Assessing Health Insurance Coverage and the determinants of non-enrollment among adults in rural Tanzania. A cross-sectional study in Mlimba District

Abstract Background Health insurance is a key financial risk protection mechanism aimed at reducing out-of-pocket health expenditure and improving equitable access to healthcare. Despite health financing reforms in Tanzania, many households continue to rely on direct payments, exposing them to catastrophic health expenditure, particularly among individuals with chronic illness. Evidence on health insurance coverage and its determinants in rural and semi-urban settings remains limited after the introduction of Universal Health Insurance. This study aimed to assess health insurance coverage and identify determinants of non-enrollment among adults in Mlimba District, thereby providing baseline evidence to inform implementation of Universal Health Insurance. Methods A community-based analytical cross-sectional study was conducted in December 2025 among 201 adults selected through multistage sampling. Data on socio-demographic characteristics, health status, and insurance-related factors were collected using structured questionnaires administered through Kobo Collect. Modified Poisson regression was applied to estimate prevalence ratios for factors associated with insurance non-enrollment using STATA version 17.0. Results Participants had a median age of 31 years (IQR: 25–41); 55.7% were female, 52.7% had primary education, and 76.1% were self-employed. Overall, 94.5% (95% CI: 90.4–97.0) were not enrolled in any health insurance scheme. Only government employment (aPR = 0.53; 95% CI: 0.29–0.96) and presence of chronic illness (aPR = 0.28; 95% CI: 0.09–0.90) were independently associated with lower prevalence of non-enrollment. Conclusion Health insurance non-enrollment in Mlimba District Council remains critically high, underscoring persistent challenges in implementing and enforcing mandatory health insurance enrollment under the UHI framework, particularly among informal sector populations.