Health insurance coverage among men and women in six countries within the Southeast Asia Region (2015–2022): a multilevel analysis of Demographic and Health Surveys
{"title":"Health insurance coverage among men and women in six countries within the Southeast Asia Region (2015–2022): a multilevel analysis of Demographic and Health Surveys","authors":"Nishikant Singh , Pratheeba John , Sudheer Kumar Shukla , Rimjhim Bajpai , Rituparna Sengupta , Rajeev Sadanandan , Navin Singh","doi":"10.1016/j.lansea.2025.100634","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Equitable access to quality healthcare without financial hardship is key to achieving Universal Health Coverage (UHC), especially in low- and middle-income countries in the WHO Southeast Asia Region (SEAR). Despite health insurance programmes, high out-of-pocket expenditures remain a barrier. This study evaluates health insurance coverage in SEAR, analysing socioeconomic and demographic factors.</div></div><div><h3>Methods</h3><div>This cross-sectional study used data from Demographic and Health Surveys (2015–2022) conducted in countries within the SEAR (data from six countries for women and five for men). Our analysis separately examined women and men aged 15–49 years using data from their respective individual Demographic and Health Survey datasets. Pooled estimates of health insurance coverage were calculated with 95% CI. Multilevel logistic regression quantified variations at the country and community-levels and identified factors influencing health insurance uptake.</div></div><div><h3>Findings</h3><div>Health insurance coverage varied across SEAR, with Indonesia reporting highest for women (58.2%; 95% CI: 57.65–58.72) and men (56.6%; 95% CI: 55.31–57.88), while lowest in Bangladesh for women (0.3%; 95% CI: 0.22–0.39) and Myanmar for men (1.4%; 95% CI: 1.04–1.83). Indonesia also had highest social security health insurance (women: 31.0%; 95% CI: 30.49–31.49, men: 27.9%; 95% CI: 26.74–29.03). Private insurance was lowest in Myanmar (women: 0.6%; 95% CI: 0.42–0.72, men: 0.9%; 95% CI: 0.60–1.27) and highest in Indonesia (women: 28.0%; 95% CI: 27.54–28.5, men: 30.0%; 95% CI: 28.81–31.14). Health insurance coverage was higher among individuals with higher education, greater exposure to mass media, rural residence, and older age. Insurance uptake was influenced by contextual factors beyond individual characteristics. India had highest community-attributable variation in health insurance uptake [women (53.1%; 95% CI: 52.56–53.62); men (56.3%; 95% CI: 55.17–57.46)], while lowest in Indonesia among women (17.7%; 95% CI: 16.40–18.99) and Maldives among men (10.8%; 95% CI: 6.71–16.84), after adjusting for demographic and socioeconomic factors.</div></div><div><h3>Interpretation</h3><div>With an ageing population, healthcare demand and costs in SEAR will rise. Context-specific health insurance policies and targeted interventions are crucial for bridging coverage gaps and achieving UHC.</div></div><div><h3>Funding</h3><div>There is no specific funding for this study.</div></div>","PeriodicalId":75136,"journal":{"name":"The Lancet regional health. Southeast Asia","volume":"39 ","pages":"Article 100634"},"PeriodicalIF":6.2000,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Lancet regional health. Southeast Asia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772368225001052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Equitable access to quality healthcare without financial hardship is key to achieving Universal Health Coverage (UHC), especially in low- and middle-income countries in the WHO Southeast Asia Region (SEAR). Despite health insurance programmes, high out-of-pocket expenditures remain a barrier. This study evaluates health insurance coverage in SEAR, analysing socioeconomic and demographic factors.
Methods
This cross-sectional study used data from Demographic and Health Surveys (2015–2022) conducted in countries within the SEAR (data from six countries for women and five for men). Our analysis separately examined women and men aged 15–49 years using data from their respective individual Demographic and Health Survey datasets. Pooled estimates of health insurance coverage were calculated with 95% CI. Multilevel logistic regression quantified variations at the country and community-levels and identified factors influencing health insurance uptake.
Findings
Health insurance coverage varied across SEAR, with Indonesia reporting highest for women (58.2%; 95% CI: 57.65–58.72) and men (56.6%; 95% CI: 55.31–57.88), while lowest in Bangladesh for women (0.3%; 95% CI: 0.22–0.39) and Myanmar for men (1.4%; 95% CI: 1.04–1.83). Indonesia also had highest social security health insurance (women: 31.0%; 95% CI: 30.49–31.49, men: 27.9%; 95% CI: 26.74–29.03). Private insurance was lowest in Myanmar (women: 0.6%; 95% CI: 0.42–0.72, men: 0.9%; 95% CI: 0.60–1.27) and highest in Indonesia (women: 28.0%; 95% CI: 27.54–28.5, men: 30.0%; 95% CI: 28.81–31.14). Health insurance coverage was higher among individuals with higher education, greater exposure to mass media, rural residence, and older age. Insurance uptake was influenced by contextual factors beyond individual characteristics. India had highest community-attributable variation in health insurance uptake [women (53.1%; 95% CI: 52.56–53.62); men (56.3%; 95% CI: 55.17–57.46)], while lowest in Indonesia among women (17.7%; 95% CI: 16.40–18.99) and Maldives among men (10.8%; 95% CI: 6.71–16.84), after adjusting for demographic and socioeconomic factors.
Interpretation
With an ageing population, healthcare demand and costs in SEAR will rise. Context-specific health insurance policies and targeted interventions are crucial for bridging coverage gaps and achieving UHC.