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 (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.