Abstract
Understanding how sexual behaviors cluster in distinct population subgroups along the life course is critical for effective targeting and tailoring of HIV prevention messaging and intervention activities. We examined interrelatedness of sexual behaviors and variation between men and women across a wide age range in a rural South African setting with a high HIV burden. Data come from the Ha Nakekela population-based survey of people aged 15–85-plus drawn from the Agincourt Health and Socio-Demographic Surveillance System. We used latent class analysis of six sexual behavior indicators to identify distinct subgroup sexual behavior clusters. We then examined associations between class membership and sociodemographic and other behavioral risk factors and assessed the accuracy of a reduced set of sexual behavior indicators to classify individuals into latent classes. We identified three sexual behavior classes: (1) single with consistent protective behaviors; (2) risky behaviors; and (3) in union with lack of protective behaviors. Patterns of sexual behaviors varied by gender. Class membership was also associated with age, HIV status, nationality, and alcohol use. With only two sexual behavior indicators (union status and multiple sexual partners), individuals were accurately assigned to their most likely predicted class. There were distinct multidimensional sexual behavior clusters in population subgroups that varied by sex, age, and HIV status. In this population, only two brief questions were needed to classify individuals into risk classes. Replication in other situations is needed to confirm these findings.
Original language | English (US) |
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Pages (from-to) | 2057-2068 |
Number of pages | 12 |
Journal | Archives of Sexual Behavior |
Volume | 49 |
Issue number | 6 |
DOIs | |
State | Published - Aug 1 2020 |
All Science Journal Classification (ASJC) codes
- Arts and Humanities (miscellaneous)
- General Psychology
Keywords
- Clustering
- HIV
- Sexual behavior
- South Africa