Subst Abus. 2021 Jun 18:1-9. doi: 10.1080/08897077.2021.1931634. Online ahead of print.


Background: Social ecological models designed to understand disparities in sexually transmitted infection (STI) prevalence highlight understudied structural and community risk factors. Guided by a social ecological model, this study identified profiles based on substance use-related STI risk, and examined associations of the profiles with selected indicators of structural-, community-, and individual-level STI risk factors. Methods: Repeated measures latent class analysis was applied to Pittsburgh Girls Study data (n = 2,138; 58% Black, 42% White) at ages 18-20. Profile indicators included: women’s and partner’s alcohol and cannabis use, women’s sexual risk behavior, and self-reported STI. Profile predictors included racial background, structural-, community-, and individual-level risk factors. Results: Two of the five identified profiles had low STI likelihood: « Low Use » of alcohol and cannabis (25.5%; overrepresented by Black women), and « Alcohol Only » (19.1%; overrepresented by White women). Three profiles, all representing co-use of alcohol and cannabis, had higher STI likelihood: « Co-Use: Increasing Alcohol and Occasional Cannabis use » (16.5%; overrepresented by White women), « Co-Use: Occasional Alcohol and Cannabis use » (26.1%; overrepresented by Black women), and « Co-Use: Frequent Cannabis and Occasional Alcohol use » (12.8%; overrepresented by Black women). Structural STI risk (household use of public assistance at wave 1) was associated with « Low Use » and « Co-Use: Frequent Cannabis and Occasional Alcohol use » profiles. STI risk at multiple levels (structural, neighborhood, individual) was associated with the « Co-Use: Frequent Cannabis and Occasional Alcohol use » profile. Conclusions: Co-use of alcohol and cannabis is an important target for STI prevention efforts. Results also highlight structural- and community-level STI risk factors that disproportionately impact Black women, and the importance of multi-level interventions that are targeted to profile of risk to optimize the effectiveness of interventions.

PMID:34143947 | DOI:10.1080/08897077.2021.1931634

Source: ncbi 2

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