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      Population ageing and mortality during 1990–2017: A global decomposition analysis

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          Abstract

          Background

          As the number of older people globally increases, health systems need to be reformed to meet the growing need for medical resources. A few previous studies reported varying health impacts of population ageing, but they focused only on limited countries and diseases. We comprehensively quantify the impact of population ageing on mortality for 195 countries/territories and 169 causes of death.

          Methods and findings

          Using data from the Global Burden of Disease Study 2017 (GBD 2017), this study derived the total number of deaths and population size for each year from 1990 to 2017. A decomposition method was used to attribute changes in total deaths to population growth, population ageing, and mortality change between 1990 and each subsequent year from 1991 through 2017, for 195 countries/territories and for countries grouped by World Bank economic development level. For countries with increases in deaths related to population ageing, we calculated the ratio of deaths attributed to mortality change to those attributed to population ageing. The proportion of people aged 65 years and older increased globally from 6.1% to 8.8%, and the number of global deaths increased by 9 million, between 1990 and 2017. Compared to 1990, 12 million additional global deaths in 2017 were associated with population ageing, corresponding to 27.9% of total global deaths. Population ageing was associated with increases in deaths in high-, upper-middle-, and lower-middle-income countries but not in low-income countries. The proportions of deaths attributed to population ageing in 195 countries/territories ranged from −43.9% to 117.4% for males and −30.1% to 153.5% for females. The 2 largest contributions of population ageing to disease-specific deaths globally between 1990 and 2017 were for ischemic heart disease (3.2 million) and stroke (2.2 million). Population ageing was related to increases in deaths in 152 countries for males and 159 countries for females, and decreases in deaths in 43 countries for males and 36 countries for females, between 1990 and 2017. The decreases in deaths attributed to mortality change from 1990 to 2017 were more than the increases in deaths related to population ageing for the whole world, as well as in 55.3% (84/152) of countries for males and 47.8% (76/159) of countries for females where population ageing was associated with increased death burden. As the GBD 2017 does not provide variances in the estimated death numbers, we were not able to quantify uncertainty in our attribution estimates.

          Conclusions

          In this study, we found that population ageing was associated with substantial changes in numbers of deaths between 1990 and 2017, but the attributed proportion of deaths varied widely across country income levels, countries, and causes of death. Specific preventive and therapeutic techniques should be implemented in different countries and territories to address the growing health needs related to population ageing, especially targeting the diseases associated with the largest increase in number of deaths in the elderly.

          Abstract

          Guoqing Hu and colleagues estimate the contribution of population aging on mortality across 195 countries over the past two decades.

          Author summary

          Why was this study done?
          • Evidence on the change in number deaths related to population ageing is important for each individual government to improve its healthcare system to address the increasing healthcare needs of older adults.

          • Previous research assessing changes in health indicators (e.g., number of deaths, mortality) influenced by population ageing was limited to specific countries or specific diseases.

          • Quantitative methods for decomposing changes in the total number of deaths that were adopted by previous studies are sensitive to the choice of the decomposition order of the 3 factors—population growth population ageing, and age-specific mortality rate—and the selection of reference group.

          What did the researchers do and find?
          • Using a decomposition method that is not influenced by the selection of decomposition order of the 3 factors and the choice of the reference group, we conducted a comprehensive analysis to quantify the impact of population ageing on changes in the number of deaths in 195 countries/territories, and for 169 causes of death, from 1990 to 2017.

          • Changes in the number of deaths related to population ageing varied greatly across the 195 countries/territories; the attributed proportion ranged from −43.9% to 117.4% for males and −30.1% to 153.5% for females.

          • The causes of death for which population ageing was associated with the greatest increases in global deaths between 1990 and 2017 were ischemic heart disease (3.2 million) and stroke (2.2 million).

          • The decreases in deaths attributed to mortality change exceeded the increases in deaths related to population ageing between 1990 and 2017 for the whole world, as well as in 55.3% (84/152) of countries for males and 47.8% (76/159) of countries for females where population ageing was associated with increased death burden.

          What do these findings mean?
          • Globally, population ageing was related to increases in deaths, highlighting the importance and urgency of improving health systems to meet the health needs of older adults.

          • Varying death burden related to population ageing suggests flexible health policies should target the leading causes of attributed death burden in different countries/territories.

          • The death burden related to population ageing could be alleviated or even overcome through implementation of evidence-based interventions to reduce mortality.

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          Most cited references11

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          The economic burden of dementia in China, 1990–2030: implications for health policy

          Abstract Objective To quantify and predict the economic burden of dementia in China for the periods 1990–2010 and 2020–2030, respectively, and discuss the potential implications for national public health policy. Methods Using a societal, prevalence-based, gross cost-of-illness approach and data from multiple sources, we estimated or predicted total annual economic costs of dementia in China. We included direct medical costs in outpatient and inpatient settings, direct non-medical costs – e.g. the costs of transportation – and indirect costs due to loss of productivity. We excluded comorbidity-related costs. Findings The estimated total annual costs of dementia in China increased from 0.9 billion United States dollars (US$) in 1990 to US$ 47.2 billion in 2010 and were predicted to reach US$ 69.0 billion in 2020 and US$ 114.2 billion in 2030. The costs of informal care accounted for 94.4%, 92.9% and 81.3% of the total estimated costs in 1990, 2000 and 2010, respectively. In China, population ageing and the increasing prevalence of dementia were the main drivers for the increasing predicted costs of dementia between 2010 and 2020, and population ageing was the major factor contributing to the growth of dementia costs between 2020 and 2030. Conclusion In China, demographic and epidemiological transitions have driven the growth observed in the economic costs of dementia since the 1990s. If the future costs of dementia are to be reduced, China needs a nationwide dementia action plan to develop an integrated health and social care system and to promote primary and secondary prevention.
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            Improving the public health utility of global cardiovascular mortality data: the rise of ischemic heart disease

            Background High-quality, cause-specific mortality data are critical for effective health policy. Yet vague cause of death codes, such as heart failure, are highly prevalent in global mortality data. We propose an empirical method correcting mortality data for the use of heart failure as an underlying cause of death. Methods We performed a regression analysis stratified by sex, age, and country development status on all available ICD-10 mortality data, consisting of 142 million deaths across 838 country-years. The analysis yielded predicted fractions with which to redistribute heart failure-attributed deaths to the appropriate underlying causes of death. Age-adjusted death rates and rank causes of death before and after correction were calculated. Results Heart failure accounts for 3.1% of all deaths in the dataset. Ischemic heart disease has the highest redistribution proportion for ages 15-49 and 50+ in both sexes and country development levels, causing gains in age-adjusted death rates in both developed and developing countries. COPD and hypertensive heart disease also make significant rank gains. Reproductive-aged women in developing country-years yield the most diverse range of heart failure causes. Conclusions Ischemic heart disease becomes the No. 1 cause of death in several developed countries, including France and Japan, underscoring the cardiovascular epidemic in high-income countries. Age-adjusted death rate increases for ischemic heart disease in low- and middle-income countries, such as Argentina and South Africa, highlight the rise of the cardiovascular epidemic in regions where public health efforts have historically focused on infectious diseases. This method maximizes the use of available data, providing better evidence on major causes of death to inform policymakers in allocating finite resources.
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              The boomers are coming: a total cost of care model of the impact of population aging on health care costs in the United States by Major Practice Category.

              To project the impact of population aging on total U.S. health care per capita costs from 2000 to 2050 and for the range of clinical areas defined by Major Practice Categories (MPCs). Secondary data: HealthPartners health plan administrative data; U.S. Census Bureau population projections 2000-2050; and MEPS 2001 health care annual per capita costs. We calculate MPC-specific age and gender per capita cost rates using cross-sectional data for 2002-2003 and project U.S. changes by MPC due to aging from 2000 to 2050. HealthPartners data were grouped using purchased software. We developed and validated a method to include pharmacy costs for the uncovered. While total U.S. per capita costs due to aging from 2000 to 2050 are projected to increase 18 percent (0.3 percent annually), the impact by MPC ranges from a 55 percent increase in kidney disorders to a 12 percent decrease in pregnancy and infertility care. Over 80 percent of the increase in total per capita cost will result from just seven of the 22 total MPCs. Understanding the differential impact of aging on costs at clinically specific levels is important for resource planning, to effectively address future medical needs of the aging U.S. population.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: SoftwareRole: Writing – original draft
                Role: MethodologyRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: ValidationRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                8 June 2020
                June 2020
                : 17
                : 6
                Affiliations
                [1 ] Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
                [2 ] Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
                [3 ] Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
                [4 ] Department of Psychology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America
                [5 ] Department of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America
                [6 ] Division of Epidemiology, College of Public Health, Ohio State University, Columbus, Ohio, United States of America
                [7 ] National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
                Harvard Medical School, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Article
                PMEDICINE-D-19-03747
                10.1371/journal.pmed.1003138
                7279585
                32511229
                31b1d911-9b64-4590-a39a-60bfea3a0563
                © 2020 Cheng et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 4, Tables: 3, Pages: 17
                Product
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Developmental Biology
                Organism Development
                Aging
                Biology and Life Sciences
                Physiology
                Physiological Processes
                Aging
                Medicine and Health Sciences
                Physiology
                Physiological Processes
                Aging
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Death Rates
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Cancer Risk Factors
                Aging and Cancer
                Medicine and Health Sciences
                Oncology
                Cancer Risk Factors
                Aging and Cancer
                Medicine and Health Sciences
                Public and Occupational Health
                Global Health
                Medicine and Health Sciences
                Vascular Medicine
                Coronary Heart Disease
                Medicine and Health Sciences
                Cardiology
                Coronary Heart Disease
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Dementia
                Alzheimer's Disease
                Medicine and Health Sciences
                Neurology
                Dementia
                Alzheimer's Disease
                Medicine and Health Sciences
                Neurology
                Neurodegenerative Diseases
                Alzheimer's Disease
                People and Places
                Population Groupings
                Age Groups
                Biology and Life Sciences
                Population Biology
                Population Metrics
                Population Growth
                Custom metadata
                All data used in this research were derived from the online resources of the Global Burden of Disease Study 2017 ( http://ghdx.healthdata.org/gbd-results-tool; http://ghdx.healthdata.org/gbd-2017).

                Medicine
                Medicine

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