{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T16:13:51Z","timestamp":1785860031084,"version":"3.56.0"},"reference-count":102,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"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>Introduction<\/jats:title>\n                    <jats:p>Life expectancy is determined by several structural interplays. This study examines the impact of economic growth, AI (as measured by digitalization), and carbon emissions on life expectancy in GCC countries from 2000 to 2024.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This research relies on a standard model derived from the health economics function, which combines panel fixed effects and dynamic models (System GMM) to measure the impact of economic growth, digital transformation, and environmental sustainability on public health. Estimates were obtained using static fixed effects and a dynamic specification corresponding to the generalized multiple methods approach. These estimates are useful for controlling for unobserved heterogeneity, health persistence, and possible internal relationships among income, technology, and health. Life expectancy indicates a high level of persistence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The dynamic estimates indicate that the lag values of the current health outcome can explain the outcome over 70 years. After controlling for static and dynamic specifications and internalities, the economic growth role is positive but reduced. All specifications indicate that digital transformation has a positive and robust effect on life expectancy, with an economically significant magnitude. In contrast, a strong correlation exists between per capita carbon dioxide emissions and low life expectancy. The proportion of health expenditure to GDP is not significantly associated with life expectancy in the GCC countries.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>Overall, these findings imply that population health improvements in GCC countries are probably driven less by health expenditure volumes and more by structural changes in the digital and environmental efficiency of population health production. Economic development will expand fiscal space for health-sector expenditures. The development of the digital economy clearly increases the productivity of health sector expenditures. Conversely, carbon-intensive growth imposes significant health costs. The findings elucidate that digital and environmental health organizations within the public health sector are essential for achieving health gains and long-term sustainability in GCC countries.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1785053","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T05:34:48Z","timestamp":1774935288000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Beyond health economics: economic growth, artificial intelligence, and environmental externalities in shaping life expectancy"],"prefix":"10.3389","volume":"14","author":[{"given":"Mohammed Moosa","family":"Ageli","sequence":"first","affiliation":[{"name":"Department of Economics, College of Business Administration, King Saud University","place":["Riyadh, Saudi 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