标题：A Social Network–Informed Latent Class Analysis of Patterns of Substance Use, Sexual Behavior, and Mental Health: Social Network Study III, Winnipeg, Manitoba, Canada
摘要：Objectives. We assessed whether a meaningful set of latent risk profiles could be identified in an inner-city population through individual and network characteristics of substance use, sexual behaviors, and mental health status. Methods. Data came from 600 participants in Social Network Study III, conducted in 2009 in Winnipeg, Manitoba, Canada. We used latent class analysis (LCA) to identify risk profiles and, with covariates, to identify predictors of class. Results. A 4-class model of risk profiles fit the data best: (1) solitary users reported polydrug use at the individual level, but low probabilities of substance use or concurrent sexual partners with network members; (2) social–all-substance users reported polydrug use at the individual and network levels; (3) social–noninjection drug users reported less likelihood of injection drug and solvent use; (4) low-risk users reported low probabilities across substances. Unstable housing, preadolescent substance use, age, and hepatitis C status predicted risk profiles. Conclusions. Incorporation of social network variables into LCA can distinguish important subgroups with varying patterns of risk behaviors that can lead to sexually transmitted and bloodborne infections. Infection with HIV and other sexually transmitted and bloodborne infections (STBBIs) has been described as occurring in a nexus of risk, in which a diverse range of life circumstances interact to create a risk environment. 1 This nexus-of-risk concept is similar to the social epidemiology literature, which seeks to better understand how individual, social, and structural factors create a risk environment conducive to disease transmission. 2 In addition to their contribution to understanding risk, contextual approaches of this type are important for developing targeted, effective public health interventions. The efficacy of structural HIV prevention interventions is largely determined by whether the social and structural factors underlying transmission are accurately identified. 3–5 Further, interventions focused on individual-level behaviors are likely to be more effective when, rather than targeting an entire population with a universal message, they develop communications that resonate with a population subgroup’s particular needs. 6 Specific statistical techniques facilitate identification of subgroups in social contextual analyses. Latent class analysis (LCA) has proven its worth as an inductive technique that uncovers underlying (latent) profiles or classes of individuals with shared characteristics. 7,8 To date, LCA has been applied in several analyses relevant to STBBI risk. Alcohol abuse has been examined in relation to place of consumption, 9 sexual behavior, 10 and mental disorders. 11 Investigations of illicit drug use have focused on profiles associated with specific substances or groups of substances, 12,13 with some investigators incorporating routes of administration. 6,14–16 Higher-order social and structural factors, analogous to the concept of the nexus of risk, have been incorporated to assess HIV risk in relation to homelessness, incarceration, income level, and housing. 5 Smith and Lanza have brought in elements of an individual’s social network to compare theorized network roles with those observed empirically, with the intent to inform opinion leader interventions focused on HIV. 17 To our knowledge, the analysis by Smith and Lanza is the only LCA concerning HIV and STBBIs to incorporate aspects of social networks. 17 Their analysis focuses on the potential influence of social network roles as underlying determinants of the success of HIV interventions. We used social network variables of substance use and sexual behavior to assess whether a meaningful set of subgroups could be identified. An approach of this kind could ultimately provide a more nuanced understanding of risk as well as inform the development of more effective prevention programs.
