1. Longitudinal patterns of substance abuse in the Veterans Aging Cohort Study (VACS)
Traci Craig Green
Yale School of Public Health
Yale Center for Interdisciplinary Research on AIDS
Kirschstein Pre-doctoral National Research Service
Training Fellowship, NIDA (5F31DA023862)
VACS Investigators Meeting
14 October, 2008
Longitudinal patterns of substance abuse in the Veterans Aging Cohort Study (VACS)

2. Substance Abuse, Aging, & HIV
Prevalence of drug abuse increasing in older age groups
Natural history of substance use/abuse suggests
Chronicity, little initiation >age 30, reduction of use w/time
Little known about patterns of substance use/abuse over course of disease
Alcohol use can affect adherence, HIV progression, death
Inconsistent associations between drug use & HIV progression, death
py illicit drug use increased between 2002 and 2005 among people
Aging of baby boomer generation—which has the highest rates of substance abuse vs. previous generations
Everyone knows that People living longer with HIV

3. A Latent Variable Framework
Latent variables
Cannot be directly observed
Inferred from other, directly observable & measurable variables
Example: happiness
Assumptions
Individuals can be divided into meaningful subgroups (latent classes: c1-c5), based on similarities in responses
Classes are mutually exclusive & exhaustive
Empirical method of classification
Figure serves as illustration of LCA approach where c1-c5 represent subpopulations of the total population of “drug users” which we otherwise cannot directly observe. Instead, we ‘detect’ these subpopulations by analyzing indicators of their presence—here, self-reported use/non use of drugs.

4. Conceptualizing latent trajectories
GMM=Growth Mixture Model
HLM=Hierarchical Linear Model
LCGA=Latent Class Growth Analysis

5. N=6351

6. Class
Putative class description
Similarities with other classes
Uniqueness of class
HIV-specific differences 1
Nonusers
Fewer minorities like class 2,5
Injection history, lifestyle instability low like class 2
High medical problems, obesity like class 3
Older age, more gender diversity
Low psychiatric diseases, high quality of life/mental scores, low alcohol use & problem drinking
Higher quality of life physical scores for HIV+
Fewer comorbidities for HIV+, lowest rate of AIDS associated illness 2
Past primarily marijuana
Like class 1 in most socio-demographics, lifestyle stability, quality of life
Lowest medical disease
More history of smoking, past year drinking than class 1
HIV+ similar to HIV+ class 5: fewer non-white, employment, lifestyle stability but less past year drinking, better quality of life mental health
AIDS-associated illness similar to 3,5 3
Past multidrug
Racial/ethnic background, employment status, obesity like class 1
Smoking prevalence like class 4, 5
Problematic scores among drinkers like class 4, 5
Oldest of drug using classes (2-5)
Highest HCV prevalence, medical problems, former IVD
Lowest past year drinking prevalence
Current lifestyle stability
HCV coinfection highest
HIV+ more likely to smoke
HIV+ formerly injected heroin and cocaine; HIV- less often injected any drug
AIDS-associated illness similar to class 2, 5 4
High consequence, multidrug
HCV positivity, history of smoking & IVD like class 3
HIV- like class 5 HIV-
Primarily males aged 41-50, African American, unmarried/ not living with partner, lowest income, employment & education status, greatest lifestyle instability
Many currently smoking & injecting drugs, recent & heavy drinking
Highest psychiatric disease; receiving treatment (SA,MH)
More injection of drugs, cigarette smoking among HIV+ vs. HIV-
Less problematic drug use among HIV+ vs. HIV-
HIV+ receiving proportionately less treatment (SA, MH)
High prevalence of AIDS-associated illness 5
Low consequence, primarily marijuana
HIV+ like classes 1, 2 -socio-demographics, highly stable, lower problem drinking (class 2) -lower medical & psychiatric disease
HIV- like classes 3, 4 -drink as heavily & often (class 4), currently smoke -history of lifestyle instability (class 3)
Low HCV prevalence
History of but no current IVD
SA treatment rare
MH scores low but treatment not common
Least likely of HIV+ classes to be obese; lowest prevalence of diabetes, hypertension
Youngest HIV+ class, highest education level, lowest minority membership
AIDS-associated illness lower than other users (class 4)

7. Study Aims
To determine the prevalence & correlates of substance abuse trajectories among an older adult population with & without HIV
Hypotheses:
>3 trajectories of substance abuse
HIV status will differentiate trajectories
Age, race, medical & psychiatric disease, & treatment status will contribute to definition of trajectories

8. Analysis Indicators of self reported substance use
VACS8, 2+ survey responses N=4920
Demographically & clinically similar to full sample
Indicators of self reported substance use
AUDIT-C score & frequency of use of heroin, cocaine/stimulants, marijuana
Baseline, Follow ups 1,2,3
Single & Joint substance LCGA & GGMMs, quadratic change, class sizes 1-9
Correlates
Socio-demographics (age, race, education, income)
Medical & psychiatric comorbidities baseline diagnosis
Substance abuse, mental health treatment past year

9. HIV- HIV+ 8 trajectory classes for HIV+ and 8 for HIV-.
HIV differentiates class prevalence (how tall the colored stacks are) and the actual class composition (color of stacks).
HIV-
HIV+

10. trajectories do overlap but also several unique patterns
Alcohol
trajectories do overlap but also several unique patterns
slopes for many substances close to 0, suggesting not much change in drug use over 4 years' time
No positve slopes! That is, no new drug use initiation at this point
LCA classes are repeated, but splinter when slopes become relevant: marijuana use class, current multidrug users class
Similarities
reducers, non users, past multidrug users, and current multidrug users
recreational drug use (cocaine, marijuana)
Differences
HIV- had more change, HIV+ had more stability in substance use classes (14 vs. 8 sig slopes/quad parameters)
HIV+ exhibited fewer problem drinking patterns (1.6% vs. 6.1% HIV-)
HIV- unique class: high AUDITC with past primarily marijuana use
HIV+ unique classes: marijuana use (daily) with past hx of other drugs & heavy marijuana use with no hx of other drugs
recreational drug use class among HIV- has more problem drinking

11. HIV+ reducers—increase SA and MH tx over time—highest use and greater mh need/dx vs. multidrug users whose tx hx is erratic
HIV- reducers—increase SA (2nd highest) and MH (1st highest) tx over time; multidrug users MH tx is very erratic despite similar psychiatric disease dx rates
Not correlated: Hispanic/other ethnicity, death, CD4, AIDS-associated illness (bl, f/u 4)

12. Limitations Sample generalizability
Did not measure abuse of prescription drugs, benzodiazepines, club drugs
Unmeasured covariates: motivations for use, expectancies, readiness to quit

13. Conclusions
Multiple trajectories of substance use exist, HIV status differentiates several distinct patterns
Trajectories indicate current drug use is prevalent even with older age, despite illness: 21.9% HIV-, 36.8% HIV+
Interventions needed to increase adherence, age-appropriate treatment
Results can help suggest ways to better target efforts
-not a simple dichotomy
-NSDUH 2005: 14.4% of adults have used an illicit drug in the past year

14. Thank you!
Special thanks to the VACS writing committee: Kendall Bryant, Nancy Day, David Fiellin, Adam Gordon, Joe Goulet, Robert Heimer, Amy Justice, Trace Kershaw, Kevin Kraemer, Haiqun Lin, Steve Maisto