Determinants of household community based health insurance membership and healthcare expenditures in rural Awi Zone, Ethiopia : a bivariate logistic regression approach

Abstract

INTRODUCTION : In many developing countries, including Ethiopia, out-of-pocket expenditures for healthcare at the point of service delivery often hinder access to necessary health services, particularly in rural areas where poverty prevails. The purpose of this study was to assess the factors associated with healthcare expenditure and Community Based Health Insurance (CBHI) membership in rural areas of the Awi Zone, Northwest Ethiopia. METHODS : A community-based cross-sectional study on 2939 heads of household was conducted using a multistage sampling technique. The data were edited and cleaned using STATA 18 and analyzed in SAS 9.4. Bivariate logistic regression analyses were used to identify factors associated with healthcare expenditure and CBHI membership. RESULTS : Out of the 2939 participants, 1740 (59.2%) were members of the CBHI, and 1757 (59.8%) incurred healthcare expenses, Disability was a significant predictor for both CBHI membership (AOR = 1.45; 95% CI: 1.23, 2.86) and healthcare expenditure (AOR = 1.53; 95% CI: 1.07, 2.19). income with 5001–10,000Birr also a significant predictor for both CBHI membership (AOR = 0.43; 95% CI: 0.31, 0.58) and healthcare expenditure ( AOR = 1.69; 95% CI: 1.27, 2.24). no chronic illness also other significant predictor for both CBHI membership (AOR = 1.53; 95% CI: 1.23, 1.86) and healthcare expenditure (AOR = 1.3; 95% CI: 1.07, 1.58). In addition, gender, family size for health care expenditures, and place of residence for CBHI membership were significant predictors. CONCLUSION : These findings highlight the need for targeted interventions to improve the understanding and perception of CBHI among rural households, with a focus on these key determinants. Policies should aim to increase CBHI membership and minimize healthcare expenditure, and awareness campaigns should be enhanced, with a focus on vulnerable groups such as females, people with disabilities, those with chronic illnesses, and low-income households.