Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.

<h4>Background</h4>Access to healthcare services for women in low- and middle-income countries (LMICs) is crucial for maternal and child health and achieving the Sustainable Development Goals (SDGs). However, women in LMICs face barriers to accessing healthcare, leading to poor health ou...

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Main Authors: Bewuketu Terefe, Belayneh Shetie Workneh, Gebreeyesus Abera Zeleke, Enyew Getaneh Mekonen, Alebachew Ferede Zegeye, Agazhe Aemro, Berhan Tekeba, Tadesse Tarik Tamir, Mulugeta Wassie, Mohammed Seid Ali
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0314309
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author Bewuketu Terefe
Belayneh Shetie Workneh
Gebreeyesus Abera Zeleke
Enyew Getaneh Mekonen
Alebachew Ferede Zegeye
Agazhe Aemro
Berhan Tekeba
Tadesse Tarik Tamir
Mulugeta Wassie
Mohammed Seid Ali
author_facet Bewuketu Terefe
Belayneh Shetie Workneh
Gebreeyesus Abera Zeleke
Enyew Getaneh Mekonen
Alebachew Ferede Zegeye
Agazhe Aemro
Berhan Tekeba
Tadesse Tarik Tamir
Mulugeta Wassie
Mohammed Seid Ali
author_sort Bewuketu Terefe
collection DOAJ
description <h4>Background</h4>Access to healthcare services for women in low- and middle-income countries (LMICs) is crucial for maternal and child health and achieving the Sustainable Development Goals (SDGs). However, women in LMICs face barriers to accessing healthcare, leading to poor health outcomes. This study used Demographic and Health Survey (DHS) data from 61 LMICs between 2010-2023 to identify women's healthcare access challenges.<h4>Methods</h4>This study used data from the DHS conducted in 61 LMICs to identify women's healthcare access challenges from 2010 to 2023. A weighted sample of 1,722,473 women was included in the study using R-4.4.0 version software. A mixed-effects modeling approach was used to analyze access to healthcare, considering individual-level factors and contextual factors. The mixed-effects model takes into account clustering within countries and allows for the examination of fixed and random effects that influence women's healthcare access across LMICs. For the multivariable analysis, variables with a p-value ≤0.2 in the bivariate analysis were considered. The Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) and a P value < 0.05 was reported to indicate statistical significance and the degree of association in the final model.<h4>Results</h4>The pooled prevalence of the healthcare access problem was found to be 66.06 (95% CI: 61.86, 70.00) with highly heterogeneity across countries and regions. Women aged 25-34 years, and 35-49 years, had primary education, and secondary or higher education, married women, poorer, middle, richer, and richest wealth indices, had mass media exposure, first birth at age ≥20 years, birth interval of 24-36, 37-59 and >59 months as compared to < 24 months birth interval, had health insurance, delivered at a health facility, had at least one ANC visit, being from lower-middle-income countries, upper-middle-income countries, regions like West Africa, South Asia, and East Asia/Pacific compared to women living in East Africa, low literacy rates, medium literacy rates, and high literacy rates as compared to very low literacy rate were associated with lower odds of having problems accessing healthcare respectively. On the other hand, divorced/widowed women, having 1-2, and more than two under five, living in households with 6-10 family members and >10 members, female household heads, living in rural areas, women living in South/Central Africa, Middle East/North Africa, Europe/Central Asia, and living in Latin America/Caribbean were associated with higher odds of having problems accessing healthcare respectively.<h4>Conclusions</h4>Approximately two-thirds of women face healthcare access problems. Sociodemographic factors such as age, education, marital status, wealth, media exposure, and health insurance are associated with lower odds of experiencing healthcare access issues. On the other hand, factors such as divorce/widowhood, the number of young children, household size, female household heads, rural residence, and region have been linked to higher odds of facing healthcare access challenges. To address these disparities, policies, and interventions should focus on vulnerable populations by improving access to health insurance, increasing educational attainment, and providing support for single mothers and large households. Additionally, tailored regional approaches may be necessary to overcome barriers to healthcare access.
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spelling doaj-art-f2a92be9c1fc4f709497343f15953ec42025-02-05T05:31:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031430910.1371/journal.pone.0314309Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.Bewuketu TerefeBelayneh Shetie WorknehGebreeyesus Abera ZelekeEnyew Getaneh MekonenAlebachew Ferede ZegeyeAgazhe AemroBerhan TekebaTadesse Tarik TamirMulugeta WassieMohammed Seid Ali<h4>Background</h4>Access to healthcare services for women in low- and middle-income countries (LMICs) is crucial for maternal and child health and achieving the Sustainable Development Goals (SDGs). However, women in LMICs face barriers to accessing healthcare, leading to poor health outcomes. This study used Demographic and Health Survey (DHS) data from 61 LMICs between 2010-2023 to identify women's healthcare access challenges.<h4>Methods</h4>This study used data from the DHS conducted in 61 LMICs to identify women's healthcare access challenges from 2010 to 2023. A weighted sample of 1,722,473 women was included in the study using R-4.4.0 version software. A mixed-effects modeling approach was used to analyze access to healthcare, considering individual-level factors and contextual factors. The mixed-effects model takes into account clustering within countries and allows for the examination of fixed and random effects that influence women's healthcare access across LMICs. For the multivariable analysis, variables with a p-value ≤0.2 in the bivariate analysis were considered. The Adjusted Odds Ratio (AOR) with a 95% Confidence Interval (CI) and a P value < 0.05 was reported to indicate statistical significance and the degree of association in the final model.<h4>Results</h4>The pooled prevalence of the healthcare access problem was found to be 66.06 (95% CI: 61.86, 70.00) with highly heterogeneity across countries and regions. Women aged 25-34 years, and 35-49 years, had primary education, and secondary or higher education, married women, poorer, middle, richer, and richest wealth indices, had mass media exposure, first birth at age ≥20 years, birth interval of 24-36, 37-59 and >59 months as compared to < 24 months birth interval, had health insurance, delivered at a health facility, had at least one ANC visit, being from lower-middle-income countries, upper-middle-income countries, regions like West Africa, South Asia, and East Asia/Pacific compared to women living in East Africa, low literacy rates, medium literacy rates, and high literacy rates as compared to very low literacy rate were associated with lower odds of having problems accessing healthcare respectively. On the other hand, divorced/widowed women, having 1-2, and more than two under five, living in households with 6-10 family members and >10 members, female household heads, living in rural areas, women living in South/Central Africa, Middle East/North Africa, Europe/Central Asia, and living in Latin America/Caribbean were associated with higher odds of having problems accessing healthcare respectively.<h4>Conclusions</h4>Approximately two-thirds of women face healthcare access problems. Sociodemographic factors such as age, education, marital status, wealth, media exposure, and health insurance are associated with lower odds of experiencing healthcare access issues. On the other hand, factors such as divorce/widowhood, the number of young children, household size, female household heads, rural residence, and region have been linked to higher odds of facing healthcare access challenges. To address these disparities, policies, and interventions should focus on vulnerable populations by improving access to health insurance, increasing educational attainment, and providing support for single mothers and large households. Additionally, tailored regional approaches may be necessary to overcome barriers to healthcare access.https://doi.org/10.1371/journal.pone.0314309
spellingShingle Bewuketu Terefe
Belayneh Shetie Workneh
Gebreeyesus Abera Zeleke
Enyew Getaneh Mekonen
Alebachew Ferede Zegeye
Agazhe Aemro
Berhan Tekeba
Tadesse Tarik Tamir
Mulugeta Wassie
Mohammed Seid Ali
Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.
PLoS ONE
title Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.
title_full Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.
title_fullStr Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.
title_full_unstemmed Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.
title_short Uncovering women's healthcare access challenges in low- and middle-income countries using mixed effects modelling approach: Insights for achieving the Sustainable Development Goals.
title_sort uncovering women s healthcare access challenges in low and middle income countries using mixed effects modelling approach insights for achieving the sustainable development goals
url https://doi.org/10.1371/journal.pone.0314309
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