Using latent class analysis (LCA) to analyze patterns of drug use in a population of illegal opioid users

Background: The objective of this paper is to empirically determine a categorization of illegal opioid users in Canada in order to describe and analyze drug use patterns within this population. Methods: Drug use patterns of 679 eligible illegal opioid users outside treatment from the OPICAN study, a pan-Canadian cohort (recruited March to December, 2002) involving the cities of Toronto, Montreal, Vancouver, Edmonton and Quebec City, were empirically examined using latent class analysis. These latent classes were then further analyzed for associations using chi-square and t-test statistics. Findings: The opioid and other drug user sample surveyed were categorized into three latent classes. Class I (N=256) was characterized by the use of Tylenol 3 and benzodiazepines along with high levels of depression and self-reported pain. Class 2 (N=68) was described by the non-injection use of both heroin and crack while having a high level of homelessness. Class 3 (N=344) was shown to consist of injection drug users of heroin and cocaine exhibiting the highest levels of HIV and Hepatitis C infections amongst the classes. Conclusions: Using latent class analysis we found distinct patterns of drug use amongst illegal opioid users differing in terms of type of drugs co-used, social context, and co-morbid pathologies. These data may be useful as the empirical basis for the planning of specific prevention and treatment interventions. (c) 2006 Elsevier Ireland Ltd. All rights reserved.