Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster survey

Introduction: This study explores the ability of sociodemographic and contextual variables, including ethnicity, rural/urban residence, and region, to predict health insurance enrollment among men in Ghana. Methods: This study employs primary data from the Ghana Micro Indicator Cluster Survey (MI...

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Main Author: Richard Boateng
Format: Article
Language:English
Published: International Network for the Advancement of Medicine, Psychology, and Public Health (INAMPPH) 2024-04-01
Series:Advances in Medicine, Psychology, and Public Health
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Online Access:https://ampphealthjournal-network.org/wp-content/uploads/2024/02/AMPPH_2024_62_73.pdf
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author Richard Boateng
author_facet Richard Boateng
author_sort Richard Boateng
collection DOAJ
description Introduction: This study explores the ability of sociodemographic and contextual variables, including ethnicity, rural/urban residence, and region, to predict health insurance enrollment among men in Ghana. Methods: This study employs primary data from the Ghana Micro Indicator Cluster Survey (MICS) 2017/2018. The compositional and contextual variables were tested as the main predictors of health insurance coverage in two multivariable ordinal logistic models using odd ratios and p-values after Spearman's rho correlation analysis was conducted. Results: Spearman's rho correlation analysis revealed a positive relationship between age and health insurance coverage and a similar relationship between rural/urban residence and health insurance coverage. Educational level and wealth index quintile were the most significant predictors of health insurance coverage among men in Model 1. Including ethnicity, rural/urban area of residence, and regional location as contextual factors in Model 2 revealed an improved effect of the existing sociodemographic variables except for functional difficulty, which was not statistically significant. Discussion: Low health insurance coverage among men can increase vulnerabilities and gendered tendencies associated with enrolment in health insurance services. The sociodemographic and geo-related context-specific variations depict the differential effects in the predictors of men's health insurance coverage.
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institution Kabale University
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spelling doaj-art-049fbfff78324d67b8f12d23bbd0222c2024-11-28T22:44:22ZengInternational Network for the Advancement of Medicine, Psychology, and Public Health (INAMPPH)Advances in Medicine, Psychology, and Public Health3034-88032024-04-0112627310.5281/zenodo.10637403Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster surveyRichard Boateng0https://orcid.org/0000-0002-8642-0895University of Education, Winneba. Department of Health Administration and Education, Winneba, Ghana.Introduction: This study explores the ability of sociodemographic and contextual variables, including ethnicity, rural/urban residence, and region, to predict health insurance enrollment among men in Ghana. Methods: This study employs primary data from the Ghana Micro Indicator Cluster Survey (MICS) 2017/2018. The compositional and contextual variables were tested as the main predictors of health insurance coverage in two multivariable ordinal logistic models using odd ratios and p-values after Spearman's rho correlation analysis was conducted. Results: Spearman's rho correlation analysis revealed a positive relationship between age and health insurance coverage and a similar relationship between rural/urban residence and health insurance coverage. Educational level and wealth index quintile were the most significant predictors of health insurance coverage among men in Model 1. Including ethnicity, rural/urban area of residence, and regional location as contextual factors in Model 2 revealed an improved effect of the existing sociodemographic variables except for functional difficulty, which was not statistically significant. Discussion: Low health insurance coverage among men can increase vulnerabilities and gendered tendencies associated with enrolment in health insurance services. The sociodemographic and geo-related context-specific variations depict the differential effects in the predictors of men's health insurance coverage.https://ampphealthjournal-network.org/wp-content/uploads/2024/02/AMPPH_2024_62_73.pdfhealth insurancemen's healthhealth disparitiesghana
spellingShingle Richard Boateng
Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster survey
Advances in Medicine, Psychology, and Public Health
health insurance
men's health
health disparities
ghana
title Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster survey
title_full Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster survey
title_fullStr Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster survey
title_full_unstemmed Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster survey
title_short Sociodemographic and contextual variables as predictors of men’s health insurance enrolment in Ghana: Evidence from a micro indicator cluster survey
title_sort sociodemographic and contextual variables as predictors of men s health insurance enrolment in ghana evidence from a micro indicator cluster survey
topic health insurance
men's health
health disparities
ghana
url https://ampphealthjournal-network.org/wp-content/uploads/2024/02/AMPPH_2024_62_73.pdf
work_keys_str_mv AT richardboateng sociodemographicandcontextualvariablesaspredictorsofmenshealthinsuranceenrolmentinghanaevidencefromamicroindicatorclustersurvey