{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T07:57:45Z","timestamp":1790668665346,"version":"4.1.0"},"reference-count":51,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Public Health Challenges"],"published-print":{"date-parts":[[2026,12]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>In low\u2010 and middle\u2010income countries, healthcare systems rely heavily on out\u2010of\u2010pocket payments, causing financial hardship and limiting access to care. Globally, 800 million people spend over 10% of household income on healthcare, driving 100 million into extreme poverty due to catastrophic health expenditures (CHE). In South Asia, out\u2010of\u2010pocket (OOP) payments remain the primary funding source, with India and Bangladesh reporting significant CHE burdens. Health insurance (HI) can reduce costs, improve access and mitigate CHE, playing a key role in achieving universal health coverage.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>We conducted this systematic review and meta\u2010analysis to estimate the proportion of willingness\u2010to\u2010pay (WTP) for HI and to explore the factors generally associated with it.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Electronic searches of PubMed, Google Scholar and Bangladesh Journals Online (BanglaJOL), as well as citation tracking, were conducted to identify eligible studies. Study quality was assessed using the Newcastle\u2010Ottawa Scale. Publication bias was evaluated using Egger's test and funnel plots. Leave\u2010one\u2010out sensitivity and subgroup analyses by WTP elicitation method and insurance type were conducted. All analyses were conducted in STATA 19.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We included 17 studies from 5 South Asian countries in the analysis. The pooled proportion of WTP for HI was 0.72 (95% CI: 0.61\u22120.82), with a 95% prediction interval of 0.20\u22121.00 and considerable heterogeneity (\n                      <jats:italic>I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a099.59%,\n                      <jats:italic>\u03c4<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u00a0=\u00a00.2474). The pooled proportion from Bangladeshi studies was higher than that of Indian studies (0.83 and 0.69, respectively). Leave\u2010one\u2010out estimates ranged from 0.70 to 0.76. Age, sex, level of education, size of the family, socio\u2010economic status, monthly personal income, occupation, family income, healthcare utilisation and healthcare expenditure were generally associated with WTP.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Overall, 72% of participants were willing to pay for HI, although substantial heterogeneity was observed across studies. Further robust studies are needed to better characterise WTP for HI in South Asia.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/puh2.70394","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T07:36:42Z","timestamp":1790667402000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Willingness\u2010to\u2010Pay for Health Insurance in South Asia: A Systematic Review and Meta\u2010Analysis"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6695-6342","authenticated-orcid":false,"given":"Md Fuad Al","family":"Fidah","sequence":"first","affiliation":[{"name":"National Institute of Preventive and Social Medicine  Dhaka Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9513-8103","authenticated-orcid":false,"given":"Sayeda Sumaiya","family":"Efa","sequence":"additional","affiliation":[{"name":"BADAS TB Initiative Diabetic Association of Bangladesh (BADAS)  Dhaka Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4481-7699","authenticated-orcid":false,"given":"Md Ridwan","family":"Islam","sequence":"additional","affiliation":[{"name":"International Center for Diarrhoeal Disease Research, Bangladesh Dhaka Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0707-0437","authenticated-orcid":false,"given":"Md Abdullah Saeed","family":"Khan","sequence":"additional","affiliation":[{"name":"National Institute of Preventive and Social Medicine  Dhaka Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12913\u2010017\u20102047\u20100"},{"key":"e_1_2_12_3_1","unstructured":"WHO World Bank TrackingUniversal Health Coverage: 2017Global Monitoring Report(World Health Organization 2017)."},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/heapol\/czs073"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10754\u2010011\u20109089\u20103"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1093\/inthealth\/ihab015"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.2471\/BLT.18.209858"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/hpm.2371"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2017.3133"},{"key":"e_1_2_12_10_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12961\u2010024\u201001202\u2010x"},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.2471\/BLT.12.115428"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12962\u2010020\u201000206\u2010y"},{"key":"e_1_2_12_13_1","volume-title":"Impact of Health Insurance in Low\u2010 and Middle\u2010Income Countries","author":"Escobar M.\u2010L.","year":"2010"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.4103\/ijcm.IJCM_252_18"},{"key":"e_1_2_12_15_1","volume-title":"Cost\u2010Benefit Analysis","author":"Mishan E. 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