{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T10:33:58Z","timestamp":1792924438650,"version":"4.5.0"},"reference-count":31,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T00:00:00Z","timestamp":1779667200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Global health progress accelerated from 2000 to 2019, followed by severe disruptions during the COVID-19 pandemic. This study provides a demographic and econometric assessment of Healthy Life Expectancy (HALE) trends, associations between socioeconomic factors and health service coverage, and projections to 2030 under alternative policy scenarios. Because the analysis is observational, findings should be interpreted as associations rather than causal effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We applied a continuous-change demographic decomposition to partition HALE gains (2000\u20132019) and pandemic losses (2019\u20132021) across 22 causes of death and 10 age groups in 167 countries. Country and year fixed-effects panel regressions estimated associations between health determinants and six outcomes\u2014HALE, under-five mortality (U5MR), maternal mortality (MMR), UHC Service Coverage Index (SCI), catastrophic health spending, and DTP3 immunization\u2014over 2000\u20132021. Socioeconomic inequality in DTP3 coverage was measured using the Slope Index of Inequality (SII) from 88 DHS\/MICS surveys (2014\u20132023). Dynamic simulation models projected outcomes to 2030 under business-as-usual, primary health care expansion, and accelerated equity-focused reform scenarios with Monte Carlo uncertainty. Robustness checks used Driscoll\u2013Kraay standard errors for cross-sectional dependence and system GMM for dynamic panel specification; results were consistent with the main findings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>\n                      Global HALE increased by 5.25\u202fyears (95% CI: 4.89\u20135.61) from 2000 to 2019, with communicable disease reductions accounting for an estimated 65% of gains. The pandemic reduced HALE by 1.50\u202fyears globally, with COVID-19 responsible for over 80% of losses and substantial regional heterogeneity. The estimated income association for HALE was 0.687 (\n                      <jats:italic>p<\/jats:italic>\n                      &amp;lt;\u202f0.001), while female education showed stronger associations with mortality reductions in LMICs. UHC expansion was positively associated with catastrophic spending (elasticity 0.214), a pattern consistent with service\u2013financial protection decoupling. Median DTP3 inequality was 10.4 percentage points, and subnational gender inequality correlated with immunization coverage (\n                      <jats:italic>\u03c1<\/jats:italic>\n                      =\u202f0.49). Under business-as-usual, 34 countries reach UHC SCI\u202f\u2265\u202f80 by 2030, compared with 78 under equity-focused reform.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interpretation<\/jats:title>\n                    <jats:p>HALE gains have relied largely on communicable disease control, now approaching diminishing returns. Persistent inequalities and pandemic setbacks highlight the need for equity-focused financing and gender-responsive reforms, while future quasi-experimental and intervention studies are needed to confirm these observational findings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1811111","type":"journal-article","created":{"date-parts":[[2026,5,25]],"date-time":"2026-05-25T06:06:09Z","timestamp":1779689169000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Global health trajectories: analysis of health production functions and inequality decomposition"],"prefix":"10.3389","volume":"14","author":[{"given":"Mayadhar","family":"Sethy","sequence":"first","affiliation":[{"name":"Nabakrushna Choudhury Centre for Development Studies","place":["Bhubaneswar, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sandhya R.","family":"Mahapatro","sequence":"additional","affiliation":[{"name":"Nabakrushna Choudhury Centre for Development Studies","place":["Bhubaneswar, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Udaya S.","family":"Mishra","sequence":"additional","affiliation":[{"name":"International Institute for Population Sciences","place":["Mumbai, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grace B.","family":"Mundu","sequence":"additional","affiliation":[{"name":"Fakir Mohan University","place":["Balasore, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,25]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1223","DOI":"10.1016\/S0140-6736(20)30752-2","article-title":"Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the global burden of disease study 2019","volume":"396","author":"Murray","year":"2020","journal-title":"Lancet"},{"key":"ref2","volume-title":"World Health Statistics 2024: Monitoring Health for the SDGs","year":"2024"},{"key":"ref3","volume-title":"Transforming our World: The 2030 Agenda for Sustainable Development","year":"2015"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"1950","DOI":"10.2105\/AJPH.2021.306490","article-title":"The inverse equity hypothesis: analyses of institutional deliveries in 286 national surveys","volume":"111","author":"Victora","year":"2021","journal-title":"Am J Public Health"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1038\/s41586-022-05522-2","article-title":"The WHO estimates of excess mortality associated with the COVID-19 pandemic","volume":"613","author":"Msemburi","year":"2023","journal-title":"Nature"},{"key":"ref6","volume-title":"Second Round of the National Pulse Survey on Continuity of Essential Health Services During the COVID-19 Pandemic: January-March 2021","year":"2022"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"1649","DOI":"10.1038\/s41562-022-01450-3","article-title":"Life expectancy changes since COVID-19","volume":"6","author":"Sch\u00f6ley","year":"2022","journal-title":"Nat Hum Behav"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"499","DOI":"10.4054\/DemRes.2002.7.14","article-title":"Algorithm for decomposition of differences between aggregate demographic measures and its application to life expectancies, healthy life expectancies, parity-progression ratios and total fertility rates","volume":"7","author":"Andreev","year":"2002","journal-title":"Demogr Res"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.4054\/DemRes.2008.19.35","article-title":"An integrated approach to cause-of-death decomposition of life expectancy and lifespan variation","volume":"19","author":"Beltr\u00e1n-S\u00e1nchez","year":"2008","journal-title":"Demogr Res"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1186\/s12939-024-02105-7","article-title":"Are the poorest being left behind? 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