Identifying groups of people with similar sociobehavioural characteristics in Malawi to inform HIV interventions: a latent class analysis

Introduction Within many sub‐Saharan African countries including Malawi, HIV prevalence varies widely between regions. This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influence the transmission of HIV and the uptake of prev...

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Veröffentlicht in:Journal of the International AIDS Society 2020-09, Vol.23 (9), p.e25615-n/a
Hauptverfasser: Merzouki, Aziza, Styles, Amanda, Estill, Janne, Orel, Erol, Baranczuk, Zofia, Petrie, Karen, Keiser, Olivia
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container_start_page e25615
container_title Journal of the International AIDS Society
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creator Merzouki, Aziza
Styles, Amanda
Estill, Janne
Orel, Erol
Baranczuk, Zofia
Petrie, Karen
Keiser, Olivia
description Introduction Within many sub‐Saharan African countries including Malawi, HIV prevalence varies widely between regions. This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influence the transmission of HIV and the uptake of prevention. In this study, we intended to identify groups of people in Malawi with similar risk profiles. Methods We used data from the Demographic and Health Survey in Malawi (2015 to 2016), and stratified the analysis by sex. We considered demographic, socio‐behavioural and HIV‐related variables. Using Latent Class Analysis (LCA), we identified groups of people sharing common sociobehavioural characteristics. The optimal number of classes (groups) was selected based on the Bayesian information criterion. We compared the proportions of individuals belonging to the different groups across the three regions and 28 districts of Malawi. Results We found nine groups of women and six groups of men. Most women in the groups with highest risk of being HIV positive were living in female‐headed households and were formerly married or in a union. Among men, older men had the highest risk of being HIV positive, followed by young (20 to 25) single men. Generally, low HIV testing uptake correlated with lower risk of having HIV. However, rural adolescent girls had a low probability of being tested (48.7%) despite a relatively high HIV prevalence. Urban districts and the Southern region had a higher percentage of high‐prevalence and less tested groups of individuals than other areas. Conclusions LCA is an efficient method to find groups of people sharing common HIV risk profiles, identify particularly vulnerable sub‐populations, and plan targeted interventions focusing on these groups. Tailored support, prevention and HIV testing programmes should focus particularly on female household heads, adolescent girls living in rural areas, older married men and young men who have never been married.
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This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influence the transmission of HIV and the uptake of prevention. In this study, we intended to identify groups of people in Malawi with similar risk profiles. Methods We used data from the Demographic and Health Survey in Malawi (2015 to 2016), and stratified the analysis by sex. We considered demographic, socio‐behavioural and HIV‐related variables. Using Latent Class Analysis (LCA), we identified groups of people sharing common sociobehavioural characteristics. The optimal number of classes (groups) was selected based on the Bayesian information criterion. We compared the proportions of individuals belonging to the different groups across the three regions and 28 districts of Malawi. Results We found nine groups of women and six groups of men. Most women in the groups with highest risk of being HIV positive were living in female‐headed households and were formerly married or in a union. Among men, older men had the highest risk of being HIV positive, followed by young (20 to 25) single men. Generally, low HIV testing uptake correlated with lower risk of having HIV. However, rural adolescent girls had a low probability of being tested (48.7%) despite a relatively high HIV prevalence. Urban districts and the Southern region had a higher percentage of high‐prevalence and less tested groups of individuals than other areas. Conclusions LCA is an efficient method to find groups of people sharing common HIV risk profiles, identify particularly vulnerable sub‐populations, and plan targeted interventions focusing on these groups. Tailored support, prevention and HIV testing programmes should focus particularly on female household heads, adolescent girls living in rural areas, older married men and young men who have never been married.</description><identifier>ISSN: 1758-2652</identifier><identifier>EISSN: 1758-2652</identifier><identifier>DOI: 10.1002/jia2.25615</identifier><identifier>PMID: 32985772</identifier><language>eng</language><publisher>Switzerland: International AIDS Society</publisher><subject>Acquired immune deficiency syndrome ; Adolescent ; Adult ; Age ; AIDS ; Bayes Theorem ; Child ; Demographic aspects ; Disease transmission ; Female ; Health aspects ; HIV ; HIV infection ; HIV infections ; HIV Infections - epidemiology ; HIV Infections - psychology ; HIV prevalence ; HIV testing ; Households ; Human immunodeficiency virus ; Humans ; Interpersonal relations ; Latent Class Analysis ; Literacy ; Malawi ; Malawi - epidemiology ; Male ; Medical tests ; Middle Aged ; Population ; Prevalence ; Prevention ; Risk factors ; risk groups ; Rural Population - statistics &amp; numerical data ; Sex Factors ; Sexual intercourse ; Sexually transmitted disease prevention ; Social aspects ; Social Behavior ; spatial distribution ; Variables ; Women ; Young Adult</subject><ispartof>Journal of the International AIDS Society, 2020-09, Vol.23 (9), p.e25615-n/a</ispartof><rights>2020 The Authors. Journal of the International AIDS Society published by John Wiley &amp; Sons Ltd on behalf of the International AIDS Society.</rights><rights>COPYRIGHT 2020 International AIDS Society</rights><rights>COPYRIGHT 2020 John Wiley &amp; Sons, Inc.</rights><rights>2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). 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This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influence the transmission of HIV and the uptake of prevention. In this study, we intended to identify groups of people in Malawi with similar risk profiles. Methods We used data from the Demographic and Health Survey in Malawi (2015 to 2016), and stratified the analysis by sex. We considered demographic, socio‐behavioural and HIV‐related variables. Using Latent Class Analysis (LCA), we identified groups of people sharing common sociobehavioural characteristics. The optimal number of classes (groups) was selected based on the Bayesian information criterion. We compared the proportions of individuals belonging to the different groups across the three regions and 28 districts of Malawi. Results We found nine groups of women and six groups of men. Most women in the groups with highest risk of being HIV positive were living in female‐headed households and were formerly married or in a union. Among men, older men had the highest risk of being HIV positive, followed by young (20 to 25) single men. Generally, low HIV testing uptake correlated with lower risk of having HIV. However, rural adolescent girls had a low probability of being tested (48.7%) despite a relatively high HIV prevalence. Urban districts and the Southern region had a higher percentage of high‐prevalence and less tested groups of individuals than other areas. Conclusions LCA is an efficient method to find groups of people sharing common HIV risk profiles, identify particularly vulnerable sub‐populations, and plan targeted interventions focusing on these groups. Tailored support, prevention and HIV testing programmes should focus particularly on female household heads, adolescent girls living in rural areas, older married men and young men who have never been married.</description><subject>Acquired immune deficiency syndrome</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Age</subject><subject>AIDS</subject><subject>Bayes Theorem</subject><subject>Child</subject><subject>Demographic aspects</subject><subject>Disease transmission</subject><subject>Female</subject><subject>Health aspects</subject><subject>HIV</subject><subject>HIV infection</subject><subject>HIV infections</subject><subject>HIV Infections - epidemiology</subject><subject>HIV Infections - psychology</subject><subject>HIV prevalence</subject><subject>HIV testing</subject><subject>Households</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Interpersonal relations</subject><subject>Latent Class Analysis</subject><subject>Literacy</subject><subject>Malawi</subject><subject>Malawi - epidemiology</subject><subject>Male</subject><subject>Medical tests</subject><subject>Middle Aged</subject><subject>Population</subject><subject>Prevalence</subject><subject>Prevention</subject><subject>Risk factors</subject><subject>risk groups</subject><subject>Rural Population - statistics &amp; 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This variability may be related to the distribution of population groups with specific sociobehavioural characteristics that influence the transmission of HIV and the uptake of prevention. In this study, we intended to identify groups of people in Malawi with similar risk profiles. Methods We used data from the Demographic and Health Survey in Malawi (2015 to 2016), and stratified the analysis by sex. We considered demographic, socio‐behavioural and HIV‐related variables. Using Latent Class Analysis (LCA), we identified groups of people sharing common sociobehavioural characteristics. The optimal number of classes (groups) was selected based on the Bayesian information criterion. We compared the proportions of individuals belonging to the different groups across the three regions and 28 districts of Malawi. Results We found nine groups of women and six groups of men. Most women in the groups with highest risk of being HIV positive were living in female‐headed households and were formerly married or in a union. Among men, older men had the highest risk of being HIV positive, followed by young (20 to 25) single men. Generally, low HIV testing uptake correlated with lower risk of having HIV. However, rural adolescent girls had a low probability of being tested (48.7%) despite a relatively high HIV prevalence. Urban districts and the Southern region had a higher percentage of high‐prevalence and less tested groups of individuals than other areas. Conclusions LCA is an efficient method to find groups of people sharing common HIV risk profiles, identify particularly vulnerable sub‐populations, and plan targeted interventions focusing on these groups. Tailored support, prevention and HIV testing programmes should focus particularly on female household heads, adolescent girls living in rural areas, older married men and young men who have never been married.</abstract><cop>Switzerland</cop><pub>International AIDS Society</pub><pmid>32985772</pmid><doi>10.1002/jia2.25615</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-6418-2945</orcidid><orcidid>https://orcid.org/0000-0001-9544-1447</orcidid><oa>free_for_read</oa></addata></record>
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subjects Acquired immune deficiency syndrome
Adolescent
Adult
Age
AIDS
Bayes Theorem
Child
Demographic aspects
Disease transmission
Female
Health aspects
HIV
HIV infection
HIV infections
HIV Infections - epidemiology
HIV Infections - psychology
HIV prevalence
HIV testing
Households
Human immunodeficiency virus
Humans
Interpersonal relations
Latent Class Analysis
Literacy
Malawi
Malawi - epidemiology
Male
Medical tests
Middle Aged
Population
Prevalence
Prevention
Risk factors
risk groups
Rural Population - statistics & numerical data
Sex Factors
Sexual intercourse
Sexually transmitted disease prevention
Social aspects
Social Behavior
spatial distribution
Variables
Women
Young Adult
title Identifying groups of people with similar sociobehavioural characteristics in Malawi to inform HIV interventions: a latent class analysis
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