Cargando…
Socio-economic differences in the uptake of HIV testing and associated factors in South Africa
BACKGROUND: Improved understanding of barriers to HIV testing is important for reaching the first of the UNAIDS 90–90-90 targets, which states that 90% of HIV positive individuals ought to know their HIV status. This study examined socio-economic status (SES) differences in HIV testing uptake and as...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390264/ https://www.ncbi.nlm.nih.gov/pubmed/34445996 http://dx.doi.org/10.1186/s12889-021-11583-1 |
_version_ | 1783743054345142272 |
---|---|
author | Jooste, Sean Mabaso, Musawenkosi Taylor, Myra North, Alicia Shean, Yolande Simbayi, Leickness Chisamu |
author_facet | Jooste, Sean Mabaso, Musawenkosi Taylor, Myra North, Alicia Shean, Yolande Simbayi, Leickness Chisamu |
author_sort | Jooste, Sean |
collection | PubMed |
description | BACKGROUND: Improved understanding of barriers to HIV testing is important for reaching the first of the UNAIDS 90–90-90 targets, which states that 90% of HIV positive individuals ought to know their HIV status. This study examined socio-economic status (SES) differences in HIV testing uptake and associated factors among youth and adults 15 years and older in South Africa. METHODS: This study used data from a national cross-sectional, population-based household survey conducted in 2017 using a multi-stage sampling design. A composite SES score was created using multiple correspondence analyses of household assets; households were classified into wealth quintiles and dichotomised into low SES/poorest (lowest 3 quintiles) and high SES/less-poor (highest 2 quintiles). Bivariate and multivariate logistic regression models were used to examine factors associated with the uptake of HIV testing in low and high SES households. RESULTS: HIV testing uptake was 73.8 and 76.7% among low and high SES households, respectively, both of which were below the first 90 targets. Among both low and high SES households, increased HIV testing uptake was significantly associated with females than males. The decreased likelihood was significantly associated with residing in rural formal areas than urban areas, those with no education or low levels of educational attainment and alcohol drinkers among low SES households. Whites and Indians/Asians had a decreased likelihood than Black Africans in high SES households. CONCLUSIONS: HIV testing interventions should target males, residents in rural formal areas, those with no or low education and those that consume alcohol in low SES households, including Whites and Indians/Asians from high SES households in order to bridge socio-economic disparities in the uptake of HIV testing. This should entail expanding HIV testing beyond traditional centres for voluntary counselling and testing through outreach efforts, including mobile testing and home-based testing. |
format | Online Article Text |
id | pubmed-8390264 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83902642021-08-27 Socio-economic differences in the uptake of HIV testing and associated factors in South Africa Jooste, Sean Mabaso, Musawenkosi Taylor, Myra North, Alicia Shean, Yolande Simbayi, Leickness Chisamu BMC Public Health Research Article BACKGROUND: Improved understanding of barriers to HIV testing is important for reaching the first of the UNAIDS 90–90-90 targets, which states that 90% of HIV positive individuals ought to know their HIV status. This study examined socio-economic status (SES) differences in HIV testing uptake and associated factors among youth and adults 15 years and older in South Africa. METHODS: This study used data from a national cross-sectional, population-based household survey conducted in 2017 using a multi-stage sampling design. A composite SES score was created using multiple correspondence analyses of household assets; households were classified into wealth quintiles and dichotomised into low SES/poorest (lowest 3 quintiles) and high SES/less-poor (highest 2 quintiles). Bivariate and multivariate logistic regression models were used to examine factors associated with the uptake of HIV testing in low and high SES households. RESULTS: HIV testing uptake was 73.8 and 76.7% among low and high SES households, respectively, both of which were below the first 90 targets. Among both low and high SES households, increased HIV testing uptake was significantly associated with females than males. The decreased likelihood was significantly associated with residing in rural formal areas than urban areas, those with no education or low levels of educational attainment and alcohol drinkers among low SES households. Whites and Indians/Asians had a decreased likelihood than Black Africans in high SES households. CONCLUSIONS: HIV testing interventions should target males, residents in rural formal areas, those with no or low education and those that consume alcohol in low SES households, including Whites and Indians/Asians from high SES households in order to bridge socio-economic disparities in the uptake of HIV testing. This should entail expanding HIV testing beyond traditional centres for voluntary counselling and testing through outreach efforts, including mobile testing and home-based testing. BioMed Central 2021-08-26 /pmc/articles/PMC8390264/ /pubmed/34445996 http://dx.doi.org/10.1186/s12889-021-11583-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Jooste, Sean Mabaso, Musawenkosi Taylor, Myra North, Alicia Shean, Yolande Simbayi, Leickness Chisamu Socio-economic differences in the uptake of HIV testing and associated factors in South Africa |
title | Socio-economic differences in the uptake of HIV testing and associated factors in South Africa |
title_full | Socio-economic differences in the uptake of HIV testing and associated factors in South Africa |
title_fullStr | Socio-economic differences in the uptake of HIV testing and associated factors in South Africa |
title_full_unstemmed | Socio-economic differences in the uptake of HIV testing and associated factors in South Africa |
title_short | Socio-economic differences in the uptake of HIV testing and associated factors in South Africa |
title_sort | socio-economic differences in the uptake of hiv testing and associated factors in south africa |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390264/ https://www.ncbi.nlm.nih.gov/pubmed/34445996 http://dx.doi.org/10.1186/s12889-021-11583-1 |
work_keys_str_mv | AT joostesean socioeconomicdifferencesintheuptakeofhivtestingandassociatedfactorsinsouthafrica AT mabasomusawenkosi socioeconomicdifferencesintheuptakeofhivtestingandassociatedfactorsinsouthafrica AT taylormyra socioeconomicdifferencesintheuptakeofhivtestingandassociatedfactorsinsouthafrica AT northalicia socioeconomicdifferencesintheuptakeofhivtestingandassociatedfactorsinsouthafrica AT sheanyolande socioeconomicdifferencesintheuptakeofhivtestingandassociatedfactorsinsouthafrica AT simbayileicknesschisamu socioeconomicdifferencesintheuptakeofhivtestingandassociatedfactorsinsouthafrica |