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Wealth inequality as a predictor of HIV-related knowledge in Nigeria

INTRODUCTION: Considering the high state-level heterogeneity of HIV prevalence and socioeconomic characteristics in Nigeria, it is a relevant setting for studies into the socioeconomic correlates of HIV-related knowledge. Although the relationship between absolute poverty and HIV transmission has be...

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Autores principales: Faust, Lena, Yaya, Sanni, Ekholuenetale, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759704/
https://www.ncbi.nlm.nih.gov/pubmed/29333285
http://dx.doi.org/10.1136/bmjgh-2017-000461
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author Faust, Lena
Yaya, Sanni
Ekholuenetale, Michael
author_facet Faust, Lena
Yaya, Sanni
Ekholuenetale, Michael
author_sort Faust, Lena
collection PubMed
description INTRODUCTION: Considering the high state-level heterogeneity of HIV prevalence and socioeconomic characteristics in Nigeria, it is a relevant setting for studies into the socioeconomic correlates of HIV-related knowledge. Although the relationship between absolute poverty and HIV transmission has been studied, the role of wealth inequality in the dynamics of the HIV epidemic has yet to be investigated in Nigeria. The current study, therefore, investigates wealth inequality and other sociodemographic covariates as predictors of HIV-related knowledge, in order to identify subgroups of the Nigerian population that would benefit from HIV preventive interventions. METHODS: This study used the nationally representative 2013 Nigerian Demographic and Health Survey (NDHS). HIV-related knowledge was computed as a total score based on HIV-related knowledge indicators in the NDHS, dichotomised using the sample median as the cut-off. Wealth inequality and other relevant sociodemographic variables were introduced into a logistic regression model based on their significance in bivariate analyses. ORs derived from the model were interpreted to identify risk groups for low HIV-related knowledge after adjusting for confounding factors. RESULTS: The regression model indicated that individuals with lower literacy levels were almost twice as likely as literate respondents to have low HIV-related knowledge (adjusted OR (AOR): 1.95, 95% CI 1.85 to 2.05, P<0.001), and individuals in the upper wealth quintile were less than half as likely than those in the lower wealth quintile to have low HIV-related knowledge (AOR: 0.40, 95% CI 0.35 to 0.46, P<0.001). Women were also more than twice as likely as men to have low HIV-related knowledge at each level of wealth inequality. In addition, women were 80% less likely to have low mother-to-child transmission knowledge than men, but had over 1.5 times higher odds of having poor knowledge of HIV risk reduction measures. Ethnicity, religious affiliation, relationship status and residing in rural areas were additional significant predictors of HIV-related knowledge. CONCLUSION: HIV-related knowledge in this sample is generally low among women, those with low literacy levels, the poor, the unemployed, those residing in rural areas, those with traditional religious beliefs and those living in states with the highest wealth inequality ratios. The identification of these risk groups for low HIV-related knowledge facilitates the implementation of future evidence-based interventions among these groups in order to potentially reduce HIV transmission.
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spelling pubmed-57597042018-01-12 Wealth inequality as a predictor of HIV-related knowledge in Nigeria Faust, Lena Yaya, Sanni Ekholuenetale, Michael BMJ Glob Health Research INTRODUCTION: Considering the high state-level heterogeneity of HIV prevalence and socioeconomic characteristics in Nigeria, it is a relevant setting for studies into the socioeconomic correlates of HIV-related knowledge. Although the relationship between absolute poverty and HIV transmission has been studied, the role of wealth inequality in the dynamics of the HIV epidemic has yet to be investigated in Nigeria. The current study, therefore, investigates wealth inequality and other sociodemographic covariates as predictors of HIV-related knowledge, in order to identify subgroups of the Nigerian population that would benefit from HIV preventive interventions. METHODS: This study used the nationally representative 2013 Nigerian Demographic and Health Survey (NDHS). HIV-related knowledge was computed as a total score based on HIV-related knowledge indicators in the NDHS, dichotomised using the sample median as the cut-off. Wealth inequality and other relevant sociodemographic variables were introduced into a logistic regression model based on their significance in bivariate analyses. ORs derived from the model were interpreted to identify risk groups for low HIV-related knowledge after adjusting for confounding factors. RESULTS: The regression model indicated that individuals with lower literacy levels were almost twice as likely as literate respondents to have low HIV-related knowledge (adjusted OR (AOR): 1.95, 95% CI 1.85 to 2.05, P<0.001), and individuals in the upper wealth quintile were less than half as likely than those in the lower wealth quintile to have low HIV-related knowledge (AOR: 0.40, 95% CI 0.35 to 0.46, P<0.001). Women were also more than twice as likely as men to have low HIV-related knowledge at each level of wealth inequality. In addition, women were 80% less likely to have low mother-to-child transmission knowledge than men, but had over 1.5 times higher odds of having poor knowledge of HIV risk reduction measures. Ethnicity, religious affiliation, relationship status and residing in rural areas were additional significant predictors of HIV-related knowledge. CONCLUSION: HIV-related knowledge in this sample is generally low among women, those with low literacy levels, the poor, the unemployed, those residing in rural areas, those with traditional religious beliefs and those living in states with the highest wealth inequality ratios. The identification of these risk groups for low HIV-related knowledge facilitates the implementation of future evidence-based interventions among these groups in order to potentially reduce HIV transmission. BMJ Publishing Group 2017-12-20 /pmc/articles/PMC5759704/ /pubmed/29333285 http://dx.doi.org/10.1136/bmjgh-2017-000461 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Research
Faust, Lena
Yaya, Sanni
Ekholuenetale, Michael
Wealth inequality as a predictor of HIV-related knowledge in Nigeria
title Wealth inequality as a predictor of HIV-related knowledge in Nigeria
title_full Wealth inequality as a predictor of HIV-related knowledge in Nigeria
title_fullStr Wealth inequality as a predictor of HIV-related knowledge in Nigeria
title_full_unstemmed Wealth inequality as a predictor of HIV-related knowledge in Nigeria
title_short Wealth inequality as a predictor of HIV-related knowledge in Nigeria
title_sort wealth inequality as a predictor of hiv-related knowledge in nigeria
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5759704/
https://www.ncbi.nlm.nih.gov/pubmed/29333285
http://dx.doi.org/10.1136/bmjgh-2017-000461
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