TY - JOUR
T1 - Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017
T2 - A systematic analysis for the Global Burden of Disease Study 2017
AU - Kyu, Hmwe Hmwe
AU - Abate, Degu
AU - Abate, Kalkidan Hassen
AU - Abay, Solomon M.
AU - Abbafati, Cristiana
AU - Abbasi, Nooshin
AU - Abbastabar, Hedayat
AU - Abd-Allah, Foad
AU - Abdela, Jemal
AU - Abdelalim, Ahmed
AU - Abdollahpour, Ibrahim
AU - Abdulkader, Rizwan Suliankatchi
AU - Abebe, Molla
AU - Abebe, Zegeye
AU - Abil, Olifan Zewdie
AU - Aboyans, Victor
AU - Abrham, Aklilu Roba
AU - Abu-Raddad, Laith Jamal
AU - Abu-Rmeileh, Niveen M.E.
AU - Accrombessi, Manfred Mario Kokou
AU - Acharya, Dilaram
AU - Acharya, Pawan
AU - Ackerman, Ilana N.
AU - Adamu, Abdu A.
AU - Adebayo, Oladimeji M.
AU - Adekanmbi, Victor
AU - Ademi, Zanfina
AU - Adetokunboh, Olatunji O.
AU - Adib, Mina G.
AU - Adsuar, Jose C.
AU - Afanvi, Kossivi Agbelenko
AU - Afarideh, Mohsen
AU - Afshin, Ashkan
AU - Agarwal, Gina
AU - Agesa, Kareha M.
AU - Aggarwal, Rakesh
AU - Aghayan, Sargis Aghasi
AU - Agrawal, Anurag
AU - Ahmadi, Alireza
AU - Ahmadi, Mehdi
AU - Ahmadieh, Hamid
AU - Ahmed, Muktar Beshir
AU - Ahmed, Sayem
AU - Aichour, Amani Nidhal
AU - Aichour, Ibtihel
AU - Aichour, Miloud Taki Eddine
AU - Akinyemiju, Tomi
AU - Akseer, Nadia
AU - Al-Aly, Ziyad
AU - Alkerwi, Ala'A
AU - GBD 2017 DALYs and HALE Collaborators
N1 - Funding Information:
Carl Abelardo Antonio reports personal fees from Johnson & Johnson (Philippines). Cyrus Cooper reports personal fees from Alliance for Better Bone Health, Amgen, Eli Lilly, GlaxoSmithKline (GSK), Medtronic, Merck, Novartis, Pfizer, Roche, Servier, Takeda, and UCB. Louisa Degenhardt reports grants from Indivior, Mundipharma, and Seqirus. Seana Gall reports grants from the National Health and Medical Research Council and the National Heart Foundation of Australia. Panniyammakal Jeemon reports a Clinical and Public Health Intermediate Fellowship from the Wellcome Trust-DBT India Alliance (2015–20). Jacek Jóźwiak reports a grant from Valeant; personal fees from Valeant, ALAB Laboratoria, and Amgen; and non-financial support from Microlife and Servier. Nicholas Kassebaum reports personal fees and other support from Vifor Pharmaceuticals. Srinivasa Vittal Katikireddi reports grants from UK NHS Research Scotland (SCAF/15/02), UK Medical Research Council (MC_UU_12017/13 and MC_UU_12017/15), and the Scottish Government Chief Scientist Office (SPHSU13 and SPHSU15). Jeffrey Lazarus reports personal fees from Janssen and Cepheid, and grants and personal fees from AbbVie, Gilead Sciences, and MSD. Stefan Lorkowski reports personal fees from Amgen, Berlin-Chemie, MSD Sharp & Dohme, Novo Nordisk, Sanofi-Aventis, Synlab, and Unilever; and non-financial support from Preventicus. Winfried März reports grants and personal fees from Siemens Diagnostics, Aegerion Pharmaceuticals, Amgen, AstraZeneca, Danone Research, Pfizer, BASF, Numares AG, and Berline-Chemie; personal fees from Hoffmann LaRoche, MSD, Sanofi, and Synageva; grants from Abbott Diagnostics; and other from Synlab Holding Deutschland GmbH. Walter Mendoza is currently a Program Analyst for Population and Development at the Peru Country Office of the United Nations Population Fund-UNFPA, which does not necessarily endorse this study. Ted Miller reports an evaluation contract from AB InBev Foundation. Maarten Postma reports grants from Mundipharma, Bayer, BMS, AstraZeneca, Arteg, and AscA; grants and personal fees from Sigma Tau, MSD, GSK, Pfizer, Boehringer Ingelheim, Novavax, Ingress Health, AbbVie, and Sanofi; personal fees from Quintiles, Astellas, Mapi, OptumInsight, Novartis, Swedish Orphan, Innoval, Janssen, Intercept, and Pharmerit; and stock ownership in Ingress Health and Pharmacoeconomics Advice Groningen. Kazem Rahimi reports grants from National Institute for Health Research Biomedical Research Centres, the Economic and Social Research Council, and Oxford Martin School. Kenji Shibuya reports grants from the Ministry of Health, Labour, and Welfare, Japan, and from the Ministry of Education, Culture, Sports, Science, and Technology, Japan. Mark Shrime reports grants from Mercy Ships and Damon Runyon Cancer Research Foundation. Jasvinder Singh reports consulting for Horizon, Fidia, UBM, Medscape, WebMD, the National Institutes of Health, and the American College of Rheumatology; they serve as the principal investigator for an investigator-initiated study funded by Horizon pharmaceuticals through a grant to Dinora, a 501c3 entity; they are on the steering committee of OMERACT. Jeffrey Stanaway reports a grant from Merck. Cassandra Szoeke reports a grant from the National Medical Health Research Council, Lundbeck, Alzheimer's Association, and the Royal Australasian College of Practicioners; and she holds patent PCT/AU2008/001556. Muthiah Vaduganathan receives research support from the US National Institute of Health National Heart, Lung, and Blood Institute and serves as a consultant for Bayer AG and Baxter Healthcare. Denis Xavier reports grants from Cadila Pharmaceuticals, Boehringer Ingelheim, Sanofi Aventis, Pfizer, and Bristol-Myers Squibb.
Funding Information:
Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Ageing of the National Institutes of Health (award P30AG047845) , and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163) . The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. We thank the Russia Longitudinal Monitoring Survey, done by the National Research University Higher School of Economics and ZAO Demoscope together with the Carolina Population Center, University of North Carolina at Chapel Hill and the Institute of Sociology RAS, for making these data available. Health Behaviour in School-aged Children (HBSC) is an international study carried out in collaboration with WHO/EURO. The International Coordinator of the 1997/98, 2001/02, 2005/06, and 2009/10 surveys was Candace Currie and the databank managers were Bente Wold for the 1997–98 survey and Oddrun Samdal for the following surveys. A list of principal investigators in each country can be found on the HBSC website . The Health and Retirement Study is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is done by the University of Michigan. This research uses data from Add Health, a programme project designed by J Richard Udry, Peter S Bearman, and Kathleen Mullan Harris, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 17 other agencies. Special acknowledgment is due to Ronald R Rindfuss and Barbara Entwisle for assistance in the original Add Health. People interested in obtaining data files from Add Health should contact Add Health, Carolina Population Center, 123 W. Franklin Street, Chapel Hill, NC 27516-2524 ( addhealth@unc.edu ). No direct support was received from grant P01-HD31921 for this analysis. Data for this research were provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. This research used data from the National Health Survey 2003. We are grateful to the Ministry of Health of Chile, the survey copyright owner, for allowing us to have the database. All results of the study are those of the authors and in no way committed to the Ministry. This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No. N01-HC-25195). Collection of these data was made possible by the USAID under the terms of cooperative agreement (GPO-A-00-08-000_D3-00). The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with license number SLN2014-3-170, after subjecting data to processing, aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law, 2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data. This paper uses data from SHARE Waves 1, 2, 3 (SHARELIFE), 4, 5 and 6 (DOIs: 10.6103/SHARE.w1.611, 10.6103/SHARE.w2.611, 10.6103/SHARE.w3.611, 10.6103/SHARE.w4.611, 10.6103/SHARE.w5.611, 10.6103/SHARE.w6.611), see Börsch-Supan et al (2013) for methodological details. The SHARE data collection has been primarily funded by the European Commission through FP5 (QLK6-CT-2001-00360), FP6 (SHARE-I3: RII-CT-2006-062193, COMPARE: CIT5-CT-2005-028857, SHARELIFE: CIT4-CT-2006-028812), and FP7 (SHARE-PREP: N°211909, SHARE-LEAP: N°227822, SHARE M4: N°261982). Additional funding from the German Ministry of Education and Research, the Max Planck Society for the Advancement of Science, the US National Institute on Aging (U01_AG09740-13S2, P01_AG005842, P01_AG08291, P30_AG12815, R21_AG025169, Y1-AG-4553-01, IAG_BSR06-11, OGHA_04-064, HHSN271201300071C), and from various national funding sources is gratefully acknowledged. This study was realised using data collected by the Swiss Household Panel, which is based at the Swiss Centre of Expertise in the Social Sciences FORS. The project is financed by the Swiss National Science Foundation. Data reported here were supplied by the United S Renal Data System. The interpretation and reporting of these data are the responsibility of the authors and in no way should be seen as an official policy or interpretation of the US Government.
Publisher Copyright:
Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
PY - 2018/11/10
Y1 - 2018/11/10
N2 - Background: How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted lifeyears (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severityof ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-speci?c mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Sociodemographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the ?ve leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2). Interpretation With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health.
AB - Background: How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted lifeyears (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severityof ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-speci?c mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Sociodemographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the ?ve leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2). Interpretation With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health.
UR - http://www.scopus.com/inward/record.url?scp=85056187313&partnerID=8YFLogxK
U2 - 10.1016/S0140-6736(18)32335-3
DO - 10.1016/S0140-6736(18)32335-3
M3 - Article
C2 - 30415748
AN - SCOPUS:85056187313
SN - 0140-6736
VL - 392
SP - 1859
EP - 1922
JO - The Lancet
JF - The Lancet
IS - 10159
ER -