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Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model

OBJECTIVES: To identify HIV-socioeconomic predictors as well as the most-at-risk groups of women in Malawi. DESIGN: A cross-sectional survey. SETTING: Malawi PARTICIPANTS: The study used a sample of 6395 women aged 15–49 years from the 2010 Malawi Health and Demographic Surveys. INTERVENTIONS: N/A P...

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Autores principales: Emina, Jacques B O, Madise, Nyovani, Kuepie, Mathias, Zulu, Eliya M, Ye, Yazoume
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657656/
https://www.ncbi.nlm.nih.gov/pubmed/23793677
http://dx.doi.org/10.1136/bmjopen-2012-002459
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author Emina, Jacques B O
Madise, Nyovani
Kuepie, Mathias
Zulu, Eliya M
Ye, Yazoume
author_facet Emina, Jacques B O
Madise, Nyovani
Kuepie, Mathias
Zulu, Eliya M
Ye, Yazoume
author_sort Emina, Jacques B O
collection PubMed
description OBJECTIVES: To identify HIV-socioeconomic predictors as well as the most-at-risk groups of women in Malawi. DESIGN: A cross-sectional survey. SETTING: Malawi PARTICIPANTS: The study used a sample of 6395 women aged 15–49 years from the 2010 Malawi Health and Demographic Surveys. INTERVENTIONS: N/A PRIMARY AND SECONDARY OUTCOME MEASURES: Individual HIV status: positive or not. RESULTS: Findings from the Pearson χ(2) and χ(2) Automatic Interaction Detector analyses revealed that marital status is the most significant predictor of HIV. Women who are no longer in union and living in the highest wealth quintiles households constitute the most-at-risk group, whereas the less-at-risk group includes young women (15–24) never married or in union and living in rural areas. CONCLUSIONS: In the light of these findings, this study recommends: (1) that the design and implementation of targeted interventions should consider the magnitude of HIV prevalence and demographic size of most-at-risk groups. Preventive interventions should prioritise couples and never married people aged 25–49 years and living in rural areas because this group accounts for 49% of the study population and 40% of women living with HIV in Malawi; (2) with reference to treatment and care, higher priority must be given to promoting HIV test, monitoring and evaluation of equity in access to treatment among women in union disruption and never married or women in union aged 30–49 years and living in urban areas; (3) community health workers, households-based campaign, reproductive-health services and reproductive-health courses at school could be used as canons to achieve universal prevention strategy, testing, counselling and treatment.
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spelling pubmed-36576562013-05-21 Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model Emina, Jacques B O Madise, Nyovani Kuepie, Mathias Zulu, Eliya M Ye, Yazoume BMJ Open HIV/AIDS OBJECTIVES: To identify HIV-socioeconomic predictors as well as the most-at-risk groups of women in Malawi. DESIGN: A cross-sectional survey. SETTING: Malawi PARTICIPANTS: The study used a sample of 6395 women aged 15–49 years from the 2010 Malawi Health and Demographic Surveys. INTERVENTIONS: N/A PRIMARY AND SECONDARY OUTCOME MEASURES: Individual HIV status: positive or not. RESULTS: Findings from the Pearson χ(2) and χ(2) Automatic Interaction Detector analyses revealed that marital status is the most significant predictor of HIV. Women who are no longer in union and living in the highest wealth quintiles households constitute the most-at-risk group, whereas the less-at-risk group includes young women (15–24) never married or in union and living in rural areas. CONCLUSIONS: In the light of these findings, this study recommends: (1) that the design and implementation of targeted interventions should consider the magnitude of HIV prevalence and demographic size of most-at-risk groups. Preventive interventions should prioritise couples and never married people aged 25–49 years and living in rural areas because this group accounts for 49% of the study population and 40% of women living with HIV in Malawi; (2) with reference to treatment and care, higher priority must be given to promoting HIV test, monitoring and evaluation of equity in access to treatment among women in union disruption and never married or women in union aged 30–49 years and living in urban areas; (3) community health workers, households-based campaign, reproductive-health services and reproductive-health courses at school could be used as canons to achieve universal prevention strategy, testing, counselling and treatment. BMJ Publishing Group 2013-05-15 /pmc/articles/PMC3657656/ /pubmed/23793677 http://dx.doi.org/10.1136/bmjopen-2012-002459 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/3.0/ and http://creativecommons.org/licenses/by-nc/3.0/legalcode
spellingShingle HIV/AIDS
Emina, Jacques B O
Madise, Nyovani
Kuepie, Mathias
Zulu, Eliya M
Ye, Yazoume
Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model
title Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model
title_full Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model
title_fullStr Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model
title_full_unstemmed Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model
title_short Identifying HIV most-at-risk groups in Malawi for targeted interventions. A classification tree model
title_sort identifying hiv most-at-risk groups in malawi for targeted interventions. a classification tree model
topic HIV/AIDS
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3657656/
https://www.ncbi.nlm.nih.gov/pubmed/23793677
http://dx.doi.org/10.1136/bmjopen-2012-002459
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