Clusters of HIV Risk and Protective Sexual Behaviors in Agincourt, Rural South Africa: Findings from the Ha Nakekela Population-Based Study of Ages 15 and Older.
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 w...
| Publicado en: | Archives of Sexual Behavior Vol. 49; no. 6; pp. 2057 - 2069 |
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| Autores principales: | , , , , , , , , |
| Formato: | journal article |
| Publicado: |
Springer Nature
Aug2020
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=144236988&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 144236988 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00040002 ASX jtl: Archives of Sexual Behavior issn: 00040002 maglogo: N pubinfo: dt: Aug2020 vid: 49 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 144236988 10.1007/s10508-020-01663-5 ppf: 2057 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P size: 645KB tig: atl: Clusters of HIV Risk and Protective Sexual Behaviors in Agincourt, Rural South Africa: Findings from the Ha Nakekela Population-Based Study of Ages 15 and Older. aug: au: Houle, Brian Yu, Shao-Tzu Angotti, Nicole Schatz, Enid Kabudula, Chodziwadziwa W. Gómez-Olivé, Francesc Xavier Clark, Samuel J. Menken, Jane Mojola, Sanyu A. affil: School of Demography, The Australian National University, #9 Fellows Road, Acton, 2601, Canberra, ACT, Australia MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA Department of Sociology and Center on Health, Risk and Society, American University, Washington, DC, USA Department of Public Health, University of Missouri, Columbia, MO, USA INDEPTH Network, Accra, Ghana Department of Sociology, The Ohio State University, Columbus, OH, USA Department of Sociology and Woodrow Wilson School of Public and International Affairs, and Office of Population Research, Princeton University, Princeton, NJ, USA su: South Africa Human sexuality & society Sexual health Rural health Human sexuality HIV prevention South African social conditions Research Research methodology Evaluation research Medical cooperation Comparative studies Research funding sug: subj: Human sexuality & society Sexual health Rural health Human sexuality South Africa HIV prevention South African social conditions Research Research methodology Evaluation research Medical cooperation Comparative studies Research funding keyword: Clustering HIV Sexual behavior Clustering HIV Sexual behavior ab: 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. pubtype: Academic Journal doctype: journal article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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