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Psychiatric Disorders and Drug Use Among Human Immunodeficiency Virus–Infected Adults in the United States
Eric G. Bing, MD, PhD, MPH;
M. Audrey Burnam, PhD;
Douglas Longshore, PhD;
John A. Fleishman, PhD;
Cathy Donald Sherbourne, PhD;
Andrew S. London, PhD;
Barbara J. Turner, MD, MSEd;
Ferd Eggan, MA;
Robin Beckman, MPH;
Benedetto Vitiello, MD;
Sally C. Morton, PhD;
Maria Orlando, PhD;
Samuel A. Bozzette, MD, PhD;
Lucila Ortiz-Barron, MD;
Martin Shapiro, MD, PhD
Arch Gen Psychiatry. 2001;58:721-728.
ABSTRACT
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Background There have been no previous nationally representative estimates of the
prevalence of mental disorders and drug use among adults receiving care for
human immunodeficiency virus (HIV) disease in the United States. It is also
not known which clinical and sociodemographic factors are associated with
these disorders.
Subjects and Methods We enrolled a nationally representative probability sample of 2864 adults
receiving care for HIV in the United States in 1996. Participants were administered
a brief structured psychiatric instrument that screened for psychiatric disorders
(major depression, dysthymia, generalized anxiety disorders, and panic attacks)
and drug use during the previous 12 months. Sociodemographic and clinical
factors associated with screening positive for any psychiatric disorder and
drug dependence were examined in multivariate logistic regression analyses.
Results Nearly half of the sample screened positive for a psychiatric disorder,
nearly 40% reported using an illicit drug other than marijuana, and more than
12% screened positive for drug dependence during the previous 12 months. Factors
independently associated with screening positive for a psychiatric disorder
included number of HIV-related symptoms, illicit drug use, drug dependence,
heavy alcohol use, and being unemployed or disabled. Factors independently
associated with screening positive for drug dependence included having many
HIV-related symptoms, being younger, being heterosexual, having frequent heavy
alcohol use, and screening positive for a psychiatric disorder.
Conclusions Many people infected with HIV may also have psychiatric and/or drug
dependence disorders. Clinicians may need to actively identify those at risk
and work with policymakers to ensure the availability of appropriate care
for these treatable disorders.
INTRODUCTION
PSYCHIATRIC AND substance abuse disorders among people with human immunodeficiency
virus (HIV) infections may impair quality of life,1, 2
adversely affect the need for and use of health services,3
impact health outcomes,4, 5 and compromise
adherence with complicated medication regimens.6
Psychiatric and substance abuse disorders may also be associated with unsafe
sexual and needle-sharing behaviors that increase the likelihood of HIV transmission.7, 8, 9, 10 In addition,
psychiatric and drug-use disorders produce substantial social burden11, 12 and can increase health care costs.13, 14, 15, 16 Population-based
estimates of the prevalence of these disorders among people with HIV and factors
associated with them are important for the development of policies and programs
that will enhance access to appropriate care, increase individual well-being,
and reduce the social and economic costs of care.
Previous research suggests that rates of psychiatric and drug disorders
vary depending on the population studied and the comparison groups used. Depression
in HIV-infected clinic populations has been found to range from 22% to 32%,17, 18, 19, 20, 21
which is 2 to 3 times higher than the prevalence of depression in general
community populations.22, 23, 24
The rates of disorders among gay men in some studies are high,20, 25
although high rates of psychiatric disorders have also been found among general
population studies of gay men.26 Studies that
have also included seronegative comparisons from the same population as those
who are HIV positive have not found large differences in the prevalence of
psychiatric disorders among the seronegative and seropositive subpopulations.21, 25, 27, 28, 29, 30
The prevalence of drug use and drug dependence among people with HIV
disease is suspected to be high, at least in part due to the association between
injection drug use and HIV transmission. In the United States, injection drug
use has shown an increasing trend as a transmission route for infection and
currently stands as the cause of approximately one third of the nation's acquired
immunodeficiency syndrome (AIDS) cases.31, 32
In some HIV-positive cohorts, illicit drug use is common. In the Multicenter
AIDS Cohort Study, for example, the proportion of gay and bisexual men reporting
use of an illegal drug in the prior 6 months ranged from 92% to 55%, depending
on the period, between 1985 and 1989.33 Nevertheless,
such high rates of illicit drug use among gay men declined during the 1990s,
paralleling a decline in national rates during this period.34
National estimates of the prevalence of psychiatric and drug disorders
among people with HIV disease are not currently available. Prior studies have
generally relied on convenience samples, which may not be representative of
the broader population and often are limited to specific subpopulations, such
as gay men.35, 36 This study, based
on data from the HIV Cost and Services Utilization Study (HCSUS), presents
the first national estimates of the 12-month prevalence of psychiatric disorders,
illicit drug use, and drug dependence among people with HIV infection. This
study also examines the association of clinical and sociodemographic factors
with the prevalence of these disorders.
SUBJECTS AND METHODS
STUDY DESIGN AND SAMPLE
The HCSUS cohort is a nationally representative probability sample of
HIV-infected adults receiving medical care in the continental United States.
The reference population was adults (aged  18 years) who had HIV infection
and made at least 1 medical visit for regular or ongoing HIV-related care,
excluding emergency, military, and prison settings, between January 5 and
February 29, 1996. (In 1 metropolitan statistical area, recruitment began
2 months later due to delays receiving institutional review board approval.)
For full details of the study design, see Bozzette et al37
and Frankel et al.38
HCSUS used a multistage sampling design in which geographical areas,
medical providers, and patients were sampled. In the first stage, 28 metropolitan
statistical areas and 24 clusters of rural counties were sampled with probabilities
based on the number of reported AIDS cases during 1995. In the second stage,
we sampled 58 urban and 28 rural "known providers" from lists of all providers
in each area known by local informants to be providing HIV care. In addition,
we also randomly selected 87 urban and 23 rural "other providers" from the
physician master file of the American Medical Association who had reported
caring for HIV patients in a screening survey in the selected geographic areas.
In the third stage, we randomly selected 4042 patients from anonymous lists
of all eligible patients who visited participating providers during the recruitment
period. To the extent possible, duplicate entries of persons appearing on
more than 1 list were removed. We set the third-stage sampling rates such
that the overall probability of selection was as uniform as possible within
subgroups. The sampling rate was doubled for women and for members of staff
model health maintenance organizations.
We enrolled 57 of 58 urban known providers (the refusing institution
was replaced with a similar institution in the same city), 22 of 28 rural
known providers, 61 of 87 urban other providers, and 19 of 23 rural other
providers. Nonresponse in these latter 3 groups was handled by weighting.
Among selected patients, 2864 (71%) completed the full interview at baseline.
This baseline sample provides a 68% coverage rate of the population that would
have been directly represented if there were no refusals at any stage. Analytic
weights were adjusted for the study sample design and for nonresponse (using
data from short form, proxy forms, or basic nonresponse information that was
collected on those who failed to complete the full interviews).
BASELINE SURVEY AND MEASURES
All interviews were conducted by trained interviewers using computer-assisted
personal interviewing instruments over a 15-month period, beginning in January
1996. Ninety-one percent of the full interviews were conducted in person at
a private location convenient to the participant and the remainder were conducted
over the telephone.
The interview assessed basic demographic and clinical information, psychiatric
disorders, and drug use as well as other topics. Demographic characteristics
included sex, age, race/ethnicity, and education. We used information on household
composition at the time of the interview to categorize respondents as living
with a spouse, with an unmarried partner, with others (either related or unrelated),
or alone; a small number of persons39 who reported
being homeless were combined with those living alone. Sexual behavior was
assessed by asking respondents to indicate the gender(s) of their sexual partners
in the past 6 months (ie, all of the opposite sex, all of the same sex, those
of the same and opposite sex, or no partners). On the basis of this information,
we classified respondents as "heterosexual," "gay," "bisexual," or "currently
abstinent."
Respondents reported their employment status at the time of the interview.
We classified respondents as either "working full-time" or "working part-time,"
"unemployed," "disabled," or "not working" (eg, on sick leave, retired). Disability
refers to self-reported employment status or ineligibility for income support
programs. Respondents also reported total family income in 1995; persons who
were reluctant to report their specific income were asked to indicate which
of several income ranges was appropriate. Respondents provided information
on current insurance coverage and were categorized as having no medical insurance;
having Medicaid, Medicare, or Veterans Affairs benefits; or being privately
insured. Individuals with both Medicaid and Medicare were classified as having
Medicare.
We used self-reported clinical data to determine HIV disease progression.
Participants identified which of 13 HIV-related clinical symptoms they had
experienced in the previous 6 months (new or persistent headaches; fevers,
sweats, or chills; pain in the mouth, lips, or gums; white patches in the
mouth; painful rashes or sores on the skin; nausea or loss of appetite; trouble
with the eyes; a sinus infection, pain or discharge; numbness or tingling
in the hands or feet; persistent cough or difficulty breathing; diarrhea or
watery stools; weight loss; and among women, an abnormal vaginal discharge).
Since women could report 1 more HIV-related symptom than men, we calculated
the percentage of total possible symptoms that the patient reported.
The HIV disease stage was determined by asking participants if they
currently had any of the symptoms noted above, had ever been diagnosed as
having any of 22 AIDS-indicator conditions, and their lowest CD4+
lymphocyte count. Individuals classified as "asymptomatic" reported no HIV-related
symptoms, an AIDS-defining illness, or a CD4+ lymphocyte count
less than 200/µL. Symptomatic individuals reported 1 or more HIV-related
symptoms, but not an AIDS-defining illness or CD4+ count less than
200/µL. Individuals with AIDS reported an AIDS-defining illness and/or
a CD4+ count less than 200/µL.
All participants were screened for symptoms of major depression, dysthymia,
generalized anxiety disorders (GAD), panic attacks, and illicit drug use and
dependence within the past year. We selected these disorders because they
are relatively common in the general population and can often be treated with
existing therapeutic techniques. We screened for major depression, dysthymia,
GAD, and panic attacks using the University of Michigan Composite International
Diagnostic Interview (UM-CIDI) brief screener.40
The UM-CIDI is based on DSM-III-R criteria for the
disorders within the general population. For major depression, GAD, and panic
attacks, the reported sensitivity of the instrument in the general population
is 0.90, 0.99, and 0.67, respectively; corresponding reported specificities
are 0.94, 1.00, and 1.00. The sensitivity and specificity of the dysthymia
screener have not been reported.
The screeners for drug use and drug dependence are based on the UM-CIDI
brief screener for drug dependence, with modifications for this study. Participants
were asked if they had used marijuana, sedatives, amphetamines, analgesics,
cocaine, inhalants, lysergic acid diethylamide or hallucinogens, or heroin
during the previous 12 months. Participants who reported using any of these
drugs were asked whether (1) they had to use larger amounts to get the same
effect and whether (2) they had experienced any emotional or psychological
problems from using drugs. Those who gave affirmative responses to either
question were classified as drug dependent. Participants were categorized
into 4 mutually exclusive categories: "no drug use," "marijuana use only without
dependence," "other illicit drug use without dependence," and "drug dependence."
Participants were asked questions on quantity and frequency of alcohol
consumption in the past 4 weeks. Based on their responses, they were classified
into 4 categories: "none, non–heavy drinking" (drank alcohol in the
past 4 weeks, but never 5 drinks in a day), "heavy drinking" (drank 5
drinks on 1-3 days in the past 4 weeks), and "frequent heavy drinking" (drank 5
drinks on 4 days in the past 4 weeks).
ANALYSES
For each respondent, an analytic weight was constructed consisting of
the product of 3 individual weights.41 The first
component is a sampling weight, which is the inverse of a respondent's sampling
probability and which adjusts for the differential selection probabilities
across subgroups of the population. The second component is a nonresponse
weight, which adjusts for differential cooperation rates using the supplemental
data (abbreviated and proxy interviews and nonresponse data), collected for
nonresponding patients and providers. The third component is a multiplicity
weight, which adjusts for the fact that some patients were seen by more than
1 eligible provider and thus had more than 1 opportunity to enter the sample.
The analytic weight is equivalent to an estimate of the number of persons
represented by that respondent. All analyses in this article incorporate these
analytic weights and also adjust for the complex multistage sampling design.
To adjust SEs and statistical tests for the differential weighting and the
complex sampling design, we used linearization methods42
available in the SUDAAN (Research Triangle Institute, Research Triangle Park,
NC) and Stata (Stata Corp, College Station, Tex) software packages.
We used 2 summary-dependent variables: any psychiatric disorder that
indicates whether the respondent scored positive on at least 1 of the 4 psychiatric
disorder screeners (vs all negative scores), and drug dependence that indicates
dependence on illicit drugs (vs no use and drug use without dependence). Multiple
logistic regression analyses of (1) any psychiatric disorder and (2) drug
dependence were conducted to determine associations with clinical and sociodemographic
variables. We report multiple logistic regressions that include the full array
of independent variables; ancillary analyses (not shown) examined potential
collinearity by removing subsets of variables (eg, insurance, employment,
and income) to assess the sensitivity of the results to model specification.
RESULTS
POPULATION DESCRIPTION
The majority of the 2864 participants were men and between the ages
of 35 and 49 years (Table 1). Approximately
half of the sample was nonwhite and more than 40% were heterosexual. Almost
two thirds were not employed and more than 40% reported annual incomes of
less than $10 000. Most of the sample had an advanced stage of HIV disease:
more than half had a CD4+ lymphocyte count less than 200/µL
and more than 9 of 10 were symptomatic or had AIDS.
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Table 1. Sample Characteristics*
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PSYCHIATRIC DISORDERS
Nearly half of the population screened positive for 1 or more of the
4 psychiatric disorders during the 12 months preceding the interview (Table 2). More people screened positive
for mood disorders (major depression and dysthymia) than for anxiety disorders
(GAD and panic attacks). More than one third of the population screened positive
for major depression and more than one quarter experienced symptoms of dysthymia
during the previous 12 months. Twenty-one percent of the population screened
positive for both major depression and dysthymia (data not shown). More people
screened positive for GAD than panic attacks, and 5% of the population screened
for both GAD and panic attacks (data not shown).
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Table 2. Percentage of People Screening Positive for Conditions*
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Multiple logistic regression analyses of participants who screened positive
for any of the 4 psychiatric disorders during the previous 12 months (Table 3, column 1) showed that the likelihood
of screening positive for a psychiatric disorder was lower among those aged
50 years or older compared with those younger than 35 years and was also lower
among African Americans compared with whites. The likelihood of screening
positive for a psychiatric disorder was greater among individuals who lived
alone or lived with someone with whom they were not romantically involved
compared with those who lived with a spouse. Sexual behavior, however, was
not significantly related to screening positive for a psychiatric disorder.
The likelihood of screening positive for a psychiatric disorder was greater
among persons who were unemployed or disabled compared with those working
full-time or part-time.
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Table 3. Multiple Logistic Regression on 12-Month Positive Screener
for Psychiatric Disorders and Drug Dependence in 2864 Subjects*
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Clinical stage was not associated with screening positive for a psychiatric
disorder; however, HIV-related symptoms were associated with screening positive
for a psychiatric disorder and the strength of the association increased with
increasing HIV-related symptoms. There were strong relationships between illicit
drug use other than marijuana and drug dependence and screening positive for
a psychiatric disorder. Individuals who used marijuana only, however, were
not more likely to screen positive for a psychiatric disorder than those who
did not use any drugs. Individuals who were heavy alcohol users compared with
those who did not drink were more likely to screen positive for a psychiatric
disorder than those who did not consume alcohol. In the analyses in which
the drug use variable (data not shown) was removed from the model, the coefficients
for most variables did not change substantially, with the exception of the
alcohol variable. In the reduced model that excluded drug use, both heavy
and frequent heavy drinking were independently associated with having a psychiatric
disorder.
DRUG USE AND DRUG DEPENDENCE
Approximately half of the HCSUS population reported using an illicit
drug during the previous 12 months (Table
2). Twelve percent reported only marijuana use, one quarter reported
illicit drug use other than marijuana but were not drug dependent, and 12%
screened positive for dependence with respect to at least 1 illicit drug during
the previous 12 months.
Multiple logistic regression analyses results predicting drug dependence
(Table 3, column 2) showed that
persons 35 to 49 years old or older than 50 years compared with those who
were younger were less likely to be drug dependent. Compared with persons
living with spouses, those in each of the other living situations were more
likely to be dependent on illicit drugs, with the adjusted odds being especially
high among those who lived alone. Compared with heterosexuals, gays and individuals
who were sexually abstinent were less likely to be drug dependent.
Clinical stage was not associated with drug dependence; however, individuals
having many HIV-related symptoms (75%-100% of the total possible) were much
more likely to screen positive for drug dependence than those without symptoms.
Screening positive for a psychiatric disorder was independently associated
with screening positive for drug dependence. As expected, frequent heavy drinking
was positively associated with drug dependence. In the reduced model (data
not shown) that excluded any psychiatric disorder as an independent variable,
we found only minor changes in the coefficients for the other variables.
COMMENT
The prevalence of psychiatric disorders, drug use, and drug dependence
among people receiving care for HIV disease in the United States appears to
be high, as indicated by the high proportion of respondents in this nationally
representative sample who screened positive for these disorders. Nearly half
of the population screened positive for a psychiatric disorder and half reported
using illicit drugs (including marijuana) during the past year.
The proportion of people screening positive for disorders in this sample
is considerably higher than that obtained in general population samples. The
National Household Survey on Drug Abuse (NHSDA), which interviewed a sample
of 22 181 people in 1994, used the same UM-CIDI screeners for major depression,
GAD, and panic attacks as those used in the HCSUS.43
As shown in Table 2, the proportion
of people screening positive for major depression in HCSUS is nearly 5 times
greater than in the NHSDA (36.0% vs 7.6%), while the proportion for GAD is
nearly 8 times higher (15.8% vs 2.1%) and for panic attacks is more than 4
times higher (10.5% vs 2.5%). In addition, the prevalence of drug abstinence
is much lower than reported in the NHSDA.
Having many HIV-related symptoms was a strong predictor of having a
psychiatric disorder within the previous year. In addition to being intrinsically
unpleasant, HIV-related symptoms may serve as a salient reminder of disease
status and thereby increase psychological distress and anxiety. Alternatively,
preexisting psychiatric disorders may influence the perception and subjective
report of symptoms. It is also possible that use of illicit drugs may be associated
with factors, such as poor health maintenance behaviors that may weaken the
immune system and lead to increased symptomatology. Although causal inferences
cannot be made, these results highlight the important connection between the
experience of HIV-related symptoms and psychiatric disorders and drug dependence.
Multivariate analyses supported earlier clinical observations that more HIV-related
symptoms are associated with psychiatric disorders.44
Some of our findings differ from those of prior research among the general
population as well as among HIV-positive samples. Contrary to previous reports
of much higher rates of psychiatric disorders among gay men compared with
heterosexual men,35, 36 sexual behavior
was unrelated to having a psychiatric disorder in multivariate analyses. Gay
persons were also less likely to report dependence on illicit drugs than heterosexuals,
which may reflect the strong relationship between heterosexual transmission
of HIV and injection drug use. Consistent with other studies, psychiatric
disorders and drug dependence were more common among younger respondents.23
Unemployment and work-related disability were found to be independent
predictors of screening positive for a psychiatric disorder. This may be because
people with psychiatric problems have more difficulty obtaining and maintaining
employment. Another explanation may be that as HIV disease progresses, infected
individuals may lose the ability to work, and may not feel like productive
members of society. The lack of ability to work may lead to decreased personal
income, which may also contribute to distress.
Living alone or with someone other than a spouse or partner was predictive
of screening positive for a psychiatric disorder and drug dependence. This
may be because of the stability and social support that one may obtain in
a committed relationship. It may also be because individuals who have emotional
and/or drug problems may have difficulty sustaining relationships or successfully
living with others.
Several limitations of this study should be recognized. The HCSUS sample
represents persons with HIV who are receiving regular care in the general
outpatient setting. Persons infected with HIV who received care exclusively
in military, prison, emergency, psychiatric, or drug treatment settings were
not studied. The prevalence of psychiatric disorders, illicit drug use, and
drug dependence may be higher in many of these subpopulations. A second limitation
is that we did not screen for all possible psychiatric disorders due to resource
constraints, but rather focused on the disorders believed to be common in
this population and for which effective treatments exist. Measuring other
important disorders, such as psychotic disorders, organic disorders, personality
disorders, and alcohol dependence, would have increased our already high prevalence
estimates. A third limitation is inherent in any cross-sectional study: unambiguous
causal inferences cannot be made from observed associations. Several associations,
such as those involving employment, household composition, and income, could
have arisen as a result of psychiatric disorder or illicit drug use, rather
than causing them.
A final limitation of the study lies with our use of diagnostic screeners
rather than formal diagnostic interviews. We did not wish to overburden participants
with a lengthy interview. Although these screeners are reported to have high
sensitivity and specificity for disorders in general population samples,40 they have never been validated in an HIV-infected
population. Analyses to validate the HCSUS screeners using data from a subsample
of HCSUS participants who completed the UM-CIDI screeners and at a later date
completed the full UM-CIDI suggest that the sensitivity and specificity of
the screeners may be lower than that reported by Kessler et al.40
The "any psychiatric disorder" variable in HCSUS has a sensitivity of 0.80
and a specificity of 0.76.45 The UM-CIDI screeners
used in HCSUS appear to have worked better among individuals with fewer HIV-related
symptoms and for those who did not experience a lag time between the administration
of the UM-CIDI brief screener and full UM-CIDI. Thus, our prevalence estimates
should be interpreted as indicating a high probability of disorder rather
than a clinically confirmed diagnosis.
Despite its limitations, this study has important clinical and health
care policy implications. This study highlights the high proportion of people
with HIV in care that may also have psychiatric and drug use problems. These
disorders may decrease quality of life, interfere with ability to adhere to
antiretroviral treatment, and increase caregiver burden and health care costs.
Fortunately, each of the disorders examined in this study is readily treatable;
however, before individuals with these disorders can be treated, they first
must be identified and referred to appropriate services. Clinicians and policymakers
must recognize that to effectively treat people with HIV, mental health and
substance abuse services must be available, accessible, and limited to medical
care.
AUTHOR INFORMATION
Accepted for publication March 22, 2001.
The HCSUS is being conducted under cooperative agreement U-01HS08578
between RAND and the Agency for Healthcare Research and Quality (formerly
Agency for Health Care Policy and Research) (Dr Shapiro, principal investigator;
Dr Bozzette, co–principal investigator). Substantial additional funding
for this cooperative agreement was provided by the Health Services Resources
Administration, Rockville, Md; the National Institute of Mental Health; the
National Institute on Drug Abuse, Bethesda, Md; and the National Institutes
of Health (NIH) Office of Research on Minority Health through the National
Institute for Dental Research, Bethesda, Md. Additional support for this project
was provided by the Robert Wood Johnson Foundation, Princeton, NJ; Merck and
Company, Whitehouse Station, NJ; Glaxo-Wellcome, Incorporated, Research Triangle
Park, NC; the National Institute on Aging, Bethesda; and the Office of the
Assistant Secretary for Planning and Evaluation in the US Department of Health
and Human Services, Washington, DC. Dr Bing received support for this study
from the National Institute of Mental Health as a University of California,
Los Angeles Faculty Scholar in Mental Health Services Research (grant MH00990),
the California Universitywide AIDS Research Program, Oakland, and the NIH
Center on Minority Health and Health Disparities through the National Institute
on Alcohol Abuse and Alcoholism, Bethesda (grant AA11899).
We thank Frank Galvan, PhD, LCSW, Ellen Lazarus, BS, and John Ahrens,
MS, for their diligent assistance with the preparation of the manuscript.
From the Center for AIDS Research, Education and Services and Collaborative
Alcohol Research Center, Charles R. Drew University of Medicine & Science,
Los Angeles, Calif (Dr Bing); RAND, Santa Monica, Calif (Drs Burnam, Sherbourne,
Orlando, Bozzette, and Shapiro and Ms Beckman); RAND, Santa Monica, Calif
(Dr Longshore); University of California, Los Angeles Drug Abuse Research
Center (Dr Longshore); Agency for Healthcare Research and Quality, Rockville,
Md (Dr Fleishman); Department of Sociology, Kent State University, Kent, Ohio
(Dr London); Division of General Medicine, Department of Medicine, University
of Pennsylvania, Philadelphia (Dr Turner); AIDS Coordinator's Office, City
of Los Angeles (Mr Eggan); National Institute of Mental Health, Bethesda,
Md (Dr Vitiello); RAND Statistics Group, Santa Monica, Calif (Dr Morton);
Health Services Research and Development Unit, Veterans Affairs San Diego
Healthcare System, School of Medicine, University of California, San Diego
(Dr Bozzette); College of Medicine, Michigan State University, East Lansing
(Dr Ortiz-Barron); Department of General Internal Medicine, University of
California, Los Angeles (Dr Shapiro).
Corresponding author and reprints: Eric G. Bing, MD, PhD, MPH, Center
for AIDS Research, Education and Services and Collaborative Alcohol Research
Center, Charles R. Drew University of Medicine & Science, 1651 E 120th
St, Los Angeles, CA 90059 (e-mail: erbing{at}cdrewu.edu).
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ABSTRACT
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