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Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble

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Kontis, Vasilis, Bennett, James E, Mathers, Colin D, Li, Guangquan, Foreman, Kyle, Ezzati, Majid·2017·The Lancet

Abstract

BACKGROUND: Projections of future mortality and life expectancy are needed to plan for health and social services and pensions. Our aim was to forecast national age-specific mortality and life expectancy using an approach that takes into account the uncertainty related to the choice of forecasting model. METHODS: We developed an ensemble of 21 forecasting models, all of which probabilistically contributed towards the final projections. We applied this approach to project age-specific mortality to 2030 in 35 industrialised countries with high-quality vital statistics data. We used age-specific death rates to calculate life expectancy at birth and at age 65 years, and probability of dying before age 70 years, with life table methods. FINDINGS: Life expectancy is projected to increase in all 35 countries with a probability of at least 65% for women and 85% for men. There is a 90% probability that life expectancy at birth among South Korean women in 2030 will be higher than 86·7 years, the same as the highest worldwide life expectancy in 2012, and a 57% probability that it will be higher than 90 years. Projected female life expectancy in South Korea is followed by those in France, Spain, and Japan. There is a greater than 95% probability that life expectancy at birth among men in South Korea, Australia, and Switzerland will surpass 80 years in 2030, and a greater than 27% probability that it will surpass 85 years. Of the countries studied, the USA, Japan, Sweden, Greece, Macedonia, and Serbia have some of the lowest projected life expectancy gains for both men and women. The female life expectancy advantage over men is likely to shrink by 2030 in every country except Mexico, where female life expectancy is predicted to increase more than male life expectancy, and in Chile, France, and Greece where the two sexes will see similar gains. More than half of the projected gains in life expectancy at birth in women will be due to enhanced longevity above age 65 years. INTERPRETATION: There is more than a 50% probability that by 2030, national female life expectancy will break the 90 year barrier, a level that was deemed unattainable by some at the turn of the 21st century. Our projections show continued increases in longevity, and the need for careful planning for health and social services and pensions. FUNDING: UK Medical Research Council and US Environmental Protection Agency.

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Research works printed but not linked: 19

  1. Oeppen, 2002, Broken limits to life expectancy, Science, 296, 1029, 10.1126/science.1069675 · DOI · Paper page
  2. Booth, 2008, Mortality modelling and forecasting: a review of methods, Ann Actuarial Sci, 3, 3, 10.1017/S1748499500000440 · DOI · Paper page
  3. Vaupel, 2010, Biodemography of human ageing, Nature, 464, 536, 10.1038/nature08984 · DOI · Paper page
  4. Hoeting, 1999, Bayesian model averaging: a tutorial, Stat Sci, 14, 382
  5. Olshansky, 2001, Demography—prospects for human longevity, Science, 291, 1491, 10.1126/science.291.5508.1491 · DOI · Paper page
  6. Manton, 1991, Limits to human life expectancy–evidence, prospects, and implications, Pop Develop Rev, 17, 603, 10.2307/1973599 · DOI
  7. Parr, 2016, A cost of living longer: projections of the effects of prospective mortality improvement on economic support ratios for 14 advanced economies, Popul Stud (Camb), 70, 181, 10.1080/00324728.2016.1190029 · DOI
  8. Beltran-Sanchez, 2015, Twentieth century surge of excess adult male mortality, Proc Natl Acad Sci USA, 112, 8993, 10.1073/pnas.1421942112 · DOI
  9. Yang, 2010, Understanding the rapid increase in life expectancy in South Korea, Am J Public Health, 100, 896, 10.2105/AJPH.2009.160341 · DOI
  10. Ikeda, 2011, What has made the population of Japan healthy?, Lancet, 378, 1094, 10.1016/S0140-6736(11)61055-6 · DOI · Paper page
  11. 2016, A century of trends in adult human height, eLife, 5, e13410, 10.7554/eLife.13410 · DOI · Paper page
  12. Di Cesare, 2013, Inequalities in non-communicable diseases and effective responses, Lancet, 381, 585, 10.1016/S0140-6736(12)61851-0 · DOI · Paper page
  13. Khang, 2016, Age- and cause-specific contributions to income difference in life expectancy at birth: findings from nationally representative data on one million South Koreans, Eur J Public Health, 26, 242, 10.1093/eurpub/ckv128 · DOI
  14. Babones, 2008, Income inequality and population health: correlation and causality, Soc Sci Med, 66, 1614, 10.1016/j.socscimed.2007.12.012 · DOI · Paper page
  15. Deaton, 2003, Health, inequality, and economic development, J Econ Lit, 41, 113, 10.1257/.41.1.113 · DOI · Paper page
  16. Grinshteyn, 2016, Violent death rates: the US compared with other high-income OECD countries, 2010, Am J Med, 129, 266, 10.1016/j.amjmed.2015.10.025 · DOI · Paper page
  17. Alkema, 2016, Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group, Lancet, 387, 462, 10.1016/S0140-6736(15)00838-7 · DOI · Paper page
  18. You, 2015, Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation, Lancet, 386, 2275, 10.1016/S0140-6736(15)00120-8 · DOI · Paper page
  19. Ezzati, 2012, Can noncommunicable diseases be prevented? Lessons from studies of populations and individuals, Science, 337, 1482, 10.1126/science.1227001 · DOI

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Metadata

Authors
Kontis, V., Bennett, J. E., Mathers, C. D., Li, G., Foreman, K., & Ezzati, M.
Venue
The Lancet
Publisher
Elsevier BV
Published
2017-04
Volume
389
Issue
10076
Pages
1323-1335
ISSN
  • 0099-5355 (ISSN-L)
  • 0140-6736
OpenAlex
W2590687529
Cited by
1,219
References
9
FWCI
370.50
Type
journal article
Language
en
Open access
hybrid
Licence

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CoChat. (2026). Citation check: Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. https://app.cochat.ai/papers/10.1016/s0140-6736(16)32381-9
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Kontis, V., Bennett, J. E., Mathers, C. D., Li, G., Foreman, K., & Ezzati, M. (2017). Future life expectancy in 35 industrialised countries: projections with a Bayesian model ensemble. The Lancet. https://doi.org/10.1016/s0140-6736(16)32381-9

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