Evidence map›Paper›PMID 32232623›Full record

ArticleArchives of sexual behavior2020

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.

Brian Houle, Shao-Tzu Yu, Nicole Angotti, Enid Schatz, Chodziwadziwa W Kabudula, Francesc Xavier Gómez-Olivé, Samuel J Clark, Jane Menken, Sanyu A Mojola

Abstract read
In one paragraph

Article in Archives of sexual behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Brian HouleSchool of Demography, The Australian National University, #9 Fellows Road, Acton, Canberra, ACT, 2601, Australia. brian.houle@anu.edu.au.ORCID 0000-0003-2157-3118
Shao-Tzu YuSchool of Demography, The Australian National University, #9 Fellows Road, Acton, Canberra, ACT, 2601, Australia.
Nicole AngottiMRC/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.ORCID 0000-0002-9206-5914
Enid SchatzMRC/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.ORCID 0000-0003-3963-2745
Chodziwadziwa W KabudulaMRC/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.
Francesc Xavier Gómez-OlivéMRC/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.
Samuel J ClarkMRC/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.
Jane MenkenMRC/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.ORCID 0000-0002-0008-0325
Sanyu A MojolaDepartment of Sociology and Woodrow Wilson School of Public and International Affairs, and Office of Population Research, Princeton University, Princeton, NJ, USA.

Funding

University of Colorado Population CenterP2CHD066613 · NICHD · UNIVERSITY OF COLORADO · PI JANE A MENKEN · 2015 to 2026
$3.7M
Verbal Autopsy: Reimagining Data & Automated Cause Assignment (using ALPHA Network data)R01HD086227 · NICHD · OHIO STATE UNIVERSITY · PI CLARK, SAMUEL J · 2016 to 2021
$2.4M
The University of Colorado Population CenterR24HD066613 · NICHD · UNIVERSITY OF COLORADO · PI PAMPEL, FRED C · 2010 to 2014
$1.9M
Partnership for Social Science AIDS Research in South African's Era of ART RollouR24AG032112 · NIA · UNIVERSITY OF COLORADO · PI MENKEN, JANE A · 2007 to 2011
$1.6M
HIV after 40 in Rural South Africa: Aging in the Context of an HIV/AIDS EpidemicR01AG049634 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MOJOLA, SANYU AMIMO · 2016 to 2020
$1.3M
Predicting Impacts of Infectious Disease on Structure and Dynamics of PopulationsK01HD057246 · NICHD · UNIVERSITY OF WASHINGTON · PI CLARK, SAMUEL J · 2008 to 2012
$620k
NIA NIH HHS R01 AG049634NIA NIH HHS R24 AG032112NICHD NIH HHS K01 HD057246NICHD NIH HHS P2C HD066613NICHD NIH HHS R01 HD086227NICHD NIH HHS R24 HD066613Wellcome TrustWellcome Trust 058893/Z/99/AWellcome Trust 069683/Z/02/ZWellcome Trust 085477/B/08/ZWellcome Trust 085477/Z/08/Z
6 · The paper itself

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.

Indexed as

AdolescentAdultAgedAged, 80 and overFemaleHIV InfectionsHumansMaleMiddle AgedSexual BehaviorSouth AfricaYoung AdultClusteringHIVSexual behaviorSouth Africa

Identifiers

PMID32232623
PMCPMC7321875

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.