The correlates and predictive validity of HIV risk groups among drug users in a community-based sample: methodological findings from a multi-site cluster analysis

Abstract

Outreach and intervention with out-of-treatment drug users in their natural communities has been a major part of our national HIV-prevention strategy for over a decade. Intervention design and evaluation is complicated because this population has heterogeneous patterns of HIV risk behaviors. The objectives of this paper are to: (a) empirically identify the major HIV risk groups; (b) examine how these risk groups are related to demographics, interactions with others, risk behaviors, and community (site); and (c) evaluate the predictive validity of these risk groups in terms of future risk behaviors. Exploratory cluster analysis of a sample of 4445 out-of-treatment drug users from the national data set identified eight main risk subgroups that could explain over 99% of the variance in the 20 baseline indices of HIV risk. We labeled these risk groups: Primary Crack Users (29.2%), Cocaine and Sexual Risk (12.8%), High Poly Risk Type 2 (0.3%), Poly Drug and Sex Risk (10.9%), Primary Needle Users (24.1%), High Poly Risk Type 1 (1.4%), High Frequency Needle Users (19.8%), and High Risk Needle Users (1.6%). Risk group membership was highly related to HIV characteristics (testing, sero-status), demographics (gender, race, age, education), status (marital, housing, employment, and criminal justice), prior target populations (needle users, crack users, pattern of sexual partners), and geography (site). Risk group membership explained 63% of the joint distribution of the original 20 HIV risk behaviors 6 months later (ranging from 0.03 to 37.2% of the variance individual indices). These analyses were replicated with both another 25% sample from the national data set and an independent sample collected from a new site. These findings suggest HIV interventions could probably be more effective if they targeted specific subgroups and that evaluations would be more sensitive if they consider community and sub-populations when evaluating these interventions.

Patterns of Sexual Risk Behavior Change Among Sexually Transmitted Infection Clinic Patients

“…Wechsberg et al showed that identifying differential intervention outcomes for different subgroups of women may help inform future efforts to tailor and target behavioral interventions. Although responses to risk reduction interventions vary, the patterns of change over time are not known (Dennis, Wechsberg, McDermeit, Campbell, & Rasch, 2001).…”

Who Participates in the Criminal Justice Drug Abuse Treatment Studies (CJ-DATS)?

“…Sexual behavior that increases the risk of HIV infection or transmission may also be associated with poly-substance use (Dennis, Wechsberg, McDermeit, Campbell, & Rasch, 2001;Lang & Belenko, 2001). The current samples were recruited for drug treatment research studies, and therefore study participants had a history of drug use.…”

Health and Economic Impacts of an HIV Intervention in Out of Treatment Substance Abusers: Evidence from a Dynamic Model

“…We employed a cluster analysis of observed sex-and drug-risk behaviors, established within the national multisite study [5,44], to classify each individual in the target population into one of eight risk groups. Each risk group has a distinctive pattern of social behavior in terms of drug use (category, method, and frequency) and sexual behavior (sexual acts, frequency, barter for drugs/money, baseline protection).…”