Factors associated with partial health insurance coverage among households in Malawi - Phiri, Jane (Unknown, 2026)
Health insurance has proven ideal for curbing the increase in household contribution towards health expenditure. However, despite efforts to expand health insurance in Sub-Saharan Africa, coverage has remained low and favouring higher-income groups. Malawi is among the countries that face this low uptake, with only 3% of the total population insured. Moreover, within insured households, coverage is often incomplete, leaving some members without protection. This partial insurance coverage increasingly contributes to a reliance on out-of-pocket expenditure (OOPE), a regressive and inequitable financing mechanism that disproportionately affects vulnerable households. However, there is dearth of evidence on factors associated with this phenomenon among households in Malawi, thus, understanding the dynamics of partially insured households is crucial to addressing these gaps, reducing financial barriers to healthcare, and promoting Universal Health Coverage (UHC). Methodology: This study aimed to examine the determinants associated with partially insured households in Malawi. The thesis is divided into three parts: a structured literature review, a journal manuscript and a policy brief. The literature review revealed that most studies in Africa and elsewhere have focused on individual health insurance coverage determinants and not intrahousehold health insurance coverage status determinants. In Malawi, this is coupled with a low health insurance uptake. There is also limited information on factors influencing households to insure some but not all members. This study therefore aimed to fill this gap in literature and inform health financing policies. This quantitative study used cross-sectional secondary Data from the 2019-2020 Multiple Indicator Cluster Survey (MICS). The individual health insurance status; insured and uninsured, was defined as coverage by any health insurance. Using unique identifiers (cluster number, household number and line number), every individual was grouped into their respective households. Consequently, household size was used to determine a household's health insurance coverage status where a household with all members as insured was categorized as fully insured, a household with at least one but not all members insured as partially insured and a household with no member covered as completely uninsured. A two-stage analysis approach was then utilized in this study. Firstly, descriptive statistics were used to analyse and compare fully insured households, partially insured households and completely uninsured households. Zoning into partially insured households, the second stage applied multivariate binary logistic regression to identify factors associated with health insurance coverage. Analysis was done using STATA statistical package version 18. Results: This study had 64,615 unique individuals from 22,886 households. Only 0.6% of individuals had health insurance. A higher proportion of the households were completely uninsured (22,649; 98.96%) with 228 households (1%) being partially insured and the remaining 9 households (0.04%) were fully insured. Household sizes differed significantly among fully, partially insured, and completely uninsured households (median of 1, 5, & 4 respectively; p-value=<0.001). Higher education levels of household heads were strongly associated with full and partial insurance coverage and in contrast, lower education levels, such as no education or primary education, were linked to a lack of insurance coverage (89% vs 50% vs 72%; p-value=<0.001). All fully insured households were from the richest quintile. Age of household head [AOR 1.025 (1.000-1.050);p-value=0.045], higher education level of an individual [ AOR 4.470 (1.519-13.154); p-value=0.007], an individual's access to media [AOR 2.276 (1.050-4.931); p-value=0.037] and a higher dependency ratio [AOR 1.655 (1.111-2.466);p-value=0.014] were positively associated with being an insured individual from a partially insured household with household size [AOR 0.813 (0.682-0.969); p-value=0.022] being negatively associated with the outcome. On the other hand, residential area, sex of an individual and region were not associated with health insurance ownership in partially insured households. Households, therefore, were partially insured mainly because of being with large household members (median size of 5), higher dependency ratio, media access, individuals having no or primary education and being from the poorest quintile. Conclusion: Socioeconomics and household dynamics influence health insurance coverage. This study highlights education, household size, wealth, dependency ratio, and media exposure as significant determinants influencing partial household health insurance enrolment. Partially insured households remain particularly vulnerable as they continue to face financial risks due to uninsured members, highlighting the need for targeted interventions to facilitate their transition to full coverage. The findings emphasize socioeconomic and informational disparities. Therefore, efforts to enhance health insurance enrolment should focus on improving education access, supporting larger and economically disadvantaged households, and leveraging media channels to raise awareness about the benefits of comprehensive health insurance coverage. Implementing policies that enhance affordability, and accessibility will also be essential in achieving universal coverage and reducing financial vulnerability among households. Moreover, these findings are timely given Malawi's commitment to UHC, Sustainable Development Goal 3, and regional targets such as the Abuja Declaration, reinforcing the need for equitable health financing policies that address partial household insurance coverage.