Factors Associated With Coverage of Health Insurance Among Women in Malawi

**Background:** Universal health coverage (UHC) is a global priority, yet many low-income countries face significant gaps in health insurance coverage, particularly among vulnerable groups such as women. In Malawi, the health system is predominantly public (63% of services), but out-of-pocket expenditures are rising, and only 1% of women have health insurance. Women bear a disproportionate burden of disease and caregiving, and face economic inequalities that limit their access to healthcare. This study aimed to identify demographic and socioeconomic factors associated with health insurance coverage among women in Malawi to inform policy and health financing reforms.

**Methods:** This was a quantitative, cross-sectional analysis of secondary data from the 2015–2016 Malawi Demographic and Health Survey (MDHS). The study included 24,562 women aged 15–49 years who responded to the health insurance module. Data were collected using structured questionnaires by trained enumerators. The dependent variable was ownership of health insurance (dichotomized as yes/no). Independent variables included age (continuous), residence (urban/rural), education (primary vs. higher), occupation (informal vs. formal), marital status (not in union vs. married), household head (male/female), and wealth (poorer, middle, richest). Bivariate analysis used chi-squared tests, and multivariate analysis used binary logistic regression. The model was fitted using STATA version 13, with backward elimination of non-significant variables. Goodness of fit was assessed using Pearson's chi-squared test.

**Key Results:** Of the 24,562 women (mean age 28 years, SD 9.3), only 1.5% (380) had health insurance. Among those insured, 87% had employment-linked coverage and the remainder had commercial insurance. Most women were from rural areas (81.7%), married (65.7%), and in male-headed households (70.5%). The majority had primary education or less (96.98%) and worked in the informal sector (87.9%). In bivariate analysis, education, wealth, occupation, and age were significantly associated with insurance coverage (p < 0.01), while residence, marital status, and household head were not. In the multivariate logistic regression, the following factors were significantly associated with health insurance ownership: higher education (OR = 5.61, 95% CI: 4.26–7.38, p < 0.001), middle wealth (OR = 3.03, 95% CI: 1.56–5.92, p = 0.001), richest wealth (OR = 15.98, 95% CI: 8.45–30.20, p < 0.001), and formal occupation (OR = 2.40, 95% CI: 1.85–3.12, p < 0.001). Age (OR = 1.01, p = 0.254), residence (OR = 0.79, p = 0.079), household head (OR = 0.93, p = 0.607), and marital status (OR = 1.29, p = 0.089) were not statistically significant. The model had a pseudo R² of 0.2345 and a Pearson chi² of 1,461.89 (p < 0.001).

**Clinical Implications:** The extremely low health insurance coverage among Malawian women (1.5%) underscores a critical gap in financial protection for healthcare. The strong associations with education, wealth, and formal employment suggest that current insurance mechanisms primarily benefit the socioeconomically advantaged. Policymakers should consider designing a social health insurance system with progressive premiums, targeting women in the informal sector through cooperatives and associations (e.g., NABW, MUFIS). Investments in women's tertiary education and expansion of economic opportunities to rural areas are essential to address underlying determinants. Cross-sectoral collaboration between health, education, gender, and economic development ministries is needed to achieve universal health coverage and reduce gender-based health inequities.