Uninsurance Among Nonelderly Adults With and Without Frequent Mental and Physical Distress in the United States

Article (PDF Available)inPsychiatric services (Washington, D.C.) 62(10):1131-7 · October 2011with5 Reads
DOI: 10.1176/appi.ps.62.10.1131 · Source: PubMed
Abstract
This research describes uninsurance rates over time among nonelderly adults in the United States with or without frequent physical and mental distress and provides estimates of uninsurance by frequent mental distress status and sociodemographic characteristics nationally and by state. Data from the 1993 through 2009 Behavioral Risk Factor Surveillance System, a telephone survey that uses random-digit dialing, were used to examine the prevalence of uninsurance among nearly 3 million respondents by self-report of frequent physical and frequent mental distress and sociodemographic characteristics, response year, and state of residence. After adjustment for sociodemographic characteristics, uninsurance among adults aged 18 to 64 years was markedly higher among those with frequent mental distress only (22.6%) and those with both frequent mental and frequent physical distress (21.8%) than among those with frequent physical distress only (17.7%). The prevalence of uninsurance did not differ markedly between those with only frequent mental distress and those with both frequent mental distress and frequent physical distress. The prevalence of uninsurance among those with frequent mental distress only and those with neither frequent mental distress nor frequent physical distress increased significantly over time. Uninsurance rates among nonelderly adults with frequent mental distress were disproportionately high. The results of this analysis can be used as baseline data to assess whether implementation of the Affordable Care Act is accompanied by changes in health care access, utilization, and self-reported measures of health, particularly among those with mental illness.
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T
he 12-month estimates of di-
agnosable mental disorders
among adults in the United
States range from 26% to 30%, and
lifetime estimates range from 46% to
50% (1,2). Although mental disorders
account for only 6.2% of the nation’s
health care expenditures in direct
costs, their indirect costs, in terms of
reduction in labor, public income
support payments, incarceration, and
homelessness, are exorbitant (3).
For example, depression alone
causes a loss of $44 billion each year
in both presenteeism, defined as loss
of productivity that occurs when em-
ployees perform poorly due to com-
ing to work sick, and absenteeism (4).
Moreover, among those with serious
mental illness—approximately 6% of
the population (1)—each year $100
billion is spent on health care (5),
$193 billion is lost in earnings (6), and
$24 billion is spent for disability ben-
efits (7). Decreased adherence with
medical regimens, increased risk of
adverse health behaviors, and in-
creased risk of heart disease and oth-
er chronic conditions compound the
indirect cost of mental illness (8) and
further jeopardize insurance status
through ineligibility and job loss (9).
Notably, increased costs are not limit-
ed to those with the most serious ill-
nesses. Without treatment, even mild
disorders can become serious (1) and
assume a chronic course (10).
Persons with mental illness face
many challenges with respect to
health care insurance coverage. They
are disproportionately denied insur-
ance because of preexisting conditions
(11). Moreover, among those who are
insured, high cost-sharing, for exam-
ple, through deductibles, copayments,
and coinsurance, and limits on the
number of covered visits make it diffi-
cult to obtain adequate care (11–14).
On March 23, 2010, President
Obama signed the Patient Protection
Uninsurance Among Nonelderly Adults
With and Without Frequent Mental and
Physical Distress in the United States
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Dr. Strine, Dr. Zack, Mr. Dhingra, and Dr. Simoes are affiliated with the National Center
for Chronic Disease Prevention and Health Promotion, Division of Adult and Community
Health, Behavioral Surveillance Branch, Centers for Disease Control and Prevention, 4770
Buford Highway NE, Mailstop K-66, Atlanta, GA 30341 (e-mail: tws2@cdc.gov). Dr. Druss
is with the Rollins School of Public Health, Emory University, Atlanta.
Objectives: This research describes uninsurance rates over time among
nonelderly adults in the United States with or without frequent physical
and mental distress and provides estimates of uninsurance by frequent
mental distress status and sociodemographic characteristics nationally
and by state. Methods: Data from the 1993 through 2009 Behavioral
Risk Factor Surveillance System, a telephone survey that uses random-
digit dialing, were used to examine the prevalence of uninsurance
among nearly 3 million respondents by self-report of frequent physical
and frequent mental distress and sociodemographic characteristics, re-
sponse year, and state of residence. Results: After adjustment for so-
ciodemographic characteristics, uninsurance among adults aged 18 to
64 years was markedly higher among those with frequent mental dis-
tress only (22.6%) and those with both frequent mental and frequent
physical distress (21.8%) than among those with frequent physical dis-
tress only (17.7%). The prevalence of uninsurance did not differ
markedly between those with only frequent mental distress and those
with both frequent mental distress and frequent physical distress. The
prevalence of uninsurance among those with frequent mental distress
only and those with neither frequent mental distress nor frequent phys-
ical distress increased significantly over time. Conclusions: Uninsurance
rates among nonelderly adults with frequent mental distress were dis-
proportionately high. The results of this analysis can be used as baseline
data to assess whether implementation of the Affordable Care Act is ac-
companied by changes in health care access, utilization, and self-re-
ported measures of health, particularly among those with mental illness.
(Psychiatric Services 62:1131–1137, 2011)
and Affordable Care Act (P.L. 111-
148). This act was later amended
through a reconciliation process, and
the resulting Health Care and Educa-
tion Reconciliation Act (P.L. 111-152)
was enacted on March 30, 2010. It is
now often referred to as the Afford-
able Care Act (ACA). The purpose of
the ACA is to eliminate the sociode-
mographic disparities in health care
coverage by holding insurance com-
panies more accountable, lowering
health care costs, and guaranteeing
more health care choices (www.
healthcare.gov/law/about/index.html).
The ACA also prohibits insurers from
denying coverage or charging more
for persons with preexisting condi-
tions (15), another factor that dispro-
portionately affects insurance cover-
age among persons with mental ill-
ness (11). Incremental reforms began
in 2010, but the most substantial
changes, such as individual mandates,
employer requirements, expansion of
public programs, premium- and cost-
sharing to individuals, premium sub-
sidies to employers, tax changes, and
health insurance exchanges, take ef-
fect in 2014 (www.commonwealth
fund.org/Health-Reform/Health-Re
form-Resource.aspx).
This study provided information
about uninsurance rates during four
retrospective time periods for ongo-
ing trend analysis of changes in insur-
ance coverage before and after phas-
ing in of the ACA. (Four time periods
were chosen because two points are
not sufficient to establish a trend
line.). Experience in Massachusetts,
which enacted a similar mandatory
insurance act on April 12, 2006,
showed that health insurance uptake,
in spite of penalties, is slow and
steady and is characterized by pat-
terns related to sociodemographic
factors, behaviors, and perceived
health needs of individuals (16–18).
In this study, data from the 1993
through 2009 Behavioral Risk Factor
Surveillance System (BRFSS) were
used to examine uninsurance rates
among nonelderly adults in the Unit-
ed States over four time periods
(1993–1996, 1997–2001, 2002–2005,
and 2006–2009) grouped by whether
they experienced frequent physical or
mental distress. Results of the analy-
sis were used to determine the group
or groups at highest risk of uninsur-
ance over the four time periods. They
were also used to generate adjusted
nationwide and state-specific esti-
mates of uninsurance on the basis of
sociodemographic factors.
Methods
The BRFSS is a state-based surveil-
lance system, operated by state health
departments in collaboration with the
Centers for Disease Control and Pre-
vention. The objective of the BRFSS is
to collect uniform, state-specific data
about preventive health practices and
risk behaviors linked to chronic dis-
eases, injuries, and preventable infec-
tious diseases in the adult population
(19,20). Trained interviewers collect
data on a standardized questionnaire
monthly from an independent proba-
bility sample of households with tele-
phones among the noninstitutional-
ized U.S. adult population. The BRF-
SS questionnaire consists of core ques-
tions asked in all 50 states and the Dis-
trict of Columbia; supplemental mod-
ules containing a series of questions
about specific topics, such as adult
asthma history, intimate partner vio-
lence, and mental health; and state-
added questions. All BRFSS question-
naires, data, and reports are available
at www.cdc.gov/brfss.
Beginning in 1993, questions about
mentally and physically unhealthy days
were included in the BRFSS. These
measures are widely used in state
health reports and annual reports of
state-level health status and mental
health indicators (21). They are useful
for identifying unmet health needs
and disparities among demographic
and socioeconomic subpopulations,
characterizing the symptom burden of
disabilities and chronic diseases, and
tracking population patterns and
trends (21). Unlike physical and men-
tal health screening questionnaires
that attempt to assess the likelihood
that the respondent meets criteria for
a particular mental or physical illness,
the physically and mentally unhealthy
days questions assess perceived level
of physical and mental health.
Two questions involve respondents’
self-assessment of their health over
the previous 30 days. The question,
“How many days was your physical
health, which includes physical illness
or injury, not good?” assesses physi-
cally unhealthy days. The question,
“How many days was your mental
health, which includes stress, depres-
sion, and problems with emotions,
not good?” assesses mentally un-
healthy days. These questions have
demonstrated validity and reliability
for population health surveillance
(21–23). For example, adults with se-
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TTaabbllee 11
Percentage of uninsured persons, by sociodemographic characteristics and year
a
1993–1996 1997–2001 2002–2005 2006–2009
Characteristic % SE % SE % SE % SE
Total 16.1 .1 16.5 .1 17.9 .1 18.0 .1
Sex
Male 17.3 .2 17.2 .2 19.3 .1 19.4 .2
Female 15.0 .1 15.7 .1 16.5 .1 16.5 .1
Age
18–34 22.3 .2 22.7 .2 25.3 .2 26.2 .2
35–64 12.1 .1 13.0 .1 14.0 .1 13.9 .1
Race or ethnicity
White, non-Hispanic 13.2 .1 12.6 .1 12.9 .1 12.7 .1
Black, non-Hispanic 20.6 .3 20.5 .3 21.2 .3 23.0 .3
Hispanic 34.2 .6 35.8 .5 38.5 .4 38.1 .4
Other, non-Hispanic
b
19.1 .6 18.3 .5 18.3 .4 17.3 .4
Education
Less than high school 34.3 .5 39.2 .4 42.8 .4 43.2 .4
High school 18.8 .2 19.7 .2 22.7 .2 24.6 .2
Greater than high school 10.8 .1 10.3 .1 11.1 .1 10.9 .1
a
Behavioral Risk Factor Surveillance System respondents (N=2,815,246)
b
Asian, Native Hawaiian or Pacific Islander, American Indian or Alaska Native, other, and multiple
races or ethnicities
rious psychological distress report
five times as many mentally un-
healthy days as those without serious
psychological distress (24).
We categorized mentally and phys-
ically unhealthy days as indicating ei-
ther infrequent distress (zero to 13
days) or frequent distress (14 to 30
days). To be included in the analysis,
persons must have responded to both
questions about physically and men-
tally unhealthy days. Responses were
further categorized into four mutual-
ly exclusive groups—those with nei-
ther frequent mental nor physical dis-
tress, those with frequent mental dis-
tress only, those with frequent physi-
cal distress only, and those with both
frequent mental and physical distress.
These categories were later collapsed
into two categories, frequent mental
distress and no frequent mental dis-
tress, on the basis of the uninsurance
patterns observed in the data.
We categorized health care cover-
age using yes or no responses to the
question, “Do you have any kind of
health care coverage, including
health insurance, prepaid plans such
as health maintenance organizations,
or Medicare or other government
plan?” Covariates of interest included
sex, age group (18–34 and 35–64),
race or ethnicity (non-Hispanic
white, non-Hispanic black, Hispanic,
and non-Hispanic other), and educa-
tion (less than high school, high
school graduate, and at least some
college education). We limited data
analyses to those aged 18 to 64 years
because those aged 65 years or older
were generally covered by Medicare.
Data, including information about
insurance status and physically and
mentally unhealthy days, were avail-
able for 2,815,246 respondents aged
18 to 64 years. Data were available for
all states in all years except in 2002,
when data were available for only 22
states. Unadjusted prevalence esti-
mates were calculated to examine
uninsurance—that is, lack of health
care coverage—over time by sociode-
mographic characteristic and state to
provide background about the popu-
lation being examined. Logistic re-
gression models were created to ex-
amine adjusted prevalence estimates
(predicted marginals) of uninsurance
over time by mutually exclusive cate-
gory of frequent physical and mental
distress status adjusted for sex, age,
race or ethnicity, and educational sta-
tus. Further analyses examined the
adjusted prevalence estimates of
uninsurance over four time periods
by frequent mental distress status, in-
dividual sociodemographic character-
istic, and individual state. SUDAAN
software was used for all analyses to
account for BRFSS’s complex survey
design.
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Percentage of uninsured persons by state and year
a
1993–1996 1997–2001 2002–2005 2006–2009
State % SE % SE % SE % SE
Total 16.1 .1 16.5 .1 17.9 .1 18.0 .1
Alabama 16.4 .6 18.2 .6 18.3 .6 18.2 .5
Alaska 18.1 .8 21.8 .8 18.8 .6 18.0 .6
Arizona 18.7 .8 17.1 .7 21.6 .7 20.6 .8
Arkansas 19.8 .6 19.9 .6 21.8 .5 23.3 .6
California 22.5 .5 21.6 .4 18.8 .4 19.7 .4
Colorado 16.6 .6 15.8 .6 17.6 .4 19.0 .4
Connecticut 11.2 .5 10.8 .4 11.1 .3 10.9 .4
Delaware 13.5 .5 10.7 .5 9.1 .5 9.7 .4
District of
Columbia 12.5 .7 13.5 .6 12.0 .6 8.8 .4
Florida 21.3 .5 21.4 .4 23.4 .5 23.1 .5
Georgia 12.6 .5 15.4 .5 17.9 .4 18.9 .5
Hawaii 7.5 .4 8.1 .4 9.4 .3 8.3 .3
Idaho 16.9 .5 19.4 .4 19.1 .4 21.7 .5
Illinois 12.7 .5 13.1 .4 15.5 .4 17.0 .5
Indiana 13.1 .5 14.1 .5 16.7 .4 17.9 .5
Iowa 11.1 .4 11.4 .4 12.1 .4 11.9 .4
Kansas 12.0 .5 12.3 .4 14.1 .3 14.3 .4
Kentucky 17.6 .5 16.9 .4 19.0 .4 18.5 .5
Louisiana 24.9 .7 24.7 .7 25.3 .4 23.5 .5
Maine 17.4 .7 15.5 .6 14.7 .5 13.3 .4
Maryland 11.2 .3 12.2 .4 12.6 .5 13.2 .4
Massachusetts 11.3 .5 9.8 .4 10.8 .3 6.9 .2
Michigan 11.0 .4 11.2 .4 13.2 .4 14.7 .4
Minnesota 9.0 .3 8.6 .3 7.8 .3 9.5 .4
Mississippi 17.5 .7 20.7 .6 22.2 .5 23.6 .5
Missouri 16.1 .6 14.1 .5 14.9 .4 16.1 .5
Montana 19.0 .7 19.4 .6 23.0 .6 20.3 .5
Nebraska 10.7 .5 9.8 .4 15.4 .5 14.9 .5
Nevada 18.5 .7 17.9 .8 23.4 .7 24.0 .8
New Hampshire 14.1 .6 12.3 .6 13.3 .3 12.8 .4
New Jersey 11.8 .6 13.6 .5 15.6 .3 15.9 .4
New Mexico 22.4 .8 26.1 .6 25.7 .5 24.5 .6
New York 15.0 .5 16.2 .5 17.3 .4 14.7 .4
North Carolina 14.5 .5 15.0 .5 19.8 .4 21.0 .4
North Dakota 13.5 .5 13.7 .5 14.3 .5 13.5 .5
Ohio 12.8 .6 11.6 .5 13.9 .5 14.2 .5
Oklahoma 20.7 .7 20.7 .6 24.6 .4 23.7 .4
Oregon 16.6 .5 16.7 .5 19.9 .4 19.7 .5
Pennsylvania 12.1 .4 11.9 .4 12.7 .4 13.0 .4
Rhode Island 12.4 .6 12.5 .5 12.7 .4 13.0 .5
South Carolina 16.2 .6 17.7 .5 19.7 .4 19.5 .4
South Dakota 12.0 .5 14.2 .5 13.3 .4 14.9 .5
Tennessee 14.0 .4 13.9 .4 14.0 .5 17.7 .6
Texas 23.0 .7 26.5 .5 29.8 .4 28.7 .5
Utah 14.2 .5 13.2 .5 16.3 .4 16.3 .5
Vermont 15.1 .5 13.8 .4 13.3 .3 12.5 .4
Virginia 13.9 .5 12.3 .4 13.4 .4 12.7 .5
Washington 14.3 .4 12.6 .4 15.3 .3 16.1 .3
West Virginia 20.2 .6 21.9 .6 22.9 .5 20.1 .5
Wisconsin 10.7 .5 10.6 .5 11.7 .4 11.5 .4
Wyoming 18.6 .7 20.5 .6 20.0 .4 18.9 .4
a
Behavioral Risk Factor Surveillance System respondents (N=2,815,246)
Results
Uninsurance by year and
sociodemographic characteristic
The proportion of nonelderly unin-
sured adults increased significantly over
time, from 16.1% (95% confidence in-
terval [CI]=15.9–16.3) in 1993–1996 to
18.0% (CI=17.8–18.2) in 2006–2009
(Table 1). Throughout this time, a high-
er proportion of males (versus females),
younger adults (versus older adults),
Hispanics (versus all other racial and
ethnic groups), and persons with less
than a high school education (versus
high school graduates and those with at
least some college or technical school
education) were uninsured.
Uninsurance by state and year
The proportion of nonelderly unin-
sured adults also varied over time by
state (Table 2). The proportion of
uninsured significantly increased be-
tween the time periods 1993–1996
and 2006–2009 in Arkansas, Col-
orado, Georgia, Idaho, Illinois, Indi-
ana, Kansas, Maryland, Michigan,
Mississippi, Nebraska, Nevada, New
Jersey, North Carolina, Oklahoma,
Oregon, South Carolina, South Dako-
ta, Tennessee, Texas, Utah, and
Washington. The proportion of unin-
sured significantly decreased during
the same period in California,
Delaware, the District of Columbia
(Washington, D.C.), Maine, Massa-
chusetts, and Vermont.
Uninsurance by mental and
physical distress and year
Overall between 1993 and 2009, after
adjustment for sex, age, race and eth-
nicity, and educational attainment,
nonelderly adults with neither fre-
quent mental distress nor frequent
physical distress were least likely to
be uninsured (16.6%; 16.4%–16.8%),
followed by those with frequent phys-
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FFiigguurree 11
Prevalence of uninsured persons with or without frequent mental or physical
distress, 1993–2009
a
15
20
25
30
1993–1996 1997–2001 2002–2005 2006–2009
Both frequent physical and mental distress
Frequent mental distress only
Frequent physical distress only
Neither frequent physical nor mental distress
Percentage
a
Behavioral Risk Factor Surveillance System respondents under age 65 (N=2,815,246). Prevalence
adjusted by sex, age, race or ethnicity, and education
TTaabbllee 33
Adusted percentage of uninsured persons with and without frequent mental distress (FMD), by sociodemographic
characteristic and year
a
1993–1996 1997–2001 2002–2005 2006–2009
No No No No
FMD FMD FMD FMD FMD FMD FMD FMD
Characteristic % SE % SE % SE % SE % SE % SE % SE % SE
Total 21.6 .4 15.8 .1 21.3 .3 16.1 .1 22.1 .3 17.2 .1 23.8 .3 17.3 .1
Sex
Male 24.3 .7 17.1 .2 22.8 .6 16.9 .2 24.6 .5 18.5 .1 26.4 .5 18.6 .2
Female 19.4 .5 14.5 .1 19.8 .4 15.2 .1 19.9 .3 15.8 .1 21.5 .3 16.1 .1
Age
18–34 28.7 .8 23.0 .2 28.7 .6 22.6 .2 29.2 .6 24.1 .2 32.2 .6 24.5 .2
35–64 17.7 .5 11.7 .1 17.0 .4 12.4 .1 18.0 .3 13.3 .1 19.0 .3 13.4 .1
Race or ethnicity
b
White, non-Hispanic 17.7 .4 11.8 .1 17.6 .3 11.8 .1 19.0 .3 12.6 .1 20.5 .3 12.6 .1
Black, non-Hispanic 25.2 1.2 19.0 .3 24.2 1.0 19.9 .3 25.6 .8 20.9 .3 28.2 .9 23.3 .3
Hispanic 38.7 2.4 33.7 .6 38.7 1.4 35.3 .5 36.0 1.2 38.3 .4 39.9 1.1 38.5 .4
Other, non-Hispanic 20.5 1.8 18.3 .6 21.2 1.8 18.1 .5 25.3 1.2 17.6 .4 24.7 1.2 16.8 .4
Education
Less than
high school 38.7 1.3 37.4 .5 42.3 1.1 39.7 .5 41.1 .9 41.4 .5 42.7 .9 40.9 .5
High school 26.6 .7 18.7 .2 25.4 .6 19.7 .2 26.8 .5 21.7 .2 29.1 .5 23.2 .2
More than
high school 17.3 .6 10.4 .1 16.3 .4 9.9 .1 17.5 .4 10.4 .1 18.8 .4 10.2 .1
a
Behavioral Risk Factor Surveillance System respondents (N=2,815,246). Model for each sociodemographic characteristic adjusted by sex, age, race or
ethnicity, and education
b
Asian, Native Hawaiian or Pacific Islander, American Indian or Alaska Native, other, and multiple races or ethnicities
ical distress only (17.7%; 17.3%–
18.1%), those with both frequent
mental distress and frequent physical
distress (21.8%; 21.2%–22.4%), and
those with frequent mental distress
only (22.6%; 22.2%–23.0%). The
prevalence of uninsurance remained
fairly consistent over time among
those with frequent physical distress
only and those with both frequent
mental distress and frequent physical
distress. However, it increased signif-
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TTaabbllee 44
Adjusted percentage of uninsured persons with or without frequent mental distress (FMD), by state and year
a
1993–1996 1997–2001 2002–2005 2006–2009
No No No No
FMD FMD FMD FMD FMD FMD FMD FMD
Characteristic % SE % SE % SE % SE % SE % SE % SE % SE
Total 21.6 .4 15.8 .1 21.3 .3 16.1 .1 22.1 .3 17.2 .1 23.8 .3 17.3 .1
Alabama 23.9 2.1 15.4 .5 22.9 1.6 17.3 .6 25.3 1.3 17.4 .6 24.8 1.5 17.9 .6
Alaska 21.7 2.8 17.4 .8 22.9 2.5 21.3 .8 25.2 1.8 18.5 .7 22.0 2.7 17.9 .6
Arizona 25.2 2.9 19.1 .8 27.0 3.6 16.5 .7 21.9 1.9 21.4 .8 27.0 2.4 19.6 .8
Arkansas 22.8 2.1 19 .6 25.1 1.7 19.1 .6 26.5 1.4 21.2 .6 33.3 1.9 22.5 .6
California 29.6 1.9 23.2 .5 25.0 1.3 21.6 .4 22.3 1.2 18.3 .4 23.2 1.0 17.8 .4
Colorado 22.0 1.9 16.3 .6 21.4 1.9 15.5 .6 21.5 1.4 17.2 .4 25.0 1.1 18.2 .4
Connecticut 15.6 2.0 10.6 .5 17.5 2.1 9.6 .4 15.5 1.1 10.7 .4 14.2 1.2 11.3 .4
Delaware 17.2 1.7 12.2 .5 12.7 1.5 10.2 .5 13.4 1.5 9.7 .5 11.6 1.4 10.1 .5
District of Columbia 20.0 3.6 11.5 .7 21.7 2.4 12.7 .6 13.7 1.9 11.9 .6 12.1 1.6 9.0 .5
Florida 27.5 1.6 20.5 .5 26.7 1.4 20.7 .4 29.7 1.5 22.5 .5 30.9 1.3 22.7 .5
Georgia 16.5 1.8 11.9 .5 21.0 1.6 14.8 .5 21.7 1.2 17.1 .5 28.7 1.5 18.4 .5
Hawaii 10.2 1.6 7.2 .4 8.4 1.7 7.8 .4 12.8 1.3 9.3 .3 9.9 1.3 8.5 .4
Idaho 22.7 1.9 16.2 .5 23.8 1.5 19.3 .4 26.5 1.4 18.5 .4 30.7 1.5 20.3 .5
Illinois 19.0 1.9 12.5 .5 17.2 1.4 13.0 .4 21.2 1.4 14.5 .4 22.5 1.5 16.6 .5
Indiana 15.9 1.4 12.5 .5 23.1 1.8 13.5 .5 21.2 1.1 16.1 .4 25.5 1.4 17.0 .5
Iowa 17.3 1.5 10.4 .4 17.4 1.4 10.7 .4 18.7 1.3 11.6 .4 16.4 1.5 11.4 .4
Kansas 20.5 2.2 11.4 .5 17.9 1.5 11.7 .4 21.8 1.1 13.6 .3 22.3 1.2 13.6 .4
Kentucky 21.0 1.3 15.8 .5 19.2 .9 15.8 .4 23.5 1.0 18.4 .5 26.1 1.3 18.9 .6
Louisiana 29.2 2.3 23.5 .7 33.2 2.1 23.4 .7 33.9 1.5 24.2 .4 33.0 1.6 23.9 .5
Maine 23.0 2.7 15.5 .6 20.7 2.1 14.5 .6 19.1 1.7 14.6 .5 15.9 1.3 14.1 .4
Maryland 15.2 1.3 10.7 .3 16.1 1.4 11.4 .4 15.8 1.2 12.8 .5 19.2 1.3 12.7 .4
Massachusetts 15.7 1.8 10.8 .5 12.9 1.2 9.5 .4 14.0 .9 10.4 .3 8.9 .7 6.8 .2
Michigan 14.1 1.4 10.1 .4 18.2 1.5 10.2 .4 19.1 1.3 12.4 .4 19.5 1.1 14.8 .4
Minnesota 13.1 1.2 8.2 .3 12.0 1.1 8.3 .3 12.0 1.2 7.5 .3 14.6 1.5 9.3 .5
Mississippi 22.8 2.3 16.6 .7 25.4 2.0 20.2 .6 27.2 1.3 21.3 .5 29.9 1.2 22.9 .5
Missouri 20.7 2.1 14.9 .6 17.8 1.5 13.8 .5 20.2 1.2 14.5 .5 22.4 1.5 15.6 .5
Montana 27.5 2.7 18.1 .7 25.2 2.3 19.2 .6 28.0 1.7 22.4 .6 27.8 1.4 19.8 .5
Nebraska 11.7 1.7 10.9 .5 13.9 1.5 9.7 .4 21.3 1.4 14.4 .5 22.0 1.6 14.4 .4
Nevada 25.8 2 19.6 .7 28.4 2.7 18.5 .8 28.7 2.3 21.8 .7 31.1 2.0 21.6 .7
New Hampshire 17.9 2.4 12.6 .6 18.2 2.4 11.4 .6 22.9 1.4 12.5 .4 21.8 1.4 12.9 .4
New Jersey 18.0 2.2 12.2 .6 15.9 1.6 13.2 .5 19.0 1.0 14.8 .3 18.9 1.1 15.4 .4
New Mexico 30.0 2.9 23.2 .8 30.3 1.7 24.9 .5 29.2 1.3 24.9 .5 27.1 1.3 24.3 .5
New York 21.1 1.7 14.8 .5 20.5 1.7 16.4 .5 17.6 1.0 16.6 .4 17.8 1.2 14.3 .4
North Carolina 21.9 2.1 14.4 .5 24.4 1.8 15.3 .5 24.2 1.1 18.9 .4 27.3 1.0 19.8 .4
North Dakota 16.0 1.7 13.2 .5 20.7 2.2 13.1 .5 17.9 1.7 14.2 .5 19.5 1.9 12.9 .5
Ohio 14.4 2.1 11.6 .6 19.3 2.1 10.8 .5 19.3 1.5 13.6 .5 23.2 1.5 13.8 .5
Oklahoma 33.4 3.1 20.1 .7 29.2 2.2 20.7 .6 29.7 1.2 23.5 .5 28.7 1.1 22.5 .4
Oregon 23.3 1.6 16.7 .5 20.0 1.5 16.1 .5 24.4 1.1 18.5 .4 26.8 1.8 19.5 .5
Pennsylvania 15.1 1.4 11.4 .4 14.0 1.3 11.6 .4 16.6 1.2 12.4 .4 18.7 1.2 12.7 .4
Rhode Island 13.5 1.8 12 .6 16.1 1.7 12.2 .5 15.0 1.3 12.2 .4 19.0 1.7 12.8 .5
South Carolina 18.9 1.8 15 .6 26.2 1.9 16.5 .5 27.6 1.1 19 .4 27.8 1.2 19.3 .5
South Dakota 20.5 2.5 11.1 .5 20.2 2.0 13.7 .4 20.3 1.3 13.1 .4 22.5 1.6 14.4 .5
Tennessee 15.0 1.6 13.2 .4 14.2 1.3 13.7 .5 18.1 1.5 13.6 .6 26.2 1.7 17.3 .6
Texas 32.0 2.4 25.1 .7 30.4 1.5 25.1 .5 33.9 1.2 28.2 .4 35.8 1.4 28.1 .5
Utah 19.9 1.8 14.1 .5 19.0 1.6 13.2 .5 21.7 1.3 15.5 .4 21.1 1.4 15.2 .5
Vermont 18.3 1.7 13.8 .5 15.9 1.6 13.2 .4 15.6 1.1 13.4 .4 15.3 1.2 13.1 .4
Virginia 16.8 1.8 12.6 .5 16.7 1.6 12.0 .4 18.0 1.2 12.8 .4 17.3 1.5 13.0 .6
Washington 19.0 1.4 13.7 .4 17.1 1.6 12.7 .4 20.7 .8 14.6 .3 20.3 .8 15.4 .3
West Virginia 23.7 1.8 19 .5 25.1 1.8 21.2 .6 29.7 1.4 21.9 .6 24.3 1.3 20.6 .6
Wisconsin 13.4 1.8 9.9 .5 14.9 1.6 10.3 .5 15.6 1.4 11.5 .4 16.3 1.5 11.2 .5
Wyoming 25.8 2.7 17.5 .7 26.3 1.9 20.3 .6 25.3 1.5 19.5 .4 24.4 1.5 18.4 .4
a
Behavioral Risk Factor Surveillance System respondents (N=2,815,246). Model for each state adjusted by sex, age, race or ethnicity, and education
icantly between 1993–1996 and 2006–
2009, from 15.5% (CI=15.3%–
15.8%) to 17.0% (CI=16.8%–17.2%),
among those with neither frequent
mental distress nor frequent physical
distress and from 22.8% (CI=21.8%–
23.7%) to 26.6% (CI=25.9%–27.3%)
among those with frequent mental
distress only (Figure 1).
Given that the uninsurance esti-
mates for the categories of frequent
mental distress and both frequent
physical distress and frequent mental
distress were very similar and signifi-
cantly higher than for the categories
of frequent physical distress only and
neither frequent physical nor mental
distress, the four categories were col-
lapsed into two groups—persons with
frequent mental distress and persons
with no frequent mental distress—for
the remaining analysis.
Uninsurance by mental distress,
characteristics, and year
Overall, after adjustment for sex, age,
race and ethnicity, and educational at-
tainment, the prevalence of non-
elderly uninsured adults increased sig-
nificantly between the time periods
1993–1996 and 2006–2009 among
those with frequent mental distress,
from 21.6% (CI=20.8%–22.5%) to
23.8% (CI=23.3%–24.4%). Among
persons with frequent mental distress,
significant increases in uninsurance
between the two time periods were
found for females (19.4%, CI=18.4%–
20.4%, to 21.5%, CI=20.9%–22.1%),
those aged 18 to 34 years (28.7%,
CI=27.2%–30.1%, to 32.2%, CI=
31.0%–33.5%), white non-Hispanics
(17.7%, CI=16.9%–18.5%, to 20.5%,
CI=20.0%–21.0%), and persons with a
high school education (26.6%, CI=
25.2%–27.9%, to 29.1%, CI=28.1%–
30.1%) (Table 3).
Uninsurance by mental
distress, state, and year
After adjustment for sex, age, race
and ethnicity, and educational attain-
ment, there was a significant increase
in nonelderly uninsured adults with
frequent mental distress between the
time periods 1993–1996 and 2006–
2009 in Arkansas (from 22.8% to
33.3%), Georgia (16.5% to 28.7%),
Idaho (22.7% to 30.7%), Indiana
(15.9% to 25.5%), Michigan (14.1%
to 19.5%), Mississippi (22.8% to
29.9%), Nebraska (11.7% to 22.0%),
Ohio (14.4% to 23.2%), South Caroli-
na (18.9% to 27.8%), and Tennessee
(15.0% to 26.2%). Notably, there was
a significant decrease in uninsurance
over the same time period for people
with frequent mental distress in Cali-
fornia (29.6% to 23.2%) and Massa-
chusetts (15.7% to 8.9%) (Table 4).
Discussion
This research contained several note-
worthy findings. First, even after ad-
justment for sociodemographic char-
acteristics, uninsurance among adults
aged 18 to 64 years was markedly
higher among those with frequent
mental distress only and those with
both frequent mental distress and fre-
quent physical distress than among
those with frequent physical distress
only. Second, the prevalence of unin-
surance did not differ markedly be-
tween those with only frequent men-
tal distress and those with both fre-
quent mental distress and frequent
physical distress, suggesting that fre-
quent mental distress may be the
driving factor in the prevalence of
uninsurance in this population. Final-
ly, the prevalence of uninsurance
among those with frequent mental
distress only and those with neither
frequent mental distress nor frequent
physical distress increased signifi-
cantly over time.
Sociodemographic characteristics
play a critical role in one’s ability to
obtain insurance (25). Uninsured
adults have less access to recom-
mended care, receive poorer quality
of care, and experience worse health
outcomes than insured adults (9). In
this study, among those with fre-
quent mental distress, 40% of adults
with less than a high school educa-
tion and more than 25% of minority
populations (more than 25% of non-
Hispanic blacks and 35% of Hispan-
ics) were uninsured. According to
the National Survey on Drug Use
and Health, 79% of uninsured adults
with mental illness or substance
abuse who reported that they need-
ed treatment indicated that they
could not obtain it because of cost
(26). Moreover, many persons with
mental illness report incomes 200%
below the federal poverty level
(FPL) (27). Among persons 100% to
200% below the FPL who have men-
tal illness or substance use disorders,
approximately one-third lack public
or private insurance (26).
Populations with expectations of
high health care costs—such as those
with chronic physical or mental ill-
nesses—are more likely to attempt to
purchase insurance than those with
low risk, such as young healthy adults.
However, insurance companies are
more likely to deny coverage to these
high-risk populations (28). Persons
with mental illness are disproportion-
ately denied insurance because of
preexisting conditions (11) and ac-
cording to our study the gap in cover-
age between those with and without
mental distress is increasing over
time. Our research indicated that
even after adjustment for sociodemo-
graphic characteristics, the preva-
lence of uninsurance among those
with frequent mental distress only
and both frequent mental distress
and frequent physical distress was sig-
nificantly higher than among those
with frequent physical distress only.
Moreover, our results indicated that
healthy young adults, persons without
frequent mental or physical distress,
increasingly have chosen to opt out of
buying health insurance.
Our study had several limitations.
First, the BRFSS may underestimate
the burden of physical and mental
distress because it excludes those
without land-line telephones and
those unable to answer the phone be-
cause of impaired physical or mental
health. Second, BRFSS is based on
self-reported data, and biases in re-
porting health insurance coverage
and number of physically and men-
tally unhealthy days in the past 30
days may have occurred. Third, be-
cause BRFSS data about physical
and mental distress for 2002 were
available for only 22 states, the re-
sults for that year may not be repre-
sentative of the entire country. Final-
ly, because BRFSS data are cross-
sectional, whether the lack of health
insurance coverage affected or re-
sulted from physical distress, mental
distress, or both is uncertain. In oth-
er words, persons with frequent
physical or mental distress or both
may not seek health insurance cover-
PSYCHIATRIC SERVICES o ps.psychiatryonline.org o October 2011 Vol. 62 No. 10
11113366
age or may be denied insurance be-
cause of a preexisting condition, or
people who cannot afford insurance
may be more likely to subsequently
develop frequent distress.
Conclusions
Given the disproportionately high
rate of uninsurance among nonelder-
ly adults with frequent mental dis-
tress, it will be important to monitor
potential changes in health care ac-
cess, utilization, and self-reported
health after implementation of the
ACA, particularly among those with
mental illness.
Acknowledgments and disclosures
The authors report no competing interests.
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    • "Even though losing or changing jobs may create a gap in health insurance coverage between employed and unemployed individuals [26], disparities in health care coverage also exist among other groups, especially younger and less-educated individuals and racial/ethnic minority groups. In general, those with lower income, younger age, less education , and being of Hispanic ethnicity were found to have higher percentages of having no health insurance [1, 34, 34]. These disparities can also be quite large, for instance it was estimated from the US National Health Interview Survey in 2013 that 42.6 % of 18–64 adults with no high school diploma were uninsured compared with 14.0 % with more than a high school education, and an estimated 41.4 % of uninsured Hispanics were found compared with 15.2 % uninsured non-Hispanic whites [1]. "
    [Show abstract] [Hide abstract] ABSTRACT: Objective To explore the changing disparities in access to health care insurance in the United States using time-varying coefficient models. Data Secondary data from the Behavioral Risk Factor Surveillance System (BRFSS) from 1993 to 2009 was used. Study design A time-varying coefficient model was constructed using a binary outcome of no enrollment in health insurance plan versus enrolled. The independent variables included age, sex, education, income, work status, race, and number of health conditions. Smooth functions of odds ratios and time were used to produce odds ratio plots. Results Significant time-varying coefficients were found for all the independent variables with the odds ratio plots showing changing trends except for a constant line for the categories of male, student, and having three health conditions. Some categories showed decreasing disparities, such as the income categories. However, some categories had increasing disparities in health insurance enrollment such as the education and race categories. Conclusions As the Affordable Care Act is being gradually implemented, studies are needed to provide baseline information about disparities in access to health insurance, in order to gauge any changes in health insurance access. The use of time-varying coefficient models with BRFSS data can be useful in accomplishing this task.
    Article · May 2016
    • "Even if medical treatments for common mental health conditions were consistently effective, coverage for mental health conditions is often limited and costly. Mental health parity legislation has sought to address glaring benefit disparities, but there are significant gaps in state and federal mandates (Barry and Busch 2007; Golberstein and Busch 2013; Sarata 2011; Strine et al. 2011). Although the 2008 MHPAEA and the 2010 ACA address these benefit disparities to some extent, the high cost of mental health services continues to limit access to needed care (Mechanic 2011; Rowan, McAlpine, and Blewett 2013). "
    [Show abstract] [Hide abstract] ABSTRACT: Although numerous studies have considered the effects of having health insurance on access to health care, physical health, and mortality risk, the association between insurance coverage and mental health has been surprisingly understudied. Building on previous work, we use data collected from a two-year follow-up of low-income women living in Boston, Chicago and San Antonio to estimate a series of latent fixed effects regression models assessing the association between insurance status and symptoms of psychological distress. We find that having any insurance and private insurance is unrelated to depression, anxiety, and somatization. Having public insurance is unrelated to depression and somatization, but there is some evidence that having public insurance is associated with greater anxiety. Although not a direct test of the Affordable Care Act, our results suggest that the expansion of coverage may have a limited impact on symptoms of psychological distress among low-income urban women with children.
    Full-text · Article · Mar 2015
  • [Show abstract] [Hide abstract] ABSTRACT: Objective: Since 2008 Massachusetts has had universal health insurance with an individual mandate. As a result, only about 3% of the population is uninsured. However, patients who use behavioral health services are uninsured at much higher rates. This 2011 study sought to understand reasons for the discrepancy and identify approaches to reduce disenrollment and sustain coverage. Methods: The qualitative study was based on structured interviews and focus groups. Structured interviews were conducted with 15 policy makers, consumer advocates, and chief executive officers of provider organizations, and three focus groups were held with 33 patient volunteers. Results: The interviews and focus groups identified several disenrollment opportunities, all of which contribute to "churn" (the process by which disenrolled persons who remain eligible are reenrolled in the same or a different plan): missing and incomplete documentation, acute and chronic conditions and long-term disabilities that interfere with a patient's ability to respond to program communications, and lack of awareness among beneficiaries of the consequences of changes that trigger termination and the need to transfer to another program. Although safeguards are built into the system to avoid some disenrollments, the policies and procedures that drive the system are built on a default assumption of ineligibility or disenrollment until the individual establishes eligibility and completes requirements. Practices that can sustain enrollment include real-time Web-based prepopulated enrollment and redetermination processes, redetermination flexibility for designated chronic illnesses, and standardized performance metrics for churn and associated costs. Conclusions: Changes in the information system infrastructure and in outreach, enrollment, disenrollment, and reenrollment procedures can improve continuity and retention of health insurance coverage.
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