Latent class profiles of internalizing and externalizing psychosocial health indicators are differentially associated with sexual transmission risk: Findings from the CFAR network of integrated clinical systems (CNICS) cohort study of HIV-infected men engaged in primary care in the United States

Abstract

Objective: To examine whether latent class indicators of negative affect and substance use emerged as distinct psychosocial risk profiles among HIV-infected men, and if these latent classes were associated with high-risk sexual behaviors that may transmit HIV.

Methods: Data were from HIV-infected men who reported having anal intercourse in the past 6 months and received routine clinical care at 4 U.S. sites in the Centers for AIDS Research Network of Integrated Clinical Systems cohort (n = 1,210). Latent class membership was estimated using binary indicators for anxiety, depression, alcohol and/or drug use during sex, and polydrug use. Generalized estimating equations modeled whether latent class membership was associated with HIV sexual transmission risk in the past 6 months.

Results: Three latent classes of psychosocial indicators emerged: (a) internalizing (15.3%; high probability of anxiety and major depression); (b) externalizing (17.8%; high probability of alcohol and/or drug use during sex and polydrug use); (c) low psychosocial distress (67.0%; low probability of all psychosocial factors examined). Internalizing and externalizing latent class membership were associated with HIV sexual transmission risk, compared to low psychosocial class membership; externalizing class membership was also associated with higher sexual transmission risk compared to internalizing class membership.

Conclusions: Distinct patterns of psychosocial health characterize this sexually active HIV-infected male patient population and are strongly associated with HIV sexual transmission risk. Public Health intervention efforts targeting HIV sexual risk transmission may benefit from considering symptom clusters that share internalizing or externalizing properties.

Figure 1

Latent class analysis: Item response probabilities by latent class membership (n=1,210).