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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 pre...

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Detalles Bibliográficos
Autores principales: Merzouki, Aziza, Styles, Amanda, Estill, Janne, Orel, Erol, Baranczuk, Zofia, Petrie, Karen, Keiser, Olivia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7521110/
https://www.ncbi.nlm.nih.gov/pubmed/32985772
http://dx.doi.org/10.1002/jia2.25615
Descripción
Sumario: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.