidence of nutrition- and lifestyle-related chronic diseases require 
comprehensive characterization of the complex interactions between 
environment and genetic makeup. Systems thinking in human nutrition, 
environment, and health requires improvement and translational thinking 
in three areas:

  (a)  In vitro and in vivo models: a systems approach to human health 
            implies rethinking of in vitro and in vivo models with 
            regard to their translatability into human phenotypes: 
            natural human cell models and panels of rodent strains 
            should complement cancer cell lines and single rodent 
            strains.

  (b)  Human intervention study designs: classical case/control designs 
            of human clinical/nutritional intervention studies should 
            be complemented by longitudinal crossover studies, in which 
            every subject is one's own case and control. Human clinical 
            study subjects should not only be assessed at homeostasis, 
            but also during a challenge to, and restoration of, 
            homeostasis.

  (c)  Tools for molecular phenotyping and capturing of human diet and 
            lifestyle: nutrigenomic studies have typically been 
            technology-driven rather than technology-rooted. Normative 
            science methods and approaches need to be complemented by 
            more comprehensive systems biology-based investigations 
            deploying a multitude of omic platforms in an integrated 
            fashion.(41) While comprehensive and 
            quantitative omics are rapidly progressing in terms of data 
            generation, quantitative capture and monitoring of diet and 
            lifestyle have lagged behind. Non-invasive technologies are 
            now providing more attractive and precise image- and 
            webbased or body-wearable consumer/research 
            interfaces.(42) The bottleneck in knowledge 
            generation has moved from (omics and clinical) data 
            acquisition to processing, visualization, and 
            interpretation. Innovative tools and methods for 
            statistical treatment and biological network analysis are 
            now at the forefront of nutritional and biomedical 
            sciences.(43)

    To achieve this transformation and advancement of nutritional 
science, it is critical to connect researchers from all disciplines 
conducting direct or indirect research in the areas, e.g., (gen) omics, 
clinicals, dietetics, food science and technology, physiology, 
epidemiology, bioengineering, analytics, biomathematics. A 
transdisciplinary approach needs to be considered--enabling a spectrum 
of communicating and sharing from fundamental laboratory research, 
patient- and consumer-relevant outputs from personalized dietary/
nutritional counseling to monitoring/diagnostics. Progress in advancing 
nutrigenomic interventions for consumers and patients can only be 
accelerated if nutrition research is broadened to include quantitative, 
holistic, and molecular sciences.(44)
    ``Let the food be your medicine, and medicine be your food,'' a 
statement attributed to Hippocrates, the father of Western Medicine, 
delineates the impact of nutrition in human health and disease. Indeed, 
several decades of research at the interface of nutrition and 
immunology demonstrate that infectious, immune-mediated and metabolic 
diseases are safely and effectively preventable through dietary 
interventions. Nonetheless, there is a major disconnect between the 
description of nutrition-based protection from disease and an 
insufficient mechanistic understanding at the systems-level of the 
complex network interactions by which nutrition mediates clinical 
protection. As a result, a comprehensive understanding of the 
mechanisms of action underlying the actions of nutritional 
interventions and the combinatorial effects of nutrients (i.e., 
synergistic, antagonistic, or additive) at the systems-level remains 
largely unknown. As about 70% of the immune system is located in the 
gastrointestinal tract since the gut mucosa houses the largest 
repertoire of immune cells and commensal microbiota that symbiotically 
coexist to elicit protective immunity, studying nutritional immunology 
of the gut mucosa is incredibly important.(45) Coupling 
host-nutrient-microbiota actions, enabled through computational 
modeling of the gastrointestinal tract (46-50) with systems 
immunology frameworks has the potential to predict combinatorial 
outcomes of nutrient-microbiota-immune system interactions and advance 
toward a comprehensive systems-level mechanistic understanding of how 
nutrition and foods prevent disease. Computational models of 
nutritional immunology that funnel omics and cellular data judiciously, 
coupled with systems biology models of the underlying disease/organ, 
will bridge the connection between traditional methods of nutritional 
immunology research and their effect on the whole organism, which will 
enhance mechanistic insights and translational value. Over 163 
nutrition themed systems biology markup language models (SBML) are 
already available in the Biomodels database.(51) In summary, 
applying the iterative systems biology cycle of model building, 
calibration, refinement, and validation in nutritional immunology 
research has the potential to accelerate the discovery of novel network 
biomarkers and systems-level mechanistic understanding of the action of 
dietary components on immuneresponses.
    There has been an explosion in data collection and aggregation, 
some of which can be used for public health purposes, including obesity 
and nutrition-related research. Consequently, ample opportunities 
emerge to utilize ``big data'' in the pursuit of interesting outcomes 
and effectiveness studies related to nutrition and obesity using 
techniques such as quasi-experimental approaches. These approaches, 
when assumptions are satisfied, are intermediate between ordinary 
association tests and randomized controlled trials (37) in 
terms of presenting evidence for causality. In this article, the term 
``big data,'' which is often used subjectively, refers to very large 
amounts of data: structured and unstructured that may also increase 
over time rapidly.(52) These types of data are collected by 
both the public and private sectors and increasingly require a 
distributed architecture to manage them efficiently. Big data analysis 
has generally referred to the confluence of statistical, machine 
learning and computational approaches to synthesize and analyze these 
large amounts of data. Administrative data, such as micro-level data 
aggregated by governments as well as private companies, can be used to 
evaluate the effectiveness of pharmacological and surgical 
interventions. In fact, private companies have started collecting 
unprecedented amounts of data with some companies specializing in data 
linkages. For example, companies such as Optum not only aggregate 
claims data from private insurance companies but are able to provide 
linked clinical data from the corresponding electronic health records 
(EHR). Data linkages are an extremely powerful tool since they allow 
researchers to answer questions that are otherwise not accessible using 
a single data source. For example, claims data do not provide 
information about the height and weight of an individual, but the 
linked clinical data do. Similarly, the increasing availability of EHR 
data and the initiatives to link these EHR data with genomic data can 
enable us to pursue a variety of studies, including pharmacogenetic and 
precision medicine studies. One of the challenges in accessing and 
leveraging ``big data'' is the resources, including the associated cost 
of purchasing the data, especially from private companies. 
Collaborations between industry and academic researchers are essential 
to fully exploit the data and to overcome logistical 
challenges.(53-54)
    So far, big data analysis has primarily focused on high-dimensional 
prediction models. The data mining and statistical toolkit for such 
approaches includes, but is not limited to, techniques such as 
boosting, random forests, classification and regression trees, and 
lasso-like penalized regression models.(53) While randomized 
control trials are considered gold standards, there are a variety of 
methods and designs that may allow us to generate evidence that may lie 
in the spectrum between purely association and definitively causal. 
Coupled with ``big data'' is an opportunity to estimate a degree of 
causality using techniques such as high-dimensional propensity score 
and differential comparison approaches to provide evidence that is 
indicative of causality.(55-56) There is also a potential to 
use instrument variable approaches, used commonly in health policy 
studies, by identifying appropriate instruments from ``big data.'' 
Recent attempts to develop methods that enable to provide a degree of 
causal evidence are very encouraging and can allow us to maximize the 
potential of ``big data''.(57-58)
Authenticity and Safety of Foods
(Michael Rychlik)

    The authenticity of food is generally related to one or more of the 
following attributes: geographic origin, type of agricultural 
production, species and kind of raw materials, or certain process 
qualities such as sustainability or ecological foot print.
    Regularly uncovered crises of food adulteration underline the 
sensitivity of consumers to this issue. Apart from meat, foods that are 
often adulterated are olive oil, fish, organic foods, spices, tea, 
cocoa, coffee, and nuts.
    In recent years, there has been tremendous progress in high-
resolution methods to elucidate the molecular fingerprint of food. On 
the genetic scale, apart from classical polymerase chain reaction, new 
developments of isothermal amplifications or next generation sequencing 
will enable more accurate identification of species.
    On the protein level, specific biomarker peptides can be used. For 
a fingerprint of metabolites, the new methods of non-targeted and 
targeted metabolomics already allow a specific authentication. In this 
field, the methods currently showing the best resolution are Fourier 
transform ion cyclotron mass spectrometry (FT/ICR-MS) or nuclear 
magnetic resonance (NMR) spectroscopy.(59) These new 
methodologies generate ``big data,'' from which the relevant 
information is only accessible when applying novel bioinformatics 
approaches.
    Regarding food safety, microbiological decay and foodborne 
infections still play an important role. However, contaminants also 
endanger the safety of all links in the whole food chain. The recent 
discoveries of process contaminants encompass simple molecules, such as 
acrylamide, furan, benzene, styrene, as well as more complex compounds 
such as 3-monochloropropane-1,2-diol (MCPD) esters. An end of new 
discoveries cannot be foreseen yet and we may assume that the sum of 
all these contaminants has a significant impact on life-style diseases 
such as cancer. Further new contaminants arise from packaging materials 
such as mineral oil saturated hydrocarbons (MOSH) or mineral oil 
aromatic hydrocarbons (MOAH), and pollutants from the environment such 
as the polyfluorinated alkyl substances (PFAS). Moreover, the historic 
toxin arsenic is more relevant than ever as rice and rice products are 
often contaminated and the mechanisms of arsenic carcinogenicity are 
still under controversial discussion.
    Generally, risk assessment of food contaminants or residues is 
predominantly performed on single compounds. However, almost completely 
missing is an assessment of the combined effects of toxins, be it 
within one group of compounds or spanning various structural groups. 
The current concept for assessing combinatorial effects is that of 
cumulative assessment groups (CAGs), which, e.g., assess the cumulative 
potency corrected dose of acute reference doses (ARfD) for pesticides 
showing the same mode of toxic action.(60) However, this 
approach is still preliminary and lacks comprehensive confirmation.
The Science Behind Food-Related Behavior in Humans
(Adrian Meule, Chor San H. Khoo, and Claus Vogele)

    Numerous environmental, social, and individual factors influence 
human food choice and intake.(61) In Western and Westernized 
societies, household expenditures and dietary energy availability 
decreased for unprocessed or minimally processed foods in the last 
decades while they increased for convenience foods and processed 
products.(62-63) An environment where there is easy and 
frequent accessibility to food, and where cues signaling food are 
ubiquitous, requires constant self-monitoring and -regulation in order 
to prevent or manage weight gain.(61) This, however, can be 
a highly effortful endeavor, leading many people to struggle with long-
term weight maintenance. As evident from data from the last century, 
these self-regulatory efforts are made more difficult by increased 
consumption of energy-dense palatable foods and ingredients (e.g., 
sugar, fat, and salt).(64) As a result, some have argued 
that these foods might have an addictive potential and that a subset of 
individuals who have difficulties in controlling consumption of these 
foods may be addicted to them.(65-68)
    In the scientific literature, the association between food and 
addiction and the actual use of the term food addiction has a long 
history, dating back to the 1950s and even earlier 
times.(69-70) Not until recently, however, have researchers 
tried to more precisely define what is meant by food addiction and to 
systematically investigate its validity, as a consequence of which the 
number of publications, including the term food addiction, increased 
substantially over the past 5-6 years.(65, 71) In humans, 
research on food addiction has been promoted by the Yale Food Addiction 
Scale (YFAS), a self-report questionnaire developed in 2009, which 
measures symptoms of addiction-like eating based on the diagnostic 
criteria for substance dependence as outlined in the fourth version of 
the Diagnostic and Statistical Manual of Mental Disorders (DSM-
IV).(72) Since 2013, these diagnostic criteria have been 
revised in the fifth version of the DSM and a new version of the YFAS, 
which has been adapted accordingly, is currently under 
way.(73)
    Although research on food addiction is growing, it remains a 
controversial and debated topic with many researchers questioning the 
validity of the food addiction concept based on conceptual 
considerations or physiological mechanisms.(74-78) To 
address these issues, more and better human studies are needed to 
resolve questions related to, for example, whether animal models of 
food addiction are transferable to human eating 
behavior.(79-80) These controversies, in particular, lead us 
to argue that food addiction research in humans is still in its 
infancy, that it would be premature to conclude that some foods are 
addictive, and that research efforts to clarify this will further 
increase in the years to come.
    There are numerous avenues for future directions, which may 
include, but are not limited to: how do we define and harmonize 
definitions of food addiction? What are the implications of changes in 
the diagnostic criteria for substance dependence in the DSM-5 for food 
addiction? (73) Are all addiction criteria (as described in 
the DSM-5) equally applicable to human eating behavior? If not, does 
this obliterate the concept of food addiction? (81) How can 
food addiction be measured in humans other than using the YFAS and 
which methodological improvements need to be made to better design 
human behavior studies, including randomized controlled trials? 
(72) How relevant is the concept of food addiction for the 
treatment of obesity or binge eating and in public policy making? If it 
is relevant, how can it best be implemented? (70, 82) What 
are the disadvantages (if any) of the concept of food addiction? 
(83-85) How can animal models of addiction-like eating be 
improved to more specifically reflect relevant processes in humans? 
(86) Which foods are possibly addictive? (87) Can 
addiction-like eating actually be reduced to the addictive effects of 
substances or should the discussion about ``food addiction'' rather be 
replaced by a discussion on ``eating addiction''? (88)
The Molecular and Physiological Science Underlying Nutrition and Brain 
        Health
(Pierre Magistretti, Johannes le Coutre, and Suzanne L. Dickson)

    Cognitive decline, dementia, Alzheimer's disease, and other age-
related neurological diseases are on a rise in high income countries as 
well as in low and middle income countries.(89) Achieving 
and maintaining brain health is a lifelong endeavor with identifiable 
targets that are specific for each period in a lifetime. Thus, 
targeting cognitive development in the early phases of life and 
preventing cognitive decline during aging are priorities for any 
preventive or interventional approach. While pharmacological approaches 
can only be envisioned for brief periods of time and, for the most 
part, have been unsuccessful, nutritional approaches are implementable 
for extended periods of time. Initiatives on brain health should 
incorporate a nutrition-based approach that can be implemented 
throughout the different phases of life.
    In order to identify valid nutritional approaches for brain health, 
it is important to better understand the mechanisms that are at the 
basis of brain energy metabolism regulation. Key advances have been 
made in recent years in the identification of the molecular and 
cellular mechanisms that regulate the delivery of energy to active 
neurons. In particular, an active metabolic exchange has been 
characterized between neurons and astrocytes with specific molecular 
steps that can become targets for nutritional interventions.
    For the identification of the efficacy of such nutritional 
interventions, means for appropriate monitoring of markers need to be 
defined. This can be achieved by monitoring with brain imaging 
techniques, structural markers with morphometric approaches and 
myelination with MR as well as functional activation with fMRI, PET, 
EEG, and MRS, coupled with neuropsychological tests monitoring 
cognitive performance, motivation, and attention. The utility of these 
technologies goes beyond brain health and many of these approaches are 
being used to validate, in humans, the neuroscience of nutrition that, 
so far, has only been conducted in rodent models.(90-91)
    There is no doubt that targeting the molecular steps of brain 
metabolism with nutritional interventions and monitoring their 
structural and functional outcomes in vivo in humans, in particular 
regarding cognitive performance, represents a promising approach for 
developing nutritional interventions for achieving brain health that 
can be maintained on the long term. Meaningful nutrient intake and 
nutritional intervention likely has an impact on the development of 
cognitive and behavioral performance measures, thereby determining our 
health span throughout life. Brain imaging studies on infants 
demonstrate how breast milk promotes healthy neural growth and early 
white matter development.(92)
    Nutrients also engage brain pathways linked to metabolic control, 
appetite, and food-linked behaviors. There has been a general 
expectation that it must be possible to use food formulation/
composition to control how much and what we eat by altering the 
satiating and/or reward value of food combinations.(93-94) 
Currently, we lack a sufficient scientific evidence base that certain 
``unhealthy'' foods fall short of ``healthy'' foods in their ability to 
induce satiation, limit hunger, or reduce hedonic over-eating. 
Moreover, it has not yet been demonstrated that any food or combination 
of foods has beneficial effects on appetite and energy intake of 
sufficient duration or magnitude to impact on body weight or metabolic 
health.(95) This is a new and emerging field for which major 
advances are likely to progress through a better understanding of how 
nutrients communicate with the appetite-regulatory brain networks. 
Nutrient-brain communication could be direct but likely engages 
intrinsic physiological control systems. For example, when we eat, 
sensing mechanisms in the gut signal information about the amount and 
content of the food to the brain by nervous and endocrine afferent 
signals. Indeed, gut-derived hormones such as ghrelin and glucagon-like 
peptide 1 communicate with hypothalamic and brainstem areas linked to 
energy balance but also to brain areas processing the reward value of 
food and even brain areas linked to emotion and 
cognition.(96-97) Thus, while it seems clear that appetite-
regulating hormones have a capacity to redirect behaviors important for 
governing how much and what we eat, the extent to which nutrients can 
control these behaviors through engaging intrinsic endocrine signals 
remains to be elucidated.
    A related question is whether specific nutrients or food 
combinations can act on the brain to reinforce their own intake, 
leading to addictive-like over-consumption. As reviewed recently 
(88) and as mentioned already in the previous section, it is 
very difficult to demonstrate in humans or rodents that foods act on 
the brain in a manner similar to addictive drugs, causing individuals 
to become addicted to them. It was suggested therefore that the term 
``eating addiction'' rather than ``food addiction'' should be used to 
better describe addiction-like behavioral over-eating disorders. If it 
becomes possible to diagnose this patient group, e.g., through 
combining questionnaires about addictive-like behavior for food with 
brain imaging,(98-99) there will be a large public health 
impact on treatment and prevention strategies. Additionally, industrial 
stakeholders and politicians will need to find solutions to circumvent 
or treat eating addiction.(88)
The Science of the Human Microbiome
(Dietrich Knorr and Chor San H. Khoo)

    The human body harbors over eight million microbial genes, over 
10,000 species, and plays host to over a trillion microbes. Microbial 
cells outnumber human cells by a factor of 10.(100) As a 
result, there is considerable interest to better define and understand 
the microbial role in host physiology, health, and disease etiology. In 
the last decade, there has been a tremendous surge in microbiome 
research funded by programs such as the Human Microbiome Project (HMP) 
and the MetHIT Program. Advancing new and multiple technological 
approaches--whole genome sequencing, metagenomics, high-throughput-
analysis, proteomics, transcriptomics, cultivation, metabolomics, and 
bioinformatics--has led to new insights into microbial variety and 
abundance in 15-18 body sites, including the oral cavity, skin, airway, 
gut, and vagina, from 242 healthy participants in the largest cohort 
study to date. Findings from this research were published in two 
seminal papers in 2012 by the Human Microbiome 
Consortium.(100-101) The HMP study has the largest 
collection of data on abundance and variety of the human microbiome, 
with 5,177 unique microbial taxonomic profiles from 16S ribosomal RNA 
genes, more than 3.5 terabases of metagenomic sequence, and 800 
reference strains isolated and sequenced.(100) Noteworthy 
observations from the HMP study are outlined in Table 
2.(102)

     Table 2: Variation in Microbial Ecology Among Individuals (102)
------------------------------------------------------------------------
 
-------------------------------------------------------------------------
Each person's microbiome is unique and no two individuals have the same
 microbiome (102) However, in spite of individual microbial differences,
 different individuals can still be considered healthy
Microbial communities across varying body regions may predict some
 characteristics such as breast fed history and educational level
Microbial communities from different body regions from an individual
 were predictive for others. For example, the oral community can be used
 to predict the gut community
Overall, low relative numbers of pathogens have been observed
Strong site specialization but considerable variation in diversity and
 abundance of each habitat's signature microbes among subjects
Strong functional stability. This means that while the microbial
 compositions were widely different, the functionality is similar. This
 suggests flexibility to develop microbial communities that can provide
 similar performance
Wide variation in patterns of alpha and beta diversity (alpha-diversity
 within a site; beta diversity among subjects)
Correlations between ethnicity and microbiome composition across all
 body habitats
A positive correlation of vaginal pH to microbial diversity (higher pH
 having higher diversity)
An association of age with skin microbiome-associated metabolic pathways
 and oral microbiome composition
------------------------------------------------------------------------

    Translating learnings from emerging microbiome and health research 
presents exciting opportunities for future food and nutrition 
development. The use of microbes in food product development is not 
new. Fermented products are widespread and common in the marketplace. 
Food biotechnology has been in existence for more than 8,000 
years.(103) The potential health impact of gut microbiota 
has been postulated by Metchnikoff (104) and since then, 
numerous related research results have been 
provided.(105-107) Probiotics are supplied in starter 
cultures and thus need to be preserved for transportation and use. As 
the highest possible cell density is required, losses that occur during 
processing, transportation, and storage, including in products, are 
detrimental. Consequently, approaches to increase and retain 
physiological fitness have been explored.(108-109)
    Emerging capabilities to characterize microbial communities and 
their functions in the oral cavity present insights into the role 
microbes may play in taste and olfaction, and present new opportunities 
to further personalize and refine food products to better suit 
individual taste and palatability preferences. Oral pre- and probiotics 
may be an opportunity for innovation.
    These emerging advances in human microbiome structure, diversity, 
and function present exciting new opportunities for new food products, 
ingredients, or dietary approaches that can be used for supporting 
daily health, direct or adjunct intervention for risk reduction, or for 
new therapeutics for symptom reliefs (IBS). However, to advance these 
undertakings, several key questions need to be addressed. How easy is 
it to translate microbiome research to food and dietary applications? 
Limited well-designed studies have been performed that explore the 
impact of food and diet on microbial ecology and function. What 
biomarkers are available or need to be developed to understand how food 
and diet impact on the microbiome (gut, gut-brain, gut-kidney, etc.)? 
What microbial combination will be best suited for achieving specific 
outcomes? Of challenge is the ability to identify and separate the 
``good'' from the ``bad'' microbes that can present foodborne illness 
or exacerbate disease risks. Gene sequencing and whole genome 
sequencing technologies have been used to diagnose and trace food 
contamination, and are now also applied in medicine. How can current 
microbiome research be easily translated for food and product 
applications? How easy is it to transfer available technologies and 
tools already developed for use in food and nutrition applications?
    In addition, there remains room for improvement when translating to 
innovative or tailor-made products. Needs and opportunities include 
process generated structures, which impact on food properties (process-
structure-function relationship) as outlined in the European Technology 
Platform Strategic Research Agenda (ETP SRA) (2007; 2012; 2014) for 
designing tailor-made foods for the targeted release of essential food 
constituents at points of need to support human microbiota growth and 
metabolic fitness. This needs to include the entire human digestion 
system encompassing the chewing apparatus, mouth microbiota, and 
enzymes. Moreover, food can contain viable microbial cultures as well 
as active enzymes. Understanding their role in and during digestion as 
well as their impact on gut, mouth, and skin microbiota may lead to the 
development of new food design concepts with targeted nutritional 
benefits.
    Finally, emerging technologies are being introduced to the food 
processing area, including high hydrostatic pressure, pulsed electric 
fields, and atmospheric plasma. Little is known about their impact and 
function with regard to the human microbiota. These technologies could 
open new avenues for process-function-structure relationships as well 
as provide foods with metabolic properties not achieved via traditional 
processing.(36)
Nourishing the Immune System and Preventing Disease
(Johan Garssen, Willem van Eden, and Josep Bassaganya-Riera)

    Whereas the disciplines of pharmaceutical and nutritional sciences 
have evolved separately in the Western world, for Asia these two 
research areas have been connected for centuries. However, today, with 
the ever-growing burden of chronic diseases in modern societies, the 
high relevance of specialized nutrition in both prevention and 
therapeutic approaches receives increased attention and recognition. 
The gap between food and pharma is narrowing.(110) One 
reason might be that, scientifically, the evidence for the so-called 
multi-target or polypharmacology approaches aimed at disease management 
is growing. Medical nutrition is beginning to be recognized as a unique 
and potentially powerful area in Western societies at the interface 
between food and pharma.
    Medical nutrition targets innovative nutritional therapies, 
offering healthcare professionals solutions to effectively manage 
disease-related malnutrition and specific disease states. Medical 
nutrition is and will be increasingly understood as a useful and 
sometimes even essential component in the management of patient health. 
Many medical conditions can be managed better when patients are 
receiving a specialized diet adapted to their unique circumstances. 
Sometimes, the constraints to appetite may be physical, as in the case 
of stroke patients who may find it difficult or impossible to swallow, 
or of young children with neurological disabilities. Sometimes, the 
problem may simply be insufficient intake, caused by the loss of 
appetite. It is well known that many chronic diseases are associated 
with malnutrition, a phenomenon that is not solely based on body mass 
index or body weight. Many obese patients suffer from specific 
malnutrition. Examples of disease areas that might be associated with 
specific malnutrition are cancer, stroke, and COPD. However, frail or 
elderly people are treated and fed with this type of medical nutrition 
as well. Medical nutrition might bring solutions and support to these 
cases across a broad range of care settings--in the hospital, in the 
care home, or in the community. It contains unique compositions of 
specific nutrients that would be impossible or impractical to achieve 
through normal food intake alone. In most cases, it is administered via 
the gastrointestinal tract orally or with a feeding tube, utilizing the 
natural route for nutrient digestion and absorption. These cases are 
underpinned by a unique scientific rationale, preclinical and clinical 
research, and health economic evaluation making it very similar to the 
traditional pharma approach. By making medical nutrition an integral 
part of care, patient outcomes are significantly improved. Lower 
healthcare costs by shortening hospital stays and keeping patients 
independent for longer are key outcomes for medical nutrition 
intervention. The food for special medical purposes (FSMP) is the 
regulatory directive involved with the quality/safety and efficacy of 
medical foods.
    Another and unique medical area for which medical nutrition is 
aimed is disease-specific (the so-called disease targeted) medical 
nutrition. This type of medical nutrition is a unique, effective, 
therapeutic nutritional intervention for patients with, e.g., a 
clinical need to avoid certain nutrients due to specific diseases or 
conditions where normal food intake is harmful. Examples are inborn 
errors of metabolism such as phenylketonuria (PKU) or severe cow's milk 
allergy and childhood epilepsy. Ketogenic therapy during refractory 
epilepsy can reduce seizures significantly. Other examples for disease-
specific medical nutrition are science-driven concepts containing 
different and uniquely selected nutrients that can act in an orchestra 
leading to a delay in disease progression. Validated examples have been 
described for Alzheimer's, HIV, diabetes, and 
cancer.(111-114)
    Disease-targeted medical nutrition can be aimed at conditions such 
as chronic inflammation. These inflammatory conditions are on the rise. 
This is caused by changes in life-style, food consumption patterns, and 
aging. Inflammation-associated conditions, such as atherosclerosis, 
type 1 and type 2 diabetes, obesity, Alzheimer's disease, and many 
others, are a growing burden to health budgets. Inflammatory conditions 
are thought to result from failing mechanisms of immunological 
tolerance. Of these mechanisms, deficient suppressive activities of a 
specialized subset of T cells, called regulatory T cells (Tregs), are 
being recognized as a major factor in the failure of immunological 
tolerance. A start has been made with the definition of antigen-
specific Tregs with a broad anti-inflammatory effect, such as, for 
example, those that recognize inflammation-associated stress-
proteins.(115) Herewith, the restoration of this regulation 
will be a widely sought goal, also for the field of nutrition. A 
telling example of what may be possible is the following. Wieten, et 
al., have shown that the up-regulation of stress-proteins, such as heat 
shock protein 70 (HSP70), in the cells lining the gut, leads to the 
local induction of Tregs.(116) Working with a model of 
chronic and relapsing arthritis, it was found that HSP70 was also 
induced in Peyer's patches and the induced HSP70-specific Tregs were 
having a systemic effect seen to fully control arthritis. This up-
regulation was achieved by the oral administration in mice of 
carvacrol, an essential oil of Oregano species. It showed that our diet 
may contain effective coinducers of stress-proteins and that these co-
induced proteins can elicit anti-inflammatory activity in the immune 
system. Similar activities have now been described for other food 
components.(117) Therefore, especially for the diets of the 
aging individual, substances with anti-inflammatory activities will be 
an attractive component. In the field of veterinary medicine and food 
animal production, restrictions are now being imposed on the use of 
antibiotics, certainly on the use of antibiotics as growth-enhancers. 
Also here, feed additives are searched with the purpose of controlling 
inflammation and thereby enhancing weight gain.
    In combination with drugs, medical devices and lifestyle 
modification, medical nutrition, and immune system targeted 
nutraceuticals can play an essential role in health care and precision 
medicine. Expectedly, it will lead to lower costs of care: fewer 
complications, shorter hospital stays and reduced mortality, and the 
reduction of disease manifestations.
    Over the coming years, Medical Nutrition and Nutraceuticals have 
the opportunity to be accepted as a bridge between food and traditional 
pharma approaches--not as isolated therapy but as part of integrated 
systems-wide health care. Additionally, pharma often is focusing on a 
monotherapeutic approach (one molecule one target) and medical 
nutrition will be recognized as the multi-target approach for disease 
management. Regulation and acceptance depends on national and 
international guidelines. Changes in regulation for medical nutrition 
are to be expected since medical nutrition is a relatively new 
therapeutic area that falls between different regulations and 
guidelines. For instance, in the USA, under section 5(b) of the Orphan 
Drug Act [21 U.S.C. 360ee(b)(3)], a medical food is formulated to be 
consumed or administered enterally under the supervision of a physician 
and which is intended for the specific dietary management of a disease 
or condition for which distinctive nutritional requirements, based on 
recognized scientific principles, are established by medical 
evaluation. Thus, from a regulatory perspective, medical foods are 
different than dietary supplements in that claims for medical foods can 
allude to disease management whereas dietary supplement claims cannot. 
Medical foods are exempted from the labeling requirements for health 
claims and nutrient content claims under the Nutrition Labeling and 
Education Act of 1990. In order to be a medical food, a product must 
meet the following criteria: to be a food for oral or tube feeding, the 
product must be labeled for the dietary management of a specific 
medical disorder, disease, or condition for which there are distinctive 
nutritional requirements, and the product must be intended to be used 
under medical supervision. Essentially, medical food comes into play 
when dietary management cannot be achieved by the modification of the 
normal diet alone. For instance, medical foods could be used to replete 
key metabolic components that might be depleted in diabetes or 
inflammation. Only translational research and randomized, placebo 
controlled double-blind clinical trials can validate these new 
concepts.

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    Conflict of Interest Statement: The authors declare that the
 research was conducted in the absence of any commercial or financial
 relationships that could be construed as a potential conflict of
 interest.
    Copyright 2015 Allison, Bassaganya-Riera, Burlingame, Brown, le
 Coutre, Dickson, van Eden, Garssen, Hontecillas, Khoo, Knorr, Kussmann,
 Magistretti, Mehta, Meule, Rychlik and Vogele. This is an open-access
 article distributed under the terms of the Creative Commons Attribution
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                              attachment 5
Unintended Consequences of Obesity-Targeted Health Policy
  Virtual Mentor
  American Medical Association Journal of Ethics
  April 2013, Volume 15, Number 4: 339-346.
  Policy Forum
  Andrew W. Brown, Ph.D., and David B. Allison, Ph.D.

          L'enfer est plein de bonnes volontes et desirs. [Hell is full 
        of good wishes and desires.]
                              Saint Bernard of Clairvaux.[1]

    The conflict between individual freedom of choice and a 
government's obligation to protect its citizenry from threats to public 
health is often at the center of health policy debates. This has played 
out in New York City, for instance, with freedom of choice being the 
rallying cry of those opposed to a citywide ban on large containers of 
beverages,[2] while saving lives through health-motivated 
policies is offered as the justification for the 
regulations.[3] However, several other ethical concerns 
exist related to the creation or implementation of public policy. 
Herein, we will discuss a catalog of ethical concerns identified by M. 
ten Have, et al.[4] related to policies intended to prevent 
or treat obesity.
    We discuss these ethical concerns in light of two key issues: (1) 
Under which circumstances does obesity merit being considered a public, 
as opposed to simply a common, health concern? Whether or not obesity 
is considered a public health concern is important in deciding whether 
impinging on individuals' rights may be warranted. (2) How plausible is 
it that a given policy or program will have negative unintended 
consequences? These consequences are important to consider when 
deciding if a policy should be implemented. We then suggest strategies 
for minimizing ethical and other unintended adverse consequences of 
obesity-targeted health policies.
Ethical Concerns in Obesity-Targeted Health Policies
    In ``Ethics and Prevention of Overweight and Obesity: An 
Inventory,'' Marieke ten Have and colleagues identify ethical concerns 
posed by 60 actual or proposed public policies, corporate initiatives, 
and behavior recommendations intended to prevent or treat 
obesity.[4] One group of ethical concerns comprises direct 
negative consequences of a program, including physical and psychosocial 
harm, dissemination of inadequate information, and creation or 
exacerbation of inequalities. The other group of ethical concerns 
encompasses disrespect for individuals and their rights and values, 
including transgressing personal and cultural values of eating, 
invading privacy, assigning fault for obesity, and abridging freedom of 
choice. Typically, more than one of these concerns exist with varying 
degrees of severity for any proposed policy or recommendation, but 
often the debate is dichotomized as a desire to promote health versus a 
desire to preserve individual liberty.
    The complexity of ethical considerations in obesity policymaking 
can be demonstrated by a policy that would allow the government to 
remove an obese child from his or her home (see Table 1). Note that the 
pros and cons listed in the table are not necessarily weighted by 
importance because importance is dependent on individual perspectives 
and specific situations. Here, the assumed benefit of the policy is 
that removing the child from the home will improve his or her weight 
and therefore health, though that assumption is itself 
contentious.[5] As the table shows, the ethical 
considerations are far more complex than health vs. freedom of choice. 
To add to the complexity, a given individual may consider one specific 
ethical concern more important than all others: for health advocates 
the physical health implications may outweigh all other concerns, while 
for the parents the sanctity of the parent-child relationship may be 
paramount.[6]

 Table 1. Ethical Concerns of an Example Policy in Which the Government
Is Allowed To Remove Obese Children From Homes. The Ethical Concerns Are
  Not Necessarily Equally Prevalent and Do Not Necessarily Carry Equal
                                 Weight
------------------------------------------------------------------------
   Ethical concern [4]        Pro-policy view        Anti-policy view
------------------------------------------------------------------------
Physical health            Improved health if    There may not be the
                            professionals can     resources or knowledge
                            affect weight.        to improve the health
                                                  of the removed child
                                                  in the long term.
Psychosocial well-being    Obesity is            Removing children from
                            associated with       parents may be more
                            psychological         traumatic than the
                            disorders.            obesity.
Equality                   All children have     Obesity affects the
                            the right to a        poor and minorities to
                            healthy childhood     a greater extent, so
                            and life.             this policy will
                                                  disproportionately
                                                  target these groups.
Informed choice                                  Parents are no longer
                                                  able to make decisions
                                                  for their child.
Social/cultural values     The social value      The social value placed
                            placed on fitness     on parent-child
                            and health is         relationships is
                            upheld.               violated.
Privacy                                          The family's and
                                                  child's privacy may be
                                                  compromised.
Attribution of             Responsibility for    The parents are
 responsibility             the child's obesity   directly or indirectly
                            is shared among       blamed for the obesity
                            society and medical   and stigmatized.
                            professionals.
Liberty                                          The parent's and
                                                  child's liberties are
                                                  violated.
------------------------------------------------------------------------

Under Which Circumstances Should Obesity Be Considered a Public Health 
        Concern?
    The example in Table 1 has ramifications for specific individuals 
in specific circumstances and particularly focuses on minors, who are 
broadly considered not fully responsible for their own actions. The 
justifications and ramifications of broad health-targeted policies 
affecting ordinary adults are quite different.
    Before proceeding, we must distinguish between two distinct uses of 
the phrase ``public health'' as a prefix to terms such as ``problem,'' 
``concern,'' or ``issue.'' The phrase is often used merely to convey 
that the problem affects a large number of people. The term 
``population health'' is emerging to express this idea.[7] 
But in debates about policies that may impinge on individual rights and 
values, the phrase is used more specifically to denote health problems 
in which individuals' actions may not be sufficient to protect them 
from ill health and collective action may offer such protection. 
Examples of the latter definition include certain infectious diseases 
from which protection can be afforded by mass vaccination and toxins in 
public drinking water supplies, which can be minimized by a variety of 
government policies.
    Using the more specific definition, it is not clear that obesity 
qualifies as a public health concern in all 
circumstances.[8] When considering some putative 
contributors to obesity, such as adenovirus 36 or environmental 
endocrine disruptors,[9] the definition does seem to apply: 
individuals generally cannot fully detect and protect themselves from 
exposure to these factors by their own action, and collective action at 
a societal level mandated by government policies might do so. However, 
when considering some other putative contributors to obesity such as 
ingesting excess energy or being insufficiently active, there generally 
are not external unavoidable constraints, as opposed to influences, on 
individuals. Thus, collective action to protect individuals from 
undetectable or unavoidable contributing factors is not required in 
such cases.
    At this point, we should address a related argument. This is 
perhaps the most commonly used argument to justify policies about 
obesity: obesity is costly to society, largely through the healthcare 
system, and this justifies collectively infringing upon individual 
liberty to decrease obesity. We do not agree with this argument. 
Regardless of the cost of obesity, that cost itself does not 
necessarily justify society's imposing such policies. The fact that one 
party (society in this case) voluntarily takes on an obligation to 
cover some costly benefit to a second party (individual citizens in 
this case) does not necessarily give the first party the right to 
dictate the behaviors of the second party. There are several 
alternatives which include society's not volunteering to take on the 
obligation, society's taking on the obligation but distributing the 
costs equitably to its members (e.g., charging obese persons more for 
health coverage), or society's voluntarily accepting the obligation and 
then simply agreeing to be ``magnanimous'' and bear the additional 
expense of costly behaviors in the interests of preserving individual 
liberty.
    This is not to say that obesity is not a problem. Obesity is 
associated with many chronic diseases, decreased productivity, and 
psychosocial difficulties. But if a health policy targeting a putative 
cause of obesity does not address an issue in which individuals' 
actions are insufficient to protect themselves from obesity, then the 
policy may be unwarranted regardless of cost.
Good Intentions, Unintended Consequences
    Various policy advocates insist that obesity needs to be addressed 
by public policy, either because they reject the definition of public 
health provided above or because they believe action must be taken 
despite obesity's not specifically being a public health concern. 
Innumerable policy recommendations have been proposed or enacted in an 
effort to reduce obesity, from ``sin'' taxes [10] and 
``psychic'' taxes [11] to information campaigns 
[12] and alterations to the built 
environment.[13] In some cases, the scientific evidence 
demonstrates fairly clearly that the recommendation will not 
substantially reduce obesity, which means these policies not only raise 
ethical concerns but may have no beneficial outcome; other 
recommendations are simply equivocal--the potential exists for benefits 
and harms--and the balance between ethical consequences and health 
benefits is thus uncertain.[14]
    When the outcomes of a particular proposal are uncertain, 
especially for interventions grounded in ``common sense,'' one could 
ask, ``How could it hurt to try?'' Some ways various policies could 
hurt, despite good intentions, were previously 
highlighted.[15] Such negative consequences include direct 
negative effects and encroachment on individual freedom like the list 
from ten Have, et al., but also include direct costs of resources, 
damage to scientific and political credibility, and distraction from 
more promising efforts and policies. In fact, direct, unintended 
negative consequences of some policy proposals have been demonstrated 
(Table 2).

 Table 2. Unintended Consequences of Actions Intended To Affect Obesity
------------------------------------------------------------------------
                                                  Documented unintended
         Action              Good intention            consequence
------------------------------------------------------------------------
Tax sugar-sweetened      Decrease energy intake  Increased consumption
 beverages (SSBs).        to decrease weight.     of beer beyond the
                                                  decrease in sugar-
                                                  sweetened
                                                  beverages.[17]
Alert patients to their  Make the patient aware  Patients may feel
 heavy weight status.     of a problem as a       stigmatized, become
                          first step in           depressed and eat
                          addressing it.          more, and avoid future
                                                  appointments.[16]
Labeling calories on     Awareness of calories   Purchases of SSBs
 vending machine          will result in          increased in some
 beverages.               decreased               settings.[18]
                          consumption.
Label ``unhealthful''    Increase ``healthful''  Increased selection of
 foods with messages      behaviors and           an ``unhealthful''
 that encourage           decrease                snack.[19]
 consuming fruits and     ``unhealthful''
 vegetables.              behaviors.
Describe certain         Decrease caloric        Consumers consumed more
 restaurants and foods    consumption and shift   calories in side
 as more ``healthful''    consumption toward      dishes and beverages,
 and ``low-calorie.''     ``healthful'' foods.    and underestimated
                                                  total meal calories
                                                  when choosing
                                                  ``healthy''
                                                  restaurants or main
                                                  dishes.[20]
Labeling calories and    Awareness of calories   Men ate more
 removing value pricing   and eliminating value   calories.[21]
 on menu items.           pricing will decrease
                          energy consumption.
Discourage chocolate     Decrease caloric        Chocolate consumption
 consumption.             consumption.            increased for some
                                                  women in some
                                                  circumstances.[22]
Encourage children to    Children prompted to    Children ate as many
 consume fruits by        eat fruits will         calories when prompted
 incorporating them       increase consumption    by fruit games as when
 into games.              of ``healthful''        prompted by energy-
                          foods and decrease      dense-snack games, did
                          caloric consumption     not increase fruit
                          overall.                consumption, and ate
                                                  more overall than when
                                                  not prompted by
                                                  food.[23]
------------------------------------------------------------------------

    For instance, the ``common sense'' impetus behind informing 
patients that they are obese may be the old maxim, ``the first step in 
solving a problem is admitting you have one.'' Yet, there is evidence 
that clinically relevant words to describe a patient's weight (e.g., 
morbidly obese and obese) are considered stigmatizing, which patients 
state may make them avoid future appointments.[16]
    It is important to note that the good intentions and unintended 
consequences in the table represent hand-picked examples and these 
interventions may not be negative in all circumstances. For instance, 
there is some evidence that the effects of menu labeling on consumer 
choice can be inconsistent or even positive if delivered in specific 
ways, including whether or not educational information is included and 
whether the participants are male or female.[21, 24-25] 
Thus, the selected examples in Table 2 bring up yet another ethical 
concern: if a policy intervention benefits one subset of the population 
but harms another, what action should be taken? One could argue against 
implementing a policy so as to do no harm to one group, while another 
could argue that failing to act is tantamount to harming the group that 
stands to benefit.[26-27]
Minimizing Negative Ethical Consequences in Reversing Obesity
    Marieke ten Have and colleagues raise an important complementary 
point to ethical concerns over policy recommendations: ``The fact that 
objections are raised does not automatically imply that a programme 
should not be implemented''.[4] When considering an obesity-
targeted public health policy, we propose six recommendations:

  1.  Evaluate whether the proposed policy addresses an exposure that 
            can truly be considered a public health 
            concern.[8]

  2.  Be honest about the quality and quantity of evidence about the 
            policy.[14]

  3.  Generate sufficient, high-quality evidence before implementing 
            the policy and have plans in place to generate quality 
            evidence about the effectiveness of the policy once 
            instated.[28]

  4.  Do not assume there is negligible or no harm from the policy (see 
            Table 2).

  5.  Do not assume that achieving a health benefit overrides respect 
            for other values and ethical principles.[4, 29]

  6.  Given a choice between two or more plausible policies, choose the 
            policy that least compromises ethical 
            values.[29]

    These guidelines should help prevent us from paving the roads to 
health with good wishes but unintended consequences.

                               References
 
 
 
    1. Shapiro F.R., ed. The Yale Book of Quotations. New Haven, CT:
 Yale University Press; 2006: 319.
    2. Grynbaum M.M.. New York plans to ban sale of big sizes of sugary
 drinks.New York Times. May 30, 2012. http://www.nytimes.com/2012/05/31/
 nyregion/bloomberg-plans-a-ban-onlarge-sugared-
 drinks.html?pagewanted=all&_r=0. Accessed January 3, 2013.
    3. Levine S. Supporters of Mayor Bloomberg's anti-obesity initiative
 [news release]. New York: City of New York; September 13, 2012. http://
 www.nyc.gov/html/om/html/2012b/support_for_soda_limits.html. Accessed
 January 8, 2013.
    4. ten Have M., de Beaufort I.D., Teixeira P.J., Mackenbach J.P.,
 van der Heide A. Ethics and prevention of overweight and obesity: an
 inventory. Obes. Rev. 2011; 12(9): 669-679.
    5. Summar P. Anamarie 4 years later: weight gain, size of child, 7,
 remain unexplained. Albuquerque Journal. March 13, 2005. http://
 www.abqjournal.com/news/metro/320825metro03-13-05.htm. Accessed January
 4, 2013.
    6. Parents visit overweight child. ABC News. August 31, 2000. http://
 abcnews.go.com/US/story?id=95940&page=1. Accessed January 4, 2013.
    7. Kindig D., Stoddart G. What is population health? Am. J. Public
 Health. 2003; 93(3): 380-383.
    8. Anomaly J. Is obesity a public health problem? Public Health
 Ethics. 2012; 5(3): 216-221.
    9. McAllister E.J., Dhurandhar N.V., Keith S.W., et al. Ten putative
 contributors to the obesity epidemic. Crit. Rev. Food. Sci. Nutr. 2009;
 49(10): 868-913.
    10. Chaufan C., Hong G.H., Fox P. Taxing ``sin foods''--obesity
 prevention and public health policy. N. Engl. J. Med. 2009; 361(24):
 e113.
    11. Lucas, Jr. G. Paternalism and psychic taxes: the government's
 use of negative emotions to save us from ourselves. http://
 papers.ssrn.com/sol3/papers.cfm?abstract_id=2150402. Accessed March 20,
 2013.
    12. Puhl R., Peterson J.L., Luedicke J. Fighting obesity or obese
 persons? Public perceptions of obesity-related health messages. Int. J.
 Obes. (Lond). 2012. [Epub ahead of print]
    13. White House Task Force on Childhood Obesity. Solving the Problem
 of Obesity Within a Generation: White House Task Force on Childhood
 Obesity Report to the President. 2010: 78-82. http://www.letsmove.gov/
 sites/letsmove.gov/files/
 TaskForce_on_Childhood_Obesity_May2010_FullReport.pdf. Accessed March
 20, 2013.
    14. Casazza K., Fontaine K.R., Astrup A., et al. Myths,
 presumptions, and facts about obesity. N. Engl. J. Med. 2013; 368(5):
 446-454.
    15. Allison D.B. Evidence, discourse and values in obesity-oriented
 policy: menu labeling as a conversation starter. Int. J. Obes. (Lond).
 2011; 35(4): 464-471.
    16. Puhl R., Peterson J.L., Luedicke J. Motivating or stigmatizing?
 Public perceptions of weight-related language used by health providers.
 Int. J. Obes. (Lond). 2012. [Epub ahead of print]
    17. Wansink B., Just D.R., Cawley J., et al. From Coke to Coors: a
 field study of a sugar-sweetened beverage tax and its unintended
 consequences. http://papers.ssrn.com/sol3/
 papers.cfm?abstract_id=2079840. Accessed March 20, 2013.
    18. Jue J.J., Press M.J., McDonald D., et al. The impact of price
 discounts and calorie messaging on beverage consumption: A multi-site
 field study. Prev. Med. 2012; 55(6): 629-633.
    19. Werle C.O.C., Cuny C. The boomerang effect of mandatory sanitary
 messages to prevent obesity. Marketing Letters. 2012; 23(3): 883-891.
    20. Chandon P., Wansink B. The biasing health halos of fast-food
 restaurant health claims: lower calorie estimates and higher side-dish
 consumption intentions. J. Consumer Res. 2007; 34(3): 301-314.
    21. Harnack L.J., French S.A., Oakes J.M., Story M.T., Jeffery R.W.,
 Rydell S.A. Effects of calorie labeling and value size pricing on fast
 food meal choices: results from an experimental trial. Int. J. Behav.
 Nutr. Phys. Act. 2008; 5: 63.
    22. Durkin K., Hendry A., Stritzke W.G. Mixed selection. Effects of
 body images, dietary restraint, and persuasive messages on females'
 orientations towards chocolate. Appetite. 2013; 60(1): 95-102.
    23. Folkvord F., Anschutz D.J., Buijzen M., Valkenburg P.M. The
 effect of playing advergames that promote energy-dense snacks or fruit
 on actual food intake among children. Am. J. Clin. Nutr. 2012; 97(2):
 239-245.
    24. Girz L., Polivy J., Herman C.P., Lee H. The effects of calorie
 information on food selection and intake. Int. J. Obes. (Lond). 2012;
 36(10): 1340-1345.
    25. Roberto C.A., Larsen P.D., Agnew H., Baik J., Brownell K.D.
 Evaluating the impact of menu labeling on food choices and intake. Am.
 J. Public Health. 2010; 100(2): 312-318.
    26. Vartanian L.R., Smyth J.M. Primum non nocere: obesity stigma and
 public health. J. Bioeth. Inq. 2013; 10(1): 49-57.
    27. Gill T.P. Key issues in the prevention of obesity. Br. Med.
 Bull. 1997; 53(2): 359-388.
    28. Landefeld C.S., Shojania K.G., Auerbach A.D. Should we use large
 scale healthcare interventions without clear evidence that benefits
 outweigh costs and harms? No. BMJ. 2008; 336(7656): 1277.
    29. Have M.T., van der Heide A., Mackenbach J.P., de Beaufort I.D.
 An ethical framework for the prevention of overweight and obesity: a
 tool for thinking through a programme's ethical aspects. Eur. J. Public
 Health. 2012. [Epub ahead of print]
 


 
 
 
    Andrew W. Brown, Ph.D., is a postdoctoral trainee in the Office of
 Energetics and Nutrition Obesity Research Center at the University of
 Alabama at Birmingham. Trained in nutritional biochemistry and
 statistics, Dr. Brown's research focuses on establishing an evidence
 base for common assumptions about nutrition and health on such topics
 as organic agriculture, artificial sweeteners, and dietary supplements.
 His recent work relates to research reporting fidelity and its
 implications for science and policy.
    David B. Allison, PhD, is distinguished professor, Quetelet Endowed
 Professor of Public Health, associate dean for science, director of the
 Office of Energetics, and director of the NIH-funded Nutrition Obesity
 Research Center at the University of Alabama at Birmingham. He has
 authored more than 450 scientific publications, received many awards
 for his research and mentoring, is an elected fellow of many academic
 societies, and in 2012 was elected to the Institute of Medicine of the
 National Academies.
 
Disclosure
 
    Dr. Brown receives grant support from the Coca-Cola Foundation
 through his institution.
    Dr. Allison has served as an unpaid board member for the
 International Life Sciences Institute of North America. He has
 received: payment for board membership from Kraft Foods; consulting
 fees from Vivus, Ulmer and Berne, Paul, Weiss, Rifkind, Wharton,
 Garrison, Chandler Chicco, Arena Pharmaceuticals, Pfizer, National
 Cattlemen's Association, Mead Johnson Nutrition, Frontiers Foundation,
 Orexigen Therapeutics, and Jason Pharmaceuticals; lecture fees from
 Porter Novelli and the Almond Board of California; payment for
 manuscript preparation from Vivus; travel reimbursement from
 International Life Sciences Institute of North America; other support
 from the United Soybean Board and the Northarvest Bean Growers
 Association; grant support through his institution from Wrigley, Kraft
 Foods, Coca-Cola, Vivus, Jason Pharmaceuticals, Aetna Foundation, and
 McNeil Nutritionals; and other funding through his institution from the
 Coca-Cola Foundation, Coca-Cola, PepsiCo, Red Bull, World Sugar
 Research Organisation, Archer Daniels Midland, Mars, Eli Lilly and
 Company, and Merck. Dr. Allison has no financial interests in any of
 these companies.
 
Acknowledgments
 
    We would like to thank Michelle M. Bohan Brown, Ph.D. (University of
 Alabama at Birmingham), for her valuable input.
    The viewpoints expressed on this site are those of the authors and
 do not necessarily reflect the views and policies of the AMA.
    Copyright 2013 American Medical Association. All rights reserved.
 

                              attachment 6
Evidence, Discourse, and Values in Obesity-Oriented Policy: Menu-
        Labeling as a Conversation Starter
Commentary
D.B. Allison.*
---------------------------------------------------------------------------
    * Correspondence: Dr. D.B. Allison, Department of Biostatistics, 
Ryals Public Health Building, 1665 University Boulevard, University of 
Alabama at Birmingham, UAB Station, Birmingham, AL 35294-0022, USA.
    E-mail: [email protected].
---------------------------------------------------------------------------
Departments of Biostatistics and Nutrition Sciences, Nutrition Obesity 
Research Center, University of Alabama at Birmingham, Birmingham, AL, 
USA.
International Journal of Obesity (2011) 35, 464-471; doi:10.1038/
ijo.2011.28; published online 15 March 2011.

    The new study by Dr. Elbel and colleagues provides an opportunity 
to reflect on where we are with respect to menu labeling as a tool in 
our antiobesity arsenal and more generally to consider some issues 
surrounding policy-level proposals for stemming the obesity epidemic. 
By `menu labeling', I refer to listing the calories of menu items on 
the menu. In this commentary, I address two aspects: evidence on menu 
labeling per se; and, at least as important, several scientific, 
social/political and epistemological issues that generally apply when 
considering obesity-related policies.
    Elbel, et al.,\1\ deserve praise for this interesting paper. Dr 
Elbel previously offered that menu labeling is a good idea and should 
be implemented, stating `I see particular value in it when the options 
are this versus nothing at all . . . Given that the problem is so 
intense, I think we have to try things.' \2\ Yet, despite his previous 
favorable view, he does not mince words upon completing his latest 
study: `Our evaluation of New York City's labeling law suggests that . 
. . this public policy intervention had no significant effect on 
purchasing behavior within our study period for a low-income, racially 
and ethnically diverse population of parents and adolescents.' The 
authors' qualifying clauses are appropriate as their study cannot rule 
out any effect, in any period, for any population. Yet, it certainly is 
one more bit of evidence tipping the scales toward the conclusion that 
menu labeling does not have substantial or consistent beneficial 
effects on energy intake.
Strengths and Limitations of the Study by Elbel, et al.
    The study had multiple strengths, including using Newark as a 
comparator city, acquisition of actual receipts, the real-world setting 
and a population of interest. There are also key limitations. First, it 
is an observational (non-experimental) study that, similar to all 
observational studies, is subjected to potential confounding and cannot 
alone justify conclusions about causation. Second, because no body mass 
index measurements were taken, we cannot discern whether a thinner or 
more obese clientele was buying food at these restaurants, which might 
affect our interpretation of the value of menu labeling or whether some 
body mass index categories increased and others decreased their 
calories purchased. Third, the statistical analyses did not account for 
potential clustering (potential non-independence) of observations 
within restaurants and families as it should have, although it seems 
unlikely that this would make the nonsignificant results significant. 
Finally, and importantly, the study only looks at calories purchased at 
a single eating occasion. It does not tell us about calories actually 
consumed at that occasion (except perhaps the upper limit), about 
whether the knowledge of the calories one purchased on that occasion or 
simply being `attuned to calories' might have affected energy intake 
throughout the day, nor about how menu labeling affected body weight or 
body fat over an extended time period, the ultimate goal of menu 
labeling. Although the fact that calories purchased did not differ 
before and after menu labeling makes a beneficial effect less 
plausible, one cannot rule out that, for example, patrons who realized 
how many calories were in their purchases chose to eat less of the 
total food they purchased or chose to indulge at the restaurant, but 
eat less later.
    If we are to understand the value of any macro-environmental 
manipulation intended to reduce obesity levels, we must eventually 
measure body weight, fat or obesity levels because we know that people 
often compensate for perturbations in energy intake or expenditure 
(c.f. 3). For example, Anderson and Matsa4 showed that `On average, 
when a given individual eats out, he consumes 238 more calories per 
meal than when he eats at home. . . . (However,) eating out increases 
intake over the entire day by only 35 calories . . . although 
individuals tend to eat more at restaurants, they compensate to a 
substantial degree by eating less throughout the rest of the day. Meal-
level estimates therefore overestimate the net effect of restaurants on 
total caloric intake.'
Empirical Issues
What does the empirical literature show on the effects of menu 
        labeling?
    Although it is impossible to comprehensively summarize this 
literature herein (for an extensive tabulation through mid 2009, see 
ref. 5), the study by Elbel, et al., accords with most literature in 
showing no clear and consistent benefit. Furthermore, to my knowledge, 
no study has assessed effects on weight, total energy balance or total 
energy intake for periods beyond 24 h. Thus, no studies are truly 
probative on the actual question of interest: whether menu labeling 
reduces obesity levels.
    Of the extant studies, many are observational 6-7 and 
those that are experimental are typically, if not exclusively, in 
laboratory analog settings (for example, see ref. 8). Some studies show 
that menu labeling is associated with or affects reduced calories 
purchased, although among men the association appears less than among 
women, or is absent entirely.9-10 Other studies show no 
association or effect,\7\ and some even show statistically significant 
increases (adverse effects) in calories purchased with menu labeling 
among young men.8, 11 One study suggests menu labeling may 
decrease calories that parents purchase for children, but not calories 
that they purchase for themselves.\12\ Another study suggests that, 
when ingested calories (measured by self-report) after the eating 
occasion on the same day in which menu labeling is used are considered, 
there is a reduction in total energy intake if the menu labeling is 
accompanied by a statement that `The recommended daily caloric intake 
for an average adult is 2,000 calories.' \13\ As treatment-induced 
biases in self-report measures are well documented (for example, see 
ref. 14), it is unclear whether this statement affected actual intake 
or merely reporting. Finally, yet another study shows that calorie 
labeling may either increase or decrease energy consumed, depending on 
the food item labeled.\15\ Thus, although under some circumstances 
there are hints of short-term (that is, within one eating occasion or 
day) benefits on energy purchased or consumed, overall the results do 
not offer compelling evidence for effectiveness. When we contrast these 
recent results with earlier literature offering statements such as `. . 
. we estimated that menu labeling would avert 40.6% of the 6.75 million 
pound average annual weight gain in the county population aged 5 years 
and older',\16\ it seems that some initial expectations were overly 
optimistic.
Important Biases To Consider
    In reviewing this literature, it is also important to note biases 
that may be present. One type is what Cope and Allison \17\ called 
`white hat bias,' the tendency to distort research information in the 
service of seemingly righteous ends. Cope and Allison \18\ cited an 
example of the Food and Drug Administration in its proposed ruling on 
menu labeling, citing a study as supporting a favorable conclusion that 
its data did not actually support. As another example, consider an 
article that reported in the abstract `Results were similar in most 
analyses conducted stratified by factors such as age, race and 
education level'.\8\ Although not explicitly inaccurate, this seems to 
be a misleading statement given that in the article's body the authors 
report that `Average energy intake was higher among males in the . . . 
(menu labeling) conditions compared with those who selected their meal 
from the control menu' with a P-value of 0.01 and no such effect was 
observed among females. In a similar vein, a recent New York Times \19\ 
article based on private e-mails from within the NY City Health 
Department shows that in their zeal to make consumers `fear' soda as 
adiposity promoting, they were willing to knowingly `oversimplify' 
messages and knowingly ignore some science.
    Another form of bias is publication bias, whereby the probability 
that a paper is published or perhaps where it is published, and the 
resulting attention it receives, depends on its outcome, which is often 
a bias toward studies showing positive effects.\20\ Notably, opinion 
pieces suggesting that policies, such as menu labeling, front-of-pack 
labeling and taxation of sugar-sweetened beverages, will be beneficial 
have appeared in the most prominent journals such as JAMA 
21-22 or New England Journal of Medicine.23-24 
Yet, subsequent empirical reports stating that menu labeling, programs 
designed to reduce consumption of sugar-sweetened beverages and front-
of-pack labeling do not seem to be very effective have been published 
in respectable but far less prominent journals and may receive less 
attention. Moreover, several dissertations and theses that have found 
no beneficial effects do not appear to be published as yet (see Table 
below). If these studies are not published and considered, the 
published literature may offer a misleadingly favorable view.

------------------------------------------------------------------------
   Reference               Design                      Results
------------------------------------------------------------------------
          \15\   Randomized experiment      ` . . . provision of calorie
                                             information does not alter
                                             food choice but does
                                             influence the amount people
                                             eat. Although the salad and
                                             pasta contained the same
                                             number of calories, calorie
                                             information decreased
                                             consumption of pasta, but
                                             increased consumption of
                                             salad.'
          \25\   Randomized experiment      `There are no differences in
                                             total calorie . . . chosen
                                             across the three groups:
                                             price only, nutrition info
                                             only, and price + info
                                             groups.'
          \26\   Randomized experiment      `No significant differences
                                             were found in the foods
                                             ordered among the various
                                             menu conditions.'.
------------------------------------------------------------------------

Reporting quality?
    The published research record should have the greatest precision 
possible and be reported in a way that helps readers understand the 
nature of the research, including its limitations, especially when the 
research has the potential to affect clinical care, public health 
practices or legislative policies. In part because of this, company-
based clinical trials are held to rigorous scrutiny; hence, perhaps 
consequently, the reporting quality of industry-sponsored obesity 
trials seems to be at least as good as, and perhaps better than, non-
industry-sponsored trials.\27\ These same rigorous standards of 
reporting quality should be applied to all articles in peer-reviewed 
journals, especially those that may influence policy. In this light, 
consider that, although the paper by Elbel, et al.,\1\ is subtitled `A 
Natural Experiment', the design is not an experiment as defined in the 
scientific literature (for example, see ref. 28, p. 1) but a type of 
observational study sometimes referred to as a quasi-experiment.\29\ 
Such quasi-experiments do not permit the strong inferences to causation 
that true experiments do. Hence, when the conclusion by Elbel, et 
al.,\1\ states `This study examines the effects (emphasis added) of 
menu labeling . . .', causal language is used without justification. 
Although this is a common slip,\30\ it may nevertheless confuse 
readers, including mass media reporters or policy makers into thinking 
an effect (or lack thereof) has been shown when, in fact, only a lack 
of an association has been shown. Further, just as association does not 
necessarily imply causation, lack of association does not necessarily 
imply lack of causation. Similarly, Elbel, et al.,\1\ discuss `calories 
consumed', but the actual outcome of the study was calories purchased. 
This is an important distinction because the menu labeling could 
conceivably cause consumers to consume less of a perceived high-calorie 
item even if it is purchased. I state these points about precision, 
when I have made similar errors of imprecise language in my own papers, 
to point out that we should hold papers in the public health policy 
arena to every bit as rigorous a standard of reporting as we do big 
pharmaceutical randomized controlled trials (RCTs). Allowing ourselves 
to slip into imprecise language potentially creates misunderstandings 
among readers that can lead to erroneous public discourse about 
proposed policies.
Social and Philosophical Issues
Does it matter if it matters?
    At a presentation on menu labeling at the 2009 Obesity Society 
meeting, Professor K.D. Brownell asked `Does it matter if it matters?' 
That is, does it matter whether data show that menu labeling is 
beneficial in deciding whether to endorse it? He used the instructive 
analogy of tags that describe a garment's composition. We do not demand 
randomized experiments showing that such tags produce a benefit; we 
simply take as given that people have a `right' to know the composition 
of the fabrics they purchase. Can we extend this argument by analogy to 
menu labeling? Perhaps, but trying invites the question, who is `we' in 
the preceding sentence? Is it society at large? Or is it we members of 
the scientific community acting in our role as scientists per se rather 
than as member of the general public who just happen to be scientists 
by profession? This is an important distinction, because if we are not 
predicating our endorsement of a policy based on empirical evidence or 
even expert scientific opinion on the policy's effects, then this does 
not seem to be a scientific issue at all but rather one of politics, 
morality or taste, and it is not obvious that scientists qua scientists 
have anything special to add here. And if not, is this even a relevant 
topic of discussion for our scientific conferences and journals? In 
fact, because there are potential costs and harms of all interventions, 
balancing risks and benefits is important. By analogy, consider what 
Food and Drug Administration wrote in its final ruling banning ephedra 
as a weight loss supplement and in determining whether there was a 
`significant or unreasonable risk': `There is no requirement that there 
be evidence proving . . . harm to specific individuals, only that 
scientific evidence supports the existence of risk. . . . `Unreasonable 
risk,' thus, represents a relative weighing of . . . known and 
reasonably likely risks against its known and reasonably likely 
benefits.' \31\ In this light, it does matter if it matters.
Choice-Limiting Versus Choice-Promoting Strategies
    Obesity-related legislation is mushrooming. Between 2003 and 2005, 
in the United States, at least 717 bills and 134 legislative 
resolutions were proposed, of which 17% of bills and 53% of resolutions 
were adopted.\32\ Proposals for policy-based approaches almost 
invariably meet resistance when the policies offend the moral or 
political sensibilities of some persons. This especially occurs when 
the proposed policy is seen as treading on the rights or autonomy of 
individuals in the interests of public health paternalism. Therefore, 
if we wish to minimize such resistance, we should aim to advance 
proposals that are freedom and choice promoting, rather than 
restricting. Consequently, many advocates of policy level approaches 
recognize the merit of `opt-out' versus `opt-in' approaches \33\ that 
can be effective in promoting desired behavioral changes without 
compromising individual liberty. Unfortunately, not all public health 
advocates are sensitive to this issue. For example, proposals for 
taxing certain foods, such as sugar-sweetened beverages, limit 
individual freedom to negotiate a price for a desired product with the 
purveyor. By way of contrast, consider the experiments by experiments 
by Sharpe, et al.,\34\ showing that consumers' extremity avoidance 
behavior (for example, not wanting to choose the smallest or largest 
item in a series) led to a potentially useful effect. Specifically, 
merely offering a smaller size drink in addition to (not instead of) 
the existing sizes led to an overall reduction in the amount of drink 
purchased. On the basis of these results, one could imagine a policy in 
which restaurants that offer multiple sizes of drinks would be required 
to offer an additional drink smaller than their current smallest size 
and, if effective, the principle might be extended to other foods that 
are sold in multiple distinct serving sizes. Such a policy would limit 
the freedom of corporations, but not of individuals, and hence 
presumably meet far less resistance from libertarians.
    How might libertarian concerns relate to menu labeling? One benefit 
of menu labeling is that it provides more information for consumers to 
make more informed choices. As someone with libertarian leanings, I 
generally favor more and accurate information being made available to 
citizens \35\ and, as an individual consumer, I enjoy learning about 
the foods I may choose to eat; therefore, in many settings such as 
fast-food restaurants, I would enjoy menus labeled with nutritional 
information. However, that is just a statement of my personal 
preferences and tastes, not a scientific statement, and other 
individuals may have other preferences and tastes. For example, in 
2008, `After students and parents raised concerns about displayed 
calorie counts leading to or worsening eating disorders, Harvard 
University Dining Services removed the index cards detailing 
nutritional information from dining halls'.\36\ Regardless of the 
empirical basis for the Harvard parents' concerns, their feelings and 
preferences are real, and if we seek policies that allow choice, we 
will respect such feelings.
    How might advocates of menu labeling minimize the resistance they 
receive if they try to move menu labeling into all restaurants, not 
just into fast-food chains? In this light, consider that this is not 
the first time in history that restaurant menu content has been subject 
to scrutiny and change. Years ago, it was common for restaurants to 
have `blind menus' without prices listed so patrons could take out 
their guests without the mood of the dinner being affected by the guest 
seeing the prices.\37\ Although such practice is now uncommon, many 
higher-end restaurants still provide such menus to patrons upon 
request. In this way, consumer choice is enhanced. The price 
information is there for all who want it and hidden for those who do 
not (in an `opt-out' manner). There is an analogy with respect to 
calorie information. In some circumstances, for example, when someone 
takes their special someone out for that romantic dinner to propose 
marriage or celebrate an anniversary, even the most health conscious 
among us may not wish to consider the calories in our food. This 
potential preference could be respected and choice enhanced if 
consumers had the option of viewing a menu with or without the calorie 
contents (in a `opt-out' manner). In a full-service restaurant with 
printed menus, this can be easily accomplished, and if menu labeling 
advocates propose such a choice-promoting approach, they are likely to 
meet applause instead of resistance from libertarians.
Can we lead by example?
    Mohandas Gandhi said, `We must be the change we wish to see in the 
world. Change can only come from the roots upwards, never from the 
treetop down'.\38\ Our more modern guru, Michael Jackson, sang `I'm 
Starting With The Man In The Mirror. . . . If You Wanna Make The World 
A Better Place, Take A Look At Yourself And Then Make That Change!' In 
this light, an irony to the menu-labeling advocacy has occurred. 
According to Friedman,\39\ `Fast food is eaten disproportionately by 
low-income people, who are more likely to be overweight.' Further, 
meals eaten in full-service restaurants tend to be high in calories and 
fat as well,\40\ maybe even higher than those in fast-food restaurants, 
especially in the case of children's and adolescents' 
meals.41-42 Further, higher income people, who are more 
likely to patronize such restaurants, are not exempt from obesity. Yet, 
our early public health salvo at restaurants has not been aimed at 
those establishments likely frequented by the well-established senior 
academicians and high-ranking public health officials who propose the 
policies, but at those more frequented by people of lesser means. Other 
proposals that seem targeted more at persons of lesser means and that 
may seem restrictive or punitive have been made, such as restricting 
the provision of toys in children's fast-food meals, disallowing 
purchase of sugar-sweetened beverages with Supplemental Nutrition 
Assistance Program funds (food stamps), and restricting the location of 
fast-food outlets.
    I do not doubt that the intentions of most policy advocates are 
sincerely beneficent, nor that the greater uniformity of chain 
restaurants offers a rationale for starting there within the category 
of restaurants. Nevertheless, incarnations of public health paternalism 
aimed more at changing unhealthy behaviors among members of less-
powerful social classes than the equally unhealthy behaviors of the 
social classes proposing the policies cannot be seen as Gandhian and 
has likely provoked some of the pushback that has occurred. This 
sentiment is well illustrated by the feminist writer, Anna Kirkland.

          `. . . this environmental approach to obesity has been sold 
        as a progressive, structurally focused alternative to 
        stigmatization, but it actually embeds and reproduces a 
        persistent tension in feminist approaches to social problems: 
        well-meant efforts to improve poor women's living conditions at 
        a collective level often end up as intrusive, moralizing, and 
        punitive direction of their lives . . . good choice dominated 
        by elite norms of consumption and movement'.\43\

    As our field moves forward with the consideration of other public 
health policies that may have paternalistic aspects, perhaps we should 
start with the man in the mirror. Given the plausible weight-reducing 
effects of less heating and air conditioning and more sleep,\44\ 
perhaps advocates of paternalistic public health policies should first 
demand that the use of heating and air conditioning be reduced in the 
buildings in which they and we work (which would also have an 
environmental and economic benefit) and take a pledge not to work on 
grant proposals, manuscripts or e-mail correspondence after 2200 hours. 
That would be leadership that walks the walk.
Majority rules?
    An argument sometimes made in support of a proposed policy approach 
to obesity is that the general population desires the policy. Regarding 
menu labeling, a Robert Wood Johnson Foundation briefing states that 
survey and focus group research indicates that `males and females of 
diverse educational backgrounds reacted favorably to the idea of 
labeling menu items with just calorie information or identifying 
healthier options with a uniform, commonly defined symbol to help them 
make better choices'.\5\ Of course, public opinion should count. In the 
extreme case of a unanimous population opinion, the decision is easy.
    However, in cases in which there is a majority view favoring a new 
policy, but not unanimity, should majority rule? There are reasons to 
question `majority rules' as a justification for a new policy, and 
again we should be open in acknowledging that subjective values in 
addition to scientific evidence come into play. First, one should view 
opinion poll results about proposed policies with healthy scientific 
skepticism. Research on survey methodology has repeatedly shown that 
seemingly minor variations in question wording can have major 
influences on responses.\45\ For example, very different responses are 
obtained when people are asked whether the government should `forbid' 
something as opposed to whether the government should `allow' 
something, even though one question is just the complement of the 
other. Thus, we should perhaps only be persuaded by results of surveys 
purportedly showing popular support when such results are replicated 
with multiple differently worded questionnaires prepared by different 
parties.
    Second, sometimes the public may desire a policy based on an 
erroneous view of its likely effects. Those advocates who accept 
paternalistic public health approaches could argue that one should act 
in accordance with the public's interests, not necessarily on the basis 
of their expressed views.
    Finally, and most importantly from a libertarian view in which 
individual freedom is paramount, the desire of the majority is 
insufficient justification to tread upon the rights of the individual. 
Consider, for example, our response to a proposal that we have required 
prayer of a particular religious doctrine because the majority of the 
population thinks it is a desirable thing. The United States and many 
other democratic countries have already affirmed that, regardless of 
popular view, such a proposal is unacceptable. Clearly, most proposed 
obesity-related policies, including mandatory menu labeling, are not so 
extreme, and yet we should remember that multiple children in multiple 
countries (including the United States) have been removed from their 
parents' and homes by governmental actions on the basis of protecting 
them from their obesity-promoting environment,46-47 and that 
in 2008 three Mississippi legislators proposed `An Act To Prohibit 
Certain Food Establishments From Serving Food To Any Person Who Is 
Obese, Based On Criteria Prescribed By The State Department Of Health' 
(http://billstatus.ls.state.ms.us/documents/2008/pdf/HB/0200-0299/
HB0282IN.pdf). Not surprisingly, the legislation was never enacted. 
Thus, we should be skeptical of majority public opinion as a 
justification for restrictive policies.
Epistemological Issues
What constitutes an adequate evidence base?
    Consider that, after analyzing 38 policy documents from five 
European countries, authors found that `Only 22% of the obesity 
statements were evidence based'.\48\ We seem to have a dearth of 
evidence in the obesity policy domain. There is little (although not 
zero) debate that randomized experiments offer the highest quality 
evidence we can obtain about the effects of interventions, including 
policies. There is also little debate that results obtained from well-
done randomized experiments, especially on long-term outcomes on 
variables such as body weight or fat, will not always be available when 
we wish to make a statement, conclusion or decision about a proposed 
policy. In such situations, what should the standard of evidence be and 
who gets to decide that standard? At present, there is no obvious 
consensus. Importantly, answering the question of what constitutes 
adequate evidence depends on the context in which the question is 
called and will not be the academic community's alone (or in some cases 
at all) to decide. For example, in deciding whether a particular piece 
of litigation is justifiable, the level of scientific evidence required 
will be determined by applicable law as interpreted by the judiciary, 
not by academics.
    Second, in considering what constitutes adequate evidence, it is 
essential to distinguish between conclusion making and decision making. 
Scientists and public health advocates sometimes clash because they 
conflate this distinction. The advocate, who may be someone who is also 
sometimes a scientist, maligns the scientist qua scientist as trying to 
hold back progress and upholding an unreasonable standard, whereas the 
scientist maligns the advocate as playing `fast and loose with' or even 
ignoring scientific evidence. The problem is rarely that the two 
parties disagree on what evidence exists or what it shows, but rather 
they are answering two different types of questions and fail to realize 
or acknowledge this. The scientist is concerned with questions about 
the truth of propositions and addresses questions such as `By generally 
accepted scientific standards, can we reasonably conclude today to a 
reasonable degree of certainty that A causes B?' In contrast, the well-
meaning public health advocate is concerned with questions about what 
we should do, such as `Given what we know today, however limited, is it 
prudent to implement A in the hopes that B will happen in response?' If 
we recognize this, there is no contradiction between the scientist 
saying that the evidence for the benefit of a proposed policy is weak, 
limited, inconclusive, or even non-existent and the advocate saying 
that, despite the fact that there is insufficient evidence to conclude 
that the policy will be effective, we should give it a try to determine 
whether it might plausibly work and whether the likely benefits 
outweigh the likely costs. Recognizing this, the honest advocate need 
not and should not try to inflate the evidence in support of a policy 
they wish to advance, as seems to be done now,18-19 but can 
honestly acknowledge the degree of uncertainty, respect scientists for 
contributing discussions of evidence to promote an informed decision-
making process, and then advocate for prudential decision making.
Are randomized studies needed and possible?
    Some advocates of policy approaches are dismissive of the role of 
randomized trials. In arguing this position, several valid points are 
commonly noted. These are listed in the first column of Table below. 
Unfortunately, gaining acceptance of these points is often followed by 
a rhetorical sleight of hand, whereby they are replaced with the far 
stronger and fundamentally different points listed in the second column 
of the table below. Writings that cogently show the fallacies of these 
points are listed in the third column.

------------------------------------------------------------------------
                               Invalid points often
 Valid points about which    conflated with the valid       References
 there is  little if any       ones by advocates of       disputing the
          debate                 proposed  actions        invalid point
------------------------------------------------------------------------
It is difficult to         It is impossible and perhaps             \49\
 conduct randomized         irrelevant to conduct
 experiments to test the    randomized experiments to
 effects of public          test the effects of public
 policies.                  policies.
It is sometimes necessary  Once we decide to move                   \50\
 to move forward and take   forward, there is no need
 actions even in the        to do so in a manner in
 absence of the highest     which the highest quality
 quality evidence that is   evidence that is
 practically obtainable.    practically obtainable is
                            indeed obtained.
In some situations (e.g.,  In general, it is                       51	52
 when considering smoking   appropriate to draw strong
 as a cause of lung         conclusions about causation
 cancer), the scientific    in the absence of
 community has judged       experimental evidence.
 that it is appropriate
 to draw strong
 conclusions about
 causation in the absence
 of experimental
 evidence.
------------------------------------------------------------------------

    In conversation, a colleague who is a strong advocate of public 
policy interventions such as menu labeling and taxation of selected 
foods said, `You know, David, we are never going to know for sure 
whether these policies work before we implement them.' I replied, `You 
may be right, but the way we are going about it, we will never know 
afterward either.' It is unfortunate that, to date, all the evidence we 
have on menu labeling is either from short-term laboratory analog 
experiments or from non-experimental observational studies. Although 
practical complexities undoubtedly exist, it is certainly possible that 
as the Federal Government proceeds with national menu labeling \53\ 
they could randomly introduce it in \1/2\ of the states or counties in 
the United States and not in the other \1/2\ for a year in a valid 
cluster-randomized trial. At year's end, they might plausibly have 
unequivocal evidence on the effects of menu labeling on food purchases. 
Such data could offer guidance about whether to then implement the 
program in the remaining locations or discontinue the requirement. 
Similarly, many major national fast-food restaurant chains, were they 
inclined to conduct such a study, would easily have the financial 
resources and computer recording infrastructure of purchases to conduct 
such a trial by randomly assigning labeled menus to some of restaurants 
and unlabeled menus to others and then comparing the sales figures. If 
such studies were conducted at the state or county level, one could 
even solicit participation from and enroll specific subjects who are 
known to be high fast-food consumers at baseline and go beyond merely 
examining the effects on purchases at the cluster level; instead, one 
could study the actual end point of interest, body weight or fat in 
individual persons. Remarkably, for all the passion that public policy 
advocates bring to the table to push policies forward, they have not 
used that passion to demand that such studies be carried out. If they 
did so, perhaps they would help us learn how effective the policies 
they advocate are.
Could it hurt?
    An argument sometimes made by advocates of policies that seem 
intuitively sound to them but are not supported by strong evidence is 
that, even if ineffective, such policies will be harmless. This is 
fallacious reasoning. There are at least five types of harm, or more 
generically cost, that may accrue. The first is direct negative effects 
of the policies on collateral outcomes (concerns about economic impacts 
and stigmatization are sometimes raised) or on the outcomes that are 
themselves the targets of policy, such as the increase in calories 
purchased by males seen in some menu-labeling studies.11, 35 
The second is encroachment on individual freedom that occurs with some 
policies as discussed earlier. The third is that if the scientific 
community advances a policy as very likely to be beneficial, which is 
then found not to be beneficial, our credibility may be damaged and, 
like the boy who cried wolf, our voices will carry less weight when we 
genuinely have important messages to convey. The fourth cost is 
distraction. When we focus our efforts on advocating and implementing 
methods that turn out to be ineffective, we are not spending those 
efforts on other approaches that might be better. Finally, there are 
direct resource costs. Every dollar our society spends implementing one 
policy is $1 less that we have available to support education, the 
arts, or any number of other things our citizens may find as equally 
deserving causes. This is not to say that these harms or costs will 
come to fruition in implementing any one policy, but they are 
plausible, should enter into society's decision analysis, and justify 
asking about evidence of benefit when considering proposed policy 
approaches to obesity.
Conclusion
    The timely study by Elbel, et al.,\1\ adds to the growing body of 
evidence suggesting, but not demonstrating, that menu labeling has no 
important effect on reducing calories purchased at a single dining 
occasion. Moreover, it highlights the frustrating truth that, as such 
policies are implemented, they are not implemented in a manner that 
allows the most rigorous assessments of their effects to be conducted. 
Like all other studies to date, the study by Elbel, et al.,\1\ does not 
offer strong evidence about causation (or lack thereof), information 
about long-term effects, or effects on the variable that menu labeling 
is intended to affect, namely, obesity levels. As we move forward to 
consider this and other policy-level proposals for addressing obesity, 
as scientists we should hold high standards of discourse and of 
evidence and we should maintain a sense of humility about the accuracy 
of our predictions about the effects of our proposed policies. Society 
will sometimes be justified in moving forward even in the absence of 
strong evidence for the benefits of a proposed policy; yet, as 
scientists we should offer our most unbiased assessment of the current 
evidential base and ask that, as any new policies are implemented, 
rigorous evaluations of their effects should be conducted.

 
 
 
Conflict of Interest
 
    Dr. Allison has received grants, honoraria, donations and consulting
 fees from numerous food, beverage, pharmaceutical companies and other
 commercial, government and nonprofit entities with interests in obesity
 and nutrition; receives royalties from obesity-related books; and in
 the past has received funds from litigators representing the restaurant
 industry in menu-labeling litigation.
 
Acknowledgements
 
    I am grateful to Drs. Kevin Fontaine, Alexis Wood and Kyle Grimes
 for their helpful comments.
 
Disclaimer
 
    The opinions expressed are the author's and not necessarily those of
 any organization with which he is affiliated.
 


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                              attachment 7
The Development of Scientific Evidence for Health Policies for Obesity: 
        Why and How
Molly B. Richardson,[1-2] Michelle S. 
Williams,[3] Kevin R. Fontaine,[2]-[3] David B. 
Allison.[2], *
---------------------------------------------------------------------------
    \[1]\ Department of Population Health Sciences, Virginia 
Polytechnic Institute and State University.
    \[2]\ Nutrition Obesity Research Center, University of Alabama at 
Birmingham (UAB).
    \[3]\ School of Nursing, Auburn University.
    * Corresponding Author: School of Public Health, University of 
Alabama at Birmingham, Ryals Building, Room 140J, 1665 University 
Boulevard, Birmingham, Alabama 35294, Phone: (205) 975-9167, 
[email protected].
---------------------------------------------------------------------------
Running title: Scientific process to develop obesity policy

    Acknowledgements: Supported in part by the NIH (T32HL105349) and 
the Nutrition Obesity Research Center (P30DK0563360). The opinions 
expressed are those of the authors and do not necessarily represent 
those of the NIH or any other organization. We gratefully acknowledge 
Gregory Pavela, Alexandra S. Allison, Ted Kyle, Jennifer Holmes, Olivia 
Affuso, Paula Chandler-Laney, and Daniel L. Smith, Jr. for input on 
this manuscript.
    Conflict of Interest: DBA has received financial support from 
numerous nonprofit and for profit organizations including government, 
litigators, food and beverage, pharmaceutical, and publishing 
companies.
Abstract
    Potential obesity-related policy approaches have recently been 
receiving more attention. While some have been implemented and others 
only proposed, few have been formally evaluated. We discuss the 
relevance, and in some cases irrelevance, of some of the types of 
evidence that are often brought to bear in considering obesity-related 
policy decisions. We discuss major methods used to generate such 
evidence, emphasizing study design and the varying quality of the 
evidence obtained. Third, we consider what the standards of evidence 
should be in various contexts, who ought to set those standards, as 
well as the inherent subjectivity involved in making policy decisions. 
Finally, we suggest greater transparency from both academics and 
policymakers in the acknowledgment of subjectivities so they can 
distinguish and communicate the roles played by empirical evidence and 
subjective values in the formulation of policy.
Introduction
    Proposals to use policy measures such as taxing persons with 
obesity as ways to raise revenue and discourage poor health behaviors, 
including high levels of consumption, existed at least as early as 
1904.\1\ However, it was largely in the mid-1990s that the academic and 
professional dialogue around obesity shifted from one dominated by 
basic science and clinical research to involve a third branch, namely, 
public health approaches. Inspired in part by the successful efforts to 
curtail cigarette smoking, potential obesity-related policy approaches 
began receiving more attention. A selection of such policies include, 
but are not limited to, providing information (e.g., labeling 
restaurant menus with nutritional facts), marketing ideas to inspire 
behavior change (e.g., placing public health posters in subway systems 
to discourage or encourage certain food or activity behaviors), 
mandating the measurement and reporting of the body mass index (BMI) of 
schoolchildren to parents, enacting worksite economic contingencies, 
changing food offerings for schoolchildren, zoning of allowable 
restaurants, banning the sale of certain portion sizes, taxing or 
subsidizing certain foods, and providing economic incentives and 
disincentives through insurance charges. Some of these have been 
implemented and some have only been proposed. Few have been rigorously 
evaluated and fewer still have unequivocal evidence demonstrating 
efficacy in stabilizing or reducing body weight.
    Because the implementation of such policies typically involves at 
least some of the following: money, limitations on the freedom of 
businesses to engage in certain types of commerce, limitations on 
personal freedom, and opportunity cost with regard to time and 
attention; it is not surprising that obesity-related policy proposals 
often provoke heated debate. Moreover, the debate frequently focuses on 
moral issues, sometimes involving the balance between autonomy and 
beneficence or individual fairness and societal benefits. Because these 
issues revolve around morals and values, they are difficult to 
reconcile. As such, they are repeatedly deferred while the dialogue 
jumps to questions of judging the quality of evidence. Yet even here, 
disagreements abound as to the strength of evidence and whether it 
supports a particular position on a proposed policy. Equally important 
and sometimes debated, but often simply glossed over, are questions 
such as, (1) What type of evidence is needed and appropriate for a 
particular situation? (2) How can such evidence be generated? and (3) 
Is evidence even needed at all to justify the implementation or 
rejection of a particular proposed policy?
    In this article, we address three macro-level questions. First, 
concerning evidence, we raise questions about the relevance of some 
types of evidence that are often brought to bear in policy dialogues. 
Second, we discuss the major methods used to generate such evidence, 
with particular focus on the fact that there are a range of study 
designs (i.e., ordinary association tests to pure randomized controlled 
trials [RCTs]) that yield evidence of varying quality and varying 
ability to support causality. Third, we consider what the standards of 
evidence should be in various contexts, as well as who ought to set 
those standards, and emphasize the inherent subjectivities involved in 
making policy decisions. We conclude by noting that it would be 
beneficial if both academics and policymakers were transparent in 
recognizing and conveying those subjectivities while taking care to 
both understand and distinguish the roles of empirical evidence and 
subjective values.
What Do We Want Evidence About?
Evidence Regarding Plausibility
    When considering a potential policy, the first evidence-oriented 
question we might ask is, ``Is there evidence that the policy will 
plausibly be effective?'' That is, is there reason to speculate that 
the policy will work? Of course, beyond simply saying we cannot prove 
the contrary, the plausibility of a proposition is subjective, but 
one's reasons for declaring something plausible or implausible can be 
specified. At the most superficial level, many obesity policies can be 
deemed plausible on the basis of the simple concept of energy imbalance 
as a cause of obesity. Any policy directed at either increasing energy 
expenditure or decreasing energy intake might thus be assessed as 
plausible by some. In some cases, this general plausibility is all that 
is needed to initiate a policy. For example, when considering calorie-
labeling of restaurant menus, U.S. District Judge Richard J. Holwell 
ruled that:

          ``The Court agrees with Dr. Allison that one cannot conclude 
        with scientific certainty from the available evidence that a 
        regulation of this type will ultimately be successful in 
        combating obesity. But even if there are no data demonstrating 
        conclusively that Regulation 81.50 will be effective, 
        conclusive proof is not required to establish a reasonable 
        relationship between Regulation 81.50 and the City's interest 
        in reducing obesity. Based on the evidence presented by the 
        City, as well as common sense, it seems reasonable to expect 
        that some consumers will use the information disclosed pursuant 
        to Regulation 81.50 to select lower calorie meals when eating 
        at covered restaurants and that these choices will lead to a 
        lower incidence of obesity.'' \2\

    In contrast, empiricists (or Bayesians) might state that the 
existing evidence indicates that no proposed public health approach to 
obesity has been convincingly shown to work or, at best, that no 
approach has more than very modest effects when it has been applied or 
tested.3-4 Therefore, the a priori expectation is that the 
next proposed policy will have little to no effect. By analogy, this 
rationale is similar to the statistically minded high school guidance 
counselor who advises the basketball star to study academics because, 
while the counselor cannot rule out that this player will be the one to 
get drafted to the NBA or WNBA, it is unlikely.
    Plausibility may also be low in some people's minds for policies 
that aim to affect one component of energy balance in one context while 
leaving other components of energy balance untouched. Such policies, 
even if effective in altering the one component of energy balance in 
the desired direction, will only be effective if this alteration is not 
compensated (or is at least incompletely compensated) for by 
alterations in other components of energy balance. Empirical, 
experimental evidence indicates that such compensation does indeed 
occur, although the compensation is usually incomplete.\5\ This 
suggests that the plausible effects of policies that work through 
proposed alterations in one component of energy balance should not be 
based on models that assume no compensation (c.f., The Caloric 
Calculator, which estimates average caloric impact, which predicts 
effect sizes for childhood obesity interventions),\6\ as such models 
will likely markedly overestimate plausible effects.
    The plausible benefit of many proposed policy approaches also rests 
of the assumption of additivity--a small effect coupled with several 
other slight effects will collectively produce a larger response in the 
outcome. This is particularly applicable to the category of ``nudge,'' 
a term introduced by Thaler and Sunstein to describe multiple, minor, 
likely unnoticeable changes to alter one's behavior.\7\ Rozin, et al., 
showed that multiple modest changes, or nudges, affecting food 
accessibility (location of ingredients at a salad bar and size and type 
of serving utensils) in a cafeteria setting reduced the calories 
purchased during single meals without removing choices.\8\ They 
predicted that the reduced purchasing would translate to a cumulative 
benefit of weight loss over 1 year. Again, this type of study relies on 
several assumptions: that fewer calories purchased translates to fewer 
calories consumed; that ``all else is equal,'' i.e., that no 
compensation occurs; that short-term effects persist in the long term; 
that multiple interventions have additive effects; and that effects of 
interventions work equally well when subjects are fully aware of the 
interventions (as in ordinary commerce) as when the interventions are 
not disclosed (as in many studies). Such a study also brings up 
questions of whether patrons would purchase fewer calories in an 
ordinary setting such as a store and that would result in weight loss. 
For example, Wansink. et al., found that increasing the cost of soda 
resulted in reduced soda purchased but was associated with increased 
sales of beer.\9\ These nudges also may elicit a different response 
when persons are made aware of the interventions or with repeated long-
term exposure (i.e., daily or weekly grocery shopping).\10\ The nudge 
approach has also been criticized on several other 
grounds,11-12 and such criticism highlights that what seems 
plausible to one person may not seem so to another.
Evidence Regarding Postulated Intermediaries
    Evidence of the effectiveness of obesity policy may also rest on 
evidence regarding presumed mediating variables. An example is a 
proposed policy for an action intended to increase fruit and vegetable 
consumption, with the main assumption being that increased intake of 
fruits and vegetables (the mediating factor) will decrease adiposity or 
promote less weight gain. Empirical support for the policy may include 
a demonstration that the proposed action does indeed lead to increased 
fruit and vegetable consumption. However, such support can only be 
suggestive because it does not necessarily follow that increases in 
fruit and vegetable intake will actually decrease or prevent adiposity 
or lessen weight gain, and the same argument applies for other 
postulated intermediaries.13-14
Evidence from Analogue Studies
    Analogue studies attempt to represent key aspects of ordinary life 
while controlling or limiting external factors, which increases 
internal validity and can yield key insights \15\ yet potentially 
decreases external validity.\16\ An example of an analogue study was 
conducted by Epstein, et al., to compare the effects of taxation versus 
subsidization on food purchases.\17\ They found that using taxes on 
foods with low nutrient density but also high caloric content was 
successful at reducing caloric intake, whereas subsidizing low-calorie 
foods increased caloric intake. This type of evidence supports the 
plausibility, but not necessarily the effectiveness, of a policy for 
decreasing obesity. One area of opportunity is the use of pragmatic 
RCTs, which emphasize rigorous methods in real-world contexts.\18\
Direct Evidence Regarding Effectiveness
    Of course, the key evidence desired is evidence of a policy's 
effectiveness on the ultimate outcome: decreased levels of obesity. 
Although optimal, such evidence is often difficult to obtain. 
Ultimately, an ideal study would bear direct evidence of effectiveness, 
under actual conditions of use, during extended periods of time, and 
would be of a nature to allow strong inference of cause and effect. 
These would be randomized studies of actual policy or of extremely 
close proximity. There is no question that these studies would be 
difficult, expensive, time-consuming, and in some cases potentially 
unethical. We do not advocate a lack of action without this type of 
evidence; however, there should be a clear understanding that without 
such evidence, statements about the effects of a policy remain 
speculative.
Evidence Regarding Unintended Consequences
    It is important to keep in mind that implementation of any policy 
often brings with it unintended and undesirable consequences. Many of 
these consequences have been previously highlighted.19-20 
Such consequences can include, but are not limited to, inequitable 
distribution of the costs to implement the policy, encroaching on 
individual freedoms, over-consumption or increased purchasing of 
certain foods, stigmatization, depression, and avoidance of doctor 
appointments.19-20 One author contends that the emphasis on 
body weight has led to weight-based bullying, increased disordered 
eating, body dissatisfaction, extreme dieting, and complications from 
obesity surgery, among others.\21\ While some evidence exists on 
potential unintended and undesirable consequences, it is fairly limited 
as this field has not been fully investigated. Again, fear of 
unintended negative consequences should not paralyze us into inaction, 
but should lead us to practice humility about the potential value of 
our proposals, to think things through carefully, and to vigilantly 
monitor implemented policies for any potential unintended consequences.
Evidence Regarding Public Opinion
    Reports of the results of public opinion surveys on the 
desirability of particular obesity-related policies have proliferated 
in recent years.\22\ By implication, this suggests that if a large 
portion of the population supports a proposed policy, then implementing 
the proposal is merited. Is such a conclusion reasonable? Should 
evidence of public opinion about the desirability of policies be 
considered?
    Suh, et al., suggest that public opinion should be solicited to 
``better understand the public mindset about relevant policy 
strategies, and to identify attitudes among different subsets of the 
population towards specific legal measures that can increase 
protections for individuals affected by obesity.'' \23\ Pollard, et 
al., also contend that it is important to survey public opinion or 
community perception, especially when the policy in question involves 
what may be thought of as government ``interference'' in issues 
concerning food (labeling, advertising, and supply of environmentally 
friendly food).\24\ But are such opinions always important? When 
assessing public opinion is warranted, which methodologic issues are 
involved? And, are there actually circumstances when assessing public 
opinion would be quite inappropriate? Because this article is primarily 
about evidence for effectiveness, we consider these questions only 
briefly here.
    Are scientific assessments of public opinions about policies always 
important? Throughout the history of the United States, political 
leaders have wrestled with the pursuit of what seems morally right 
based on fundamental principles and doing what is popular. One such 
example is the famous Lincoln-Douglas debates about slavery. In one of 
the debates, Lincoln famously said, ``In this and like communities, 
public sentiment is everything. With public sentiment, nothing can 
fail; without it nothing can succeed. Consequently he who moulds public 
sentiment, goes deeper than he who enacts statutes or pronounces 
decisions. He makes statutes and decisions possible or impossible to be 
executed.'' \25\ It is noteworthy that Lincoln, like some modern day 
authors interested in obesity policy,\26\ is talking about ``moulding'' 
public opinion to enable what one has already determined is right and 
just, and not assessing public opinion to determine what is right and 
just.
    If Lincoln had conducted a public opinion poll and found that most 
pre-Civil War Americans favored retaining slavery in the United States, 
would he have judged that pertinent evidence as to whether the practice 
should be abolished? Would we? The answer is evidently no. When 
something is judged to be morally wrong, it is wrong and should be 
``off the table'' for discussion regardless of its popularity. Consider 
the recent posting from Ted Kyle on a ``UK Proposal for Explicit Weight 
Discrimination in Healthcare.'' \27\ Kyle argues that a proposed policy 
was a grossly unjust form of discrimination against persons with 
obesity in terms of health care access. Or, consider proposed policies 
that entail institutionalized ``fat shaming'' \28\ or a failed/
withdrawn Mississippi bill to limit access of persons with obesity to 
restaurants.\29\ Many, including the current authors, would consider 
such proposals morally indefensible, and if one adopts such a position, 
then no public opinion polls are needed. If moral opinion has superior 
authority relative to public opinion, this invites important questions 
of who or how many determine the moral authority and on what basis.
    When public opinion assessment is warranted, which methodologic 
issues are involved? The above notwithstanding, situations certainly 
exist where public opinion is important, such as to determine whether a 
policy which is neither morally indefensible nor a moral imperative is 
desired by the citizenry. In such situations, it will be important to 
rely on good principles of designing and interpreting opinion surveys 
and to keep in mind that who is surveyed \30\ and how questions are 
worded \31\ can both be used to manipulate the answers one receives. 
Extensive discussions on these and other methodologic points are 
covered in standard textbooks on survey and sampling methods.
    Are there actually circumstances when assessing public opinion 
would be quite inappropriate? Finally, we suggest that in some 
circumstances, assessing public opinion is not only unnecessary, but 
inappropriate. Specifically, in situations where a proposed approach is 
morally indefensible, to admit the value of public opinion surveys on 
determining whether a policy should be enacted invites a ``tyranny of 
the majority.'' 32-33 An interesting corollary of this is 
that empirical evidence on the harm or lack of benefit for some morally 
indefensible practice might also be seen as not only unnecessary, but 
counterproductive, because the very act of considering the empirical 
evidence implies that the practice under consideration might be worthy 
of adoption if the evidence came out a particular way. For example, 
consider this headline from an Internet posting: ``Science Says Fat 
Shaming Backfires--So Can We Finally Stop It?'' \34\ The article seems 
to be referencing an observational study \35\ that is interpreted to 
show that perceived weight discrimination leads to greater future 
obesity in the person experiencing the discrimination. The answer to 
the headline's rhetorical query, So Can We Finally Stop It?, in our 
opinion is that we unequivocally should stop fat shaming, but not 
because of this (or any other) study but rather because it is wrong. 
Even if one accepts our view that fat shaming is wrong a priori, might 
one ask where the harm is of buttressing the position with some 
empirical support. The harm is that the empirical support, like all 
empirical support, is subject to differential interpretation, 
criticism, and being overturned. In the observational study in this 
example, it would be easy to point out many limits, most notably that 
the study cannot show cause and effect. This may lead others to 
conclude, ``Well, if the wrongness of fat shaming depended in part on 
the empirical evidence and the empirical evidence has holes in it, I 
guess fat-shaming may not be wrong after all.'' If this example is not 
stark enough, we can ask ourselves would we take seriously the need for 
studies to show deleterious effects of policies that institutionalized 
racial or religious discrimination as justifications for eliminating 
such heinous policies?
How Might Evidence for Obesity Policies Be Generated?
    We now turn from the question of what evidence we want to the 
question of how such evidence can be generated. In doing so, we 
emphasize that we are focusing in this section on questions regarding 
the effects of potential policies on outcomes and do not consider 
questions about assessing other things such as public opinion about 
policies. In considering the generation of evidence regarding the 
effects of potential policies, we are considering questions of cause 
and effect and readers may find the videos available from an annual 
short course on this topic of interest (see: 
http://www.norc.uab.edu/courses/shortcourse).
    Here, we divide the types of research to be considered into three 
categories: (1) research that can be determinative of the causal 
effects of policies; (2) research that can contribute to an overall 
assessment of the causal effects of policies, but cannot on its own 
determine causation; and (3) research that formally synthesizes 
multiple sources of information to estimate the causal effects of 
policies.
Research That Can Be Determinative of the Causal Effects of Policies
Role of Randomized Controlled Trials
    Empirical evidence derived from RCTs aimed at identifying factors 
that increase or decrease the risk or magnitude of obesity can provide 
the strongest evidence to guide the development of obesity 
policies.\36\ RCTs are regarded as the gold standard in the hierarchy 
of research designs because they are the most reliable method for 
determining causality.\37\ Evidence generated from RCTs has been used 
to guide the development of several types of obesity policies such as 
dietary recommendations, sugar-sweetened beverage taxes, and food 
pricing.38-40 Despite the acknowledgement that RCTs offer 
the strongest inferences about cause and effect, several arguments are 
commonly offered against reliance on RCTs for causal inference in 
policy research. We very briefly review these arguments here.

  1.  RCTs are imperfect. Some authors note that RCTs are imperfect. 
            They can be designed and executed with flaws. Like all 
            empirical studies, they are subject to stochastic 
            variation. Finally, they often entail subject selection 
            criteria and/or study conditions that limit 
            generalizability of the results owing to the broader 
            population and more ``real-life'' circumstances. These are 
            all legitimate criticisms, but two things are noteworthy. 
            First, these weaknesses are all surmountable. RCTs can be 
            designed and executed well and can be executed in large 
            enough samples and tested with small enough nominal type 1 
            error levels to minimize stochastic errors. Finally, 
            pragmatic controlled trials offer investigators the ability 
            to conduct a study that examines the effectiveness and 
            efficacy of an intervention in the real world by allowing 
            for the inclusion of a diverse sample of the population and 
            by enabling the intervention to be adapted to local 
            settings.\41\ For example, the Moving to Opportunity study 
            found that certain social programs involving housing 
            vouchers providing the ``opportunity to move from a 
            neighborhood with a high level of poverty to one with a 
            lower level of poverty was associated with [caused] modest 
            but potentially important reductions in the prevalence of 
            extreme obesity and diabetes.'' \42\

  2.   RCTs are sometimes impractical or impossible. We agree that RCTs 
            are sometimes impractical or impossible, but this has no 
            bearing on the extent to which RCTs and other designs can 
            or cannot provide strong inferences or causation. The 
            argument that (a) RCTs are sometimes impractical or 
            impossible, (b) such that if we relied on only them for 
            strong causal inferences we would not be able to make 
            strong causal inferences in some situations in which we 
            wished to make strong causal inferences, and (c) therefore 
            we should not make strong causal inferences solely from 
            RCTs is simply a special case of Argumentum ad 
            Consequentiam.\43\

  3.  There are no RCTs showing that parachutes work. It is sometimes 
            noted that we accept many propositions as true on the basis 
            of some evidence and intuitive obviousness such as that 
            smoking causes lung cancer or that parachutes save lives 
            among skydivers.\44\ This is an example of argument by 
            analogy.\45\ Arguments by analogy can be useful foils to 
            provoke thought, but in and of themselves prove or disprove 
            nothing.

  4.  We cannot wait for perfect data. It is sometimes argued that we 
            cannot (or more aptly should not) wait for perfect data to 
            take certain actions, such as enact certain policies. We 
            agree with this proposition. However, the statement ``we 
            cannot (or more aptly should not) wait for perfect data to 
            take certain actions'' is not equivalent to ``we cannot (or 
            more aptly should not) wait for perfect data to draw strong 
            conclusions about causation.'' Taking actions and drawing 
            causal conclusions are distinct processes and the need and 
            justification to take prudent action in the face of 
            uncertainty is not a justification for denying that the 
            uncertainty exists.19, 46-47

  5.  Inadvertently Promoting a False Dichotomy. Majumdar and Soumerai 
            \48\ have cogently noted that ``some contend that only 
            randomized controlled trials produce trustworthy evidence. 
            Unfortunately, such a position discounts valid 
            nonrandomized or quasi-experimental study designs, even 
            though health policy randomized controlled trials are 
            rarely feasible. Such a constrained view inappropriately 
            lumps together valid evidence from strong nonrandomized 
            designs (that is, before-after studies with concurrent 
            controls or the interrupted time series study in which a 
            policy causes a sudden, visible change in trend) with 
            evidence from weak designs that permit little causal 
            inference (that is, the commonly conducted cross-sectional 
            analysis that looks at outcomes only after a policy has 
            been implemented).'' We agree that there is a continuum of 
            non-RCT designs that vary in the strength of causal 
            inferences they justify. We also agree that the stronger 
            designs are underutilized as we discuss later in this 
            article. However, these recognitions do not affect the 
            validity of propositions that randomization is key to valid 
            causal inference.\49\ If we accepted otherwise, we would 
            again be engaging in Argumentum ad Consequentiam.\43\
Research That Can Contribute to an Overall Assessment of the Causal 
        Effects of Policies
    Having emphasized the critical role of RCTs in humans on the policy 
under question and for the outcomes under question in drawing strong 
causal inference, we also note that with such information often 
unavailable and sometimes unattainable, it is frequently necessary to 
make decisions about actions without drawing firm conclusions about 
causation. In doing so, we must commonly integrate multiple sources of 
information, none of which alone is unequivocally dispositive about a 
conclusion of causation, to make informed decisions about what might 
reasonably be expected to work. Several sources of evidence can 
contribute to such decisions.
Role of Model Organism Evidence
    Model organisms are used to generate information regarding casual 
relationships that cannot be derived through human studies. For 
example, exposure to environmental obesogens, such as endocrine-
disrupting chemicals, has been identified as a possible factor that 
increases the risk of obesity.50-51 Such studies are vital 
in policy decisions, for example, to approve or disapprove use of a 
food additive, but cannot offer unequivocal conclusions about causation 
in humans because of the possible heterogeneity of effects across 
species.\52\
Role of Observational Evidence: of Ordinary Association Tests (OATs) 
        and Extended Assoc[i]ation Tests (EATs)
    Observational evidence generally plays a vital role in assessing 
the likely value of proposed policies. Observational studies are useful 
in generating hypotheses that can inform the conduct of more rigorous 
studies (i.e., randomized trials) to begin to establish causality. With 
regard to policies developed to address the obesity epidemic, 
observational studies have been used to investigate associations 
between the initiations of policies and relevant outcomes. That said, 
not all observational evidence is of equal value. Here we distinguish 
between two broad classes of observational evidence which we will call 
Ordinary Association Tests (OATs) and Extended Association Tests 
(EATs).
    Ordinary Association Tests. We define ordinary association tests 
(OATs) to be observational studies on samples of individuals in which 
the sole or primary means of controlling for potential confounding 
factors is inclusion of measures of some potential confounding factors 
as covariates in statistical models (or stratifying by measures of such 
factors). OATs are heavily relied upon in thinking about plausible 
effects of polices, but have also been heavily criticized in general 
53-54 and in the obesity and nutrition domains in particular 
55-57 for multiple reasons. We refer the reader to those 
references for details.
    Extended Association Tests. Most dialogue and research in obesity 
does not consider the evidence continuum between OATs, which do not 
offer strong assessments of causal effects, and RCTs, which do offer 
strong inferences, but cannot be done in all circumstances. In contrast 
to this polarized view, there are techniques that we refer to as 
extended association tests (EATs) that lie intermediary between 
ordinary association tests and RCTs, including but not limited to 
quasi-experimental studies and natural experiments. Such designs are 
increasingly used, especially in the disciplines of economics and 
genetics, but are rarely used in obesity research. However, the ability 
to draw causal inferences in obesity research could be strengthened by 
increased judicious use of such approaches. In-depth understanding and 
appropriate use of the full continuum of these methods requires input 
from disciplines including statistics, economics, psychology, 
epidemiology, mathematics, philosophy, and in some cases behavioral or 
statistical genetics. The application of these techniques, however, 
does not involve routine well-known ``cookbook'' approaches but 
requires understanding of underlying principles so the investigator can 
tailor approaches to specific and varying situations.
    Some of the key methods in use for situations where standard RCTs 
may not be available include natural experiments, quasi-experiments, 
and experiments in which true randomization is used but subjects are 
not randomized directly to levels of the independent variable, as 
described with examples in Table 1.
    Natural experiments are a useful type of observational study that 
can be used to investigate the impact of environmental changes on 
obesity, that is, changes that the investigator did not manipulate. In 
this case, investigators merely measure outcomes before and after the 
implementation of a new policy, regulation, or other factor that has 
changed. Within the context of efforts at obesity modification, natural 
experiments have been used to assess the effectiveness of new policies 
(e.g., inclusion of calorie information on menus, implementation of 
environmental elements thought to promote physical activity [i.e., 
parks, bike lanes, walking trails], use of school-based obesity 
screening and BMI report cards).61, 68-70
    A prime example comes from the U.S. Food and Drug Administration, 
which implemented regulations requiring franchise restaurant chains 
with 20 or more locations to provide calorie information on their menus 
and menu boards. In a natural experiment conducted in New York City, 
receipts were collected from patrons of fast food restaurants before 
and after menu labeling was implemented. The investigators found that 
adding calorie information to the menus did not appear to influence the 
food choices of parents or adolescents.\61\ Natural experiments such as 
this are a cost-effective way to evaluate the effects of obesity 
policies, as well as provide information that might inform 
modifications to existing policies.
    The existence of EATs seems to be less well known to many 
investigators in public health, medicine, psychology, and related 
fields. We believe that many questions about behavioral, psychological, 
and economic influences on obesity-related variables and many applied 
questions about the effects of extant or proposed interventions can be 
addressed more informatively and more rigorously if more investigators 
availed themselves of these evolving methodologies related to causal 
inference from a basis of a sound understanding of fundamental 
principles.
Research That Formally Synthesizes Multiple Sources of Information To 
        Estimate The Causal Effects of Policies
    Apart from the need to embrace and use the range of potential 
design strategies available, it is also essential to ``step back'' and 
synthesize the multiple and varied sources of information to evaluate 
what they can tell us about the causal effects of policies.
Role of Systematic Reviews and Meta-Analysis
    As a result of the growing rates of obesity around the world, the 
volume of evidence from obesity research has burgeoned. However, owing 
to variations in the quality and type of study design, implementation, 
and the outcomes measured, determining effects from various studies can 
be challenging. Debates on obesity policies are often fueled by the 
contradictory findings of empirical studies, such as those regarding 
the influence of sugar-sweetened beverage consumption on childhood 
obesity.\40\ As such, high-quality systematic reviews and meta-analyses 
can be useful when attempting to evaluate the state of the evidence 
related to a particular intervention or policy with objective 
approaches to identifying and integrating evidence.\71\ That said, as 
Ingram Olkin once wrote, ``Doing a meta-analysis is easy. Doing one 
well is hard,'' \72\ and we have found that errors in obesity-related 
meta-analyses abound.\73\ Hence, while meta-analyses are vital, our 
field needs to improve their execution, and meta-analyses should be as 
critically reviewed as are any other studies.
Role of Modelling
    One drawback of RCTs, noted above, is that they often are not large 
enough to capture the entire spectrum of effects (both desired and 
undesired) that a policy may have.\74\ Mathematical and computational 
models of health policies are tools that can be used to predict the 
outcomes of an obesity policy and to identify implementation barriers 
before the policy is adopted.\75\ Moreover, the modelling of obesity 
policy enables policymakers to estimate the costs of implementing 
policies and to determine the resource allocation required to implement 
a given policy.76-78 For example, a dynamic weight loss 
model was used to estimate the effects of a tax on sugar-sweetened 
beverages on the prevalence of obesity in New York City.\79\ The model 
suggested that there would be decreases in obesity prevalence over a 10 
year period.\79\ The model also estimated the magnitude of the 
projected reductions in obesity prevalence, allowing readers to better 
judge the potential public health impact of such a policy.\79\
    Models are also valuable for monitoring the effects of policies 
over time. Evidence has shown that the effects of health policies can 
increase or diminish with the passage of time.\78\ Therefore, new data 
concerning the effects of a policy should be continually generated to 
estimate its effects in order to allow policymakers to revise or even 
discontinue implementation of the policy if it is shown to be 
ineffective.\74\
    Despite the benefits of using models in the development and 
refinement of health policies, some challenges and limitations must be 
recognized. For example, health policy modellers are not often 
integrated into the health policymaking process. Therefore, models are 
seen as ``one-offs'' rather than as tools that should be used during 
the lifecycle of the policy to ensure that it retains its value. 
Perhaps most importantly, models offer projections of effects, not 
demonstrations of effects. Such projections can be heavily dependent on 
the input parameters (i.e., assumptions) of the model, and some 
published modelling activities (e.g.,\80\) are so heavy on assumptions 
of efficacy of the policies considered that the modelling can be seen 
as an instance of petitio principii.\81\
Standards for Evidence and Related Factors Influencing Policy Decisions
    According to Donaldson and colleagues, most obesity prevention 
bills enacted between 2010 and 2013 were based on initiating strategies 
(e.g., ``initiated farmer[s'] markets, increased access to walking 
trails, local menu labeling'') that had little to no evidence of 
benefit.\82\ But is this wrong? A vital consideration, often not made 
explicit a priori, concerns the standards for evidence that will used 
to both generate a policy decision and to evaluate its effect once 
implemented. In general, the standards of evidence for a scientific 
conclusion are thought to be far more rigorous, because they are based 
on long-established methodologies that are considered to be objective, 
repeatable, and relatively immune to biases of the individuals 
conducting the study. In contrast, the evidence (if any) needed to 
reach a policy decision (which is distinct from reaching a scientific 
conclusion) depends on many factors and is not constant across 
circumstances. Opinions can also vary. For example, the Society for 
Prevention Research states, ``To be ready for broad dissemination, a 
program must not only be of proven effectiveness, but it must also meet 
other criteria . . .'' (emphasis added).\83\ This stands in marked 
contrast to the statement of District Judge Richard J. Holwell quoted 
above that ``even if there are no data demonstrating conclusively that 
Regulation 81.50 will be effective, conclusive proof is not re-
quired . . .'' and in the context of the legal proceedings, his 
interpretation of law is what determined the evidence standard. There 
are yet other standards in different contexts and so no universal rule 
about how much evidence is or is not needed for policymaking can be 
given. This stands in contrast to occasional statements from academics 
that seem to state from no formal basis of authority that a particular 
amount of evidence is or is not needed to enact a policy.
    The four quotations listed (see Box 1) are from discussions and 
presentations involving policies directed at curbing sugar intake in 
the public. They reflect the varying perspectives of differing 
standards of evidence among researchers. The first two 84-85 
put rigor of evidence aside and instead emphasize that the decision to 
develop policy is the priority based on a decision that seems to have 
already been committed to based upon some combination of suggestive 
evidence or intuition. In contrast, the third and fourth statements 
progress from needing ``a strong sense that it will be effective'' \86\ 
to confidently requiring ``strong evidence'' prior to any public policy 
decision.\87\ Thus, disagreement on the amount and rigor or evidence 
needed to enact a policy exists even among researchers discussing a 
particular target (sugar) of public policy. They illustrate the 
subjectivity of the standards of evidence for decision making.
In Summation
    In closing, our field will benefit from a greater emphasis on 
probative research. Probative research would meaningfully move us 
forward in our ability to state that a given treatment or prevention 
strategy does or does not have a particular effect.\88\ This is in 
contrast to studies that merely continue to draw attention to the 
plausibility of some treatment having some effect but do not increase 
our knowledge that such an effect actually exists.\88\ Finally, the 
quest for rigorous evidence and scrupulous truthfulness in reporting is 
fully compatible with the quest for beneficence and passionate pursuit 
of action for the betterment of others. Recognizing these 
comparabilities (see Box 2) may pave the way for public health dialogue 
in obesity that is both more honest and more collegial.

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    Table 1. Examples of Extended Association Tests (EATs) in Obesity
                                Research
------------------------------------------------------------------------
  Topic Under Study          Design                Finding         Ref.
------------------------------------------------------------------------
Effects of            Co-Sib Control        Mixed                  58	59
 Breastfeeding on
 Offspring Obesity
Effects of            Adoption Study        Consistent with a       \60\
 Socioeconomic                               causal effect, but
 Status of Rearing                           only \1/2\ of
 Parents on Child                            ordinary
 BMI                                         association
Effects of Menu       Quasi-Experiment      No support              \61\
 Labeling on
 Calories Purchased
Effects of Migrating  Natural Experiment    Some evidence for       \62\
 from Tonga to New                           BMI increase in
 Zealand                                     some ages
Effects of Roommate   Packet Randomized     Association             \63\
 Characteristics on    Experiment            suggesting that
 Freshman Weight                             being assigned to
 Gain                                        higher BMI roommate
                                             leads to less
                                             weight gain
Effect of Education   Quasi-Experiment      No support              \64\
 on Food Choice
Effect of Casinos     Quasi-Experiment      Association             \65\
 (as Economic                                suggestive of
 Boosters) on Child                          beneficial effect
 Obesity
Effects of Altitude   Quasi-Packet-         Association             \66\
 of Residence on       Randomized            suggestive of
 Obesity               Experiment            beneficial effect
Effects of            Co-Twin Control       No support              \67\
 Environmental
 Factors Influencing
 Birthweight on
 Adult BMI
------------------------------------------------------------------------


 Box 1: Contrasting Ideas on the Amount and Rigor of Evidence Regarding
                 Policies Targeted at Sugar Consumption
                         [emphases added below].
------------------------------------------------------------------------
 
-------------------------------------------------------------------------
    ``It's a classic example. It's industry-funded authors saying that
 the dietary guidelines recommendations about sugar aren't based on
 science. I'm laughing because what kind of evidence do you need? Sugar
 is calories and no nutrients and everybody would be healthier eating
 less of it.''--Marion Nestel \84\
    ``I would be very surprised if any one pot policy had any effect on
 obesity. And in some ways I think it's a trap to expect it to do that
 because so many things are driving the problem. So many things are
 affecting the food supply, levels of physical activity, and [ . . . ]
 structural things like poverty, education, and access to healthcare. To
 expect any one policy to turn that around I think is wishful thinking.
 But it is certainly important that it be studied as much as it can so
 that you know at the end of the day, so that you know [ . . . ] where
 you get the biggest impact per dollar of policy change'' --Kelly
 Brownell \85\
    ``In public health, when someone is going to act, particularly for
 something that is a public policy my goodness, we have to have some
 pretty strong sense that it's going to be effective. Public policy
 cannot be enacted simply based on a good idea. There has to be reason
 that it's going to make a difference and a difference relative to
 public interest.''--Nancy E. Kass \86\
    ``But we should need very strong evidence before we made people burn
 a fuel in their homes that they do not like or stop smoking the
 cigarettes and eating the fats and sugar that they do like.''--Sir
 Austin Bradford Hill \87\
------------------------------------------------------------------------


    Box 2: Clarification Within Two Domains: Evidence for scientific
            conclusions and for Advocacy Of Policy Decisions
------------------------------------------------------------------------
 
------------------------------------------------------------------------
Evidence for Scientific Conclusions   Greater candor in
                                      scientific presentations 89	92
                                      Acceptance by empirically
                                      minded scientists that action can
                                      sometimes legitimately precede
                                      without strong evidence
                                      Articulating distinctions
                                      between our values and our
                                      assessments of empirical evidence
                                      \91\
Evidence for Advocacy of Policy       Eschewing fallacious
 Decisions                            rhetorical arguments
                                      Acceptance by advocates
                                      that advocacy neither requires nor
                                      justifies making evidence seem
                                      stronger than it is
------------------------------------------------------------------------

                              attachment 8
Will Reducing Sugar-Sweetened Beverage Consumption Reduce Obesity? 
        Evidence Supporting Conjecture Is Strong, But Evidence When 
        Testing Effect Is Weak
Pro v. Con Debate: Role of Sugar Sweetened Beverages in Obesity
K.A. Kaiser,[1] J.M. Shikany,[2] K.D. 
Keating,[1] and D.B. Allison [1]
---------------------------------------------------------------------------
    \[1]\ Office of Energetics, Dean's Office, School of Public Health, 
University of Alabama at Birmingham, Birmingham, Alabama, USA.
    \[2]\ Division of Preventive Medicine, School of Medicine, 
University of Alabama at Birmingham, Birmingham, Alabama, USA.
    Address for correspondence: Dr. D.B. Allison, Ryals Public Health 
Building, Rm 140J, University of Alabama at Birmingham, 1665 University 
Boulevard, Birmingham, AL 35294, USA. E-mail: [email protected].
---------------------------------------------------------------------------
Received 12 February 2013; revised 25 April 2013; accepted 26 April 
2013.
Obesity Reviews (2013) 14, 620-633.
2013 The Authors
Summary
    We provide arguments to the debate question and update a previous 
meta-analysis with recently published studies on effects of sugar-
sweetened beverages (SSBs) on body weight/composition indices (BWIs). 
We abstracted data from randomized controlled trials examining effects 
of consumption of SSBs on BWIs. Six new studies met these criteria: (i) 
human trials, (ii) %3 weeks duration, (iii) random assignment to 
conditions differing only in consumption of SSBs and (iv) including a 
BWI outcome. Updated meta-analysis of a total of seven studies that 
added SSBs to persons' diets showed dose-dependent increases in weight. 
Updated meta-analysis of eight studies attempting to reduce SSB 
consumption showed an equivocal effect on BWIs in all randomized 
subjects. When limited to subjects overweight at baseline, meta-
analysis showed a significant effect of roughly 0.25 standard 
deviations (more weight loss/less weight gain) relative to controls. 
Evidence to date is equivocal in showing that decreasing SSB 
consumption will reduce the prevalence of obesity. Although new 
evidence suggests that an effect may yet be demonstrable in some 
populations, the integrated effect size estimate remains very small and 
of equivocal statistical significance. Problems in this research area 
and suggestions for future research are highlighted.
Introduction
    The proposition we have been asked to address and for which we 
evaluate the available evidence is as follows:

          `There is sufficient scientific evidence that decreasing 
        sugar-sweetened beverage (SSB) consumption will reduce the 
        prevalence of obesity and obesity-related diseases.'
What We Are Debating
    In examining the proposition, it is useful to carefully consider 
several of its components as follows:
Sufficient Evidence
    The word sufficient invites the question, sufficient for what? As 
the remainder of the proposition indicates, the answer is for drawing a 
conclusion that decreasing SSB consumption will reduce the prevalence 
of obesity and obesity-related diseases. This must be distinguished 
from the question of sufficiency for taking public health action or 
guiding public health policy. What constitutes sufficiency for actions 
(as opposed to drawing conclusions) is not a purely scientific question 
that can be answered objectively. Such decisions depend only in part on 
scientific evidence of the likely effects of those actions and also 
depend on other inputs including but not limited to legal authority, 
moral values and personal tastes, none of which are determined by 
empirical evidence. The question `Is there sufficient evidence for 
action?' is inherently subjective and depends on which action, in which 
regulatory context and according to whose tastes and moral values. As 
Sir Austin Bradford Hill wrote, `The evidence is there to be judged on 
its merits and the judgment . . . should be utterly independent of what 
hangs upon it--or who hangs because of it'.(1)
Scientific Evidence
    We are not asked for conjecture, but rather whether empirical 
evidence exists showing that decreasing SSBs has the effects stated. We 
therefore examine the highest quality evidence available in the form of 
randomized controlled trials (RCTs). Because such trials are ethically 
possible and have been performed, we assert that this type of 
scientific evidence supersedes correlation or cohort 
studies.(2) When RCTs are not possible, other evidence must 
be amassed to attempt to inform causation. However, RCTs are possible 
to address this question and data are available. Hence, we rely on 
these results in the present case as they are probative (by probative, 
we mean studies which can generate evidence which settles questions by 
proving or disproving propositions, as opposed to simply influencing 
the strength of speculation) with respect to causation.(3)
Decreasing
    We cannot assume that the effects of decreasing consumption are the 
opposite (direction and magnitude) of the effects of increasing 
consumption. Therefore, we provide examinations of available 
experimental reports that evaluate both interventions so as to quantify 
the observed effects in each case.
Reduce the Prevalence of Obesity and Obesity-Related Diseases
    As to `obesity-related diseases,' one must first demonstrate an 
effect on obesity to suggest an effect on obesity-related diseases. 
Else in what way can the diseases be said to be obesity-related? We 
therefore focus our present meta-analysis on studies of the effect on 
body weight or body composition.
What We Are Not Debating
    Just as we have clarified the proposition being debated, it is 
equally important to not be distracted by questions that we have not 
been asked to address. For example, we have not been asked to address 
whether obesity is a crisis, if fructose is toxic, are some sugars 
worse than others, are food company marketing budgets too large, have 
portion sizes increased to absurd levels, do SSBs affect dental caries, 
are pictures of an average American's sugar consumption dramatic, is 
liberty better than paternalism (or vice versa), is food marketing like 
tobacco marketing, or do we sometimes need to take public health 
actions in the absence of strong evidence. Although these are 
provocative questions, they are not germane to the necessary evaluation 
of evidence regarding the question we have been asked to debate. Yet we 
mention them because they and similar questions are often introduced 
into such discussions and serve as emotion-raising distractions to an 
evaluation of the pertinent evidence.
There Is Evidence To Support Conjecture
    We freely concede that there is evidence to support the conjecture 
that reducing SSB consumption might reduce obesity and obesity-related 
diseases. However, many of these data are not probative in terms of 
causation. Specifically, there are three forms of human evidence 
supporting this conjecture.
    First, we address ecological correlation. SSB consumption has risen 
just as obesity rates have risen.(4) This is the weakest 
form of evidence available. Other beverage consumption patterns (e.g., 
bottled water (5) depicted in Fig. 1) have also demonstrated 
a strong correlation with the obesity epidemic in the United 
States.(6-7)
    Second, we note an association in some observational 
studies.(8-10) Whereas there is an ever-growing body of 
epidemiologic studies, some of which demonstrate statistically 
significant associations, it is well known that association does not 
establish causation. Moreover, the association is weak,(11) 
inconsistent (12-13) and biased,(14) as we will 
discuss later. Again, as Dr. Hu (our debate opponent) wrote, `Although 
the overall results were not entirely consistent, the weight of 
epidemiologic and experimental evidence indicates greater consumption 
of sugar-sweetened beverages is associated with weight gain and obesity 
in children and adults. However, the existing studies suffer from many 
methodological limitations, including cross-sectional design, small 
sample size, short follow-up, inadequate dietary assessment, and a lack 
of repeated measures of diet and lifestyle. . . . any single dietary 
factor is unlikely to have a large effect on body 
weight'.(13)
    For the third and final point which supports conjecture, we 
acknowledge that lesser compensation with liquid versus solid calories 
has been found in some in short-term feeding studies.(15-17) 
By compensation, we refer to the definition provided by Mattes 
(18) whereby later energy intake may be reduced to 
compensate for preloads or added calories from some other intervention. 
It must also be acknowledged that compensation for added intake may 
also take the form of altered energy expenditure, which can offset the 
intake component of energy balance. Few feeding studies examine this 
component. Additionally, short-term feeding effects are by no means 
equivalent to long-term weight effects.(19) Moreover, the 
short-term effects are inconsistent, with some studies showing near 
perfect compensation for liquid calories (11, 20-21) and 
others showing imperfect but equivalent (between forms) compensation to 
solid calories.(22) Finally, there is far more than zero 
compensation as implied by common and exaggerated public statements 
such as, `When we drink sugary beverages, we simply do not compensate 
by eating less food' (23) or `Liquid calories don't register 
with our appetite controls'.(24)
Figure 1 


          Rise in obesity rates (6) (round markers) and 
        bottled water consumption (5) (square markers), 
        United States. BMI, body mass index, kg m^\2\.

    We agree with Dr. Pan and Dr. Hu's statement in 2011 that `. . . 
the isolated tests in the laboratory may not be directly reproduced in 
real life because the effect of any food or food component on satiety 
could be influenced by other dietary factors. Thus, results from short-
term, well-controlled interventions may not be representative of a 
real-life setting, and long-term clinical trials on different physical 
forms of carbohydrates on energy intake and weight management are still 
lacking'.(25) Later in this article, we provide even more 
compelling evidence from longer-term trials on weight that some 
compensation for added liquid calories indeed occurs.
Evaluation of Evidence To Draw Scientifically Supported Conclusions
    When randomized trials can be performed ethically and safely (which 
they have been), these study results are the strongest level of 
evidence of independent effects. Many scientists who have gone on 
record on the question we now debate have acknowledged the limitations 
of association studies and the need for well-designed randomized 
trials.(13, 26-28) If these same scientists are calling for 
well-designed trials, it is curious that strong statements are then 
made about weaker forms of evidence. Use of Hill's guidelines 
(1) is irrelevant in the instance of the effects of SSBs on 
weight because randomized trials can be done (and have been done). In 
such situations, the `totality' of the evidence, including evidence 
that is not probative, should not be relied upon for drawing 
conclusions of causation in favour of the probative studies. More 
recent trials have taken steps to reduce the level of bias 
(29-30) and future studies may advance this effort further.
Specific Questions We Address By Use of the Best Available Evidence
  1.  Does an increase in SSB intake increase body weight or body mass 
            index (BMI) in humans?

  2.  Does reduction of SSB intake reduce body weight or BMI in humans?

    We now evaluate and summarize the currently available evidence that 
could potentially be probative with respect to drawing conclusions 
about the effects of SSB reduction on weight or obesity.
Methods
    See supporting information for details of the updated literature 
review, study selection and data extraction methods. As the present 
paper was in review, an additional study meeting our criteria became 
public as a conference abstract.(31) This trial tested the 
effects of home water delivery and an educational programme to reduce 
SSB consumption in overweight, adult, Mexican women as compared to the 
education-only control group. Based on the available information in the 
abstract, we were unable to formally include this study result in our 
meta-analysis, but we discuss the possible effects on our conclusions 
using estimates from data reported in the abstract in the next section 
on results.
Results
The Extent of the Data Available: Studies Included and Excluded
    Table 1 contains a brief listing and description of the six new 
studies (29-30, 32-36) added for meta-analysis. We provide 
more details of each study in the supporting information online. 
Supporting Information Figure S1 contains a flow chart of the screening 
and selection of recently published studies.
    In the three new studies in which SSBs were added [90 to 500 kcal 
day^\1\ to the diets of adults (30,34); 158 kcal day^\1\ in children 
(36)], statistically significant weight gain was observed in 
both adult trials, ranging from 0.39 to 1.14 kg (Supporting Information 
Table S1). No significant difference in weight gain was observed in the 
study in children between the treatment and control 
participants.(36) When we compared observed weight gain to 
theoretical weight gain from added SSBs in all RCTs published to date 
(Fig. 2), compensation appeared to occur in longer-term studies.
    In the one new study of adults (35) and the two new 
studies of children (29, 32-33) in which participants who 
drank some amount of SSBs at baseline were asked to eliminate or reduce 
their SSB consumption, standardized mean differences (SMDs) in 
percentage weight loss or BMI reduction ranged from 0.13 to 0.33 
(Supporting Information Table S2). The overall results for added SSBs 
(small but statistically significant weight gain; Fig. 3) or for 
reduced SSBs in subjects of all weight ranges (small and not 
statistically significant weight loss; Fig. 4) did not differ greatly 
from our earlier analysis.(37)
    In new studies in which all participants were overweight or obese 
at baseline, SMDs ranged from 0.13 to 0.73 (Supporting Information 
Table S3). In combination with earlier studies or subgroup analysis of 
the effects of reducing SSBs on overweight subjects (Fig. 5), the 
overall SMD was 0.25 (95% confidence interval [CI]: 0.13 to 0.38 
standard deviations, P <0.0001).
    In the newly published study by Hernandez-Cordero, et 
al.,(31) the authors reported no significant effect with a 
P-value of 0.50. Assuming this is a two-tailed P-value, the reported 
sample size yields an effect size of either ^0.086 or +0.086. The means 
were not reported so we cannot determine the direction. If the sample 
effect size were +0.086, then the summary statistic would not change at 
all from the summary estimate and CI shown in Fig. 4. Alternatively, if 
the sample effect size was ^0.086, the summary estimate would be 
reduced towards zero (from 0.06 to 0.05) and remain statistically non-
significant. Similarly, for the analysis shown in Fig. 5 for subjects 
overweight at baseline, the addition of this study would shift the 
overall estimate from 0.25 to 0.21, or as low as 0.17 depending on 
direction of observed effect.
Assessment of Study-Level Risk of Bias
    Supporting Information Figure S2 summarizes our cumulative 
assessment of potential areas of bias of the pertinent studies to date. 
The most important areas for risk of bias overall come from lack of 
participant blinding and selective reporting. Some study designs failed 
to adequately isolate treatment effects from the attention researchers 
paid to some groups. Additionally, only two studies' protocols 
(29, 34) had an objective measure of participant compliance 
(returned containers, urinary sucralose measures), making cross 
comparisons and estimates of true effects difficult. Failure to mention 
whether assessors were blinded was common (ten out of 15 studies), 
further clouding assessment of potential sources of bias.
Assessment of Publication Bias
    Supporting Information Figures S3-S5 are funnel plots 
(38) for the assessment of potential publication bias from 
only the published studies and analyses for each of the three groups of 
designs or populations we analysed (excluding some analyses we 
performed on data not published but received upon request). We also 
evaluated potential publication bias by using the rank correlation 
test.(39) We found no present evidence of publication bias 
for studies on the effects of adding SSBs; 
(30, 34, 36, 40-42) P = 0.805), for studies on the effects 
of reducing SSBs in all weight categories; 
(29, 33, 35, 43-46) P = 0.976), or for studies on the 
effects of reducing SSBs in subjects who were overweight at baseline; 
(33, 35, 43, 44, 46) P = 0.858).
Sensitivity Analysis
    Age differences. There was unequal representation of age groups 
among the types of trials. The added SSB studies were all on adults 
except one,(36) and the reducing studies were predominantly 
in children with two exceptions.(35, 47) Therefore, we 
evaluated the overall summary effects by excluding the studies 
referenced above. The overall SMD for the added SSB studies (adults 
only) increased by 0.06 (to 0.34; 95% CI: 0.15 to 0.54). The overall 
SMD for the reduction of SSBs in children of all weight categories was 
reduced by 0.01 (to 0.07; 95% CI: ^0.01 to 0.15). The overall SMD for 
the reduction studies in children only who were overweight or obese at 
baseline increased by 0.05 (to 0.30; 95% CI: 0.13 to 0.46). These 
results are not largely different from the combined analysis reported 
in Figs 3-5. Per the convention put forth by Cohen,(48) 
these standardized effects would all be categorized as `small.'

           Table 1  Studies Published Since January 2009 Meeting the Original Inclusion Criteria (37)
----------------------------------------------------------------------------------------------------------------
                       Question that can be
     Reference       addressed regarding the       How meta-analysed        Primary outcome(s) and analysis as
                    effects of SSBs on weight                               stated in trials registry and paper
----------------------------------------------------------------------------------------------------------------
Njike, et al.,      Added two servings per     Meta-analysed all          Trial registry: NCT00538083
 2011 (30)           day of sugar-free cocoa,   response data for all     Primary--Endothelial function
                     sugared cocoa, or          phases (author provided   Secondary--Blood pressure, lipid
                     placebo cocoa in obese     raw data on request)--     profile, low-density lipoprotein
                     adults in a crossover      combined both caloric      (LDL) oxidation, lipid hydroperoxide,
                     trial, 6 weeks each        groups (sugared cocoa      C-reactive protein (CRP), glucose,
                     phase.                     and placebo cocoa) and     body weight, waist circumference,
                                                subtracted sugar-free      endothelin
                                                group.                    Paper:
                                                                          Primary--Endothelial function
                                                                          Secondary--Blood pressure, lipid
                                                                           profile and fasting glucose, food
                                                                           intake, endothelin, CRP, oxidized
                                                                           LDL, lipid hydroperoxide,
                                                                           anthropometric measures (body weight,
                                                                           body mass index (BMI), waist
                                                                           circumference)
                                                                          Missing data handling: Intention to
                                                                           treat analysis
Vaz, et al., 2011   Added choco-malt beverage  Meta-analysed untreated    Trial registry: NCT00876018
 (36)                mix to water and gave      control group versus      Primary--Physical fitness and
                     one serving per day to     unfortified group.*        performance
                     children in a parallel                               Secondary--Nutritional status, muscle
                     trial.                                                strength and endurance
                                                                          Paper:
                                                                          Primary--Within participant change in
                                                                           physical performance: whole-body
                                                                           endurance, aerobic capacity, speed
                                                                           and visual reaction time
                                                                          Secondary--Nutritional status, muscle
                                                                           strength, endurance in forearm flexor
                                                                           muscle group
                                                                          Missing data handling: Complete case
                                                                           analysis
Maersk, et al.,     Added 1 litre per day of   Meta-analysed regular      Trial registry: NCT00777647
 2012 (34)           milk, regular cola, diet   cola group versus diet    Primary--Body weight, magnetic
                     cola or water in           group.                     resonance spectroscopy, magnetic
                     overweight/obese adults                               resonance imaging, dual-energy x-ray
                     in a parallel trial for                               absorptiometry scan
                     6 months.                                            Secondary--Circulating metabolic
                                                                           parameters, blood pressure
                                                                          Paper:
                                                                          Primary--Intrahaepatic fat and
                                                                           intramyocellular fat
                                                                          Secondary--Fat mass, fat distribution,
                                                                           metabolic risk factors
                                                                          Missing data handling: Complete case
                                                                           analysis except for two cases who
                                                                           dropped out at 5 months, for whom
                                                                           last observation was carried forward
Ebbeling, et al.,   Multicomponent programme   Meta-analysed weight       Trial registry: NCT00381160
 2012 (33)           to reduce/replace SSBs     change at end of 1 year   Primary--BMI change at 2 years
                     with non-caloric           intervention period.      Secondary--none stated
                     beverages in                                         Paper:
                     adolescents.                                         Primary--Change in mean BMI at 2 years
                                                                           (1 year post-intervention)
                                                                          Secondary--Differences between
                                                                           ethnicities, change in body fat as a
                                                                           percentage of total weight
                                                                          Missing data handling: Imputed--
                                                                           baseline and last observation carried
                                                                           forward in separate analyses
de Ruyter, et al.,  Provided school children   Considered an SSB          Trial Registry: NCT00893529
 2012 (29)           identically labelled SSB   reduction study as        Primary--BMI Z-score at 6, 12 and 18
                     or non-caloric             inclusion criteria was     months
                     equivalent to consume      current SSB consumers.    Secondary--Body composition using
                     one can day^\1\.                                      skinfolds, bioelectrical impedance
                                                                           analysis (BIA), waist-to-height
                                                                           ratio, dental health, sensory
                                                                           evaluation (satiety and liking of
                                                                           study drink)
                                                                          Paper:
                                                                          Primary--Z-score of BMI for age at 18
                                                                           months.
                                                                          Secondary--(all pre-specified) waist-
                                                                           to-height ratio, sum of the four
                                                                           skinfold thickness measurements and
                                                                           fat mass (BIA). Additional outcomes
                                                                           were weight, height, z score for
                                                                           height, waist circumference and
                                                                           weight change adjusted for height
                                                                           change
                                                                          Missing data handling: Multiple
                                                                           imputation and complete case analysis
Tate, et al., 2012  Substituted SSBs with      Meta-analysed water and    Trial registry: NCT01017783
 (35)                artificially sweetened     artificially sweetened    Primary--Weight change at 3 and 6
                     equivalent or water in     groups together versus     months
                     obese adults who drink     SSB group.                Secondary--Urine specific gravity,
                     two or more servings per                              fasting glucose
                     day at baseline.                                     Paper:
                                                                          Primary--Weight change at 6 months.
                                                                          Secondary--Compare the non-caloric
                                                                           beverage groups with the control
                                                                           group on criterion measures of weight
                                                                           loss, waist circumference, blood
                                                                           pressure, glucose, and urine
                                                                           osmolality from 0 to 3 and 0 to 6
                                                                           months
                                                                          Missing data handling: Multiple
                                                                           imputation for continuous variables,
                                                                           complete cases for 5% weight loss
                                                                           criterion analysis
----------------------------------------------------------------------------------------------------------------
* We originally excluded any types of beverages that had growth promotion as a function, but the unfortified
  beverage met our original inclusion criteria and is included in this analysis. SSB, Sugar-sweetened Beverage.

Figure 2 


          Observed (30, 34, 40-42, 62) versus theoretical 
        (63) weight gain effect of mandatory sugar-sweetened 
        beverage (SSB) consumption.
          Notes: For observed values on the Y axis, weight change was 
        determined by the change of those drinking more SSBs minus 
        those drinking less. The X axis was determined by multiplying 
        the added kcal per day times the duration of the study divided 
        by 1,000. Fit lines were generated by setting the origin to 
        zero and by using the linear regression (least squares) options 
        in Microsoft' Excel. The theoretical values (round 
        markers) were generated by entering mean baseline values for 
        each study sample into the NIDDK body weight simulator 
        (63) and adding the same number of calories per day 
        for the same number of days as reported in the 
        studies.(30, 34, 40-42, 62) Activity settings in the 
        simulator were at the lowest level of sedentary and no activity 
        or dietary changes over the study duration were entered into 
        the simulator. Observed data represent an average energy 
        compensation rate of 85% (range = 57-110% compensation).
Figure 3


          Forest plot comparing studies of added sugar-sweetened 
        beverage (SSB) consumption.
          Note: R square values were calculated from the overall 
        standardized mean difference estimate (d) per the method found 
        in.(64)

    Study heterogeneity in reduction studies. Because the heterogeneity 
statistic was significant (Fig. 4) in the reduction studies in both 
weight groups, we evaluated which study exerted the most influence for 
its effects on the overall SMD.(46) Exclusion of this study 
resulted in a non-significant heterogeneity statistic (x\2\ 
(6) = 10.15, P = 0.12, I\2\ = 41%) and an increased overall 
SMD of 0.13 (95% CI: 0.04 to 0.22). These analyses shifted the overall 
statistics by relatively small amounts when considering the observed 
shifts in body weight among the analysis groups.
    Interpreting the magnitude of effects. At this juncture, it may be 
helpful to express the estimated effect sizes for SSB reduction on BMI 
in some additional metrics which may ease interpretation. One such 
metric is the probability that a randomly selected person from a 
hypothetical population in which SSB reduction was implemented will be 
better off (with respect to BMI) than a randomly selected person from a 
hypothetical population that is the same in all ways except that SSB 
reduction has not been implemented. Without intervention, the 
probability is 0.50 that a person from one population weighs more than 
a person from the other population. After the interventions included in 
our analysis, these probabilities would change slightly. The 
probability that a randomly selected person from the reduced SSB 
population will have lower BMI than a person randomly selected from the 
control population would be 0.52. The probability that a randomly 
selected overweight person from the reduced SSB population will have a 
lower BMI than an overweight person randomly selected from the control 
population would be 0.57.
Figure 4 


          Forest plot comparing studies of reduced sugar-sweetened 
        beverage (SSB) consumption; subjects in all weight categories 
        included.
          Note: R square values were calculated from the overall 
        standardized mean difference estimate (d) per the method found 
        in.(64)
Figure 5


          Forest plot comparing studies of reduced sugar sweetened 
        beverage (SSB) consumption; only subjects overweight/obese at 
        baseline included.
           R square values were calculated from the overall 
        standardized mean difference estimate (d) per the method found 
        in.(64)

    Another way to place the effect sizes in perspective is to consider 
the g\2\ metric shown in Figs 3-5. Increasing consumption of SSBs 
explains 1.92% of the variance in body weight or BMI change. Reducing 
consumption of SSBs in persons of all weight categories explains 0.09% 
of the variance in body weight or BMI change. Among persons who are 
overweight or obese at baseline, reducing the consumption of SSBs 
explains 1.54% of the variance in body weight or BMI change. It is 
possible to apply other methods such as risk analysis for evaluating 
potential effects on population levels of obesity,(49) but 
that is beyond the scope of the present analysis.
Additional Considerations
    Having demonstrated that, although the conjecture that decreasing 
SSB consumption will decrease obesity and obesity-related diseases is 
reasonable, the pertinent data testing the hypothesis are equivocal 
(i.e., the pooled results are nearly but not quite statistically 
significant), we now address several related questions.
If the data are as weak as we have shown, why do some members of the 
        public and the scientific community seem to perceive that the 
        proposition has been proven?
    We suggest three major reasons for this confusion.
Emotion-Raising Language
    Emotion-raising language has often been used in discussions of SSBs 
and obesity. Some authors have used words like `plague',(50) 
`toxic',(51-52) `hazardous' (4, 53) and `deadly' 
(4, 54) when describing SSBs or the sugars they contain and 
have tried to promote perceived connections between SSB marketers and 
the worst behaviour of tobacco marketers.(55) Although such 
words may help to advance an agenda,(56) they do not educate 
or inform the public. Moreover, they likely raise emotions and impair 
logical reasoning.(57) As Kersh and Morone (56) 
wrote, `Scientific findings never carry the same political weight as 
does a villain threatening American youth. If critics successfully cast 
portions of the industry in this way, far-reaching political 
interventions are possible, even likely. When an industry becomes 
demonized, plausible counter-arguments (privacy, civil liberties, 
property rights, and the observation that ``everyone does it'') begin 
to totter.'
Figure 6


          Comparison of weight gain attributed to consumption of sugar-
        sweetened beverages for 1 year from various sources.
          Note: For the Haub study, the weight change shown above is 
        adjusted by subtracting the control group weight change.
          * Body mass index of 27.8 kg m^\2\ (NHANES 2010 50th 
        percentile for both men and women in the United States 
        (65) entered into NIDDK body weight 
        simulator.(63)
          + (66) # (67) $ (68).
Distortion of Scientific Information
    A second factor that has likely contributed to misperceptions in 
this area is the distortion of scientific information by some authors 
and commentators. Table 2 lists some of the types of distortion that 
have occurred with quantitative or anecdotal documentation. Figure 6 
depicts disparities in projected versus actual outcomes of the effects 
of added SSBs over 1 year. Clearly, such practices mislead and have 
likely contributed to misperceptions in the scientific and lay 
communities about the strength of the evidence regarding the 
proposition debated here.
The Mere Exposure Effect
    The final factor that we believe has led to the erroneous 
perception that the evidence showing that the proposition of this 
debate has been unequivocally proven is the `mere exposure effect.' The 
mere exposure effect is the label psychologists use for the phenomenon 
that the more a person is exposed to an idea, the more they come to 
like and accept it. As the Nobel Prize-winning economist Daniel 
Kahneman described, `A reliable way to make people believe in falsehood 
is frequent repetition, because familiarity is not easily distinguished 
from truth. Authoritarian institutions and marketers have always known 
this fact. But it was psychologists who discovered that you do not have 
to repeat the entire statement of a fact or idea to make it appear 
true'.(58)
    The number of articles on SSBs and obesity and the number of 
statements that SSBs are especially problematic in obesity are 
extraordinary, especially in comparison to the modest amount of 
probative data.(3) Thus, opinions about SSBs may have been 
offered so often that these opinions have become accepted as fact by 
many in the scientific community, media and lay public.

               Table 2  Some types of Distortion of Information that Have Occurred Regarding Sugar-Sweetened Beverages (SSBs) and Obesity
--------------------------------------------------------------------------------------------------------------------------------------------------------
            Type of distortion                  Where it occurs                      Documentation of occurrence                         Comments
--------------------------------------------------------------------------------------------------------------------------------------------------------
Papers citing original randomized          In the scientific peer-   Cope and Allison (14) documented in a quantitative          This is not a criticism
 controlled trials (RCTs) that              reviewed literature       analysis of the literature that this exaggerated            of the original RCTs,
 investigated the effect of SSB reduction                             reporting was the norm rather than an exception.            but rather the manner
 on weight exaggerated the extent of the                                                                                          in which subsequent
 evidence supporting a beneficial effect                                                                                          authors cite them.
Association studies are described by       In the scientific peer-   `A new study . . . suggests a key way to reduce childhood   `Cravings' were not
 using language that indicates a cause      reviewed literature       obesity could be to limit your child's salt intake. The     mentioned in the
 and effect relationship has been found     [e.g.,(69)], in           study looked at 4,000 children in Australia and found       published study,(74)
                                            government-sponsored      kids who ate more salt also had more cravings for sugary-   which did not
                                            newsletters               sweetened drinks like soda and juice.' (72)                 overstate the
                                            [e.g.,(70)], and in                                                                   findings, but were
                                            mass media articles                                                                   exaggerated in media
                                            (71	73)                                                                               coverage. This
                                                                                                                                  misleading practice is
                                                                                                                                  common in the obesity
                                                                                                                                  field overall.(75)
Public statements that contradict          Communications from       In 2010, [T]he New York Times ran an article in which,      See Figure 6 for
 available evidence                         public health agencies    through e-mails obtained under the Freedom of Information   details and specific
                                                                      Act, they showed that the New York City (NYC) Department    references.
                                                                      of Health was knowingly making exaggerated statements
                                                                      about the amount of weight gain expected from drinking
                                                                      SSBs. Even after this expose (September 2012), the NYC
                                                                      Department of Health made even more exaggerated and
                                                                      evidence-contradicted statements about the amount of
                                                                      weight gain expected from drinking SSBs.
Changing what is considered the primary    In the scientific peer-   An example (34) of this occurred in an RCT published in     This does not conform
 endpoint or analysis in an RCT             reviewed literature       the American Journal of Clinical Nutrition (AJCN). In the   to the CONSORT
                                                                      paper, the authors state `Our main aim was to test the      guidelines for
                                                                      hypothesis that sucrose-sweetened cola increases ectopic    publishing RCTs to
                                                                      fat including VAT4, total body fataccumulation, and         which authors
                                                                      metabolic risk factors . . . ,' whereas the registration    publishing in AJCN are
                                                                      in ClinicalTrials.gov states `Primary Outcome Measures:     expected to adhere.
                                                                      Body Weight; MR spectroscopy; MRI; DEXA scan.' Similarly,
                                                                      in ClinicalTrials.gov, the title of the trial is `Effect
                                                                      of Carbonated Soft Drinks on the Body Weight,' whereas in
                                                                      the article the title is `Sucrose-sweetened beverages
                                                                      increase fat storage in the liver, muscle, and visceral
                                                                      fat depot: a 6-mo randomized intervention study.' The
                                                                      fact that there was no significant effect on weight was
                                                                      not mentioned in the abstract of the paper.
Conclusion statements from paper do not    In peer-reviewed papers,  An example from the peer-reviewed literature occurred in a  Although a trained
 match the results                          press releases, and       paper in AJCN (35) in which the results section of the      scientist carefully
                                            mass media interviews     abstract stated `Mean (RSEM) weight losses at 6 months      reading the original
                                                                      were ^2.5 R0.45% in the DB group, ^2.03 R0.40% in the       papers will understand
                                                                      Water group, and ^1.76 R0.35% in the AC group; there were   the results,
                                                                      no significant differences between groups.' Yet, the        journalists,
                                                                      conclusion section of the abstract stated `Replacement of   regulators, clinicians
                                                                      caloric beverages with non-caloric beverages as a weight-   and scientists who
                                                                      loss strategy resulted in average weight losses of 2% to    only rapidly read an
                                                                      2.5%.' Given the non-significant result, it does not seem   abstract are likely to
                                                                      justifiable to state there is any weight loss as a result   be misled.
                                                                      of the treatment. Even if point estimates were being
                                                                      provided in a merely descriptive manner, the unbiased
                                                                      estimates of treatment effects in an RCT are the control-
                                                                      subtracted means, not the raw means in the treatment
                                                                      group. Examples from press releases and media interviews
                                                                      can be found in (14, 76) and in these sources.(77,78)
Publication bias                           In the scientific peer-   Cope and Allison (14) showed that in observational          This is why we wrote
                                            reviewed literature       epidemiologic studies of the association of SSB             earlier in this paper
                                                                      consumption and obesity, a standard test of publication     that the observed
                                                                      bias was significant, suggesting that investigators are     magnitude of
                                                                      more likely to publish positive statistically significant   association is likely
                                                                      findings than to publish null findings.                     biased upwards.
                                                                                                                                  Interestingly, Cope
                                                                                                                                  and Allison found that
                                                                                                                                  this publication bias
                                                                                                                                  seemed to occur among
                                                                                                                                  non-industry-funded
                                                                                                                                  authors and not among
                                                                                                                                  industry-funded
                                                                                                                                  authors.
--------------------------------------------------------------------------------------------------------------------------------------------------------


    Table 3  Quotations Illustrating that Others Do Not Believe the Benefits of Interventions Aimed at SSB Reduction on Weight Have Been Established
--------------------------------------------------------------------------------------------------------------------------------------------------------
        Person(s) or body offering statement                                              Statement                                          Reference
--------------------------------------------------------------------------------------------------------------------------------------------------------
United States Department of Agriculture Dietary      `Thus, there are mixed results on this topic. RCTs report that added sugars are not            (12)
 Guidelines Advisory Committee                        different from other calories in increasing energy intake or body weight.
                                                      Prospective studies report some relationship with SSB and weight gain, but it is
                                                      not possible to determine if these relationships are merely linked to additional
                                                      calories, as opposed to added sugars per se. The systematic reviews in this area
                                                      are also inconsistent, probably based on different measures used to determine
                                                      added sugars intake or intake of SSB.' [We should] `Conduct well-controlled and
                                                      powered research studies testing interventions that are likely to improve energy
                                                      balance in children at increased risk of childhood obesity, including dietary
                                                      approaches that reduce . . . sugar-sweetened beverages' [because] `very few solid
                                                      data are available on interventions in children.'
European Food Safety Authority                       `The Panel concludes that a cause and effect relationship has not been established             (79)
                                                      between total sugar intake and body weight gain, and that a cause and effect
                                                      relationship has not been established between the consumption of foods and
                                                      beverages in which sugars have been replaced by intense sweeteners and
                                                      contribution to the maintenance or achievement of a normal body weight.'
Lisa Te Morenga, Simonette Mallard, Jim Mann         `Trials in children, which involved recommendations to reduce intake of sugar                  (80)
                                                      sweetened foods and beverages, had low participant compliance to dietary advice;
                                                      these trials showed no overall change in body weight.'
German Nutrition Society                             `From two of the four available meta-analyses the conclusion is drawn that                     (81)
                                                      increased consumption of sugar-sweetened beverages in children and adolescents is
                                                      associated with a higher risk of obesity. In contrast, another meta-analysis
                                                      judges the effect as almost zero. The cohort studies published since then verify
                                                      this risk-increasing effect only in part. The most recent meta-analysis concludes
                                                      that the risk-increasing effect is limited to individuals with initially already
                                                      increased BMI or existing overweight, respectively.'
Thomas Baranowski                                    `Another concern is the behavior or behaviors targeted for change. Many obesity                (82)
                                                      prevention interventions have targeted increasing fruit and vegetable intake and
                                                      decreasing sweetened beverage intake. Systematic reviews, however, showed no
                                                      consistent evidence that increased fruit and vegetable intake protected against
                                                      obesity or that sweetened beverage intake contributed to it.'
Joint statement from American Heart Association and  `At this time, there are insufficient data to determine conclusively whether the               (83)
 the American Diabetes Association                    use of NNS [non-nutritive sweeteners] to displace caloric sweeteners in beverages
                                                      and foods reduces added sugars or carbohydrate intakes, or benefits appetite,
                                                      energy balance, body weight, or cardiometabolic risk factors.'
--------------------------------------------------------------------------------------------------------------------------------------------------------

Are we alone in the view that a beneficial effect of SSB reduction on 
        obesity has not been demonstrated?
    In a word, no. As the quotations in Table 3 reveal, our views are 
concordant with those of other individual scientists and authoritative 
expert panels.
What would it take to shift the balance of evidence?
    In a possibly apocryphal interchange, a devotee of Karl Popper's 
philosophy of science once challenged the great mathematical geneticist 
J.B.S. Haldane to specify what it would take to change his views about 
the validity of evolutionary theory. Haldane reportedly retorted 
`Fossil rabbits in the Precambrian!' Although a poetic retort, Haldane 
was effectively specifying objective empirical evidence that would be 
sufficient for him to change his view, something any scientist 
addressing empirical questions should be prepared to do.
    In the debate at The Obesity Society Meeting (September 20, 2012), 
the senior author [DBA] stated:

          `The day that multiple RCTs are published that

     are well designed, executed, and analyzed;

     show statistically significant outcomes in preplanned 
            analyses of the total randomized sample on measures of 
            total body weight, BMI, or total body fat and clearly 
            support the value of reducing SSBs; and

     are sufficient in inferential weight to outweigh the 
            existing RCT data;

          I will be delighted to modify my opinion.'

The day after the debate (September 21, 2012), two new RCTs were 
published.(29, 33) These two publications together met some 
(but not all) of the criteria specified above as we discussed earlier. 
Most notably, their collective evidential weight moved the integrated 
meta-analytic estimate for the effects of SSB reduction very close to 
the border of the conventional 0.05 level of statistical significance. 
For this reason, we believe that these two new studies can be described 
as `tilting the needle' in the direction of demonstrating the obesity-
reducing benefit of SSB reduction, but that the data remain equivocal. 
Nevertheless, we remain open-minded that future RCTs (and according to 
ClinicalTrials.gov some will be forthcoming) may fulfil the criteria 
above and offer unequivocal support for the proposition.
    We also suggest that the following approaches can increase the 
transparency of, and confidence in, RCTs in this area: (i) registering 
all RCTs in advance in ClinicalTrials.gov; (ii) making the raw data 
from all RCTs publicly available for common and open analyses, 
regardless of the source of funding; (iii) providing documentation via 
ClinicalTrials.gov as to which analyses are (were) pre-planned; and 
(iv) publishing all results regardless of outcome. These are laudable 
practices in all situations, but especially important in an area that 
has become so contentious.
How does the strength of evidence for conclusions relate to support for 
        actions?
    As we mentioned earlier, we are not addressing whether any 
particular policy or programme should or should not be implemented. 
Rather, our sole purpose has been to present a synthesis of the 
currently available literature that provides an estimate of the degree 
of evidence for the debate proposition. Moreover, it is important to 
note that our paper assessed the evidence for effect of reducing SSB 
consumption, which should not be conflated with the effects of 
particular policies (e.g., taxes, bans, advertising campaigns, etc.) 
intended to reduce SSB consumption. The effects of any such policies 
represent a different question and not one for which we have evaluated 
the evidence.
    The question of whether the available evidence is sufficiently 
strong to justify a particular action is a subjective one subject to 
societal perceptions, values, goals and the plausibility of unintended 
consequences.(59-60) This is illustrated by quotations from 
two authoritative sources on this point as food for thought:

          `Since taking office, the President has emphasized the need 
        to use evidence and rigorous evaluation in budget, management, 
        and policy decisions to make government work effectively. . . . 
        Where evidence is strong, we should act on it. Where evidence 
        is suggestive, we should consider it. Where evidence is weak, 
        we should build the knowledge to support better decisions in 
        the future.' (61)
          `On fair evidence we might take action on what appears to be 
        an occupational hazard, e.g., we might change from probably 
        carcinogenic oil to a non-carcinogenic oil in a limited 
        environment and without too much injustice if we are wrong. But 
        we should need very strong evidence before we made people burn 
        a fuel in their homes that they do not like or stop smoking the 
        cigarettes and eating the fats and sugar that they do like.' 
        (1)
Conclusions
    Our updated meta-analysis shows that the currently available 
randomized evidence for the effects of reducing SSB intake on obesity 
is equivocal. Even if statistical significance is ignored, the point 
estimates of effects on BMI reduction are small, accounting for only 
1.5% of the variance observed in those who were overweight at baseline. 
Therefore, we conclude that the debate proposition cannot be supported 
at this time. Of course, absence of evidence is not evidence of 
absence. The lower limit of the confidence interval around the 
estimated effect of SSB reduction is very close to the border of 
statistical significance. It is certainly possible that additional, 
larger or otherwise stronger studies will in the future provide clear 
and convincing evidence that lowering SSB consumption will reduce 
obesity and obesity-related disease prevalence. We are certainly not 
arguing against the common-sense recommendation that for individuals 
who wish to lose weight and who presently drink large amounts of SSBs, 
reducing intake of these and other sources of energy seems wise.
    We greatly respect our debate opponent, Dr. Hu, for addressing 
these issues in a manner that is both thoroughly scientific and equally 
collegial. We are hopeful that this debate may be seen not only as a 
careful consideration of the evidence regarding SSBs and obesity, but 
also as an exemplar of and call to a more informed, unexaggerated, 
open-minded, rational and civil dialogue on the many public health 
issues around obesity that, like SSB-related issues, have become so 
contentious.

 
 
 
Author Contributions
 
    KAK performed an updated systematic review, reviewed papers for
 inclusion criteria, extracted data from papers, wrote summaries of new
 studies included in appendix, checked meta-analysis calculations,
 assessed risk of bias for newly included studies, generated tables,
 generated figures and wrote a significant portion of the text. KDK
 extracted data from papers, analysed supplemental data received from
 authors, generated new meta-analysis statistics and verified prior data
 reported. JMS reviewed papers for inclusion criteria, assessed risk of
 bias for newly included studies, wrote summaries of new studies
 included in appendix and reviewed and edited text. DBA conceived of the
 project scope, developed debate arguments, directed meta-analysis
 methods, reviewed papers for inclusion criteria, edited and wrote a
 significant portion of the text.
 
Conflict of Interest Statement
    In the last 36 months, Dr. Allison has received consulting fees from
 Kraft Foods. The University of Alabama at Birmingham has received gifts
 and grants from multiple organizations including but not limited to The
 Coca-Cola Company, PepsiCo, Red Bull and Kraft Foods. Drs. Kaiser,
 Keating and Shikany have no competing interests to report.
 
Ethical Approval
 
    Not required.
 
Acknowledgements
 
    Supported in part by NIH grant P30DK056336. The opinions expressed
 are those of the authors and not necessarily those of the NIH or any
 other organization with which the authors are affiliated. This paper is
 based on a debate held at The Obesity Society 2012 Annual Meeting. The
 authors thank Sigrid Gibson; Drs. Michelle Bohan Brown, Richard
 Forshee, Richard Mattes and Douglas Weed for their suggestions on
 drafts of this manuscript. The authors also thank Dr. Marc Reitman for
 the use of Fig. 1. The authors are also grateful to those who kindly
 responded to our request for additional data about their studies: Dr.
 Valentine Njike, Dr. David Katz, Dr. Mario Vaz, Dr. Tinku Thompson, Ms.
 Janne de Ruyter, Dr. Sonia Hernandez-Cordero and Dr. Martijn Katan.
 
Supporting Information
 
    Additional Supporting Information may be found in the online version
 of this article, http://dx.doi.org/10.1111/obr.12048.
    Figure S1. Study screening and selection process of new studies
 added since the original meta-analysis (21)
    Figure S2. Methodological quality summary; review authors' judgments
 about each methodological quality item for each included study (1	6,
 20, 25	32)
    Figure S3. Funnel plot of published studies of added sugar-sweetened
 beverage (SSB) consumption (3	4, 6, 27, 30, 32)
    Figure S4. Funnel plot of published studies on reduced sugar-
 sweetened beverage (SSB) consumption in subjects of all weight
 categories (1	2, 5, 20, 26, 28, 31)
    Figure S5. Funnel plot of published studies of reduced sugar-
 sweetened beverage (SSB) consumption in subjects overweight/obese at
 baseline (2, 5, 20, 26, 31)
    Table S1. Unstandardized effect sizes of new studies assessing the
 effects of adding mandatory SSB consumption to persons diets
    Table S2. Standardized effect sizes from new studies assessing the
 effect of attempting to get people to reduce or eliminate SSB
 consumption on body composition/adiposity indicators
    Table S3. Standardized effect sizes from new studies assessing the
 effect of attempting to get people to reduce or eliminate SSB
 consumption on body mass index (BMI) only for subjects overweight/obese
 at baseline or above the top of tertile of baseline BMI
    Appendix S1. Updated literature review, selection and data
 extraction methods
 


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                              attachment 9
Liquid Calories, Energy Compensation, and Weight: What We Know and What 
        We Still Need To Learn
Invited Commentary
David B. Allison *
---------------------------------------------------------------------------
    * Office of Energetics, Nutrition Obesity Research Center, 
University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA, e-
mail [email protected].
    doi:10.1017/S0007114513003309.
---------------------------------------------------------------------------
British Journal of Nutrition (2014), 111, 384-386
' The Author 2013
(First published online 28 October 2013)

    Roughly 10,000 years ago, sugar was first domesticated in New 
Guinea. Roughly 8,000 years ago, it was transplanted to India. Sometime 
around the seventh century, cultivation and some industrial production 
began in southern Europe, and the crusades subsequently acquainted more 
Europeans with sugar imported from Arab lands. Until the sixteenth 
century, sugar was often viewed by Europeans as having medicinal 
properties. Colonisation of the New World led to mass production and 
distribution of sugar as a major foodstuff.(1-5) By 1713, a 
writer in a scholarly journal was extolling the health virtues of high 
levels of sugar consumption, including in beverages.(6) In 
1893, Harley (7) conducted self-experiments and concluded 
that consumption of 250 g (approximately 4184 kJ or approximately 1000 
kcal) of sugar greatly increased muscular work capacity. In 1899, a 
controlled trial involving soldiers reported that those given a ration 
of sugar were in better health, felt more vigorous and gained more 
weight (presumably judged to be a good thing at the 
time).(8) As the century turned, Gardner (9) 
described sugar as a nutritional necessity that increased the health 
and vigour of populations. Yet, the positive health halo of sugar could 
not last. A generation later, authors of scientific papers did write 
about `The social problem growing out of the overconsumption of sugar' 
and described school-based programmes to teach children to consume less 
sugar.(10)
    Sugar consumed in liquid form has come to be seen by some as 
especially deserving of scrutiny. In 1990, Tordoff & Alleva 
(11) published seminal trial results showing that persons 
required to consume additional sugar in the form of a beverage gained 
more weight than did a control group given a non-energetic beverage. 
After 13 years, suspicion was increasing that metabolisable energy, 
perhaps especially sugar, consumed as liquids promoted less satiety, 
less energy compensation and more weight gain than did the same energy 
consumed in solid form.(12) The topic has become 
controversial to say the least,(13) and there is substantial 
evidence that the strength of the supporting data has often been 
exaggerated and distorted.(14,15)
    Newspaper articles offer statements such as `People who drink 
sugary soft drinks do not appear to compensate by reducing calories 
somewhere else in their diets, so they tend to pack on extra pounds' 
(16) and `Study after study has shown that like experimental 
animals, people do not compensate for extra liquid calories by eating 
less food'.(17) This concept that people do not adjust their 
energy intake (or expenditure) to compensate for energy consumed as 
liquids is at the heart of the matter. Yet, is it true? Although 
opinions on matters of energy compensation in response to various forms 
of sugar intake and/or liquid energy have been offered for over 70 
years,(18,19) convincing data on these issues have been 
scarce.
    In this issue of the British Journal of Nutrition, Reid, et 
al.,(20) offer a new and valuable piece of evidence on this 
question. In a study of obese adult women, those consuming sugar in 
liquid form at a level of 1,800 kJ (approximately 430 kcal) per d 
gained far less weight than expected and no more weight than did women 
in a control group drinking zero-energy beverages. The study has 
several strengths. It was a controlled trial that was run for long 
enough to observe weight changes and that was at least partially 
conducted in a blinded fashion. It also has several limitations, 
including a modest sample size, incomplete blinding and the fact that 
it was not strictly randomised. I will not belabour those points here 
as Reid and colleagues discuss them in their article. It should also be 
noted that the study concerns only adult women and cannot necessarily 
tell us about the effects in men or children.
What does the study show?
    The study's essential finding concerns the question of compensation 
for liquid energy. The sucrose group gained no appreciable weight. This 
shows that over an extended period, at least in conditions similar to 
those of this study, women do compensate for additional energy consumed 
in the form of a sugar-sweetened beverage (SSB). Moreover, that the 
weight gained in the sucrose group was significantly less than that 
predicted by an established mathematical model based on the amount of 
energy consumed in the form of SSB further indicates that the vast 
majority of the energy consumed was compensated for. Reid, et al., 
state that `Obese women who received 1,800 kJ sucrose per day in soft 
drinks for 4 weeks gained a mean of 1.72 kg less than predicted by the 
model.' Interestingly, the model predicted a total weight gain for a 
woman with the average characteristics listed in Reid, et al.,'s Table 
1 of only about 1.8 kg.
Are the findings consistent with those of other studies?
    Yes. Kaiser, et al.,(15) meta-analysed other studies in 
which adults were required to consume additional energy in SSB in 
randomised controlled trials (RCT), and found that, on average, such 
required SSB consumption did indeed cause weight gain, but that the 
amount of weight gained was far less than \1/2\ the amount one would 
have predicted to be gained by use of the same mathematical model used 
by Reid, et al. (see Kaiser, et al.,'s Fig. 2). This indicates that, as 
Reid, et al., found, over extended periods of time, the majority of the 
energy consumed as SSB is indeed compensated for.
Do the findings inform us about the effects of reducing sugar-sweetened 
        beverage consumption among adult women?
    No. Though tempting, we cannot necessarily infer the effects of 
reducing SSB consumption from studies of the effects of increasing SSB 
consumption. That said, as Kaiser, et al.,(15) reported, no 
RCT of adults reported to date has found a statistically significant 
effect of reducing SSB consumption on weight.
Do the findings inform us about the differential effects (if any) of 
        consuming liquid v. solid energy on weight?
    No. The results of Reid, et al., only show what happens with SSB. 
From these data alone, we have no way of knowing whether the same 
results would have been obtained if the women were required to consume 
1,800 kJ of food in some solid form. Returning to the literature at 
large, there is evidence from a recent meta-analysis that in short-term 
(typically single-day) studies with food intake as the outcome, liquid 
energy is less well compensated for than is solid 
energy.(21) Yet, we cannot assume that individuals will not 
adapt to dietary changes over time. Long-term effects on weight cannot 
be reliably inferred from short-term effects on food intake. Indeed, to 
my knowledge, there are only two human RCT comparing the effects of 
liquid v. solid foods on weight over an extended period of time, and 
neither found a statistically significant difference between the liquid 
and solid conditions when the entire samples were 
analysed.(22-23)
    In conclusion, what we know from the overall literature is that 
when adults are required to consume additional energy in the form of 
SSB, on average, they gain some weight. What we also know from the 
overall literature and this new study is that, on average, adults gain 
far less weight than they would be expected to gain if they did not 
compensate. Thus, people clearly do compensate for liquid energy, 
although they do so incompletely. What we do not know, despite all the 
drama and vituperation surrounding SSB, is whether, over extended 
periods of time, people compensate any differently for liquid v. solid 
energy. It is high time we learned.

 
 
 
Acknowledgements
 
    The present work was supported in part by National Institutes of
 Health (NIH) grant P30DK056336. The opinions expressed are those of the
 author and not necessarily those of the NIH or any other organisation.
    The author received grants and gifts to his university and
 consulting fees from multiple for-profit and not-for-profit
 organisations with interests in obesity, sugar and SSB.
 


                               References
 
 
 
    1. Anonymous (1853) History of sugar. The Illustrated Magazine of
 Art, vol. 2, no. 2, p. 147. http://www.jstor.org/stable/20538093
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 Sweetness and Power: The Place of Sugar in Modern History by Sidney W.
 Mintz. Economic and Political Weekly vol. 22, no. 33 (15 August 1987),
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    3. Levi L. (1864) On the Sugar Trade and Sugar Duties. A Lecture
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 (accessed August 2013).
    4. U.S. Department of Agriculture, Economic Research Service (1971)
 A History of Sugar Marketing. Agriculture Economic Report No. 197.
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    5. Galloway J.H. (1977) The Mediterranean sugar industry. Geographic
 Rev. 67, 177-194. http://www.jstor.org/stable/214019 (accessed August
 2013).
    6. Slare F. (1713) Part of a letter from Dr. Fred Slare to Dr. Hans
 Sloane; concerning a person who had a new set of teeth after 80 years
 of age; with some observations upon the virtues and properties of
 sugar. Phil. Trans. R. Soc. (1683-1775) 28, 273-274.
    7. Harley V. (1893) Sugar as a food in the production of muscular
 work. Proc. R. Soc. Lond. 54, 480-487.
    8. Anonymous (1899) Sugar as a ration. Br. Med. J. 1, 105.
    9. Gardner H.W. (1901) The dietetic value of sugar. Br. Med. J. 1,
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    10. Sollins I.V. (1930) Sugar in diet: an experiment in instruction
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    11. Tordoff M.G. & Alleva A.M. (1990) Effect of drinking soda
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    12. Almiron-Roig E., Chen Y. & Drewnowski A. (2003) Liquid calories
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    13. Slavin J. (2012) Beverages and body weight: challenges in the
 evidence-based review process of the Carbohydrate Subcommittee from the
 2010 Dietary Guidelines Advisory Committee. Nutr. Rev. 70, Suppl. 2,
 S111-S120.
    14. Cope M.B. & Allison D.B. (2010) White hat bias: examples of its
 presence in obesity research and a call for renewed commitment to
 faithfulness in research reporting. Int. J. Obes. (Lond) 34, 84-88.
    15. Kaiser K.A., Shikany J.M., Keating K.D., et al. (2013) Will
 reducing sugar-sweetened beverage consumption reduce obesity? Evidence
 supporting conjecture is strong, but evidence when testing effect is
 weak. Obes. Rev. 14, 620-633.
    16. Hellmich N. (2007) Soda drinkers consume more calories. USA
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    17. Brody J.E. (2010) A tax to combat America's sugary diet. New
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 (accessed August 2013).
    18. Anonymous (1942) Sugar rationing called a ``Godsend'' to
 national health. Science News-Letter vol. 41, no. 11 (14 March 1942),
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    19. Anonymous (1944) Advice given to go easy on use of chocolate
 milk. Science News-Letter vol. 45, no. 25 (17 June 1944), p. 398.
    20. Reid M., Hammersley R., Duffy M., et al. (2014) Effects on obese
 women of the sugar sucrose added to the diet over 28 days, a quasi-
 randomised, single-blind, controlled trial. Br. J. Nutr. 111, 563-570.
    21. Almiron-Roig E., Palla L., Guest K., et al. (2013) Factors that
 determine energy compensation: a systematic review of preload studies.
 Nutr. Rev. 71, 458-473.
    22. DiMeglio D.P. & Mattes R.D. (2000) Liquid versus solid
 carbohydrate: effects on food intake and body weight. Int. J. Obes.
 Relat. Metab. Disord. 24, 794-800.
    23. Houchins J.A., Burgess J.R., Campbell W.W., et al. (2012)
 Beverage vs. solid fruits and vegetables: effects on energy intake and
 body weight. Obesity (Silver Spring) 20, 1844-1850.
 

                             attachment 10
Corporate Funding of Nutrition Research and Unjustified Conclusions
JAMA Internal Medicine, May 2016, Volume 176, Number 5

    To the Editor In her Viewpoint about corporate funding of food and 
nutrition research, Dr Nestle criticizes the food industry and 
scientists who associate with it.\1\
    Dr. Nestle claims that scientists who receive industry-derived 
research grants ``often fail to realize that food-industry funding may 
affect their work.''.\1\ (p. 13) She cites newspaper 
articles that ``illustrate the concerns about biases introduced by 
industry funding.'' \1\ (p. 13) She also cites reports 
2-3 showing that there are relatively few studies funded by 
industry whose results are contrary to the funders' interest and 
discusses her work on the subject including reference to her Food 
Politics blog.\4\
    The study by Massougbodji, et al.,\2\ also determined that the 
quality of the methods of the studies reviewed did not explain the 
orientation of the authors' conclusions, nor was there any relationship 
between the source of funding and the overall quality of the studies 
examined. The study by Lesser, et al.,\3\ did not examine any aspect of 
the studies that were reviewed other than funding source. The newspaper 
stories did not describe any flaw in the research of the scientists 
profiled. In addition, the authors of a great number of the presumably 
tainted industry-sponsored studies discussed on the blog written by Dr. 
Nestle \4\ explicitly stated that the funding source was not involved 
in the design, conduct, data analysis and interpretation, or manuscript 
preparation. Although Dr. Nestle also states that the quality of 
dietary advice is adversely affected by the source of research funds, 
many believe that the real problem is the overall poor quality of 
nutrition research.\5\ Before guilt by association is established, 
criticisms by Dr. Nestle deserve much more analysis.
    It would certainly be helpful, if not essential, for Dr. Nestle or 
others to show that industry-funded studies have more design flaws, 
inappropriate analyses, or unjustified conclusions relative to similar 
studies funded by other sources. Furthermore, in addition to financial 
conflicts of interest, there are nonfinancial conflicts resulting from 
career self-interest or unbounded intellectual passion that can be just 
as worrisome. Conflicts of interest in science can affect anyone, and 
are relevant to proponents of any point of view.

Richard Kahn, Ph.D.

 
 
 
    Author Affiliation: Department of Medicine, University of North
 Carolina, School of Medicine, Chapel Hill, North Carolina.
    Corresponding Author: Richard Kahn, PhD, Department of Medicine,
 University of North Carolina, School of Medicine, Chapel Hill, NC 27599-
 7005 ([email protected]).
    Conflict of Interest Disclosures: None reported.
    Additional Information: Dr. Kahn served as the Chief Scientific and
 Medical Officer of the American Diabetes Association.
 


                              [References]
 
 
 
    1. Nestle M. Corporate funding of food and nutrition research:
 science or marketing. JAMA Intern. Med. 2016; 176(1): 13-14.
    2. Massougbodji J., Le Bodo Y., Fratu R., DeWals P. Reviews
 examining sugar-sweetened beverages and body weight: correlates of
 their quality and conclusions. Am. J. Clin. Nutr. 2014; 99(5): 1096-
 1104.
    3. Lesser L.I., Ebbeling C.B., Goozner M., Wypij D., Ludwig D.S.
 Relationshipbetween funding source and conclusion among nutrition-
 related scientific articles. PLoS Med. 2007; 4(1): e5.
    4. Nestle M. Food Politics Blog. http://www.foodpolitics.com/.
 Accessed March 2, 2016.
    5. Ioannidis J.P. Implausible results in human nutrition research.
 BMJ. 2013; 347: f6698.
 

    In Reply: Dr. Kahn requests evidence that nutrition research funded 
by food companies is of lesser quality than studies funded by 
independent agencies or performed by investigators with nonfinancial 
conflicts of interest. Concerns about such issues are relatively 
recent; few published studies address them directly. Instead, concerns 
about industry sponsorship of nutrition research derive from 
comparisons with the results of studies of funding by tobacco, 
chemical, drug, or medical device companies. This research typically 
finds industry-sponsored studies to report results more favorable to 
the products of the sponsor than studies not funded by industry. It 
identifies subtle rather than substantive differences in the quality of 
this research; industry-funded studies are more likely to underreport 
unfavorable results and interpret neutral results more positively.\1\ 
When results are negative, they are less likely to be published.\2\
    Between March 2015 and March 2016, I identified 166 industry-funded 
nutrition research studies and posted and discussed them on my blog.\3\ 
Of these, 154 reported results favorable to the interest of the 
sponsor; only 12 reported contrary results. The few studies 
systematically examining the influence of industry funding on nutrition 
research tend to confirm results obtained from other industries. For 
example, a systematic review comparing industry-funded and nonindustry-
funded trials of probiotics in infant formula reported no association 
of funding source with research quality. Industry-funded studies, 
however, seemed more likely to report favorable conclusions unsupported 
by the data.\4\
    Dr. Kahn states that sponsored studies often specify that the 
funder had no role in the study. Only recently have some journals 
required such statements, and I am unaware of research on the extent of 
this practice or authors' adherence to it. Among the 166 industry-
funded studies that I reviewed, few disclosed involvement of a sponsor.
    Dr. Kahn asks whether industry funding is any more biasing than 
career self-interest or intellectual passion. Unlike industry funding, 
self-interest and passions are intrinsic to every scientist who 
conducts research, are a matter of public record, cannot be eliminated, 
and have not been shown to consistently bias research results in the 
same ways as industry funding.\5\ Fortunately, nutrition societies and 
research institutions are developing policies to manage financial 
relationships with industry.\6\ Such policies hold promise for 
preventing financial conflicts of research in nutrition research.

Marion Nestle, Ph.D., M.P.H.

 
 
 
    Author Affiliation: New York University, Nutrition, Food Studies,
 and Public Health, New York, New York.
    Corresponding Author: Marion Nestle, PhD, MPH, New York University,
 Nutrition, Food Studies, and Public Health, 411 Lafayette, 5th Floor,
 New York, NY 10003-7035 ([email protected]).
    Conflict of Interest Disclosures: Dr. Nestle's salary from New York
 University supports her research, manuscript preparation, website, and
 blog at http://www.foodpolitics.com. She also earns royalties from
 books and honoraria from lectures to university and health professional
 groups about matters relevant to this letter and the Viewpoint to which
 it refers.
 


                              [References]
 
 
 
    1. Lundh A., Sismondo S., Lexchin J., Busuioc O.A., Bero L. Industry
 sponsorship and research outcome. Cochrane Database Syst. Rev. 2012;
 12: MR000033.
    2. Rising K., Bacchetti P., Bero L. Reporting bias in drug trials
 submitted to the Food and Drug Administration: review of publication
 and presentation. PLoS Med. 2008; 5(11): e217.
    3. Nestle M. Food Politics Blog. http://www.foodpolitics.com/.
 Accessed March 2, 2016.
    4. Mugambi M.N., Musekiwa A., Lombard M., Young T., Blaauw R.
 Association between funding source, methodological quality and research
 outcomes in randomized controlled trials of synbiotics, probiotics and
 prebiotics added to infant formula: a systematic review. BMC Med. Res.
 Methodol. 2013; 13: 137.
    5. Bero L. What is in a name? Nonfinancial influences on the
 outcomes of systematic reviews and guidelines. J. Clin. Epidemiol.
 2014; 67(11): 1239-1241.
    6. Charles Perkins Centre. Engagement with Industry Guidelines 2015.
 University of Sydney, 2015. https://intranet.sydney.edu.au/perkins/
 research-support/engaging-with-industry.html. Accessed March 2, 2016.
 

                             attachment 11
The Limits of Sugar Guidelines
Is there a danger in governments offering too-specific advice on sugar 
        consumption?
The Atlantic
Nina Teicholz
Jan. 17, 2017 



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Sugary drinks on display in New York City in 2012, at a news 
        conference about a proposed ban on all soft drinks over 16 
        ounces in the city's restaurants and stores Andrew Burton/
        Reuters.

    A firestorm recently erupted over a paper in the Annals of Internal 
Medicine (https://www.ncbi.nlm.nih.gov/pubmed/27992898) that found 
official advice limiting sugar in diets to be based on ``low'' or 
``very low'' quality evidence. Because a food-industry group had funded 
the study, a slew of critics accused the authors of distorting the 
science to undermine nutrition guidelines and make sugar seem less 
harmful than it actually is. One prominent nutrition professor called 
the paper (http://www.npr.org/sections/thesalt/2016/12/19/505867535/
how-much-is-too-much-new-study-casts-doubts-on-sugar-guidelines) 
``shameful.'' ``It was really an attempt to undermine the scientific 
process,'' said another (http://www.npr.org/sections/thesalt/2016/12/
19/505867535/how-much-is-too-much-new-study-casts-doubts-on-sugar-
guidelines).
    Lost in this torrent of criticism was any significant discussion of 
the science itself. Regardless of its funding source, was the paper 
correct in saying that there is insufficient evidence to recommend 
limiting sugar? And do official guidelines even matter, since we pretty 
much know that sugar is bad for us?
    The Annals paper examined a dozen guidelines on sugar passed by 
governments around the world since 2002, including the Dietary 
Guidelines for Americans, which last year recommended limiting sugar 
intake to ten percent of calories. One would assume that such advice is 
based on an ample body of rigorous research. But the Annals study, 
which included all the papers listed in the various guidelines' 
bibliographies themselves, claimed that reviews to date had overstated 
the evidence.
    In the most rigorous review on sugar and weight (http://
www.bmj.com/content/bmj/346/bmj.e7492.full.pdf), for instance, only 
five trials lasting 6 months or longer could be found, on a total of 
just 1,245 people. According to the Annals authors, this review 
portrayed the data as more consistent than it actually was and failed 
to adequately account for evidence indicating that studies in which 
sugar was shown to have no detrimental effect may have been suppressed 
from publication.
    Moreover, less rigorous data from observational studies was widely 
found to be ``inconsistent.'' Sometimes sugar was associated with 
health problems--weight gain, Type 2 diabetes, and tooth decay--but 
sometimes it wasn't.
    ``Overall, I would say the guidelines are not trustworthy,'' 
Bradley Johnston (http://ihpme.utoronto.ca/faculty/bradley-c-johnston/
), the study's lead author and an assistant professor of clinical 
epidemiology and biostatistics at McMasters University told me.
    The study's finding should come as a surprise to anyone who has 
been avoiding sugar for years already. Sugar is a potent source of 
glucose, which, over time, does appear to wreak havoc on one's 
metabolism and pave a direct path to obesity and diabetes. A large body 
of trial evidence has shown (http://www.nytimes.com/2016/09/11/opinion/
sunday/before-you-spend-26000-on-weight-loss-surgery-do-this.html?_r=0) 
that when carbohydrate consumption is reduced, these diseases start to 
reverse themselves. Also, given all the recent headlines about sugar's 
ill effects, from Katie Couric's movie Fed Up to the passage of soda 
taxes in several cities, one could be forgiven for assuming that the 
evidence condemning sugar must be a done deal.
    Clinical trials on sugar are possible; it's just that very few have 
been done.
    Yet here were the Annals authors saying it's not. Reaction to the 
paper from nutrition experts and advocacy groups was swift, with 
criticism focused on the paper's Achilles heel: It had been paid for by 
the International Life Sciences Institute, which receives 60 percent of 
its funding from 400 industry members, including some, like Coca-Cola, 
PepsiCo, and Mars, that very much stand to benefit from a study 
questioning caps on sugar.
    ``This is a classic example of industry-funded research aimed at 
one purpose and one purpose only: to cast doubt on the science linking 
diets high in sugars to poor health,'' Marion Nestle, a prominent 
professor of nutrition at New York University, told National Public 
Radio (http://www.npr.org/sections/thesalt/2016/12/19/505867535/how-
much-is-too-much-new-study-casts-doubts-on-sugar-guidelines). Dean 
Schillinger, the chief of the division of general internal medicine at 
San Francisco General Hospital, told the New York Times (http://
www.nytimes.com/2016/12/19/well/eat/a-food-industry-study-tries-to-
discredit-advice-about-sugar.html?_r=0): ``They're hijacking the 
scientific process in a disingenuous way to sow doubt and jeopardize 
public health.''
    Schillinger, with his colleague Cristin Kearns, also penned an 
editorial in Annals (https://www.ncbi.nlm.nih.gov/pubmed/27992900), 
which likened the sugar-review authors to lackeys hired by the tobacco 
industry to be ``merchants of doubt'' about the health hazards of 
smoking.
    Industry manipulation of the science is obviously an ongoing, 
serious concern. It was, in part, why the editor-in-chief of Annals, 
Christine Laine, invited this editorial. ``I wanted to show both sides 
of the issue,'' she told me, although she said that she considered the 
editorial to be unusually ``strident and hostile'' for an academic 
journal. Indeed, Schillinger and Kearns both part-time advocates 
against sugar; they write articles (http://www.sugarscience.org/sugar-
papers-reveal-industry-role-in-shifting-focus.html#.WGdB-M6PTyA) and do 
other work for Sugar Science (http://www.sugarscience.org/), a group 
devoted to educating the public about sugar's health dangers. ``It's 
shown me that conflicts of interest are not only financial but also 
intellectual,'' said Laine, who added disclosures about the authors' 
Sugar Science affiliations to the editorial after a reader brought them 
to her attention, she says.
    Ironically, undercutting a scientific paper by focusing on its 
funding source has mainly been used in the past to shoot down sugar 
skeptics. For instance, when the British nutrition professor John 
Yudkin suggested sugar as a dietary culprit in the early 1970s, the 
University of Minnesota researcher Ancel Keys, a key defender of the 
competing hypothesis, that dietary fat was responsible for chronic 
health issues, accused Yudkin of issuing ``propaganda,'' linked to 
``commercial backers [who] are not deterred by the facts.''
    Now that the nation's top nutrition authority, the U.S. Dietary 
Guidelines, has backed off caps on total fat and begun to condemn sugar 
instead, the public debate is also increasingly focusing on the sugar 
industry--indeed, so much so that other industry actors are escaping 
scrutiny. One has to ask, for instance, why there was no similar 
outrage over another recent paper (https://www.ncbi.nlm.nih.gov/pubmed/
27881409), in The BMJ, with favorable findings for vegetable oils, 
nearly \1/2\ of whose authors were actual employees of the giant 
vegetable-oil manufacturer Unilever. This would be like workers at 
Mars, Inc. publishing a study on the health benefits of sugar. Yet this 
sizable conflict of interest largely got a pass by the many journalists 
covering the story (https://pubpeer.com/publications/DF70B2D23429
0DF834A8F183BB6F8C#fb114267).
    To be clear, industry funding absolutely can deter good science; 
tobacco promotion will always be the epitome of that. But the influence 
of funding isn't invariable: While one meta-analysis found that funding 
sources do influence the conclusions of nutrition papers (https://
www.ncbi.nlm.nih.gov/pubmed/17214504), another, by a fierce critic of 
industry (http://www.smh.com.au/technology/sci-tech/cocacolas-secret-
plan-to-monitor-sydney-university-academic-lisa-bero-20161020-
gs6m4a.html) funding, paradoxically did not (https://
www.ncbi.nlm.nih.gov/pubmed/27802480). A healthy dose of skepticism 
over funding from all sources--including governments and other 
institutions, which may have their own pet hypotheses--is warranted, so 
long as it doesn't sideline the science or shut down legitimate debate.
    Schillinger and Kearns were right to raise doubts. Sugar defenders 
have, since the early part of the 20th century, worked diligently to 
promote their product, such that President Franklin Roosevelt, in the 
mid-1930s, was quoted as saying the sugar lobby was ``the most powerful 
pressure group that had descended on the national capitol'' during his 
lifetime. The extent of industry manipulation, through ad campaigns and 
efforts to twist the science are described by the journalist Gary 
Taubes in his new book, The Case Against Sugar.
    Yet Taubes believes that any industry with a PR budget has 
attempted pretty much the same. And he is up-front about the lack of 
rigorous evidence against sugar, stating in the introduction of his 
book, ``I'm going to concede in advance a key point that those who 
defend the role of sugar in our diet will invariably 
make. . . . [I]t cannot be established definitively, with the science 
as it now stands, that sugar is uniquely harmful.''
    Clinical trials on sugar are possible; it's just that very few have 
been done. Emerging evidence suggests (https://www.ncbi.nlm.nih.gov/
pubmed/25756179) that the sugar industry may have stifled those 
inquiries (https://therussells.crossfit.com/2016/09/15/did-big-soda-
derail-the-governments-cancer-research/), but Taubes believes more 
evidence supports the explanation that for decades, a monolith of 
nutrition scientists has just genuinely and obsessively had a 
preoccupation with fat and cholesterol which simply blotted out 
everything else. The National Institutes of Health (NIH) spent billions 
of dollars on large clinical trials, all trying to pin chronic disease 
on dietary fat and cholesterol. In fact, sugar was such a non-suspect 
for so many years that the major, NIH-funded observational studies took 
few pains even to measure it.
    While the evidence to date shows zero benefit from sugar and a 
clear signal of harm, there hasn't been enough time to fund and conduct 
definitive trials. Meanwhile, governments naturally feel they can't 
wait. Facing panic over the continued, relentless climb in obesity and 
diabetes rates with no solution in sight, they've gone ahead and passed 
sugar guidelines pinned to exact thresholds, of ten percent or five 
percent of calories. This advice is clearly well-intentioned. Yet if, 
as the Annals paper concludes, experts are skirting scientific norms by 
passing guidelines based on weak evidence, the whole process of 
guideline-making is effectively watered down. And the need for reliable 
guidance is no abstract question; indeed, everything from our 
waistlines to whether we might eat eggs for breakfast depends upon it.
    As Americans well know, there have been many reversals in our 
guidelines in recent years--on dietary cholesterol, on total fat, on 
whether to eat breakfast to maintain a healthy weight. These were all 
official guidelines based on weak evidence that, when actually tested 
in clinical trials, were found to be unjustified. It turned out that 
people had been avoiding egg yolks, lobster, and fat, generally, to no 
avail, and that skipping breakfast altogether might actually be the 
best option (https://www.washingtonpost.com/news/wonk/wp/2015/08/10/
the-science-of-skipping-breakfast-how-government-nutritionists-may-
have-gotten-it-wrong/?utm_term=.ca4
bb87d6c30) for weight loss.
    It's worth at least considering criticism of the potentially 
``low'' quality evidence behind existing nutrition advice.
    Instances of flip-flopping on nutritional advice not only erode the 
public trust, but make people think that the basic science itself is 
flawed--which, for the most part, it's not. Instead, the central 
problem has been that experts and policy makers have passed judgment 
before that good science was done. And once a judgment is codified as 
policy, it's hard to repeal. This was the case, for instance, with the 
low-fat diet, which although adopted as a U.S. guideline in 1980, 
wasn't actually studied in trials for another decade-plus. This kind of 
mistake, at its very worst, is potentially deadly: Indeed, the low-fat 
advice, by shifting consumption to carbohydrates such as grains and 
sugar, is now regarded as a probable cause of the obesity and diabetes 
epidemics.
    When the Senate first passed the government's warnings against fat 
and cholesterol in the late 1970s, officials argued that the urgency of 
responding to public-health crises overrode any concerns about 
insufficient scientific evidence. ``Undoubtedly there will be people 
who have said we have not proven our point,'' said Harvard's Mark 
Hegsted (https://naldc.nal.usda.gov/naldc/download.xhtml?id=1759
572&content=PDF), an advisor to the report, at the time of its release. 
Yet, citing the epidemics of heart disease, cancer, diabetes, and 
hypertension, he stated, ``We cannot afford to temporize. We have an 
obligation to assist the public in making correct food choices. . . . 
To do less is to avoid our responsibility.''
    These are the same arguments being made today, on sugar. It makes 
sense to have a strong hunch that sugar is bad. Sugar has no 
nutritional value. It's a direct shot of glucose to the blood stream 
and fructose to the liver. The historical evidence against it presented 
by Taubes in his book is compelling. Personally, I try hard to avoid 
it. But I also tend to avoid refined carbohydrates, such as white bread 
and cereals. Based on the existing data, I suspect that too much 
fructose from today's highly sweetened fruit crops is bad, and that the 
40+ percent increase in our consumption of grains since 1970 (https://
www.ers.usda.gov/publications/pub-details/?pubid=44220) have simply 
overloaded us in carbohydrates altogether (http://
www.nutritionjrnl.com/article/S0899-9007%2815%2900077-5/abstract).
    The NIH should fund rigorous trials to sort out these issues. 
Meanwhile, in the absence of more definitive science, it's worth at 
least considering criticism of the potentially ``low'' quality evidence 
behind existing nutrition advice. Maybe the government should be 
issuing a strong cautionary note, based on the existing, emerging 
evidence, rather than a specific formal ``Guideline''--since basing 
guidelines on hunches that are probably right unavoidably opens up the 
possibility for guidelines based on hunches that are wrong.
    An educated guess is not enough, warned the late Senator Charles 
Percy, in objecting to the government's original dietary advice, 35 
years ago. He thought it paved over limitations in the data with 
excessive confidence. ``The best way to [provide dietary guidance] is 
to fully inform the public not only about what is known but also what 
remains controversial,'' he said.
    He was talking about fat and cholesterol; today's Annals paper is 
talking about sucrose, glucose, fructose. We've been down this road 
before, with experts, pressed into urgency on behalf of the public 
health, convincing themselves that insufficient evidence could suffice. 
Therefore, in the matter of national guidelines, it's worth being 
cautious--and not immediately dismissing those who send up cautionary 
flags.
                             attachment 12
Do Financial Conflicts of Interest Bias Research? An Inquiry into the 
        ``Funding Effect'' Hypothesis
Sheldon Krimsky [1]
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    \[1]\ Department of Urban & Environmental Policy & Planning, Tufts 
University, Medford, MA, USA
    Corresponding Author:
    Sheldon Krimsky, Department of Urban & Environmental Policy & 
Planning, Tufts University, Medford, MA 02155, USA. E-mail: 
[email protected].
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Science, Technology, & Human Values, 38(4) 566-587
The Author(s) 2012
Reprints and permission: sagepub.com/journalsPermissions.nav
DOI: 10.1177/0162243912456271
sthv.sagepub.com
Abstract
    In the mid-1980s, social scientists compared outcome measures of 
related drug studies, some funded by private companies and others by 
nonprofit organizations or government agencies. The concept of a 
``funding effect'' was coined when it was discovered that study 
outcomes could be statistically correlated with funding sources, 
largely in drug safety and efficacy studies. Also identified in tobacco 
research and chemical toxicity studies, the ``funding effect'' is often 
attributed, implicitly or explicitly, to research bias. This article 
discusses the meaning of scientific bias in research, examines the 
strongest evidence for the ``funding effect,'' and explores the 
question of whether the ``funding effect'' is an indicator of biased 
research that is driven by the financial interests of the for-profit 
sponsor. This article argues that the ``funding effect'' is merely a 
symptom of the factors that could be responsible for outcome 
disparities in product assessment. Social scientists should not suspend 
their skepticism and choose as a default hypothesis that bias is always 
or typically the cause.
Introduction
    The philosopher Charles Sanders Peirce claimed that of all ways of 
fixing our beliefs, science is the most dependable. He wrote in 1877, 
``Scientific investigation has had the most wonderful triumphs in the 
way of settling opinion'' (Peirce, 1877). Not only have we come to 
believe in the ``dependability'' of scientific claims, we have come to 
depend upon them for making important life decisions. It is generally 
understood that the production of scientific knowledge is accompanied 
by quality controls that are designed to filter out errors and bias. By 
errors I shall mean those assertions or calculations in a study that 
are factually incorrect and which would be recognized as such by anyone 
trained in the discipline. These can include errors in statistical 
analysis, citations, recording of data, or the application of measuring 
devices. Bias, on the other, is a more complex term.
    As distinguished from error, bias is not as simple as an oversight 
or a mistake. Bias can be conscious or unconscious. It can be 
structural (by the choice of method) or nonstructural (by the 
interpretation of data). By ``structural bias,'' I mean the adoption of 
certain norms or methods that would distort (over- or underreport) the 
effects being studied. This term has been used in media studies where a 
structural bias is said to be the result of a preference of journalists 
for some type of story or frame that leads them to pay more attention 
to some events over others (van Dalen, 2011).
    Bias could involve proper or improper (scientific misconduct) 
behavior. In his book The Bias of Science, Brian Martin considers 
``biased'' research as synonymous with ``value-laden'' research 
``conditioned by social and political forces and dependent on judgments 
and human choices'' (Martin, 1979, 7). Under this definition, science, 
according to Martin, might never be unbiased or value-free. Resnik 
(1998, 85) argues that a bias is an invalid assumption: ``The person 
who conducts biased research is more like the person who defends a 
hypothesis that is later proven wrong than a person who makes a mistake 
or attempts to deceive his audience.''
    I am using ``bias'' in a different sense. By research bias, I shall 
mean the use of a method, data collection, data analysis, or 
interpretation of results that, in the consensus view of scientists of 
a discipline, tends to yield results that distort the truth of a 
hypothesis under consideration, diminishing or negating the reliability 
of the knowledge claim. Bias must be viewed in terms of the current 
operating norms of science. Since ``bias'' distorts the truth, 
scientists must be aware of its presence and where possible prevent or 
diminish it. I leave open the question of whether research considered 
unbiased in one time period could be viewed as biased by scientists 
during another time period.
    The function of our system of peer review is to identify error or 
bias before scientific studies are accepted for publication. After a 
study is published, it may still be criticized or corrected. Moreover, 
if an empirical finding cannot be replicated, the article may be 
withdrawn by the journal editors. Unlike other sources of establishing 
belief, science is considered to be a self-correcting enterprise where 
truth claims are kept open to new evidence. No one doubts, however, 
that bias can enter into published scientific work. While bias can be 
built into scientific methodology (structural), sometimes its subtlety 
can elude even the most careful reviewer and journal editor.
    Only recently have government and journals turned their attention 
to Conflict of Interest (COI) as a source of bias. The first Federal 
guidelines on scientific COI, issued simultaneously by the Department 
of Health and Human Services' (DHHS) Public Health Service (PHS) and 
the National Science Foundation were titled ``Objectivity in 
Research.'' The stated purpose of the regulation was ``to ensure that 
the design, conduct, or reporting of research funded under PHS grants, 
cooperative agreements or contracts will not be biased by any 
conflicting financial interest of those investigators responsible for 
the research'' (DHHS, 1995). And while the DHHS focused on financial 
COIs (FCOIs), it is generally recognized that interests other than 
direct financial interests can also play a potentially biasing role in 
science (Levinsky, 2002). Writing in the journal Cell Stem Cell about 
the ethics of stem cells, Jeremy Sugarman (2008, 532) noted: ``Both 
nonfinancial and financial conflicts of interest may adversely affect 
good judgment regarding stem cell research.'' But Sugarman also wrote 
that ``financial conflicts of interest in research may be easier to 
identify, simply because financial interests can be measured and more 
easily described than those associated with nonfinancial interests, 
such as the advancement of scientific and professional concerns'' 
(Sugarman 2008, 532).
    Following the maxim ``study what you can measure,'' social 
scientists began investigating the relationship between FCOIs and bias 
in the mid-1980s, when author disclosures of author FCOIs were still in 
their infancy. Most of the studies investigating a link between author 
FCOIs and private funding of science were carried out in the field of 
medicine, specifically medical pharmacology. The concept of a ``funding 
effect'' was coined after a body of research revealed that study 
outcomes were significantly different in privately funded versus 
publicly funded drug studies (Krimsky, 2006 2010). The funding effect 
was also identified in tobacco, pharmacoeconomic, and chemical toxicity 
research (Als-Nielsen, et al., 2003). This article examines the 
strongest evidence for the ``funding effect,'' and explores the 
question of whether the ``funding effect'' is an indicator of 
scientific research bias, based on a previously stated criterion of 
``bias.'' To begin, I shall discuss sources of evidence behind the 
``funding effect.'' I shall argue that the ``funding effect'' is a 
symptom of the factors that are responsible for outcome disparities in 
product assessments and that social scientists should not, without 
further investigation and the elimination of other explanations, chose 
bias as the default hypothesis.
Evidence of the ``Funding Effect'' in Science
    Beginning in the mid-1980s, scientists began testing the hypothesis 
that the source of funding from for-profit companies compared to 
nonprofit institutions and government can be correlated with the 
outcome of research, such as safety and efficacy in drug studies. This 
has been called ``the funding effect'' in science (Krimsky, 2005). The 
assumption has been that where there is a ``funding effect'' there must 
be bias. I shall begin with the evidence for the ``funding effect,'' 
largely from a group of studies in drug trials, and then discuss the 
possible causes of the effect.
    Badil Als-Nielsen, et al. (2003) tested the hypothesis that 
industry-sponsored drug trials tend to draw pro-industry conclusions. 
The authors selected a random sample of 167 Cochrane reviews and found 
25 with meta-analyses that met their criteria. From the meta-analyses, 
they studied 370 drug trials. After coding and numerically scoring the 
trials' conclusions and applying a logistic regression analysis, the 
authors found that ``conclusions were significantly more likely to 
recommend the experimental drug as treatment of choice in trials funded 
by for-profit organizations alone compared with trials funded by 
nonprofit organizations'' (Als-Nielsen, et al., 2003, 925). The authors 
ruled out as an explanation of industry favored outcomes both the 
magnitude of the treatment effect and the occurrence of adverse events 
reported. They also noted that the clinical trial methods between for-
profit and nonprofit organizations were not of the same quality. 
``Trials funded by for-profit organizations had better methodological 
quality than trials funded by nonprofit organizations regarding 
allocation concealment and double blinding'' (Als-Nielsen, et al., 
2003, 925). The authors do not report on the sponsor involvement and 
influence on the conduct and reporting of a trial. Such information 
could help us understand whether the external funder influences the 
scientist running the trial. The effects they observed between funding 
and outcome occurred whether the sponsor's contribution was minimal 
(provided the drug) or maximal (funded the study).
    The authors distinguish between potential biases in the empirical 
trial results (collection of data) and in the interpretation of those 
results, particularly in the recommendations they make about the 
experimental drug. As previously noted, bias can enter into any or all 
the stages of a study: the methodology, execution of the study, 
interpretation of results and recommendations (whether the experimental 
drug is better than the existing drug).
    It is also possible that industry-funded studies, having been 
identified as being of higher quality, have gone through more internal 
(company-sponsored) study and analyses, than one would expect of a 
nonprofit organization. This study found statistically significant 
outcome differences in a class of studies, but not necessarily bias--
although systemic bias is one hypothesis.
    John Yaphe, et al. (2001) selected for their study randomized 
controlled trials (RCTs) published between 1992 and 1994 of drugs or 
food products with therapeutic properties appearing in five journals: 
Annals of Internal Medicine, BMJ, JAMA, Lancet, and NEJM. A total of 
314 articles met their inclusion criteria. Of the 209 industry-funded 
studies, 181 (87 percent) and 28 (13 percent) had positive and negative 
findings, respectively, while of 96 nonindustry-funded studies, 62 (65 
percent) and 34 (35 percent) had positive and negative findings, 
respectively. What can account for this disparity in the outcomes of 
industry and nonindustry trials? Clearly, the bias of an investigator 
internalizing the financial interests of the sponsor is one potential 
hypothesis.
    Paula Rochon, et al., investigated the relationship between 
reported drug performance and manufacturer association. They adopted a 
broad definition of ``manufacturer association,'' which included 
supplying the drug or sponsoring a journal supplement where the 
publication of the study appeared. The authors selected as their study 
sample randomized drug trials (identified in MEDLINE between 1997 and 
1990) of nonsteroidal anti-inflammatory drugs used in the treatment of 
arthritis (Rochon, et al., 1994). The authors found 1,008 articles 
published within that period but only 61 articles representing 69 
individuals met their inclusion criteria. All the trials in their study 
had a ``manufacturer association,'' because they reported there was a 
scarcity of nonmanufacturer-associated trials. Therefore, they could 
not compare trials funded/supported by private companies with those 
funded/supported by nonprofit organizations. The authors also used 
several rating systems to estimate drug efficacy. The critical outcome 
measure was whether the drug being tested was superior, the same, or 
inferior to a comparison drug.
    The results of the study showed the ``the manufacturer-associated 
drug is always reported as being either superior to or comparable with 
the comparison drug'' and that ``these claims of superiority, 
especially with regard to side-effect profiles, are often not supported 
by trial data'' (Rochon, et al., 1994, 158). It is logically possible 
that head-to-head testing of new versus old drugs always shows the new 
drug superior. After all, that is the impetus for developing new drugs. 
But in this case, the framing of the tests can bias the outcome. Marcia 
Angell explains the process with an illustration from statins--drugs 
that lower blood cholesterol levels. ``There is little reason to think 
one is any better than another at comparable doses. But to get a 
toehold in the market, me-too statins were sometimes tested for 
slightly different outcomes in slightly different kinds of patients, 
and then promoted as especially effective for those uses'' (Angell, 
2004, 81).
    In a study by Benjamin Djulbegovic, et al. (2000), the 
investigators explored whether the reports of pharmaceutical-industry 
sponsored randomized trials result in biased findings. They selected 
113 articles published from 1996 to 1998 that described 136 randomized 
trials on multiple myeloma (Djulbegovic, et al., 2000, 637). The 
authors compared the new therapy versus the standard therapy in the 
trials and then analyzed the outcome according to whether the sponsors 
were nonprofit or for-profit organizations. Nonprofit organizations 
showed a 53 percent versus 47 percent support for new therapies, but 
when the trials were sponsored by for-profit organizations the ratio 
was 74 percent to 26 percent, a statistically significant difference.
    Friedman and Richer (2004) investigated whether sources of funding 
could be correlated to reported findings. The authors analyzed original 
contributions in NEJM and JAMA published in 2001. They classified the 
presentation of results as positive (statistically significant clinical 
benefit from a treatment or absence of suspected side effects), mixed 
(clinical benefits but adverse side effects), negative (absence of 
clinical benefits), or other (unclear significance). They located 193 
original articles in NEJM, 76 (39.4 percent) with a COI and 205 
articles in JAMA, 76 (37.1 percent) with COI. The authors found 119 
studies that investigated drug treatments and 174 studies for all 
treatments. They observed a ``strong association between positive 
results and COI among all treatment studies'' with an odds ratio of 
2.35 and for drug studies alone an odds ratio of 2.64. The odds ratio 
is the ratio of probability of an event occurring in one group to the 
probability of it occurring in another group. An odds ratio of 2.35 for 
the drug studies is the probability of a positive result in a drug 
treatment study conducted by individuals with a FCOI divided by the 
probability of a positive result from a similar drug treatment 
conducted by individuals without a financial conflict of interest. In 
other words, an odds ratio of 2.35 means that investigators with an 
FCOI are more than twice as likely to produce positive results in a 
drug treatment study.
    Another interesting finding is that the probability of reporting 
negative results in cases where an author had a FCOI was very low. One 
negative study of the 60 drug studies with FCOIs versus 21 negative 
studies of the 59 drug studies without FCOIs were reported. The authors 
conclude that ``the odds are extremely small that negative results 
would be published by authors with COI'' (Friedman and Richter, 2004, 
53).
    The authors cannot provide an explanation for their observed 
association between FCOI and reported findings in medical treatments. 
They can only theorize about the cause. ``One could surmise that drug 
companies are selective and only want to invest in treatments proven to 
produce positive results and that early clinical trials filter out the 
most promising treatments, which could explain the small number of 
studies funded by private corporations presenting negative findings'' 
(Friedman and Richter, 2004, 55). But they also consider the 
possibility of bias and ``spin.'' The question arises as to whether an 
investigator with a conflict of interest may be more inclined to 
present findings in order to gain favor with the sponsor or achieve any 
other extraneous objective--for example, to ``spin'' (Friedman and 
Richter, 2004, 55). Notwithstanding the fact that the cause of the 
association is not apparent in their data, they state that:

          The observation that negative findings are less commonly 
        reported among studies funded by private corporations raises 
        troublesome ethical questions. Researchers appear to be failing 
        to promote both the benefits and negative side effects of 
        commercial products they review or simply failing to submit 
        negative studies for publication because they are viewed as 
        uninteresting. (Friedman and Richter, 2004, 55)

    For social scientists studying the funding effect, the issue in 
this case is less a question of bias in the reported studies than it is 
an issue of bias in a failure of reporting negative studies, that is, 
in subverting the complete scientific record.
    Not all studies testing a hypothesis that there is an association 
between trial outcome or study quality and funding source reached 
positive findings. Tammy Clifford, Barrowman, and Moher (2002) selected 
a convenience sample of RCTs published between 1999 and 2000 by hand-
searching five high impact general medical journals--Annals of Internal 
Medicine, BMJ, JAMA, The Lancet, and NEJM. The quality of the trial 
report was evaluated according to the Jadad scale, which included 
randomization, allocation concealment, and withdrawals. The authors 
classified the trials according to funding source in four categories: 
entirely industry, entirely no[t]-for-profit, mixed, and not reported. 
Sixty-six of the hundred trials reviewed were funded in whole or in 
part by industry; six did not disclose their source of funding. Of the 
100 trials, 67 favored the new therapy, six favored conventional 
treatments, 19 reported neutral findings, and for eight the outcome was 
unclear. Of the 67 trials that favored the new treatment, 30 came from 
``industry only,'' 15 came from ``not-for-profit only,'' and 16 came 
from mixed sources; of the six trials that favored the conventional 
treatment, four came from ``industry only,'' one came from ``not-for-
profit only,'' and one came from mixed sources.
    The numbers for ``favored conventional'' were so low that 
statistical findings were not relevant. Also, this study only focused 
on funding and not on the financial ties of individual faculty 
associated with the trials. The authors noted limitations of their 
results. ``Our failure to detect any significant association may result 
from a type 2 error that indicates inadequate statistical power. 
Although our results do not even hint at a trend . . . the potential 
for type 2 error is real'' (Clifford, Barrowman, and Moher, 2002, 21). 
Perhaps one conclusion can be drawn: of the 100 trials, 66 percent were 
funded in whole or in part by industry and 67 percent favored the new 
therapy. Thus, it appears that industry trials are dominant and driving 
the advocacy of new drugs over old treatments even without adding 
author FCOI.
    Finally, I shall summarize the first meta-analysis that explored 
the ``funding effect.'' Bekelman, et al., culled 1,664 original 
research articles and ended up with 37 studies that met their criteria. 
They concluded: ``Although only 37 articles met [our] inclusion 
criteria, evidence suggests that the financial ties that intertwine 
industry, investigators, and academic institutions can influence the 
research process. Strong and consistent evidence shows that industry 
sponsored-research tends to draw proindustry conclusions'' (Bekelman, 
Li, and Gross, 2003, 463). Bekelman, et al., were convinced that the 
``funding effect'' is real.
    I shall now turn to the relationship between FCOI and 
pharmacoeconomics, defined as the discipline that evaluates the 
clinical, economic, and humanistic aspects of pharmaceutical products, 
services, and programs.
Pharmacoeconomic Studies
    A few studies have examined whether the results of economic 
analyses of drugs are correlated with the funding source. Because there 
is greater discretion in developing the methodology for economic 
studies of drugs, any inferences of bias must be addressed through the 
modeling, the stakeholder interests, and the specific parameters used 
in cost-benefit analysis rather than the omission or manipulation of 
clinical data. Johnson and Coons (1995, 165) note that ``Many different 
guidelines have been proposed for conducting pharmacoeconomic studies. 
The differences among the various versions reflect the diverse and 
sometimes conflicting views of those who specialize in economic 
evaluations.''
    Mark Friedberg, et al. (2010) searched the Medline and Health Star 
databases for articles published between 1985 and 1998 on cost or cost-
effectiveness analyses of six oncology drugs. The found forty-four 
eligible articles whose texts were analyzed for qualitative and 
quantitative conclusions and the funding source, based on predetermined 
criteria. Of the forty-four articles, twenty-four were funded by 
nonprofit organizations and twenty were funded by drug manufacturers. 
The authors found a statistically significant relationship between 
funding source and qualitative conclusions. Unfavorable conclusions 
were found in 38 percent (\9/24\) of the nonprofit-sponsored studies 
and five percent (\1/20\) of company-sponsored studies.
    Studies funded by pharmaceutical companies were almost eight times 
less likely to reach unfavorable qualitative conclusions than 
nonprofit-funded studies and 1.4 times more likely to reach favorable 
qualitative conclusions.
    C.M., Bell, et al. (2006) undertook a systematic review of 
published papers on cost-utility analyses. The authors found that 
industry-funded studies were more than twice as likely to report a 
cost-utility ratio below $20,000 per quality adjusted life year (QALY) 
as compared to studies sponsored by nonindustry sources. A similar 
study reported in the International Journal of Technology Assessment in 
Health Care assessed the relation between industry funding and findings 
of pharmacoeconomic analyses (Garattini, Rolova, and Casasdei, 2010). 
The authors searched Pub Med for articles on cost-effectiveness and 
cost utility, performed during 2004-2009 on single drug treatments. 
They found 200 articles that met their criteria. They divided the 
articles into two groups based on whether or not the authors had 
financial support from the pharmaceutical industry. ``Studies co-signed 
by at least one author affiliated to a pharmaceutical company and/or 
studies that declared any type of company funding were considered 
sponsored'' (Garattini, Rolova, and Casasdei, 2010, 331). The authors 
also classified the main conclusions as favorable, doubtful, or 
unfavorable toward the drug. Of the 200 articles, 138 (69 percent) were 
sponsored by a pharmaceutical company. Sponsored articles reported a 
favorable conclusion 95 percent of the time as against 50 percent of 
the time for nonsponsored articles. They claimed that ``the presence of 
a pharmaceutical sponsorship is highly predictive of a positive 
conclusion'' (Garattini, Rolova, and Casasdei, 2010, 331). According to 
Krimsky, 1999, 1475):

          The differences observed between [pharmacoeconomic] studies 
        funded by industry and nonprofit organizations may be the 
        result of methods chosen, prescreening, or bias due to the 
        source of funding. By following the traditions of professional 
        societies, such as those of engineering and psychiatry in 
        setting guidelines of practice, pharmacoeconomists can attain a 
        special role in the health care policy community in developing 
        independent studies that are based on accepted canons that meet 
        the highest standards of the profession. Canada and the United 
        Kingdom have developed national guidelines for cost 
        effectiveness studies.

    K.S. Knox, et al. (2000) reported on data collected in Friedberg, 
et al., in comparing practices of pharmaceutical-sponsored and 
nonprofit-sponsored pharmacoeconomic studies. They found that nonprofit 
studies more likely make an explicit statement of the significance of 
the findings (38 percent vs. 20 percent), provide a source of cost data 
(67 percent vs. 45 percent), and make a clear statement about the 
reproducibility of the findings in other settings (58 percent vs. 35 
percent). As in Friedberg, et al., Knox, et al., considered only one 
type of economic relationship between industry and researchers, namely, 
direct funding of a study and omitted many other types of financial 
relationships. Had they broadened their criteria, some of the 42 
pharmacoeconomic analyses they studied might be reclassified as 
``pharmaceutical associated'' thus changing the statistical results.
    Some of the authors who found a ``funding effect'' were cautious 
about inferring a bias from the data, although it was included in the 
list of hypotheses they considered. The next section explores 
alternative explanations.
Explanations of the ``Funding Effect'' Other than Bias
    In Yaphe, et al., the authors note that ``the higher frequency of 
good outcomes in industry supported trials may stem from a decision to 
fund the testing of drugs at a more advanced stage of development'' 
(Yaphe, et al., 2001, 567). In other words, industry has already done a 
lot of internal studies weeding out ineffective drugs. Thus, by the 
time a private company funds a trial, it would likely do better than a 
drug has not gone through its internal review. To fully understand this 
process, we need to know the extent to which companies test and reject 
drugs internally before funding a study by an academic group and 
whether the outcome results of ``new drugs are always better'' would be 
found in trials of the same drugs but funded by nonprofit 
organizations.
    The methodologies of industry-funded as compared to nonprofit-
funded trials may differ. For example, comparison of new drugs with a 
placebo may be more prevalent among industry-financed studies compared 
to nonindustry-financed studies. ``Comparison with placebo may produce 
more positive results than comparison with alternative active 
treatment'' (Yaphe, et al., 2001, 567). Unless we have a profit 
organization and nonprofit organization using the same or very similar 
methods to test the same drugs, drawing an inference about bias can 
yield false conclusions. The appearance of low negative outcomes from 
private sponsors could be the result of company screening for low 
probability drugs before they sponsor the trial or the ``reticence of 
investigators to submit negative findings for publication, fearing 
discontinuation of future funding'' (Yaphe, et al., 2001, 567). These 
caveats speak against a conclusion that bias can be inferred from the 
data that show outcome differences.
    Some tests use different doses of the new drugs and compare them to 
lower doses of the old drugs. This is corroborated by Rochon, et al., 
in their study. ``When we evaluated the relative range of dosing of the 
manufacturer-associated drug and the comparison agents in the trials on 
the basis of the recommended dosage suggested in standard tests, there 
was a considerable mismatch. In the majority of cases where the doses 
were not equivalent, the drug given at the higher dose was that of the 
supporting manufacturer'' (Rochon, et al., 1994, 161).
    The authors surmise that higher doses ``bias the study results on 
efficacy in favor of the manufacturer-associated drug'' (Rochon, et 
al., 1994, 161). This illustrates that bias may enter into the 
``funding effect'' in subtle and complex ways that deal with how the 
trial is organized.
    Some authors try to explain the ``funding effect'' by maintaining 
that most industry studies use a placebo and as a result are more 
likely to show a positive outcome. Also, the method of drug delivery 
used by companies may have been different than that used in nonprofit 
sponsor trials.
    Others have questioned whether industry trials are of lower quality 
and thus are likely to produce more favorable results. Djulbegovic, et 
al., rated the trial quality and concluded that ``trials funded solely 
or in part by commercial organizations had a trend toward higher 
quality . . . than those supported by the governmental or other 
nonprofit organizations'' (Djulbegovic, et al., 2000, 637). Thus, the 
outcome effect found in the industry-funded work of this group was not 
related to poor quality trials.
    In Frieberg's pharmacoeconomic study, the authors offer several 
possible explanations for the ``funding effect.'' First, for-profit 
companies are more likely than nonprofit companies to get ``early 
looks'' at the drugs, preliminary trial results, and economic data, 
weeding out those that would fail a cost-effectiveness standard. 
Companies might censor unfavorable studies by not funding them. Second, 
they surmise that funded studies with unfavorable results are less 
likely to be submitted for peer review and published. A third 
explanation for the disproportionate favorable results could arise from 
``unconscious bias that could influence study conclusions'' from 
scientists who have a financial conflict of interest--such as being 
paid by the company or holding an equity interest in the drug. As 
previously noted, the economists engaged in the study may internalize 
the values of the study sponsor, which could translate into a 
methodology that is more likely to yield a positive economic analysis.
    And the final explanation suggested by the authors is that ``the 
pharmaceutical companies can collaborate directly with investigators in 
devising protocols for economic analyses and indirectly shape the 
economic evaluation criteria'' (Friedberg, et al., 2010, 1475). The 
assessment of bias requires a standard or norm for pharmacoeconomic 
analysis against which one can compare different outcomes (Krimsky, 
1999). Several studies have addressed the quality of pharmacoeconomic 
analysis of drugs (Sacristan, Soto, and Galende, 1993; Jefferson, et 
al., 1988). Currently, no standardization or best practice for 
pharmacoeconomic analyses exists. Because the choice of method can have 
a significant effect on outcome, a method that systematically yields 
outcomes consistent with the private sponsor's financialinterest may be 
biased.
Single Product Assessment: Tobacco
    The studies of funding effects in pharmaceutical products include 
many types of drugs in order to develop aggregate statistics. Companies 
may do in-house studies before sponsoring extramural studies. The type 
of drug studied is generally considered not relevant to the findings of 
a funding effect. However, investigators may have different histories 
with the products they are testing. Nonprofit investigators may have 
seen the product for the first time. By eliminating product 
variability, investigators of the funding effect can more precisely 
judge the possible linkage between the source of funding and outcome 
findings such as product quality, safety, or economic efficiency. Two 
product studies for a funding effect meet these criteria: tobacco and 
the chemical bisphenol A (BPA). I shall begin with a discussion of 
tobacco research.
    Turner and Spilich (1997) investigated whether there was a 
relationship between tobacco industry support of basic research and the 
conclusions reached by authors of the study. They utilized a 
comprehensive review of the literature on tobacco and cognitive 
development and used that to obtain their reference studies. Beginning 
with 171 citations, the authors selected 91 studies fulfilling their 
selection criteria that investigated the effects of tobacco and 
nicotine upon cognitive performance. They coded the conclusions of the 
papers as positive, negative, or neutral on the question of whether 
tobacco enhances performance and segmented the papers into those that 
acknowledged corporate sponsorship and those that did not. When one or 
more of the authors was an employee of a tobacco company, the article 
was coded as industry-supported. All other articles were coded as 
``noncorporate sponsorship,'' even in cases where one or more of the 
authors had previously received industry support.
    For those papers reporting a negative relationship between tobacco 
and cognitive performance, sixteen were coded ``nonindustry 
supported,'' and one was coded ``industry-supported.'' For those 
reporting a positive relationship, twenty-nine came from nonindustry 
supported papers and twenty-seven from tobacco industry-supported 
papers. Among those papers reporting a neutral effect, eleven were from 
nonindustry studies and seven from industry-supported studies. In this 
study, the industry/nonindustry demarcation in the papers shows a 
disparity in negative results compared to positive results. Why did so 
few studies funded by the tobacco industry report negative effects on 
performance from tobacco use? Because the study methodologies were 
different, we cannot say that investigator bias played a role. It may 
just be that the industry-funded studies used a method that yielded 
fewer negative outcomes compared with an alternative method(s) used by 
the nonindustry-funded studies. There is a phenomenon known as ``bias 
in the study design,'' but that was not examined in the study. As 
previously mentioned, systematic bias in a study design seeking to test 
the toxicity of a chemical would be introduced by animal models that 
are inherently insensitive to the chemical in question (Bailar, 2006).
    Deborah Barnes and Lisa Bero (1998) investigated whether review 
articles on the health effects of passive smoking reached conclusions 
that are correlated with the authors' affiliations with the tobacco 
companies. Since tobacco is a relatively homogenous product, 
differences in outcome cannot be attributed to product variability or 
company pre-testing. Just as in pharmacoeconomic studies, there is no 
canonical method in undertaking a review article. Authors make a 
selection of articles that become part of the review. Some reviewers 
make their selection algorithm transparent. Others may not. Any two 
studies may use a different selection algorithm and they may weigh 
studies differently. ``Ultimately, the conclusion of any review article 
must be based on the judgment and interpretation of the author'' 
(Barnes and Bero, 1998, 1570).
    For this study, the authors adopted a search strategy use by the 
Cochrane Collaboration to select review articles from 1980 to 1995 on 
the health effects of passive smoking from the databases MEDLINE and 
EMBASE. They located additional review articles from a database of 
symposium articles on passive smoking. Articles were evaluated on 
quality and were classified as concluding that passive smoking was 
either harmful or not harmful. The authors found that 94 percent (\29/
31\) of reviews by tobacco-industry affiliated authors concluded that 
passive smoking is not harmful compared with 13 percent (\10/75\) of 
reviews without tobacco industry affiliations. The influence of 
tobacco-industry affiliation on the finding of ``safety of passive 
smoking'' was very strong. ``The odds that a review article with 
tobacco with tobacco industry-affiliated authors would conclude that 
passive smoking is not harmful were 88.4 times higher than the odds for 
a review article with nontobacco affiliated authors, when controlling 
for article quality, peer review status, article topic, and year of 
publication'' (Barnes and Bero, 1998, 1569). The authors reported that 
the ``only factor that predicted a review article's conclusion was 
whether its author was affiliated with the tobacco industry'' (Barnes 
and Bero, 1998, 1570). In this study, the authors had no alternative 
hypotheses other than the inherent bias of authors with industry 
affiliation. Because there is a great deal of discrepancy among authors 
in how a review is carried out, including the selection and weighting 
of articles that form the basis of the review, there are a number of 
ways that the conclusion can be made to favor the funder's interests, 
not the least of which is to set a high bar for establishing evidence 
of causality. The authors impute conscious intentionality of bias to 
the funders in their statement that ``the tobacco industry may be 
attempting to influence scientific opinion by flooding the scientific 
literature with large numbers of review articles supporting its 
position [which they paid for] that passive smoking is not harmful to 
health'' (Barnes and Bero, 1998, 1569). From tobacco, I shall now turn 
to an industrial chemical used in many products--bisphenol A.
Single Product Assessment: BPA
    While there are different variants of tobacco that depend on where 
the tobacco plant is grown, and even greater variation in cigarettes 
because of chemicals added to the tobacco and the paper, there is still 
greater homogeneity in studying tobacco than in studying different 
types of drugs. BPA, on the other hand, is a synthetic chemical that 
has a precise chemical structure. It was first reported synthesized in 
1905 by a German chemist. In 1953, scientists in Germany and the United 
States developed new manufacturing processes for a plastic material, 
polycarbonate, using BPA as the starting material. In the 1990s, 
scientists began studying the toxicological effects of BPA leaching 
from plastic food and water containers. Despite the fact that some 
scientists claimed there was extensive evidence that BPA can disrupt 
mouse, rat, and human cell function at low part per trillion doses and 
that disruption at the same low doses is also found in snails [and] has 
profound implications for human health (vom Saal, et al., 2005, 249), 
other scientists disagreed. Vom Saal and Welshons (2006, 61) divided 
the studies into those funded by industry and those funded by nonprofit 
organizations. Of the 119 studies funded by the Federal Government, 109 
showed harmful toxicological outcomes while ten had outcomes which 
showed no harm. Of the studies funded by the chemical companies, there 
were zero with outcomes showing harm and 11 with outcomes of no harm.
    The authors write: ``Evidence of bias in industry-funded research 
on BPA.'' Is it systematic bias and if so what form does it take? Is 
industry using a different methodology than most of the federally-
supported studies? If so, is their methodology sound or is it designed 
to get a ``no harm'' outcome?
    vom Saal and Welshons argue that industry-funded studies have a 
built in bias [what I have referred to as structural bias] against 
finding positive effects of BPA. They maintain that ``To interpret 
whether there is a positive or negative effect of a test chemical, such 
as BPA, appropriate negative and positive controls also have to be 
examined'' (vom Saal and Welshons, 2006, 62). Vom Saal argues that the 
industry-supported tests omitted a positive control and without 
positive control findings, one cannot interpret a reason for purely 
negative results. The authors also noted that some industry-funded BPA 
studies used test animals that had very low sensitivity to exogenous 
estradiol and thus would not be expected to exhibit effects from BPA. 
Other industry-funded investigators used a type of animal feed, which 
because of its estrogenic activity, would give a false result. 
``Inclusion of an appropriate positive control . . . would have allowed 
a determination of whether the failure to find effects of BPA was due 
to the lack of activity of BPA or to a lack of sensitivity of the 
animal model and/or estrogenic contamination of the feed that was 
used'' (vom Saal and Welshons, 2006, 63).
    In his classic work, The Logic of Scientific Discovery, Karl Popper 
(1968) developed the philosophical foundations of scientific 
methodology. Science, Popper argued, is not an inductivist enterprise, 
where truth is built up from data that are consistent with a 
hypothesis. Scientists must seek to falsify a hypothesis, and only when 
a hypothesis is recalcitrant against a rigorous attempt at 
falsification can it be accepted as truth. The critical point is that 
deduction and not induction is the logical grounding of empirical 
science. In the latter case, scientists would be given: A1 
is B, A2 is B . . . An is B therefore All A is B. In the 
former case, scientists seek to falsify ``All A is B'' by trying to 
find a disconfirming instance (Ax is not B).
    For example, one can reach the conclusion that ``all crows are 
black'' by observing crops in certain parts of Africa. Or you could 
imagine a geographical location that would most likely nurture a 
nonblack crow--such as the North or South Pole. If after all the 
seeking for a falsifying instance none appears, then, under the 
Popperian program, you can claim that the hypothesis ``all crows are 
black'' is confirmed. vom Saal and Welshons illustrate this point in 
the toxicology of BPA.

          . . . it is a common event in toxicological studies conducted 
        by the chemical industry for purposes of reporting about 
        chemical safety to regulatory agencies to provide only negative 
        results from a study in which no positive control was included 
        but from which positive conclusions of safety of the test 
        chemical are drawn. (von Saal and Welshons 2006, 63)

    As Peirce noted, ``We are, doubtless, in the main logical animals, 
but are not perfectly so'' (Peirce, 1877). Both he and Popper 
understood that knowledge claims drawn inductively can be easily 
distorted by the social context of scientists. This is most notably the 
case in the field of toxicology, which is composed of academic 
scientists and contract toxicologists working on behalf of for-profit 
companies. These scientists are usually paid by chemical companies to 
fulfill the information needs of their regulatory requirements. The 
standards for doing toxicological research may vary, especially in new 
subfields like low-dose, endocrine toxicology. Thus, until the norms of 
good scientific practices are adopted across the subfield and by the 
government regulators, contract toxicologists may perform studies that 
have structural biases because they are more likely than not to produce 
false negatives. This is the take-home message from the criticism by 
vom Saal and Welshons of private-company-sponsored studies. They are 
looking to confirm the null (no effect) hypothesis rather than trying 
to falsify the null hypothesis, which would provide more confidence in 
the claim that the chemical is not harmful.
Conclusion
    This analytical review of studies of studies that investigate an 
association between funding source and study conclusions has revealed 
several important results. First, there is sufficient evidence in drug 
efficacy and safety studies to conclude that the funding effect is 
real. Industry-sponsored trials are more likely than trials sponsored 
by nonprofit organizations, including government agencies, to yield 
results that are consistent with the sponsor's commercial interests. 
Second, there is some circumstantial evidence that this effect arises 
from two possible causes. Either the drugs sponsored by industry have 
gone through more internal testing and less-effective drugs are 
screened out, or the methods used in industry-sponsored drug testing 
have a structural bias that is more likely to yield positive outcomes.
    Third, a small number of pharmacoeconomic studies also show 
evidence of a funding effect. Without standardization of economic 
studies or the use of third-party ``economic auditors'' who have no 
economic ties to a company, it is difficult to account for the factors 
that explain this effect.
    A person who files his income tax is likely to use whatever 
discretionary decisions at his disposal to reduce his tax obligation. 
Similarly, a company that performs its own economic analysis of a new 
drug is likely to choose a model and use inputs that are advantageous 
to it. When a company hires an independent agent to undertake the 
economic analysis, little is known about what influence the company has 
in shaping the study. Also, little is known about drugs that are kept 
out of the testing pool by companies because they have already done the 
economic analysis.
    When we turn to studies of the funding effect on individualized 
commodities, the results are less ambiguous. There is an extensive body 
of research on tobacco, both primary (smokers) and secondary 
(secondhand smoke) exposures. This research shows a clear demarcation 
between studies funded by the cigarette industry and studies funded by 
nonprofit and governmental organizations. From this body of research, 
it is reasonable to conclude that the tobacco industry hired scientists 
to play a similar role as their contracted lawyers, namely, to develop 
a brief, in this case a scientific argument, that provides the best 
case or their interest. If that interpretation of tobacco-funded 
research is correct, it could explain the funding effect in tobacco 
studies.
    The second homogenous product discussed in this article is BPA. 
However, with only one study of this compound found that addresses the 
funding effect, a generalization cannot be drawn. But the scientists 
who published the study help the reader understand why a funding effect 
is a probable outcome. They show the systemic bias involved in the 
industry-funded studies that ordinarily do not appear in studies funded 
by nonprofit organizations.
    What I have argued in this article is that the ``funding effect,'' 
namely the correlation between research outcome and funding source, is 
not definitive evidence of bias, but is prima facie evidence that bias 
may exist. Additional analyses of the methodology of the studies, 
interpretation of the data, interviews with investigators, and 
comparison of the products studied can resolve whether the existence of 
a funding effect is driven by scientific bias. Social scientists should 
follow Robert Merton's norm of ``organized skepticism'' when they frame 
an initial hypothesis about the cause behind the ``funding effect'' 
phenomenon (Merton, 1968, 608). The notion of bias based on possessing 
a financial conflict of interest is certainly one viable hypothesis. 
But there are others. Social scientists must be equipped to compare the 
methods used across a cluster of studies funded by for-profit and not-
for-profit companies to determine whether a particular method biases 
the results toward ``no detectable outcome'' while other more sensitive 
methods yield positive results. Certain chemical effects may show up in 
animal fetuses and not on the adult animals.
    In addition, social scientists must gain an understanding of the 
entities being tested across a series of studies to determine whether 
the differences in the entities can account for the ``funding effect.'' 
Calcium channel blockers represent a class of drugs. It is important to 
understand whether the partition of studies between for-profit and not-
for-profit funders coincides with a random distribution of the entities 
being studied. Drugs that have passed a prescreening test are more 
likely to show more favorable outcomes than similar drugs that have 
not. This potential confounder can be eliminated when the entities are 
relatively homogenous, like tobacco or a chemical like BPA.
    In some cases, ethnographic studies can determine whether for-
profit companies have made internal decisions about drugs before they 
send them out to academic laboratories for study and how that compares 
with drug studies funded by not-for-profit organizations. Ethnography 
can also help social scientists ascertain when investigators reach 
beyond the data when they interpret results and whether the frequency 
of such overinterpretation (claiming benefits not found in the data) is 
more likely in studies funded by for-profit funders. Interviews with 
academic investigators, who are funded by private for-profit companies, 
and company executives, can reveal whether and how the funding 
organization helps frame the study, contributes to the interpretation 
of the data, and plays a role in deciding whether the results get sent 
for publication. The ``funding effect'' is merely a symptom of the 
factors that could be driving outcome disparities. Social scientists 
should not suspend skepticism and choose as the default hypothesis that 
``bias'' is always the cause.

 
 
 
Acknowledgment
 
    This research was supported in part by funding from the
 International Center forAlcohol Policies.
 
Declaration of Conflicting Interests
 
    The author declared no potential conflicts of interest with respect
 to the research, authorship, and/or publication of this article.
 
Funding
 
    The author received funding for an earlier version of this paper
 from the International Center for Alcohol Policies.
 


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Author Biography
 
    Sheldon Krimsky is the Lenore Stern Professor of Humanities and
 Social Sciences at Tufts University and the Carol Zicklin Visiting
 Professor at Brooklyn College. He is author of Science in the Private
 Interest.
 

                             attachment 13
Judge the Science, Not the Funding Source
Editorial
International Journal of Obesity (2014) 38, 625; doi:10.1038/
ijo.2014.32; published online 18 March 2014
2014 Macmillan Publishers Limited All rights 
reserved 0307-0565/14
www.nature.com/ijo

    Medical research has long been engaged in debate over the 
influences of corporate sponsorship on research findings. These 
discussions are a necessary element of our scientific process. However, 
recently the issue of `funding source' has taken on a life of its own, 
particularly in the realm of obesity research. Discussions about the 
merit and objectivity of the underlying science frequently take a back 
seat to ad hominem attacks on researchers or accusations of malicious 
corporate intent in the absence of any objective scientific appraisal 
of the research.
    These discussions are based on the faulty logic that somehow direct 
corporate funding is inherently bias-producing in otherwise ethical 
researchers and that, by implication, public (for example, NIH, USDA) 
and/or philanthropic (for example, RWJ, AHA) funding, by way of the 
intervening agency, ensures objectivity. A recent controlled study of 
over 500 board-certified internists found that the participant's 
perception of methodological quality was lower if they believed a trial 
was corporate sponsored even when no actual methodological difference 
was present.\1\ This suggests a bias against scientifically valid 
studies based solely on funding source, which could in fact negatively 
impact public health through out-of-hand dismissal of relevant, high-
quality research.
---------------------------------------------------------------------------
    \1\ Kesselheim A.S., Robertson C.T., Myers J.A., Rose S.L., Gillet 
V., Ross K.M., et al. A randomized study of how physicians interpret 
research funding disclosures. N. Engl. J. Med. 2012; 367: 1119-1127.
---------------------------------------------------------------------------
    Conversely, the implied bias favoring noncorporate trial 
objectivity is equally concerning as it may lead us to overlook very 
real potential bias from publicly funded trials. For example, it could 
be argued that a scientist who is funded by USDA is at similar risk for 
being biased in favor of sugar, corn and other agriculture-based 
products vs. artificial sweeteners. Moreover, an often overlooked 
threat to objectivity is the pressure to find statistically significant 
results. This has been found in both corporate- and noncorporate-
sponsored research. A recent examination of over 4,600 scientific 
papers from all disciplines published internationally between 1990 and 
2007 found that the frequency of positive support for hypotheses has 
increased 22%. The author notes that this bias toward publishing 
positive results may influence the objectivity of the research 
literature both directly and also more subtly by discouraging more 
innovative (higher-risk) projects.\2\
---------------------------------------------------------------------------
    \2\ Fanelli D. Negative results are disappearing from most 
disciplines and countries. Scientometrics 2012; 90: 891-904.
---------------------------------------------------------------------------
    Assuming that the well-intentioned yet misguided goal of those 
leveling these ad hominem attacks is to keep scientists in check and to 
help us avoid moral and scientific pitfalls, there is a far better 
model available. When the model works, the public is protected, 
scientific discovery and rigor supported, and advances in our knowledge 
achieved. At the core of the model is a safe environment that allows 
for transparency. This includes full disclosure of all potential 
conflicts of interest without fear of judgment or reprisal and peer-
reviewed publication of findings with appropriate methodological detail 
to allow for objective analysis and scientific scrutiny. Beyond these 
commonly and universally held practices, more consistent application of 
additional tools may be useful. For example, a requirement for all 
research to be preregistered in Clinicaltrials.gov or a similar 
database. Reviewers and journal editors can be encouraged to ensure 
that final manuscripts are consistent with the stated a priori 
objectives before final acceptance of manuscripts, which could further 
add to our protection of scientific integrity. Finally, we should all 
aspire to solve the intellectual property and other barriers that limit 
our ability to review and replicate studies on the basis of lack of 
access to primary data sources in some corporate trials. Although these 
barriers are complex and beyond the scope of this paper, we need to 
begin to find solutions that will enhance the ways scientific process 
can be used to be the judge of all science.
    In summary, what are the best practices for ensuring a strong, 
unbiased body of obesity research? Certainly not refusing funding from 
those who wish to collaborate with scientists in becoming part of the 
solution; absolutely not by launching unsubstantiated attacks on 
reputable scientists with longstanding records of ethical conduct and 
meaningful scientific contribution; rather, it is first by giving 
funding source its proper position among many possible and equally 
important threats to objectivity and implementing safeguards to protect 
against such bias (and worse yet malfeasance). Second, we need to 
redouble our efforts to adhere to the basic principles of good science 
like reproducibility, replicability and other core evaluative 
procedures that ensure objective and reliable scientific reporting. 
Finally, we need to work toward open access to data regardless of its 
source. This will require the cooperation of those in the scientific 
community and among potential sources of funding. Ultimately, this type 
of transparency regardless of funding source will deliver a more robust 
and complete body of evidence. In short, scientists need to practice 
good science, sponsors must commit to transparency and noninfluence, 
media needs to practice responsible scientific journalism, and we all 
need to base our evaluations on scientific data and not on 
predetermined opinions rooted in our own emotion-laden bias for or 
against specific funding sources.

 
 
 
Conflict of Interest
 
    Dr. Martin Binks [1	2] reports the following potential conflicts of
 interest: Dr. Binks is sole proprietor of Binks Behavioral Health PLLC;
 he has also received financial compensation from: The Obesity Society
 (Communications & Social Media Consultant), 2011-present; Guidepoint
 Global Consulting, 2007-present; AbbVie Men's Health Initiative, 2012;
 Everyday Health Inc., 2006-2011; Evolution Health Systems, 2006-2011.
 Dr Binks also currently serves in the following volunteer roles: The
 Obesity Society, Secretary Treasurer & Development Chair. No funding
 from any source is directly associated with the development of this
 manuscript.
[1] Department of Nutritional Sciences, Texas Tech University, Lubbock,
 TX, USA.
[2] Binks Behavioral Health, PLLC, Hillsborough, NC, USA, E-mail:
 [email protected].
 

                             attachment 14
The Obesity Society Encourages Science-Industry Collaborations to 
        Support Obesity Science, Public Health
New Position Statement Condemns Ad Hominem Attacks on Researchers
Mar. 26, 2014, 11:00 ET from The Obesity Society 


          The Obesity Society Logo. (PRNewsFoto/The Obesity Society)

    Silver Spring, Md., March 26, 2014--PRNewswire-USNewswire--
Collaborations between scientists and industries, including food and 
pharmaceuticals, have a strong history of aiding in new scientific 
discoveries and supporting public health. For example, earlier this 
year, food industry corporations announced success in cutting 1.5 
trillion calories from food products, which The Obesity Society 
referred to (http://www.obesity.org/news-center/cutting-trillions-of-
calories-from-food-products-can-have-a-significant-impact-on-the-
nations-health.htm) as an effort that could ``make a significant 
difference in our nation's weight and health, helping to reverse the 
obesity epidemic.''
    ``It's clear, efforts to combat obesity cannot succeed without the 
engagement of the many industries that have the power to positively 
impact the health of billions of people,'' said TOS President Steven 
Smith, M.D.
    However, in recent years, nutrition and obesity researchers have 
frequently endured ad hominem attacks, or inappropriate criticisms of 
character and ethics on the sole basis of collaborative relationships 
and/or funding from Industry. Today, The Obesity Society (TOS) issued a 
position statement supporting and encouraging collaborative 
relationships between scientists and Industry in the interest of 
scientific discovery and public health. The position goes further to 
condemn these character attacks against credible and ethical 
professionals providing transparency and full disclosure about these 
collaborations.
    ``Many of our members are the obesity and nutrition scientists that 
offer valuable insight and spark meaningful dialogue with Industry 
leaders, and they deserve to be treated and recognized as the credible 
and ethical professionals that they are,'' said Dr. Smith. 
``Discrediting the scientific opinions of these professionals based on 
their working relationships has no place in the scientific process.''
    The position statement, ``Acceptance of Financial Support from 
Industry for Research, Education and Consulting,'' authored by members 
of TOS leadership, including Advocacy Chair Emily Dhurandhar, Ph.D., 
President-elect Nikhil Dhurandhar, Ph.D., Secretary-Treasurer Martin 
Binks, Ph.D., and Advocacy Advisor Ted Kyle, RPh, discourages the 
practice of ``dismissing the contributions of individual scientists and 
attempting to discredit individuals based on funding source.''
    ``We have seen too many scientists with long-standing records of 
scientific excellence and ethical conduct dragged into the spotlight of 
public criticism based solely on a funding source, and despite full 
disclosure and transparency,'' said Dr. Dhurandhar, who led the 
development of the statement. ``Scientists serve a clear role in these 
relationships and must operate with the ability to do their work to 
advance public health by engaging in free and open dialogue, offering 
expert opinion, and conducting meaningful research to support obesity 
treatment and prevention, and advance public health.''
    In the new position statement, TOS recognizes that individual 
motivations can sometimes create a risk of bias, which can come in many 
forms outside of funding source. However, from advisory panels to 
scientific publications, policies are in place to ensure transparency 
and disclosure of all potential sources of bias, which is common 
practice.
    ``Scientists are very familiar with the importance of making 
relevant disclosures and ensuring funding sources do not influence the 
design, analysis, interpretation, and publication of the scientific 
process,'' said Dr. Dhurandhar.
    The Obesity Society has a long-standing commitment to ensuring 
ethical and transparent relationships between science and Industry, and 
the organization hopes to advance the science behind obesity research, 
treatment and prevention through ongoing dialogue on this issue.
    Read the full position statement here (http://www.obesity.org/
publications/acceptance-of-financial-support-from-industry-for-
research-education-a-consulting.htm).
About The Obesity Society (http://www.obesityweek.com/)
    The Obesity Society (TOS) is the leading professional society 
dedicated to better understanding, preventing and treating obesity. 
Through research, education and advocacy, TOS is committed to improving 
the lives of those affected by the disease. For more information visit: 
www.Obesity.org.
                             attachment 15
White Hat Bias: A Threat to the Integrity of Scientific Reporting
A Different View
Acta Pjdiatrica ISSN 0803-5253
Mark B. Cope,[1] David B. Allison 
([email protected])[2]
---------------------------------------------------------------------------
    \[1]\ Solae LLC, St Louis, MO, USA.
    \[2]\ Biostatistics and Nutrition & Obesity Research Center, 
University of Alabama at Birmingham, Birmingham, AL, USA.
    Correspondence: David B. Allison, Biostatistics and Nutrition & 
Obesity Research Center, University of Alabama at Birmingham, 
Birmingham, AL, USA. Tel: 205-975-9169, Fax: 205-975-2540, E-mail: 
[email protected]


Received: 26 August 2010; accepted 2 September 2010.
DOI:10.1111/j.1651-2227.2010.02006.x

          Articles in the series A Different View are edited by Alan 
        Leviton ([email protected]) We encourage you 
        to offer your own different view either in response to A 
        Different View you do not fully agree with, or on an unrelated 
        topic.
Background
    Like other people, scientific researchers have their own 
motivations. Such motivations include, but are not limited to, direct 
financial gain, interests in recruiting financial resources to their 
institutions, fame, social dominance, being perceived as righteous and 
upstanding, and a genuine interest in beneficence and improving the 
human condition. Pursuing these motivations may at times suggest 
behaviours on the part of scientists that accord with the behaviours 
that are generally accepted as sound and honest scientific practice. 
Yet in other situations, such motives may conflict with the precepts of 
scientific research.
    Although the potential for financial conflicts of interests (COIs) 
to bias research and research reporting is widely 
recognized,(1) far less attention has been devoted to other 
factors that may contribute to bias in research. Some people within the 
research and lay communities appear to think that direct financial COIs 
resulting from industry connections are the only factors of significant 
concern. For example, Lesser, et al., wrote `We agree that financial 
conflict is not the only cause of 
bias. . . . long-standing scientific viewpoints, career considerations, 
and even political opinions might color study design or interpretation. 
However, these types of individual bias tend to cancel themselves out 
among large groups of scientists over the long term. While one 
investigator's career may rise on a cherished theory, another's may 
rise by debunking that theory. We contend that financial conflict of 
interest is qualitatively different, producing selective bias that acts 
consistently in one direction over time'.(2)
    Another report, evaluating the possible financial competing 
interest among researchers who had published clinical studies in the 
British Medical Journal, concluded that `authors' conclusions were 
positively associated with financial competing interests. Other 
competing interests such as personal or academic were not significantly 
associated withauthors' conclusions'.(3) This study had low 
power--only 19 trial reports listed `other competing interests--for 
instance, personal, academic, or political.' Also, the reporting of 
nonfinancial interests is by no means standard or covered by most 
guidelines, so most nonfinancial interests probably go unreported.
    Recently, we published a paper describing `White hat bias (WHB),' 
which we defined as bias leading to distortion of information in the 
service of what may be perceived to be righteous ends.(4) 
Using quantitative evidence, we showed, at least in some areas of 
investigation, that WHBs that do not stem from financial connections to 
industry, clearly do not `cancel out' over the long run as Lesser, et 
al.,(2) hypothesized they would. Rather, WHB seemed to be 
consistently pushing conclusions in a single direction and 
systematically distorting the research record.
    In the remainder of this paper, we summarize the results of our 
previously reported investigation into WHB, offer a few additional 
examples of apparent WHB, often anecdotal, and finally close with some 
suggestions to reduce the influence of biases, including WHBs, in 
research.
Summary of Our Previous Findings Related to Breastfeeding and Obesity
    Some reports that do not agree with main stream opinion (e.g., a 
report that sugar-sweetened beverages (SSBs) \1\ are not associated 
with obesity in children or a report that breastfeeding is not 
protective against childhood weight gain) may never be published. Other 
reports contain secondary references to support a current position, but 
incompletely or inaccurately describe the overall results from the 
secondary reference cited (4) [also labelled as `unbalanced 
citations' by Atkinson and Macdonald].(5)
---------------------------------------------------------------------------
    \1\ The term sugar-sweetened beverages (SSBs) is used for 
consistency with common use in the literature to denote any beverage, 
which has been sweetened by the addition of a substance containing a 
nontrivial amount of metabolizable energy. Thus, SSBs do not include 
beverages sweetened with high-intensity `noncaloric' sweeteners such as 
sucralose or aspartame, but may include beverages sweetened with 
substances not conventionally termed sugar.
---------------------------------------------------------------------------
    One area in which we documented WHB involved the question of the 
beneficial effect (or lack thereof) of breastfeeding on the development 
of obesity.(4) In a review commissioned and published by the 
World Health Organization (WHO) on the health benefits related to 
breastfeeding, specifically for obesity in the breastfed offspring, the 
authors presented evidence about whether breastfeeding protects against 
obesity and whether there is evidence of publication bias 
(PB).(6) PB occurs when the probability of publication 
depends on the results of the study.(7-8) For example, 
positive (statistically significant) results are much more likely to be 
reported than statistically insignificant (null) 
findings.(9)
    Within the WHO-commissioned report, the authors presented a graph 
showing clear evidence consistent with PB, suggesting that the 
probability a study was published was positively related to the degree 
it showed a statistically significant protective association of 
breastfeeding on obesity. To evaluate the impact of industry funding on 
such PB, we retrieved and reviewed the papers summarized in this graph. 
None of the papers reported any industry funding or were written by 
employees of the infant formula industry. Thus, the strong PB in the 
literature pertaining to breastfeeding and its relationship to obesity 
seems because of the behaviour of nonindustry funded scientists and 
does not appear to be fuelled by industry interests.
    Research can also be reported in a misleading manner when authors 
choose to include incorrect or questionable material and exclude 
otherwise pertinent information in their reviews or meta-analyses. In 
our review of the WHO report on breastfeeding,(4) we cited 
several examples where careful study of some of the original papers 
revealed that WHO authors selectively included some values from certain 
primary papers and thereby generated stronger associations of 
breastfeeding with reduced obesity risk and excluded less impressive 
values from the same papers without explanation. Misleading reports (or 
unexplained exclusion of data) can also occur in other areas of 
research.
Some Additional Examples and Evidence
    `Spin,' defined as distorted presentation of data, was identified 
in reports of randomized clinical trials.(10) In each, the 
primary outcome was statistically nonsignificant, yet somewhere in the 
report (title, abstract, etc.), the experimental treatment was `spun' 
in a way to mislead the reader. In an evaluation of reports of 102 
randomized clinical trials (122 published journal articles), 62% of 
them added a new outcome, had at least one of the primary outcomes 
changed, or simply omitted the findings.(11)
    Recently, the Food and Drug Administration of the U.S. Government 
issued a docket describing how menu labelling in restaurants would give 
people the opportunity to make healthier diet choices when eating 
out.(12) The docket stated that `the availability of 
nutritional information through menu labeling would provide Americans 
the opportunity to exercise personal responsibility and make informed 
choices about their diets. Studies show that providing nutrition 
information at restaurants can help people make healthier choices 
[(13), Journal of Consumer Research 2009 36(3): 494-503]' 
(14) This cited study actually reported that parents will choose 
slightly lower calorie food options for their children in a restaurant 
setting; however, the parents did not choose lower calorie foods for 
themselves (13). This is an example of an unbalanced citation. Rather 
than stating `Studies show that providing nutrition information at 
restaurants can help people make healthier choices,' an accurate 
statement from that study would have been `A single study (but not all 
studies) showed that providing nutrition information at restaurants can 
help people make healthier choices when they choose food for other 
people, but not when they choose food for themselves.'
What Can We Do?
    Faithful reporting, acknowledging study limitations and evaluating 
bodies of evidence without selectively excluding information on the 
basis of its desirability are a few examples of how paediatricians can 
become committed to scientific truthfulness. They are also encouraged 
to be sensitive to the possibility of WHB.
    Publication bias and exclusion of pertinent data for no apparent 
reason are examples of WHB and according to Atkinson and Macdonald 
(5) `all scientists should strive to have the `spin' stop 
with them'. `Science itself is the antidote to the poison of bias in 
research'.(15) We need to encourage, and perhaps require the 
publication of reports that minimize publication bias, and to require 
that trials and their protocols be registered to enable identification 
of omissions or distortions of any key procedures, which would affect 
interpretation of results. These and other ways of shoring up the 
integrity of the scientific process are not easy steps, will not solve 
all problems, will create some new challenges and cannot be implemented 
overnight. Yet we should not make the perfect the enemy of the good and 
should make the development and implementation of such procedures a 
priority.
Conclusion
    To reduce the influence of bias in research and in general media 
reporting of scientific findings, there will need to be a concerted 
effort at all levels from scientist-authors to editors and journalists. 
We do not yet know how much of WHB is inadvertent and how much it 
results from an anti-industry sentiment, feelings of righteous 
indignation, a passionate interest in justifying public health actions, 
or yet other factors. Yet regardless of the root of the WHB, medical 
professionals, reporters, government policy makers and the public 
should be aware of such biases and view scientific literature with a 
critical eye.
    Drs. Allison and Cope have received grants, book royalties, 
honoraria, donations and consulting fees from numerous food, beverage, 
dietary supplement, pharmaceutical companies, litigators and other 
commercial, government and nonprofit entities with interests in obesity 
and nutrition, including interests in breastfeeding and SSBs. Dr. Cope 
recently accepted a position with Solae LLC (St Louis, MO, USA).

                               References
 
 
 
    1. Friedman L.S., Richter E.D. Relationship between conflicts of
 interest and research results. J. Gen. Intern. Med. 2004; 19: 51-6.
    2. Lesser L.I., Ebbeling C.B., Goozner M., Wypij D., Ludwig D.S.
 Relationship between funding source and conclusion among nutrition-
 related scientific articles. PLoS Med. 2007; 4: e5.
    3. Kjaergard L.L., Als-Nielsen B. Association between competing
 interests and authors' conclusions: epidemiological study of randomised
 clinical trials published in the BMJ. BMJ 2002; 325: 249.
    4. Cope M.B., Allison D.B. White hat bias: examples of its presence
 in obesity research and a call for renewed commitment to faithfulness
 in research reporting. Int. J. Obes. (Lond) 2010; 34: 84-8; discussion
 3.
    5. Atkinson R.L., Macdonald I. White hat bias: the need for authors
 to have the spin stop with them. Int. J. Obes. (Lond) 2010; 34: 83.
    6. Horta B., Bahl R., Martines J., Victora C. Evidence of the Long-
 Term Effects of Breastfeeding: Systematic Reviews and Meta-Analysis.
 WHO, Geneva, Switzerland, 2007.
    7. Riechelmann R.P., Wang L., O'Carroll A., Krzyzanowska M.K.
 Disclosure of conflicts of interest by authors of clinical trials and
 editorials in oncology. J. Clin. Oncol. 2007; 25: 4642-7.
    8. Friedman C.P., Wyatt J.C. Publication bias in medical
 informatics. J. Am. Med. Inform. Assoc. 2001; 8: 189-91.
    9. Rosenthal R.H. The ``File Drawer Problem'' and Tolerance for Null
 Results. Psychol. Bull. 1979; 86: 638-41.
    10. Boutron I., Dutton S., Ravaud P., Altman D.G. Reporting and
 interpretation of randomized controlled trials with statistically
 nonsignificant results for primary outcomes. JAMA 2010; 303: 2058-64.
    11. Chan A.W., Hrobjartsson A., Haahr M.T., Gotzsche P.C., Altman
 D.G. Empirical evidence for selective reporting of outcomes in
 randomized trials: comparison of protocols to published articles. JAMA
 2004; 291: 2457-65.
    12. Registry F. FDA Docket. 2010; 75: 39026-8.
    13. Tandon P.S., Wright J., Zhou C., Rogers C.B., Christakis D.A.
 Nutrition menu labeling may lead to lower-calorie restaurant meal
 choices for children. Pediatrics 2010; 125: 244-8.
    14. Howlett E.A., Burton S., Bates K. and Huggins K. Coming to a
 Restaurant Near You? Potential Consumer Responses to Nutrition
 Information Disclosure on Menus. Journal of Consumer Research 2009; 36:
 494-503.
    15. Allison D.B. The antidote to bias in research. Science 2009;
 326: 522-3.
 

                             attachment 16
White Hat Bias: Examples of Its Presence in Obesity Research and a Call 
        for Renewed Commitment to Faithfulness in Research Reporting
Commentary
International Journal of Obesity (2010) 34, 84-88; doi:10.1038/
ijo.2009.239; published online 1 December 2009
M.B. Cope [1] and D.B. Allison [2]
---------------------------------------------------------------------------
    \[1]\ Department of Pharmacology and Toxicology, School of 
Medicine, University of Alabama at Birmingham, Birmingham, AL, USA.
    \[2]\ Section of Statistical Genetics, Department of Biostatistics, 
School of Public Health, and Clinical Nutrition Research Center, 
University of Alabama at Birmingham, Birmingham, AL, USA.
    Correspondence: Professor D.B. Allison, Section of Statistical 
Genetics, Department of Biostatistics, School of Public Health, 
University of Alabama at Birmingham, Ryals Public Health Building, 1530 
3rd Avenue S, RPHB 327, Birmingham, AL 35294-0022, USA. E-mail: 
[email protected].

          `White hat bias' (WHB) (bias leading to distortion of 
        information in the service of what may be perceived to be 
        righteous ends) is documented through quantitative data and 
        anecdotal evidence from the research record regarding the 
        postulated predisposing and protective effects of nutritively 
        sweetened beverages and breastfeeding, respectively, on 
        obesity. Evidence of an apparent WHB is found in a degree 
        sufficient to mislead readers. WHB bias may be conjectured to 
        be fuelled by feelings of righteous zeal, indignation toward 
        certain aspects of industry or other factors. Readers should 
        beware of WHB, and our field should seek methods to minimize 
        it.
Introduction
    Scientific dialogue is dependent on fair and open presentation of 
data and evidence, yet concerns have been raised in recent years about 
bias in research practice. We present data and examples pertinent to a 
particular bias, a `white hat bias' (WHB), which we define to be bias 
leading to distortion of research-based information in the service of 
what may be perceived as righteous ends. We evaluate WHB in the context 
of two illustrative obesity topics, nutritively sweetened beverage 
(NSB) consumption as a postulated risk factor \1\and breastfeeding as a 
postulated protective factor.\2\
Example 1--Data on citation bias
    If secondary reportings of original research misleadingly cite 
papers with statements that inaccurately describe available evidence, 
then inaccurate beliefs may inappropriately influence clinical 
practice, public policy or future research. Previously,\3\ we observed 
that two papers 4-5 had both statistically and non-
statistically significant results on body weight, body mass index (BMI) 
or overweight/obesity status, which allowed future writers to 
potentially choose which results to cite, and were also widely cited, 
permitting a quantitative analysis of citations.
Cited Versus Citing Papers
    A Web of Science search (through to October 2008) yielded 195 and 
45 papers citing James, et al.,\4\ and Ebbeling, et al.,\5\ 
respectively. We analyzed those in English (165 and 41, respectively).
    James, et al.,\4\ studied an intervention to decrease NSB 
consumption and adiposity among children. Dichotomized (overweight or 
obese versus neither overweight nor obese) and continuous (change in 
BMI) data were analyzed for statistical significance. The authors 
wrote:

          `After 12 months there was no significant change in the 
        difference in body mass index (mean difference 0.13, ^0.08-
        0.34) or z score (0.04, ^0.04-0.12). At 12 months the mean 
        percentage of overweight and obese children increased in the 
        control clusters by 7.5%, compared with a decrease in the 
        intervention group of 0.2% (mean difference 7.7%, 2.2-13.1%).'

    Ebbeling, et al.,\5\ described a randomized controlled trial of a 
25 week NSB reduction program in adolescents and wrote:

          `The net difference (in BMI), 0.14R0.21 kg/m\2\, was not 
        significant overall.'

    They then report a subgroup finding:

          `Among the subjects in the upper baseline--BMI tertile, BMI 
        change differed significantly between the intervention . . . 
        and control . . . groups, a net effect of 0.75R0.34 kg/m\2\.'

    Ebbeling, et al. (p. 676) label the analysis in the total sample as 
the `primary analysis.'

                                              Table 1  Categorization of 165 Papers Citing James, et al.\2\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                      Score                            A            B            C            D            E            F            G            H
--------------------------------------------------------------------------------------------------------------------------------------------------------
No. of references in each category                         14           74            2           21            2            1            1           50
Proportion (exact CIs) a                                0.127        0.644        0.017        0.183        0.017        0.009        0.009
                                                  (0.071-0.19  (0.548-0.72  (0.003-0.06  (0.119-0.26  (0.003-0.06  (0.001-0.05  (0.001-0.05
                                                           9)           9)           8)           8)           8)           5)           5)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Abbreviations: BMI, body mass index; CI, confidence interval.
a Proportions and CIs are calculated with only categories A through to G in the denominator. Scoring key: (A) Accurate--described the non-significant
  result on continuous outcome (change in BMI) and described the significant result on the dichotomous outcome (overweight versus non-overweight). (B)
  Mildly misleading (positively)--Described the result of the intervention study as showing efficacy, benefit or statistical significance for the
  dichotomous outcome of overweight status, without mentioning the non-significant result on the continuous outcome. (C) Moderately misleading
  (positively)--Described the result of the intervention study as showing efficacy, benefit or statistical significance on some weight-related outcome
  without explicitly stating that it was on the proportion overweight per se. (D) Explicitly misleading (positively)--Described, with a factually
  incorrect statement, that the result of the intervention for a continuous weight-related outcome was significant or showed effectiveness. (E) Mildly
  misleading (negatively)--Described the result of the intervention study as not showing efficacy, benefit or statistical significance on the continuous
  measure of BMI, without mentioning the significant result on the dichotomous outcome. (F) Moderately misleading (negatively)--Described the result of
  the intervention study as not showing efficacy, benefit or statistical significance on some weight-related outcome without explicitly stating that it
  was on the continuous measure of BMI. (G) Explicitly misleading (negatively)--Described, with a factually incorrect statement, that the result for the
  dichotomous outcome was not significant or that a lack of effectiveness was shown for the dichotomous outcome. (H) Unscorable--Did not make explicit
  statements about the effects of the study, made statements that were too ambiguous to code or made statements that were self-contradictory.

Data Coding and Analysis
    Each paper citing either James, et al.,\4\ or Ebbeling, et al.,\5\ 
was categorized (see Tables 1 and 2) on the basis of how authors cited 
results related to body weight, BMI or overweight/obesity outcomes from 
these two papers in their report. Papers citing James, et al., were 
independently coded by the authors of this paper (DBA or MBC). Any 
discrepancies were resolved by discussion. Papers citing Ebbeling, et 
al., were scored by DBA and cross-checked by MBC. Proportions (with 
confidence intervals) were calculated (Tables 1 and 2). Exact binomial 
calculation tested the null hypothesis that the proportion citing 
papers in a misleading manner that exaggerated the strength of evidence 
was equal to the proportion citing papers in a misleading manner that 
diminished the strength of evidence; as such an equal proportion would 
suggest a lack of bias in the overall literature, even if not in any 
one paper.
Citation Analysis Results
    Results were quite consistent across papers citing either James, et 
al.,\4\ or Ebbeling, et al.,\5\ The majority, 84.3% for James, et 
al.,\4\ and 66.7% for Ebbeling, et al.,\5\ described results in a 
misleadingly positive manner to varying degrees (that is, exaggerating 
the strength of the evidence that NSB reduction showed beneficial 
effects on obesity outcomes). Some were blatantly factually incorrect 
in their misleading statements, describing the result as showing an 
effect for a continuous obesity outcome, when no statistically 
significant effect for continuous obesity outcomes was observed. In 
contrast, only four papers (3.5%) were negatively misleading (that is, 
underplayed the strength of evidence) for James, et al.,\4\ and none 
were negatively misleading for Ebbeling, et al.\5\ Only 12.7 and 33% of 
papers accurately described complete overall findings related to 
obesity outcomes from James, et al.,\4\ and Ebbeling, et al.,\5\ 
respectively.
    To test whether the proportion of misleading reporting in the 
positive direction was equal to the proportion in the negative 
direction, we calculated the confidence interval on the proportion of 
misleading reportings in either direction that was positively 
misleading. This yields a proportion of 0.96 (95% CI: 0.903-0.985) for 
those citing James, et al.,\4\ and 1.00 (95% CI: .832-1.000) for those 
citing Ebbeling, et al.,\5\ and is significantly different from 1/2 for 
each (P<0.0001), indicating a clear bias and potential for readers of 
the secondary literature to be deceived.
Example 2--Data on publication bias
NSB Consumption
    A meta-analysis on NSB consumption and obesity \6\ found that 
estimated adverse associations were significantly smaller (that is, 
less adverse) among industry-funded than among non-industry-funded 
studies. One troubling conceivable explanation for this is that 
industry does something to bias results to make NSBs seem less harmful, 
but this is not the only conceivable explanation.
    To examine this further, we requested, and Dr. Vartanian \6\ 
graciously provided, his meta-analysis data file. Focusing on cross-
sectional studies, because a large number had adiposity indicators as 
outcomes, we conducted publication bias (PB) detection analyses.\7\ PB 
causes the sample of studies published to not constitute a 
representative sample of the relevant studies that hypothetically could 
have been published. With PB, the probability of a study being 
published depends on its outcome. Typically, PB involves statistically 
significant studies having a higher likelihood of being published than 
non-statistically significant ones. Our analysis (Figure 1) shows a 
clear inverse association between study precision and association 
magnitude. This PB hallmark suggests that studies with statistically 
significant NSB findings are more likely to be published than are 
nonstatistically significant ones. Interestingly, this bias seems to be 
present only for non-industry-funded research, suggesting that non-
industry-funded scientists tend not to publish their non-significant 
associations in this area. Contrarily, all industry-funded studies seem 
to exceed a minimal level of precision. Thus, much of the reason for 
the smaller associations detected by Vartanian, et al.,\6\ for 
industry-funded research seems to be because of PB in non-industry-
funded research. However, even after accounting for precision, the mean 
difference between the association magnitudes of industry and non-
industry-funded studies is reduced by 33%, but not eliminated, 
suggesting that there may be competing biases operating in industry-
funded research.

                                             Table 2  Categorization of 41 Papers Citing Ebbeling, et al.\3\
--------------------------------------------------------------------------------------------------------------------------------------------------------
                            Score                                   A            B            C            D            E            F            G
--------------------------------------------------------------------------------------------------------------------------------------------------------
No. of references in each category                                      10            9           11            0            0            7            4
Proportion (exact CIs) a                                             0.333        0.300        0.367        0.000        0.000
                                                               (0.173-0.52  (0.147-0.49  (0.199-0.56  (0.000-0.11  (0.000-0.11
                                                                        8)           4)           1)           6)           6)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Abbreviations: BMI, body mass index; CI, confidence interval.
a Proportions and CIs are calculated with only categories A through to E in the denominator. Scoring key: (A) Accurate--Described both the non-
  significant result in the total sample and the significant result in the heaviest subgroup. (B) Patently misleading overpositive--Described as
  positive on weight without mentioning anything about the result only being in heaviest children. (C) Mildly misleading overpositive--Described as
  positive among the heaviest children without explicitly mentioning that there was no significant result in the total sample. (D) Mildly misleading
  over-negative--Described the null result in the total sample without explicitly mentioning the significant result in the heaviest subgroup. (E)
  Patently misleading over-negative--Described as negative in a way that explicitly indicated that there were no significant effects even in sub-groups.
  (F) Not directly relevant--Did not make clear and explicit statements about the effects of the study. (G) Ambiguous as to whether category A or E
  applies.

Figure 1 



[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]



          Plot of sample effect sizes from cross-sectional studies of 
        the association between sugar-sweetened beverage consumption 
        and obesity indexes indicating publication bias among non-
        industry-funded studies (Blue diamonds--industry funded; Red 
        diamonds--non-industry funded).
Breastfeeding
    The World Health Organization (WHO; \8\) published a meta-analysis 
on whether breastfeeding protects against obesity and also found 
evidence of PB. Figure 2 indicates this strikingly. We retrieved all 
papers from which data were obtained for Figure 2 to evaluate the 
impact of industry funding on this PB. None of the papers reported any 
industry funding or were obviously authored by authors employed by the 
infant formula industry. Thus, as with the NSB literature, there seems 
to be a strong PB that is not apparently fueled by industry interests.
Figure 2 

[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]

          Plot of the relationship between association magnitude and 
        study precision indicating publication bias in studies of 
        breastfeeding and obesity (from Horta, et al.\8\).
Example 3--Anecdotal Examples of Miscommunications in Press Releases
    Evidence suggests that `Press releases from academic medical 
centers often promote research that has uncertain relevance to human 
health and do not provide key facts or acknowledge important 
limitations'.\9\ This is also occurring in the obesity field. For 
example, the paper by Ebbeling, et al.,\5\ states, `change in body mass 
index (BMI) was the primary end point. The net difference, 0.14R0.21 
kg/m\2\, was not significant overall,' and then reports the subgroup 
finding, `Among the subjects in the upper baseline-BMI tertile, BMI 
change differed significantly between the intervention . . . and 
control . . . groups.' Contrast this modest finding in a sample subset 
and the circumspect presentation in the original paper with the 
presentation in the press release issued by the authors' institution 
(http://www.childrenshospital.org/newsroom/Site1339/
mainpageS1339P1sublevel192.html (accessed on 31 October 2008)), which 
states `In randomized trial, a simple beverage-focused intervention led 
to weight loss' and never states that the primary analysis was not 
statistically significant.
    When the paper by James, et al.,\4\ was released, the press release 
issued on the BMJ website (http://www.bmj.com/content/vol328/issue7446/
press_release.shtml (accessed on 20 September 2009)) stated 
`Discouraging children from drinking fizzy drinks can prevent excessive 
weight gain, according to new research available on bmj.com,' despite 
the facts that no analysis of weight change per se was reported and 
that there was no significant effect on BMI change. Neither of these 
facts was mentioned in the press release.
    Finally, in 2009, describing an observational epidemiological 
study, UCLA issued a press release (http://www.healthpolicy.ucla.edu/
NewsReleaseDetails.aspx?id%35 (accessed on 20 September 2009)) stating 
`. . . research released today provides the first scientific evidence 
of the potent role soda and other sugar-sweetened beverages play in 
fueling California's expanding girth' One of the study authors was 
quoted in a subsequent news story stating `For the first time, we have 
strong scientific evidence that soda is one of the--if not the 
largest--contributors to the obesity epidemic' (http://
www.drcutler.com/poor-diet/study-soda-making-californians-fat-19373657/ 
(accessed on 25 September 2009)). These statements are inaccurate and 
also unfair to all authors of observational studies who published such 
research years before. The press release further stated `The science is 
clear and conclusive [emphasis added],' despite the fact that this was 
a correlational research, and offered no statement to the reader to 
interpret the results as indicative of correlation and not necessarily 
causation.
Example 4--Inappropriate Or Questionable Inclusion of Information
    Research may also be misleadingly presented by inclusion of 
incorrect or questionable material in reviews. In our critical review 
of the WHO report on breastfeeding, we noted several examples (see, 
Cope and Allison,\2\ p. 597) in which an inspection of the original 
papers reviewed revealed that the authors of the WHO report selectively 
included some values from certain primary papers that led to stronger 
associations of breastfeeding with reduced obesity risk and excluded 
less impressive values from the same papers without explanation.
    Similarly, Mattes, et al.,\3\ noted that several reviews of NSB 
consumption and obesity inappropriately included a study \10\ that was 
actually neither a test of nutritive sweetener-containing solid food 
versus beverage nor of NSB consumption versus non-NSB consumption. 
Sweeteners were presented in both solid and beverage food forms. The 
original authors \10\ wrote, `. . . subjects who were given 
supplemental drinks and foods [emphasis added] containing sucrose for 
10 wk experienced increases in . . . body weight', and thus the study 
should never have been considered as evaluative of NSB effects. Mattes, 
et al.,\3\ provide other examples of papers being inappropriately 
included in past reviews of NSB consumption and obesity.
Conclusion
    Finding effective methods to reduce obesity is an important goal, 
and appropriate evaluations of the strength of the evidence supporting 
the procedures under consideration are vital. Sound evaluations 
critically depend on evidence being presented in non-misleading ways. 
Alarms have been sounded about dramatic rises in obesity levels, not 
without justification. And yet, these alarms may also have aroused 
passions. Certain postulated causes have come to be demonized (for 
example, fast food, NSBs, formula feeding of infants) and certain 
postulated palliatives (for example, consumption of fruits and 
vegetables, building of sidewalks and walking trails) seem to have been 
sanctified. Such demonization and sanctification may come at a cost. 
Such casting may ignite feelings of righteous zeal.
    Some authors compare NSBs, fast foods and other food and restaurant 
industry offerings to the tobacco industry (for example, see Browne 
\11\ and Warner \11\), suggesting, for example, comparisons between 
`Joe Camel' and `Ronald McDonald' (http://www.time.com/time/magazine/
article/0,9171,1187241,00.html). To the extent that such comparisons 
inform us about important causes of obesity and how to reduce them, 
this is all to the good. But to the extent that such comparisons and 
other appeals to passions inflame rather than inform, they may cloud 
judgment and decrease inhibitions against breaching ordinary rules of 
conduct. Historians indicate that during times of war, propagandists 
demonize (that is, dehumanize) the enemy to inflame spirits and this 
facilitates some breaches of codes of conduct such as massacres.\12\ 
Although inflaming the passions of scientists interested in public 
health is unlikely to provoke bloodshed, we scientists have, as a 
discipline, our own code of conduct. Central to it is a commitment to 
faithful reporting, to acknowledging our study limitations, to 
evaluating bodies of evidence without selectively excluding information 
on the basis of its desirability--in short, a commitment to 
truthfulness. The demonization of some aspects and sanctification of 
others, although perhaps helpful in spurring social action, may be more 
harmful to us in the long run by giving unconscious permission to 
breach that code, thereby eroding the foundation of scientific 
discipline.
    Evidence presented herein suggests that at least one aspect has 
been demonized (NSB consumption) and another sanctified 
(breastfeeding), leading to bias in the presentation of research 
literature to other scientists and to the public at large, a bias 
sufficient to misguide readers. Interestingly, although many papers 
point out what seem to be biases resulting from industry funding, we 
have identified here, perhaps for the first time, clear evidence that 
WHBs can also exist in opposition to industry interests.
    Whether WHB is intentional or unintentional, and whether it stems 
from a bias toward anti-industry results, significant findings, 
feelings of righteous indignation, results that may justify public 
health actions, or yet other factors, is unclear. Future research 
should study approaches to minimize such distortions in the research 
record. We suggest that authors be more attentive to reporting primary 
results from earlier studies rather than selectively including only a 
part of the results, to avoiding PB, as well as to ensuring that their 
institutional press releases are commensurate with the studies 
described. Journal editors and peer reviewers should also be vigilant 
and seek to minimize WHB. Clinicians, media, public health policy 
makers and the public should also be cognizant of such biases and view 
the literature on NSBs, breastfeeding and other obesity-related topics 
more critically.

 
 
 
Conflict of Interest
 
    Drs. Allison and Cope have received grants, honoraria, donations and
 consulting fees from numerous food, beverage, dietary supplement,
 pharmaceutical companies, litigators and other commercial, government
 and nonprofit entities with interests in obesity and nutrition,
 including interests in breastfeeding and NSBs. Dr Cope has recently
 accepted a position with The Solae Company (St. Louis, MO, USA).
 
Acknowledgements
 
    We gratefully acknowledge Dr. Alfred A. Bartolucci for his comments
 on our data analysis and Dr. Lenny Vartanian for sharing his data file.
 Supported in part by the NIH grant P30DK056336. The opinions expressed
 are those of the authors and not necessarily those of the NIH or any
 other organization with which the authors are affiliated.
 


                               References
 
 
 
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 value of moderating nutritively sweetened beverage consumption in
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                                 ______
                                 
                           Submitted Question
Response from Diane Whitmore Schanzenbach, Ph.D., Director and Senior 
        Fellow, Economic Studies, Brookings Institution; Professor of 
        Social Policy, and of Economics, The Hamilton Project, 
        Northwestern University *
---------------------------------------------------------------------------
    * There was no response from the witness by the time this hearing 
was published.
---------------------------------------------------------------------------
Question Submitted by Hon. David Scott, a Representative in Congress 
        from Georgia
    Question. I have a question for you about the potential effects of 
adopting WIC restrictions as SNAP restrictions. As you know, WIC is 
meant to ensure low-income women have access to foods that meet the 
nutrient needs of pregnancy, infancy and developing young children. The 
purpose of SNAP, however, is meant to ensure that our low-income people 
are not hungry. WIC food packages are extremely restrictive, even when 
it comes to healthy foods, and vary widely by state. For example, 
currently only $10 is allowed per month on fruits and vegetables. In 
some states, frozen and canned fruits and vegetables are not allowed to 
be purchased with WIC benefits. Many states don't even offer yogurt, 
and when they do, they offer only the large size, certain brands and 
certain flavors. Many of us, no matter the income level, have dealt 
with a picky eater in our family, and we've had to find little 
solutions to getting them to eat healthy foods. Maybe they hate 
strawberry yogurt, but they'll eat blueberry! Maybe they won't eat raw 
broccoli, but they'll eat steamed frozen broccoli with a little cheese 
on top. It begs the question, are we trying to make it harder or easier 
for Americans to feed our families?
    Some states are considering asking for a waiver from USDA to 
restrict SNAP purchases to the preexisting and restrictive list of 
foods under WIC. Could you please describe what implementation would 
look like, health outcomes and any unintended negative consequences of 
states restricting SNAP benefits to those foods offered through the WIC 
program? Would it further the program's goal of reducing hunger?
    Answer.

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