[Federal Register Volume 64, Number 121 (Thursday, June 24, 1999)]
[Notices]
[Pages 33890-33897]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 99-15377]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Substance Abuse and Mental Health Services Administration


Estimation Methodology for Adults With Serious Mental Illness 
(SMI)

AGENCY: Center for Mental Health Services, Substance Abuse and Mental 
Health Services Administration, HHS.

ACTION: Final notice.

-----------------------------------------------------------------------

SUMMARY: This notice establishes a final methodology for identifying 
and estimating the number of adults with serious mental illness (SMI) 
within each State. This notice is being served as part of the 
requirement of Public Law 102-321, the ADAMHA Reorganization Act of 
1992.

EFFECTIVE DATE: October 1, 1999.

FOR FURTHER INFORMATION CONTACT: Ronald W. Manderscheid, Ph.D., Chief, 
Survey and Analysis Branch, Center for Mental Health Services, Parklawn 
Building, Rm 15C-04, 5600 Fishers Lane, Rockville, MD 20857, (301) 443-
3343 (voice), (301) 443-7926 (fax), [email protected] (e-mail).

Scope of Application

    All individuals whose services are funded through the Federal 
Community Mental Health Services Block Grant must fall within the 
definition announced on May 20, 1993, in the Federal Register, Volume 
58, No. 96, p. 29422. Inclusion or exclusion from the estimates is not 
intended to confer or deny eligibility for any other service or benefit 
at the Federal, State, or local level. Additionally, the estimates are 
not intended to restrict the flexibility or responsibility of State or 
local governments to tailor publicly-funded systems to meet local needs 
and priorities. Any ancillary use of these estimates for purposes other 
than those

[[Page 33891]]

identified in the legislation is outside the purview and control of 
CMHS.

Background

    Pub. L. 102-321, the ADAMHA Reorganization Act of 1992, amended the 
Public Health Service Act and created the Substance Abuse and Mental 
Health Services Administration (SAMHSA). The Center for Mental Health 
Services (CMHS) was established within SAMHSA to coordinate Federal 
efforts in the prevention, treatment, and the promotion of mental 
health. Title II of Pub. L. 102-321 establishes a Block Grant for 
Community Mental Health Services administered by CMHS, which permits 
the allocation of funds to States for the provision of community mental 
health services to children with a serious emotional disturbance (SED) 
and adults with a serious mental illness (SMI). Pub. L. 102-321 
stipulates that States will estimate the incidence (number of new cases 
in a year) and prevalence (total number of cases in a year) in their 
applications for Block Grant funds. As part of the process of 
implementing this new Block Grant, definitions of the terms ``children 
with a serious emotional disturbance and ``adults with a serious mental 
illness'' were announced on May 20, 1993, in the Federal Register, 
Volume 58, No. 96, p. 29422. Subsequent to this notice, a group of 
technical experts was convened by CMHS to develop an estimation 
methodology to ``operationalize the key concepts'' in the definition of 
adults with SMI. A similar group has prepared an estimation methodology 
for children and adolescents with SED. The final SED estimation 
methodology was published on July 17, 1998, in the Federal Register, 
Volume 63, No. 137, p. 38661.

Summary of Comments

    This final notice reflects a thorough review and analysis of 
comments received in response to an earlier draft notice published in 
the Federal Register, on March 28, 1997, Volume 62, No. 60, p. 14928.
    CMHS received only nine comments expressing opinions about the 
proposed methodology. Several questions were raised. These questions 
are summarized in four broad areas: Operational definition of SMI, 
complexity of the methodology, differences among States, and other 
related comments.

Operational Definition of SMI

    Some comments suggested that the SMI definition was too broad.
    The final definition of SMI was published on May 20, 1993, in the 
Federal Register, Volume 58, No 96, p. 29422. This definition cannot be 
changed by the methodology outlined below.
    SMI was defined as the conjunction of a DSM mental disorder and 
serious role impairment. The Diagnostic Interview Schedule (DIS) 
estimates were not enhanced. A respondent had to have a DIS/Composite 
International Diagnostic Interview (CIDI) diagnosis and an impairment 
to qualify for the operational definition of SMI. This means that the 
estimated annual prevalence of SMI is always equal to or less than the 
DIS/CIDI estimates of disorder prevalence. The charge to the technical 
committee was to make what it considered to be the best decisions based 
on available data about impairment to operationalize the definition of 
SMI. The report of the committee describes in great detail how and why 
the technical experts chose specific indicators.
    It is important to note that Pub. L. 102-321 explicitly states that 
SMI includes impairments in functioning. As a result, the technical 
experts were required to include one component of the operational 
definition that assesses functioning in social networks. Strict 
criteria were used, such as reports of extreme deficits in social 
functioning to qualify for this type of impairment. A respondent must 
either have one of the following two profiles: (i) Complete social 
isolation, defined as having absolutely no social contact of any type--
telephone, mail, or in-person--with any family member or friend and 
having no one in his or her personal life with whom he/she has a 
confiding personal relationship; or (ii) extreme dysfunction in 
personal relationships, defined as high conflict and no positive 
interactions and no possibility of intimacy or confiding with any 
family member or friend. These persons comprise about 10% of those 
classified as having SMI. The remaining 90% either have a severe 
disorder like schizophrenia or bipolar disorder, or a disorder and work 
impairment, or a disorder and report being suicidal.
    The rationale for the 57% prevalence estimate of SMI among prison 
inmates is well documented in the committee's report. A review of 
epidemiological studies in inmate populations found that the average 
estimated prevalence of any DIS disorder is 57%. The technical experts 
concluded that all inmates with one of these disorders, by definition, 
were functioning inadequately in social roles by virtue of the fact 
that they were incarcerated.
    This definition was adopted for very practical reasons. It is 
important to remember that the inmate population represents less than 
one percent of the adult population, and the prevalence estimate of 57% 
is based on published work.
    Some comments urged that the definition of SMI did not constitute 
the service population for public mental health services.
    This final notice includes a statement about the scope of 
application of the estimates. That statement defines what is and is not 
intended by the definition and the methodology.

Complexity of the Methodology

    Some comments noted that the use of the Baltimore sample as a basis 
for estimating national SMI rates among elderly persons may have 
introduced errors into the estimates for persons 55 years and older.
    The technical experts were mandated to arrive at the best estimate 
based on currently available data. The Baltimore ECA data were the best 
currently available for persons 55 years and older. Nationally 
representative data would have been used if such existed. It will be 
important in the future to improve the data available to produce 
estimates for all age groups.
    Some comments were made about distortions in State estimates and 
lack of theory.
    The technical experts used all available data on State-level 
variables that could be obtained readily from the Federal government on 
an annual basis and explored the effects of these variables in 
predicting SMI. Such variables were deliberately selected to increase 
the ease of application of the estimation methodology by the States in 
the future. The experts believed and continue to believe that they 
could do no less than exhaustively consider the full range of 
potentially important predictors of SMI, irrespective of available 
theory. The analytical iterations are explained in the committee's 
report. These explanations provide all the detail a specialist in 
applied statistics or demography would need to evaluate the procedures 
adopted. These procedures are consistent with currently accepted 
methods for making small area estimates. Government agencies currently 
use similar methodologies to make estimates of other State-level social 
policy variables.
    Some comments suggested that confidence intervals were not provided 
for State prevalence estimates.
    Confidence intervals have been provided in this final notice, since 
estimates are based upon samples rather than a complete enumeration.

[[Page 33892]]

    Some comments suggested that the estimation methodology paper was 
difficult to understand and that complex statistical procedures were 
inadequately explained, with insufficient rationale.
    In writing the paper, the authors were sensitive to the importance 
of being clear about major decisions. The authors have had a great deal 
of experience writing reports of empirical studies for critical 
scientific and peer review. By the standards of this scientific review 
process, the level of documentation presented in the estimation 
methodology report is quite high.
    Some comments indicated that no adjustment was made in the 
methodology to address the phenomenon of different levels of reporting 
of psychiatric symptoms by ethnic groups.
    The technical experts included information to discriminate 
nonhispanic whites from all other racial groups in the model. No fine-
grained distinctions were made about race/ethnicity because of the 
small numbers of people in specific race/ethnicity subsamples in the 
surveys that were analyzed. As part of the analysis, the technical 
experts obtained all the information that was readily available from 
the Census Bureau on Census Tract-level, County-level, and State-level 
demographic variables. All these variables were included in efforts to 
predict and estimate the prevalence of SMI.
    Some comments suggested that the factor analysis was inadequate and 
that important issues not described (e.g., the number of variables in 
the analysis or how missing data were handled) could have affected the 
results.
    The factor analysis was carried out on a Census data file 
containing County-level data from the 1990 Census. The sample size was 
the number of Counties in the U.S., while the number of variables was 
over 100 Census characteristics. Some of the characteristics were quite 
highly correlated across Counties, like median household income and 
mean household income, or the number of men in a County and the number 
of women in a County. Factor analysis was used as a way of reducing 
redundancy prior to performing further analyses. The factor analytic 
procedures employed represent the state-of-the-art for similar data 
reduction procedures.
    Some comments were made about the use of varimax rather than 
oblique rotation, the decision to examine only the first ten factors in 
the solution, and the use of factor-weighted scores.
    The group of technical experts explored both oblique and rigid 
rotations and also looked at the unique factors after the first ten. 
``Unique factors'' refer to factors in which there is only a single 
variable with a high loading. Variance was noted to be trivial after 
the first ten factors. No factors after the first ten had more than one 
variable with high loading. Factor-weighted and factor-based scales are 
very highly correlated, therefore the choice of one over the other did 
not affect the results of the analyses.
    Some comments noted that Census data are stronly influenced by 
population size and suggested that this effect could be removed to find 
a more meaningful structure.
    A similar procedure was actually used. All count variables were 
transformed (e.g., number of vacant houses, number of people on 
welfare) into population proportions. This procedure removes the 
effects of population size.
    Some comments suggested that users of the public mental health 
system have low levels of income. However, the key significant income 
predictor was an interaction term for high income and urbanicity 
associated with reduced prevalence of SMI.
    The technical experts were surprised to find the absence of high 
income people was a stronger predictor of SMI than the presence of low 
income people. This was investigated in considerable detail, trying a 
number of different specifications in search of a low income effect. 
These included a specification involving the assessment of 
neighborhoods with a bimodal distribution of high income and low income 
people, as well as a specification that examined the effect of degree 
of variation in income in the community (e.g., differentiation between 
a community with an average income of $30,000 due to all families 
having this income versus another with an average of $30,000 due to 10% 
of families making $210,000 and another 90% making $10,000. After a 
careful review, the technical experts concluded that the data did not 
support a low income effect or any effect of income variance for SMI. 
It is important to note that there is a strong low income effect for 
estimates of persons with severe and persistent mental illness (SPMI), 
even though such an effect could not be found for SMI.
    It is noteworthy that the analysis of income effects was confined 
to neighborhoods (Census Tracts) due to the fact that the Census Bureau 
would not release individual-level family income data cross-classified 
by other Census variables at either the Tract, County, or State levels. 
The Census Bureau decision was based on the concern to maintain 
confidentiality of Census records.
    Some comments requested future consideration of SMI incidence.
    Currently, no nationally representative data are available on 
incidence of SMI. The group of technical experts has made 
recommendations to CMHS regarding the need for future data collection 
to obtain incidence data.

State Differences

    Some comments suggested that SMI prevalence was higher in the West 
and the Southwest, compared with other regions of the US.
    The magnitude of the SMI estimates, averaging approximately 5-6% of 
the adult population in a year, is very plausible. It is generally 
agreed that 2-3% of the adult population suffer from severe and 
persistent disorders such as schizophrenia, other nonaffective 
psychoses, and bipolar disorder. Based upon the estimation methodology, 
an additional 2-3% of the adult population suffer from serious anxiety, 
nonbipolar mood disorders, and other disorders, for a total of 5-6%. It 
would be highly suspicious if the estimates were any less.
    In the draft notice of the estimation methodology, point estimates 
were provided for State SMI prevalence figures. In this final notice, a 
95% confidence interval is used to calculate the SMI prevalence rate as 
a range. State prevalence of SMI is estimated to be between the lower 
and upper percent limits for each State. Based on these analysis, one 
cannot conclude that rates differ among States. Hence, the same 
prevalence rate and percentage standard error are applied to all States 
to produce the numerical estimates provided in table 1. See the 
footnote to table 1 for further information on this estimation 
procedure.
    Some comments noted that the inclusion of Alzheimer's disease 
contributes appreciably to the counts and that, since the definition 
cannot be changed at this point, the report should clearly note that 
this is the case.
    This is a good suggestion.
    Some comments suggested that only 10 States are at or below the 
national average, and that the majority of these States are quite 
small, therefore a mathematical explanation of this phenomenon would be 
appropriate.
    This comment does not reflect the nature of the estimation 
methodology. As stated in the draft Federal Register notice of March 
23, 1997, Volume 62, No 60, page 14931, the national total estimated 
number of persons with SMI is derived from direct, weighted counts

[[Page 33893]]

from the surveys used. However, the State totals were computed from 
synthetic modeling at the County level, and county estimates were 
summed to arrive at State totals. These two approaches are not the 
same. Therefore, they are subject to different types of sampling and 
non-sampling errors. As a result, the sum of State totals will not 
necessarily equal the U.S. total, and State estimates cannot be 
compared directly with the national average.
    Some comments suggested that use of national probability estimates 
did not permit consideration of regional and state differences, which 
could affect the relationship between key analytical variables.
    Because of the difficulty of obtaining data, the technical experts 
made the assumption that the effects of all the predictor variables 
were the same across all States. More precise estimates could have been 
made if representative samples from each State were available.

Other Related Comments

    Some comments noted that the exclusion of homeless and 
institutionalized persons, those living in group quarters, and those 
without telephones excludes the segments of the population with the 
highest risk of SMI.
    The Epidemiologic Cachement Area (ECA) and the National Commobidity 
Survey (NCS) studies were both household surveys, so there is no 
exclusion of non-telephone households. Although national data were used 
to estimate the overall U.S. prevalence of the omitted population 
groups, due to lack of data, no attempt was made to estimate how many 
homeless people or persons in the other excluded segments reside in 
each State.
    Some comments suggested the need to have prevalence estimates for 
Puerto Rico.
    The prevalence estimates for Puerto Rico are included in this 
notice.
    Some comments suggested validity studies that could form the basis 
for modifications and refinements to the estimation methodology.
    Validation studies could help refine the estimation methodology. 
However, the mandate to the technical experts was to develop the best 
estimates with currently available data rather than only propose new 
data collections. As noted earlier, the technical experts have 
recommended that CMHS carry out a nationally representative survey once 
each decade in the Census year explicitly designed to assess the 
prevalence of SMI and SPMI, with oversampling to allow estimation by 
State. Execution of validation studies as part of this survey would 
permit the evaluation of and increased precision in State-level 
estimates.
    Some comments urged SAMHSA to increase Block Grant Funds for States 
to offer services to the number of persons who have SMI.
    The first step in such a process is the one currently being 
undertaken, i.e., using the estimation methodology to produce estimates 
showing that the number of adults with SMI exceeds the number who can 
be served with currently available funds.

SMI Estimation Methodology

Data Sources

    Data from two major national studies, the NCS and the ECA, were 
used to estimate the prevalence of adults with SMI. The NCS, a 
nationally representative sample household survey conducted in 1990-91 
assessed the prevalence of DSM-III-R disorders in persons aged 15-54 
years old. This sample included over 1,000 census tracts in 174 
counties in 34 States. The ECA, a general population survey of five 
local areas in the U.S., was conducted in 1980-85 to determine the 
prevalence of DSM III disorders in persons age 18 and older. The ECA 
data utilized for the present analysis were limited to the Baltimore 
site because that was the only site that had disability data needed to 
operationalize the criteria for SMI. Although the Baltimore sample is 
not nationally representative, it is used in this analysis because the 
ECA provides a rough replication and check on the NCS data. Also, the 
NCS does not have data on persons age 55 and older, so the ECA data are 
used to estimate the prevalence of serious mental illness among persons 
55 years and older.
    The group of technical experts determined that it is not possible 
to develop estimates of incidence using currently available data. 
However, it is important to note that incidence is always a subset of 
prevalence. In the future, information on both incidence and prevalence 
data will need to be collected.

Serious Mental Illness (SMI)

    As previously defined by CMHS, adults with a serious mental illness 
are persons 18 years and older who, at any time during a given year, 
had a diagnosable mental, behavioral, or emotional disorder that met 
the criteria of DSM-III-R and ``* * * that has resulted in functional 
impairment which substantially interferes with or limits one or more 
major life activities.* * *.'' The definition states that ``* * * 
adults who would have met functional impairment criteria during the 
referenced year without the benefit of treatment or other support 
services are considered to have serious mental illnesses. * * *'' DSM-
III-R ``V'' codes, substance use disorders, and developmental disorders 
are excluded from this definition.
    The following criteria were used to operationalize the definition 
of serious mental illness in the NCS and ECA data:
    (1) Persons who met criteria for disorders defined as severe and 
persistent mental illnesses (SPMI) by the National Institute of Mental 
Health (NIMH) National Advisory Mental Health Council (National 
Advisory Mental Health Council, 1993).
    To this group were added:
    (2) Persons who had another 12-month DSM-III-R mental disorder 
(with the exclusions noted above), and

--Either planned or attempted suicide at some time during the past 12 
months, or
--Lacked any legitimate productive role, or
--Had a serious role impairment in their main productive roles, for 
example, consistently missing at least one full day of work per month 
as a direct result of their mental health, or
    -Had serious interpersonal impairment as a result of being totally 
socially isolated, lacking intimacy in social relationships, showing 
inability to confide in others, and lacking social support.

Estimation Procedures

    Two logistic regression models were developed to calculate 
prevalence estimates for adults with SMI.
    (a) A Census Tract Model for years in which the decennial U.S. 
census is conducted.
    (b) A County-Level Model to be used in intercensal years.
    In non-censal years, the county-level model will be used to 
estimate SMI prevalence, after adjusting for its known relationship 
with the census tract model.

Formula

Census-Tract Model
    Using 1990 census data, a logistic regression model was developed 
to calculate predicted rates of SMI for each cell of an age by sex by 
race table for each of the 61,253 Census Tracts in the country. Next, 
the rates were multiplied by cell frequencies and subtotaled to derive 
tract-level estimates. Finally, the tract-level estimates were 
aggregated to arrive at county-level and state-level prevalence 
estimates of adults with SMI. This regression methodology is often used 
in small area estimation (Ericksen,

[[Page 33894]]

1974; Purcell & Kish, 1979). The actual Census Tract Model equation is 
specified immediately below:

               Parameter Estimates for Census Tract Model
------------------------------------------------------------------------
                                                         95% Confidence
             Predictor                  Odds ratio          interval
------------------------------------------------------------------------
    Intercept.....................              *0.02        (0.01-0.04)
------------------------------------------------------------------------
              Individual-Level Variables
------------------------------------------------------------------------
Age:
    18-24.........................              *1.94        (1.18-3.17)
    25-34.........................               1.32        (0.86-2.03)
    35-44.........................               1.46        (0.96-2.21)
    45-54.........................               1.00
Sex:
    Female........................              *2.23        (1.57-3.19)
    Male..........................               1.00
Race:
    Nonhispanic white.............               1.00
    Black/Hispanic/other..........              *0.49        (0.28-0.87)
Marital Status:
    Married/Cohabiting............               1.00
    Never Married.................              *3.90        (1.15-3.08)
    Separated/Divorced/Widowed....              *1.88        (2.41-6.31)
------------------------------------------------------------------------
             Census Tract Level Variables
------------------------------------------------------------------------
    F2 (High socio-economic                      1.16        (0.90-1.49)
     status)......................
    F4 (Immigrants)...............               0.99        (0.85-1.14)
------------------------------------------------------------------------
                County-Level Variables
------------------------------------------------------------------------
County Urbanicity:
    Metropolitan..................               1.12        (0.85-1.49)
    Other.........................               1.00
------------------------------------------------------------------------
             Interactions Among Variables
------------------------------------------------------------------------
FemaleXSeparated/Divorced/Widowed.              *0.47        (0.24-0.91)
FemaleXNever Married..............              *0.47        (0.28-0.78)
Non WhiteXSeparated/Divorced/                   *2.62        (1.29-5.33)
 Widowed..........................
Non WhiteXNever Married...........               1.81        (0.95-3.44)
FemaleXF2.........................              *0.70        (0.51-0.96)
UrbanicityXF2.....................              *0.75        (0.52-0.95)
F2XF4.............................              *0.78       (0.64-0.94)
------------------------------------------------------------------------
*Significant at the .05 level, two tailed test; F2=Census Tract factor
  score for high socioeconomic status (SES); F4=Census Tract factor
  score for immigrants.

    The estimate for persons 55 years and older is derived from 
analysis of ECA data in conjunction with NCS data. The prevalence 
ratios among ECA respondents ages 55-64 and 65 years and above, were 
found to be 84 and 31 percent as large, respectively, as the prevalence 
estimate for NCS respondents 18-54 years old, after controlling for 
differences in gender and race. NCS State-level estimates were 
extrapolated using these ratios. These ratios did not differ 
significantly by sex or race. A factor of .81 was applied to State-
level SMI estimates for the age range 18-54 to derive the rate for the 
age range 55-64, and .31 was used to arrive at the estimate for person 
65 and older. A weighted sum (by age distribution of each State) was 
calculated to determine the final State-level SMI prevalence estimate.
County Model
    U.S. Census Bureau tract-level data are available only for years in 
which the decennial U.S. Census is conducted. To obtain prevalence 
estimates for adults with SMI during intercensal years, the group of 
technical experts used biennial individual- and county-level data from 
the Census Bureau's small area estimation program. Predicted values 
from the logistic regression equation were used to calculate county-
level estimates. In contrast to the Census Tract Model, the initial 
estimates using this approach were generated at the county level. These 
county-level estimates are then summed to provide State-level 
prevalence estimates. The actual county-level model equation is 
specified immediately below:

               Parameter Estimates for County-Level Model
------------------------------------------------------------------------
                                                         95% Confidence
             Predictor                  Odds ratio          interval
------------------------------------------------------------------------
    Intercept.....................             * 0.04       (0.02-0.07)

[[Page 33895]]

 
              Individual-Level Variables
------------------------------------------------------------------------
Age:
    18-24.........................               1.69        (1.00-2.85)
    25-34.........................               1.10        (0.65-1.88)
    35-44.........................               1.24        (0.71-2.15)
    45-54.........................               1.00  .................
Sex:
    Female........................               1.58        (1.17-2.13)
    Male..........................               1.00  .................
------------------------------------------------------------------------
                County-Level Variables
------------------------------------------------------------------------
Urbanicity:
    Metropolitan..................               1.35        (0.99-1.85)
    Other.........................               1.00  .................
------------------------------------------------------------------------
*Significant at the 0.05 level, two-tailed test.

    Adjustment for persons age 55 years and older is carried out as in 
the Census Tract Model. An adjustment factor (Census Bureau, Fay, 1987; 
Fay & Herriot, 1979) based on the ratio of County-Level Model estimates 
for 1990 and Census Tract Model estimates for 1990 can be used to 
adjust estimates for subsequent years from the County-Level Model. This 
procedure assumes that the Census Tract Model is more accurate than the 
County-Level Model.

County and State Estimates

    As stated earlier, Census Tract Model prevalence estimates were 
summed to derive county estimates, and county estimates were summed to 
arrive at State estimates. The 12-month prevalence of SMI is estimated 
nationally to be 5.4 percent (with a standard error of 0.9 percent) or 
10.2 million people in the adult household population (95 percent 
confidence interval ranging from 7.0 million to 13.4 million), of which 
2.6 percent or 4.8 million adults have SPMI (figure 1). When the 
standard error is considered, State estimates do not vary. Hence, State 
estimates are defined as 5.4 percent of the adult population, with a 95 
percent confidence interval of plus or minus 1.96 times 0.9 percent.
    The above estimates are based on noninstitutionalized persons 
residing in the community. Limited information currently exists on SMI 
estimates for persons institutionalized (i.e., persons in correctional 
institutions, nursing homes, the homeless, persons in military 
barracks, hospitals/schools/homes for persons who are mentally ill or 
mentally retarded). Fischer and Breakey (1991) indicate that, on 
average, the SMI prevalence rate for these groups (including about 5 
million people or 2.7 percent of the U.S. adult population) is about 50 
percent. The following assumptions were made in deriving rough 
estimates of SMI prevalence for persons who are institutionalized: (a) 
For 1.1 million residents of correctional institutions, 100 percent of 
whom are adults, prevalence of SMI is estimated to be 57 percent; (b) 
For 1.8 million residents of nursing homes, 100 percent of whom are 
adults, prevalence of SMI is estimated to be 46 percent; (c) For 0.5 
million persons who are homeless, 80 percent of whom are adults, 
prevalence of SMI is estimated to be 50 percent; (d) For 0.6 million 
persons in military barracks, all of whom are adults, the SMI 
prevalence rate is equivalent to that of the adult household 
population; (e) For 0.4 million persons in hospitals, homes, and 
schools for persons who are mentally ill, 80 percent of whom are 
adults, prevalence of SMI is estimated to be 100 percent. (f) For 0.6 
million persons in other institutional settings such as chronic disease 
hospitals, homes and schools for persons with physical disability, and 
rooming houses, 50 percent of whom are adults, prevalence of SMI is 
estimated to be 50 percent.
    State estimates of each of these populations can be added to the 
State SMI populations identified below.
    Only a portion of adults with SMI seek treatment in any given year. 
Due to the episodic nature of SMI, some persons may not require mental 
health service at any particular time.

Provision of Estimates to States

    CMHS will provide each State mental health agency with estimates in 
order to initiate the first cycle of use. Subsequently, CMHS will 
provide technical assistance to States to implement the methodology 
using State demographic information.
    The intial set of State estimates is provided in table 1 below. 
Further background information on these estimates can be found in 
Kessler, et al. (1998).

          Table 1.--Estimated 12-Month Number of Persons With Serious Mental Illness, Age 18 and Older
                                               [By State, 1990 *]
----------------------------------------------------------------------------------------------------------------
                                                                                      95% confidence interval
                              State                               Point estimate -------------------------------
                                                                                    Lower limit     Upper limit
----------------------------------------------------------------------------------------------------------------
Alabama.........................................................         161,017         110,327         211,708
Alaska..........................................................          20,396          14,730          26,817
Arizona.........................................................         144,942         104,680         190,572
Arkansas........................................................          93,398          63,995         122,801
California......................................................       1,188,502         814,344       1,562,660
Colorado........................................................         131,389          90,026         172,752

[[Page 33896]]

 
Connecticut.....................................................         137,027          93,889         180,165
Delaware........................................................          27,153          18,605          35,701
District Columbia...............................................          26,450          18,123          34,776
Florida.........................................................         543,871         372,652         715,090
Georgia.........................................................         256,549         175,784         337,315
Hawaii..........................................................          44,718          30,640          58,795
Idaho...........................................................          37,711          27,235          49,582
Illinois........................................................         458,149         313,917         602,381
Indiana.........................................................         220,763         151,263         290,262
Iowa............................................................         111,125          76,141         146,109
Kansas..........................................................          98,062          67,190         128,933
Kentucky........................................................         147,485         101,054         193,915
Louisiana.......................................................         161,606         110,730         212,482
Maine...........................................................          49,622          34,000          65,244
Maryland........................................................         195,438         133,911         256,965
Massachusetts...................................................         251,821         172,544         331,098
Michigan........................................................         369,173         252,952         485,394
Minnesota.......................................................         173,249         118,708         227,790
Mississippi.....................................................          98,629          67,579         129,678
Missouri........................................................         205,321         140,683         269,959
Montana.........................................................          31,156          21,348          40,964
Nebraska........................................................          62,066          42,527          81,605
Nevada..........................................................          48,864          33,481          64,247
New Hampshire...................................................          44,847          30,728          58,965
New Jersey......................................................         320,259         219,437         421,082
New Mexico......................................................          57,690          39,528          75,851
New York........................................................         741,469         535,505         974,894
North Carolina..................................................         271,214         185,832         356,597
North Dakota....................................................          25,024          17,146          32,902
Ohio............................................................         434,558         297,753         571,363
Oklahoma........................................................         124,663          85,417         163,909
Oregon..........................................................         114,382          78,373         150,392
Pennsylvania....................................................         490,689         336,213         645,165
Puerto Rico.....................................................         195,719         159,550         231,817
Rhode Island....................................................          42,000          28,778          55,222
South Carolina..................................................         138,591          94,960         182,221
South Dakota....................................................          26,867          18,409          35,325
Texas...........................................................         656,136         449,575         862,698
Tennessee.......................................................         197,671         135,441         259,901
Utah............................................................          59,152          40,530          77,774
Vermont.........................................................          22,662          15,528          29,797
Virginia........................................................         252,861         173,257         332,466
Washington......................................................         194,686         133,396         255,977
West Virginia...................................................          72,895          49,946          95,843
Wisconsin.......................................................         194,550         133,303         255,798
Wyoming.........................................................          17,175          11,768          22,582
                                                                 -----------------------------------------------
    Total.......................................................      10,191,412       7,043,431      13,374,301
----------------------------------------------------------------------------------------------------------------
Does not include persons who are homeless or are institutionalized.
* Because there are no differences among States, the estimate for each State is calculated as 5.4 percent of the
  total State adult population. The size of the 95 percent confidence interval for each State is equal to the
  percentage estimate plus or minus 1.96x0.9 percent. The percentage estimate and the percentage standard error
  are identical across States. However, the numeric estimate and numeric standard error vary depending on the
  State adult population. The percentage standard error (0.9 percent) used to compute the upper and lower 95-
  percent confidence limits is estimated using jackknife repeated replication (JRR) variance analysis (Kish and
  Frankel 1974). The JRR calculations assume that the imputation ratios and the population proportions in the
  different age groups based on the census data are correct. The confidence limits simulate the error introduced
  into the estimates by imprecision in the prevalence estimates for NCS respondents in the age range 18-54.

Limitations

    The ECA and NCS were designed to study lifetime prevalence of 
mental disorders rather than 12-month prevalence. As a result, the 
emphasis in diagnostic assessment was on lifetime disorders. In 
addition, functional impairment was not a primary focus in either the 
ECA or the NCS.
    Current data cannot provide estimates of incidence. Additional 
information needs to be collected in the future.
    It is anticipated that additional work will be done in future years 
to refine and update the estimation methodology. CMHS will apprise 
States as this work develops.

References

Ericksen, E.P. (1974). A regression method for estimating population 
changes of local areas. Journal of American Statistical Association, 
69, 867-875.

[[Page 33897]]

Fay, R.E. (1987). Application of multivariate regression to small 
domain estimation. In R. Platek, J.N.K. Rao, C.E. Sarndal & M.P. 
Singh (Eds.), Small Area Statistics: An International Symposium, pp. 
91-102. New York: John Wiley and Sons.
Fay, R.E., & Herriot, R. A. (1979). Estimates of income for small 
places: An application of James-Stein procedures to Census data. 
Journal of the American Statistical Association, 74, 269-277.
Fischer, P.J., Breakey, W.R. (1991). The Epidemiology of alcohol, 
drug, and mental disorders among homeless persons. American 
Psychologist. 46, 1115-1125.
Kessler, R.C., et al. Estimation of the 12-month Prevalence of 
Serious Mental Illness (SMI). (1996). Unpublished reports to CMHS.
Kessler, R.C., et al. Population-Based Analyses: A Methodology for 
Estimating the 12-Month Prevalence of Serious Mental Illness. R.W. 
Manderscheid and M.J. Henderson, (eds.) Mental Health, United 
States, 1998. DHHS Pub. Washington, D.C.: Supt. of Docs. U.S. Govt. 
Print Off., pp. 99-112, 1998.
Kish, L., and Frankel, M.R. Inferences from complex samples, Journal 
of the Royal Statistical Society, Series B 36:1-37, 1974.
National Advisory Mental Health Council. (1993). Health care reform 
for Americans with severe mental illness. American Journal of 
Psychiatry, 150, 1447-1465.
Purcell, N.J., & Kish, L. (1979). Estimation for small domains. 
Biometrics, 35, 365-384.
Regier, D.A., Narrow, W.E., Rae, D.S., Manderscheid, R.W., Locke, 
D.Z., Goodwin, F.K. (1993). The de Facto US Mental and Addictive 
Disorders Service System. Archives of General Psychiatry, 50, 85-94.

    Dated: June 7, 1999.
Richard Kopanda,
Executive Officer, Substance Abuse and Mental Health Services 
Administration.

BILLING CODE 4162-20-P
[GRAPHIC] [TIFF OMITTED] TN24JN99.048


[FR Doc. 99-15377 Filed 6-23-99; 8:45 am]
BILLING CODE 4162-20-C