Xueying Guo, Bryan Tysinger, Hwee Lin Wee, Mythily Subramaniam, Stefan Ma, Tze Pin Ng, Cynthia Chen
{"title":"新加坡老年人的疾病负担、终生医疗保健费用和长期干预影响预测。","authors":"Xueying Guo, Bryan Tysinger, Hwee Lin Wee, Mythily Subramaniam, Stefan Ma, Tze Pin Ng, Cynthia Chen","doi":"10.1038/s43587-025-00915-0","DOIUrl":null,"url":null,"abstract":"<p><p>Singapore's rapidly aging population and increasing healthcare demands highlight the need for projections to inform policy planning. Here we adapted a previously published dynamic Markov microsimulation model, the Future Elderly Model, to estimate disease trajectories and healthcare expenditure among adults aged 51 years and older in Singapore. The model simulated four long-term lifestyle interventions aligned with the Healthier SG program from 2020 to 2050. Our projections indicate an increasing prevalence of chronic conditions, comorbidities, obesity and disabilities, with ethnic differences. The projected lifetime healthcare expenditure is the highest among Indians (US $93,900; 95% credible interval (CI), US $68,900-119,000), followed by the Chinese (US $75,700; 95% CI, US $57,600-93,800) and Malays (US $70,000; 95% CI, US $52,000-88,000). Despite having a higher chronic disease burden, Malays are expected to incur lower lifetime expenditure due to their shorter life expectancy. Implementing all 4 interventions could save US $505 million (95% CI, US $462-547 million) in healthcare use by 2050. Sustained lifestyle interventions may moderate the increase in future burdens. Policy strategies should prioritize preventive care tailored to the specific needs of diverse population subgroups.</p>","PeriodicalId":94150,"journal":{"name":"Nature aging","volume":" ","pages":"1358-1369"},"PeriodicalIF":17.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270899/pdf/","citationCount":"0","resultStr":"{\"title\":\"Disease burden, lifetime healthcare cost and long-term intervention impact projections among older adults in Singapore.\",\"authors\":\"Xueying Guo, Bryan Tysinger, Hwee Lin Wee, Mythily Subramaniam, Stefan Ma, Tze Pin Ng, Cynthia Chen\",\"doi\":\"10.1038/s43587-025-00915-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Singapore's rapidly aging population and increasing healthcare demands highlight the need for projections to inform policy planning. Here we adapted a previously published dynamic Markov microsimulation model, the Future Elderly Model, to estimate disease trajectories and healthcare expenditure among adults aged 51 years and older in Singapore. The model simulated four long-term lifestyle interventions aligned with the Healthier SG program from 2020 to 2050. Our projections indicate an increasing prevalence of chronic conditions, comorbidities, obesity and disabilities, with ethnic differences. The projected lifetime healthcare expenditure is the highest among Indians (US $93,900; 95% credible interval (CI), US $68,900-119,000), followed by the Chinese (US $75,700; 95% CI, US $57,600-93,800) and Malays (US $70,000; 95% CI, US $52,000-88,000). Despite having a higher chronic disease burden, Malays are expected to incur lower lifetime expenditure due to their shorter life expectancy. Implementing all 4 interventions could save US $505 million (95% CI, US $462-547 million) in healthcare use by 2050. Sustained lifestyle interventions may moderate the increase in future burdens. Policy strategies should prioritize preventive care tailored to the specific needs of diverse population subgroups.</p>\",\"PeriodicalId\":94150,\"journal\":{\"name\":\"Nature aging\",\"volume\":\" \",\"pages\":\"1358-1369\"},\"PeriodicalIF\":17.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270899/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature aging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1038/s43587-025-00915-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/7/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s43587-025-00915-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/15 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Disease burden, lifetime healthcare cost and long-term intervention impact projections among older adults in Singapore.
Singapore's rapidly aging population and increasing healthcare demands highlight the need for projections to inform policy planning. Here we adapted a previously published dynamic Markov microsimulation model, the Future Elderly Model, to estimate disease trajectories and healthcare expenditure among adults aged 51 years and older in Singapore. The model simulated four long-term lifestyle interventions aligned with the Healthier SG program from 2020 to 2050. Our projections indicate an increasing prevalence of chronic conditions, comorbidities, obesity and disabilities, with ethnic differences. The projected lifetime healthcare expenditure is the highest among Indians (US $93,900; 95% credible interval (CI), US $68,900-119,000), followed by the Chinese (US $75,700; 95% CI, US $57,600-93,800) and Malays (US $70,000; 95% CI, US $52,000-88,000). Despite having a higher chronic disease burden, Malays are expected to incur lower lifetime expenditure due to their shorter life expectancy. Implementing all 4 interventions could save US $505 million (95% CI, US $462-547 million) in healthcare use by 2050. Sustained lifestyle interventions may moderate the increase in future burdens. Policy strategies should prioritize preventive care tailored to the specific needs of diverse population subgroups.