{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T15:47:38Z","timestamp":1792597658052,"version":"4.5.0"},"reference-count":40,"publisher":"American Medical Association (AMA)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Population aging is contributing to rising multimorbidity across physical, psychological, and cognitive domains, yet global evidence integrating health and economic burdens in older adults remains limited.<\/jats:p>\n <\/jats:sec>\n \n Objectives<\/jats:title>\n To quantify the global health and economic burden of multimorbidity among adults aged 60 years or older and to assess trends from 2000 to 2023.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This economic evaluation used observational modeling of Global Burden of Disease study 2023 estimates as health inputs and integrated them with macroeconomic, health expenditure, and population data from World Bank Open Data, the World Health Organization Global Health Expenditure Database, and United Nations population data. Health burden analyses covered adults aged 60 years or older in 204 countries and territories from 2000 to 2023, and economic burden analyses covered 180 countries and territories. Data analyses were performed from January 27 to July 22, 2026.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Cross-domain multimorbidity spanning physical conditions, psychological disorders, and cognitive disorders, operationalized as 78 multimorbidity combinations.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n The main outcomes were years lived with disability (YLDs) per 100\u202f000 population and economic losses. All economic indicators are reported in 2021 international dollars (USD) adjusted for purchasing power parity. Joinpoint regression characterized 2000 to 2023 trends.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n From 2000 to 2023, total YLDs increased from 2367.81 (95% uncertainty interval [UI], 1067.67-4969.59) to 2941.68 (95% UI, 1252.99-6816.95) per 100 000 population, while economic losses increased from $80.10 billion (95% UI, $59.60-$104.69 billion) to $363.25 billion (95% UI, $264.04-$502.74 billion). The highest 2023 YLD rate was observed for osteoarthritis and Alzheimer disease and other dementias (369.87 [95% UI, 163.86-752.23] per 100 000 population), whereas the largest 2023 economic loss was observed for osteoarthritis and anxiety disorders ($48.51 billion [95% UI, $31.68-$76.57 billion]). The fastest-growing combination was diabetes, anxiety disorders, and Parkinson disease, with a YLD average annual percentage change (AAPC) of 3.94% (95% CI, 3.79%-4.08%) and an economic loss AAPC of 9.92% (95% CI, 9.69%-10.13%).<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this economic evaluation of the global health and economic burden of multimorbidity among adults aged 60 years or older, multimorbidity burden increased worldwide, with economic losses growing faster than YLDs. Heterogeneity across sex, country income groups, and disease combinations, together with divergence between disability and economic burden, suggest that policy priorities for aging populations should consider both health burden and economic vulnerability.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.33002","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T15:00:39Z","timestamp":1792594839000},"page":"e2633002","source":"Crossref","is-referenced-by-count":0,"title":["Dual Health and Economic Burden of Multimorbidity in Aging Populations"],"prefix":"10.1001","volume":"9","author":[{"given":"Wenjing","family":"Ji","sequence":"first","affiliation":[{"name":"Department of Pharmacy Administration, School of Pharmacy, Xi\u2019an Jiaotong University, Xi\u2019an, China"},{"name":"Center for Drug Safety and Policy Research, Xi\u2019an Jiaotong University, Xi\u2019an, Shaanxi, 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Xi\u2019an Jiaotong University, Xi\u2019an, China"},{"name":"Center for Drug Safety and Policy Research, Xi\u2019an Jiaotong University, Xi\u2019an, Shaanxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingwang","family":"Shen","sequence":"additional","affiliation":[{"name":"China-Australia Joint Research Center for Infectious Diseases, School of Public Health, Xi\u2019an Jiaotong University Health Science Center, Xi\u2019an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Minghuan","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Pharmacy Administration, School of Pharmacy, Xi\u2019an Jiaotong University, Xi\u2019an, China"},{"name":"Center for Drug Safety and Policy Research, Xi\u2019an Jiaotong University, Xi\u2019an, Shaanxi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Duolao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Clinical Sciences, 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