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: a systematic analysis for the Global Burden of Disease Study 2017

Abstract

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 life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years.

Methods: We used data for age-specific 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 Socio-demographic 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 five 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.

Funding: Bill & Melinda Gates Foundation.

Conflict of interest statement

Declaration of interests

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.

Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1. Trends of HALE at birth and years in poor health from birth by SDI quintile and sex, 1990–2017

HALE=healthy life expectancy. SDI=Socio-demographic Index.

Figure 2. Years of life gained at birth by sex and functional health status for five SDI quintiles, 21 GBD regions, and 28 countries with the largest and smallest proportions of years spent in poor health between 1990 and 2017

GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. SDI=Socio-demographic Index.

Figure 3. Difference in HALE at birth between males and females by SDI quintile, 1990–2017

HALE=healthy life expectancy. SDI=Socio-demographic Index.

Figure 4. Extra years of life expected at birth in females compared with males by functional health status for five SDI quintiles, 21 GBD regions, and 28 countries with the largest and smallest percentages of years spent in poor health, 2017

GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. SDI=Socio-demographic Index.

Figure 5. DALYs by Level 2 causes by age and sex, for global (A), high SDI (B), high-middle SDI (C), middle SDI (D), low-middle SDI (E), and low SDI (F), 2017

Scales in each panel are different. The early neonatal period is 0–6 days, the late neonatal period is 7–27 days, and the post neonatal period is 28–364 days. DALYs=disability-adjusted life-years. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. SDI=Socio-demographic Index.

Figure 5. DALYs by Level 2 causes by age and sex, for global (A), high SDI (B), high-middle SDI (C), middle SDI (D), low-middle SDI (E), and low SDI (F), 2017

Scales in each panel are different. The early neonatal period is 0–6 days, the late neonatal period is 7–27 days, and the post neonatal period is 28–364 days. DALYs=disability-adjusted life-years. GBD=Global Burden of Diseases, Injuries, and Risk Factors Study. SDI=Socio-demographic Index.

Figure 6. Leading 30 Level 3 causes of global DALYs for 1990, 2007, and 2017 with percentage change in number of DALYs and age-standardised DALY rates by sex

Solid lines indicate increases and dashed lines indicate decreases in rank between periods. Significant changes are shown in bold. COPD=chronic obstructive pulmonary disease. DALYs=disability-adjusted life-years.

Figure 6. Leading 30 Level 3 causes of global DALYs for 1990, 2007, and 2017 with percentage change in number of DALYs and age-standardised DALY rates by sex

Solid lines indicate increases and dashed lines indicate decreases in rank between periods. Significant changes are shown in bold. COPD=chronic obstructive pulmonary disease. DALYs=disability-adjusted life-years.

Figure 7. Contribution of YLLs and YLDs to DALYs by age and sex for global (A), high SDI (B), high-middle SDI (C), middle SDI (D), low-middle SDI (E), and low SDI (F), 2017

The early neonatal period is 0–6 days, the late neonatal period is 7–27 days, and the post neonatal period is 28–364 days. DALYs=disability-adjusted life-years. SDI=Socio-demographic Index. YLDs=years lived with disability. YYLs=years of life lost.

Figure 8. Difference in years between observed and expected HALE at birth on the basis of SDI for females and males, 2017

ATG=Antigua and Barbuda. FSM=Federated States of Micronesia. HALE=healthy life expectancy. Isl=Islands. LCA=Saint Lucia. SDI=Socio-demographic Index. TTO=Trinidad and Tobago. TLS=Timor-Leste. VCT=Saint Vincent and the Grenadines.