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      Measuring population ageing: an analysis of the Global Burden of Disease Study 2017

      research-article
      , ScD a , , Prof, PhD c , d , , PhD e , f , , MD a , b , , PhD a , *
      The Lancet. Public Health
      Elsevier, Ltd

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          Summary

          Background

          Traditional metrics for population health ageing tend not to differentiate between extending life expectancy and adding healthy years. A population ageing metric that reflects both longevity and health status, incorporates a comprehensive range of diseases, and allows for comparisons across countries and time is required to understand the progression of ageing and to inform policies.

          Methods

          Using the Global Burden of Diseases, Injuries, and Risk Factors Study 2017, we developed a metric that reflects age-related morbidity and mortality at the population level. First, we identified a set of age-related diseases, defined as diseases with incidence rates among the adult population increasing quadratically with age, and measured their age-related burden, defined as the sum of disability-adjusted life-years (DALYs) of these diseases among adults. Second, we estimated age-standardised age-related health burden across 195 countries between 1990 and 2017. Using global average 65-year-olds as the reference population, we calculated the equivalent age in terms of age-related disease burden for all countries. Third, we analysed how the changes in age-related burden during the study period relate to different factors with a decomposition analysis. Finally, we describe how countries with similar levels of overall age-related burden experience different onsets of ageing. We represent the uncertainty of our estimates by calculating uncertainty intervals (UI) from 1000 draw-level estimates for each disease, country, year, and age.

          Findings

          92 diseases were identified as age related, accounting for 51·3% (95% UI 48·5–53·9) of all global burden among adults in 2017. Across the Socio-demographic Index (SDI), the rate of age-related burden ranged from 137·8 DALYs (128·9–148·3) per 1000 adults in high SDI countries to 265·9 DALYs (251·0–280·1) in low SDI countries. The equivalent age to average 65-year-olds globally spanned from 76·1 years (75·6–76·7) in Japan to 45·6 years (42·6–48·2) in Papua New Guinea. Age-standardised age-related disease rates have decreased over time across all SDI levels and regions between 1990 and 2017, mainly due to decreases in age-related case fatality and disease severity. Even among countries with similar age-standardised death rates, large differences in the onset and patterns of accumulating age-related burden exist.

          Interpretation

          The new metric facilitates the shift from thinking not just about chronological age but the health status and disease severity of ageing populations. Our findings could provide inputs into policymaking by identifying key drivers of variation in the ageing burden and resources required for addressing the burden.

          Funding

          National Institute on Aging of the National Institutes of Health.

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          Most cited references14

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          Aging, Cellular Senescence, and Cancer

          For most species, aging promotes a host of degenerative pathologies that are characterized by debilitating losses of tissue or cellular function. However, especially among vertebrates, aging also promotes hyperplastic pathologies, the most deadly of which is cancer. In contrast to the loss of function that characterizes degenerating cells and tissues, malignant (cancerous) cells must acquire new (albeit aberrant) functions that allow them to develop into a lethal tumor. This review discusses the idea that, despite seemingly opposite characteristics, the degenerative and hyperplastic pathologies of aging are at least partly linked by a common biological phenomenon: a cellular stress response known as cellular senescence. The senescence response is widely recognized as a potent tumor suppressive mechanism. However, recent evidence strengthens the idea that it also drives both degenerative and hyperplastic pathologies, most likely by promoting chronic inflammation. Thus, the senescence response may be the result of antagonistically pleiotropic gene action.
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            Quantification of biological aging in young adults.

            Antiaging therapies show promise in model organism research. Translation to humans is needed to address the challenges of an aging global population. Interventions to slow human aging will need to be applied to still-young individuals. However, most human aging research examines older adults, many with chronic disease. As a result, little is known about aging in young humans. We studied aging in 954 young humans, the Dunedin Study birth cohort, tracking multiple biomarkers across three time points spanning their third and fourth decades of life. We developed and validated two methods by which aging can be measured in young adults, one cross-sectional and one longitudinal. Our longitudinal measure allows quantification of the pace of coordinated physiological deterioration across multiple organ systems (e.g., pulmonary, periodontal, cardiovascular, renal, hepatic, and immune function). We applied these methods to assess biological aging in young humans who had not yet developed age-related diseases. Young individuals of the same chronological age varied in their "biological aging" (declining integrity of multiple organ systems). Already, before midlife, individuals who were aging more rapidly were less physically able, showed cognitive decline and brain aging, self-reported worse health, and looked older. Measured biological aging in young adults can be used to identify causes of aging and evaluate rejuvenation therapies.
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              Macroeconomic implications of population ageing and selected policy responses.

              Between now and 2030, every country will experience population ageing-a trend that is both pronounced and historically unprecedented. Over the past six decades, countries of the world had experienced only a slight increase in the share of people aged 60 years and older, from 8% to 10%. But in the next four decades, this group is expected to rise to 22% of the total population-a jump from 800 million to 2 billion people. Evidence suggests that cohorts entering older age now are healthier than previous ones. However, progress has been very uneven, as indicated by the wide gaps in population health (measured by life expectancy) between the worst (Sierra Leone) and best (Japan) performing countries, now standing at a difference of 36 years for life expectancy at birth and 15 years for life expectancy at age 60 years. Population ageing poses challenges for countries' economies, and the health of older populations is of concern. Older people have greater health and long-term care needs than younger people, leading to increased expenditure. They are also less likely to work if they are unhealthy, and could impose an economic burden on families and society. Like everyone else, older people need both physical and economic security, but the burden of providing these securities will be falling on a smaller portion of the population. Pension systems will be stressed and will need reassessment along with retirement policies. Health systems, which have not in the past been oriented toward the myriad health problems and long-term care needs of older people and have not sufficiently emphasised disease prevention, can respond in different ways to the new demographic reality and the associated changes in population health. Along with behavioural adaptations by individuals and businesses, the nature of such policy responses will establish whether population ageing will lead to major macroeconomic difficulties.
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                Author and article information

                Contributors
                Journal
                Lancet Public Health
                Lancet Public Health
                The Lancet. Public Health
                Elsevier, Ltd
                2468-2667
                06 March 2019
                March 2019
                06 March 2019
                : 4
                : 3
                : e159-e167
                Affiliations
                [a ]Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
                [b ]Department of Anesthesiology & Pain Medicine, Seattle Children's Hospital, University of Washington, Seattle, WA, USA
                [c ]Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
                [d ]Columbia Aging Center, Columbia University, New York, NY, USA
                [e ]Parc Sanitari Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain
                [f ]Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Madrid, Spain
                Author notes
                [* ]Correspondence to: Dr Joseph L Dieleman, Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA dieleman@ 123456uw.edu
                Article
                S2468-2667(19)30019-2
                10.1016/S2468-2667(19)30019-2
                6472541
                30851869
                c114ecc8-2ad3-44ac-99d0-fb105eb726f3
                © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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