Determinants of healthcare insurance coverage among women of reproductive age in Tanzania: A multilevel mixed effect analysis

• DOI: 10.1371/journal.pone.0302806
• Publication Date: 2024-12-19T18:34:56Z
• Authors: Sanun Ally Kessy; Jovin R. Tibenderana; Jomo Gimonge; Fabiola V. Moshi
• Keywords: 03 medical and health sciences; 0302 clinical medicine; Science; Q; R; Medicine; Research Article

Background Health insurance has been one of the fundamental approaches of financing healthcare for sustainable Development goals (SDGs). There is a paucity of evidence on the determinants of healthcare insurance coverage among women of reproductive age in Tanzania, therefore this study aimed at assessing factors associated with access to health care insurance among women of reproductive age in Tanzania using national Demographic and health survey dataset.

Methodology This study was an analytical cross-sectional study that utilized nationally representative secondary data sourced from the Tanzania Demographic and Health Surveys (TDHS) of 2022. A weighted sample of 15,254 women of reproductive age (15–49) was included in the study. A multilevel regression analysis was used to examine factors associated with health care insurance coverage. These results were presented using adjusted odds ratio (AOR) with a 95% confidence interval.

Results In Tanzania the proportion of health insurance coverage among women of reproductive age was 5.8% whereby majority of women subscribing to employer’s insurance (3.9%). In the fixed effect model, older women (35–49) were more likely to be covered with health insurance compared those aged 15–24 (AOR = 2.75, 95% CI: 2.19, 3.45). Similarly, married women had higher likelihood of health insurance coverage compared to unmarried (AOR = 1.60, 95% CI: 1.33, 1.92). Furthermore, educated women were more likely to be covered with health insurance than uneducated women (AOR = 6.96, 95% CI: 4.74, 10.22). Similarly, women who were exposed to mass media were more likely to be covered with health care insurance compared to unexposed (AOR = 1.43, 95% CI: 1.14, 1.78), in the Random effect model Intra-Cluster Correlation (ICC) value in Model III was 0.27

Conclusion The low health insurance coverage among Tanzanian women of reproductive age reveals significant gaps in healthcare access Socioeconomic factors, along with limited access to reliable health information, highlight the importance of comprehensive and inclusive strategies to increase healthcare coverage. By implementing multifaceted approaches that tackle these root causes, Tanzania can improve the health and well-being of its women, ultimately contributing to a healthier and more resilient society.