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Abstract
‘Poly-substance use’ is increasingly prevalent among street drug user populations. The objective was to employ latent class analysis (LCA) to empirically categorize and extract potential typologies of poly-substance users within a multi-site cohort of illicit opioid and other drug users (OPICAN) in Canada, and examine potential associations with social and health indicators. Drug use patterns of 582 participants from the most recent follow-up (2005) of the cohort study–focusing on drug use prevalence indicators in the past 30 days–were empirically analyzed via LCA. These classes were further examined for associations with social and health variables using chi-square, ANOVA. Binomial logistic regression models were used to predict class membership. LCA analysis resulted in eight distinct user typologies, characterized both by the distinct relative prevalence of different substances (e.g., including: heroin, prescription opioids, benzodiazepines, cocaine, crack, alcohol, cannabis, and others) used and administration routes (e.g., injection or noninjection), the majority of which were described by the predominant use of two or more distinct substance groups (e.g., opioids and stimulants). At least two of the active poly-substance user classes were described by predominant noninjection as the primary route of administration. ‘Poor or fair’ health status was reported at the highest prevalence level by the class of intensive poly-substance injectors, while HCV-positive status was disproportionately low in the classes of current noninjectors. Analytical examination of poly-substance use patterns is a distinct challenge for meaningful drug use monitoring, also providing important evidence for targeted prevention and treatment interventions.