Spatial distribution and geographical heterogeneity factors associated with households' enrollment level in community-based health insurance - Demsash, Addisalem Workie (Frontiers in Public Health, 2024)
Healthcare service utilization is unequal among different subpopulations in low-income countries. For healthcare access and service utilization with partial or full support, households are recommended to be enrolled in a community-based health insurance system (CBHIS). However, many households in low-income countries suffer from catastrophic health expenditures. This study aimed to assess the spatial distribution and factors associated with households’ enrollment level in CBHIS. A cross-sectional study design with two-stage sampling techniques was used. The 2019 EMDHS data was used. STATA 15 software and Microsoft Office Excel were used for data management. ArcMap 10.7 and SaTScan 9.5 software were used for geographically weighted regression analysis and mapping the results. A multilevel fixed-effect regression was used to assess the association of variables. A variable with a p-value <0.05 was considered a significant factor with a 95% confidence interval. Nearly three out of ten (28.6%) households were enrolled in a CBHIS. The spatial distribution of households’ enrollment in the health insurance system wasn’t random, and households in the Amhara and Tigray regions had good enrollment in community-based health insurance. A total of 126 significant clusters were detected, and households in the primary clusters were more likely to be enrolled in CBHIS. Primary education (AOR: 1.21, 95% CI: 1.05, 1.31), age >35 years (AOR: 2.47, 95% CI: 2.04, 3.02), being poor (AOR: .31, 95% CI: .21, 1.31), media exposure (AOR: 1.35, 95% CI: 1.02, 2.27), Afar (AOR: .01, 95% CI: .003, .03), Gambela (AOR: .03, 95% CI: .01, .08), Harari (AOR: .06, 95% CI: .02, .18), and Dire Dawa (AOR: 0.02, 95% CI: .01, .06) regions were significant factors for households’ enrollment in CBHIS. Secondary educational status, poor wealth status, and media exposure had a stationary significant positive and negative effect on the enrollment of households in CBHIS across the geographical areas of the country. The majority of households hadn’t enrolled in CBHIS. Effective CBHIS frameworks and packages are required to enhance the enrollment level of households. Financial support and subsidies the premiums are also critical to enhance households’ enrollment in CBHIS.