Longitudinal Event-Level Analysis of Gay and Bisexual Men's Anal Sex Versatility: Behavior, Roles, and Substance Use.
Lindsay ShawLu WangZishan CuiAshleigh J RichHeather L ArmstrongNathan John LachowskyPaul SeredaKiffer George CardGbolahan OlarewajuDavid MooreRobert S HoggEric Abella RothPublished in: Journal of sex research (2019)
Gay and bisexual Men Who Have Sex with Men (GBM) are sexually unique in that they can practice penile-anal sex versatility, i.e. engage in insertive and receptive anal sex. Individual-level versatility is extensively researched both as a sexual behavior linked to HIV/STI transmission, and as a GBM identity that can change over time. However, there is a dearth of research on event-level versatility (ELV), defined as taking the receptive and insertive role in the same sexual encounter. We analyzed event-level data from 644 GBM in the Momentum Health Study from February 2012-February 2017 to identify factors associated with ELV prevalence, the relationship between ELV and anal sex role preference, and sero-adaptive and sexualized drug use strategies. Univariate analysis revealed ELV prevalence rates between 15% and 20%. A multivariate generalized linear mixed model indicated ELV significantly (p < .05) associated with versatile role preference and condomless sex. However, the majority of ELV came from GBM reporting insertive or receptive role preferences, and there was significantly higher condom use among sero-discordant partners, indicating sero-adaptation. Multivariate log-linear modeling identified multiple polysubstance combinations significantly associated with ELV. Results provide insights into GBM sexual behavior and constitute empirical data useful for future HIV/STI transmission pattern modeling.
Keyphrases
- men who have sex with men
- hiv testing
- hiv positive
- healthcare
- mental health
- high grade
- public health
- primary care
- electronic health record
- risk factors
- antiretroviral therapy
- multidrug resistant
- social media
- south africa
- hepatitis c virus
- human immunodeficiency virus
- artificial intelligence
- climate change
- big data
- risk assessment
- adverse drug