Abstract
Background: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution. Methods: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian metaregression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol. Findings: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa. Interpretation: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.
Original language | English |
---|---|
Pages (from-to) | 2287-2323 |
Number of pages | 37 |
Journal | The Lancet |
Volume | 386 |
Issue number | 10010 |
DOIs | |
Publication status | Published - 5 Dec 2015 |
Bibliographical note
Funding Information:RA-C has been employed by GSK, activities not related to this manuscript. JP is supported by a career development fellowship from the Wellcome Trust, Public Health Foundation of India, and a consortium of UK Universities. CK receives research grants from Brazilian public funding agencies Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), and Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS). He has also received authorship royalties from publishers Artmed and Manole. RSP Jr has been medical director for United Laboratories Consumer Health Division—United Laboratories Inc. GVP is employed by University of Sao Paulo and receives research support from the National Council for Scientific and Technological Development (CNPq), the São Paulo Research Foundation (FAPESP), Grand Challenges Canada, Fundacao Maria Cecilia Souto Vidigal, and the University of Sao Paulo. He has served as a consultant and speaker to Shire and has received royalties from Manole Editors. HJL, in addition to grant funding from the Bill & Melinda Gates Foundation, EU, WHO and Novartis, has done some consulting for GSK and on the Merck Vaccines Global Strategic Advisory Boardm outside of this report. All other authors declare no competing interests.
Funding Information:
We thank the countless individuals who have contributed to the Global Burden of Disease Study 2013 in various capacities. We acknowledge the extensive support from all staff members at the Institute for Health Metrics and Evaluation and specifically thank James Bullard, Serkan Yalcin, Evan Laurie, Andrew Ernst, Elizabeth Roberts, and Peter Speyer for their tireless support of the computational infrastructure required to produce the results and production of visualisations to review the results; Abigail McLain for her guidance on organising data; Caitlyn Steiner for her management of the GBD estimation; Adrienne Chew for her editorial assistance; Kelsey Pierce for her valuable guidance; and Linda A Ettinger for her expert executive support. We would also like to thank Ivan Ivanov for his contributions. The following individuals acknowledge various forms of institutional support: HC is supported by the Intramural Program of the NIH, the National Institute of Environmental Health Science; KD is supported by a Wellcome Trust Research Training Fellowship ( grant number 099876 )]; KBG received the NHMRC-Gustav Nossal scholarship sponsored by CSL 2015 (his award is peer-reviewed through the standard NHMRC peer-review process; CSL played no part in selection of the awardee); HH's contribution of this effort was partially supported by NIH ROI ES021446 ; NK received funding from the Japan Society for the Promotion of Science (JSPS) KAKENHI ( grant number 25253045 ); YK would like to thank the National Heart Foundation of Australia for its financial support for work on modelling cardiovascular disease and risk factors at the University of Canberra; SJL is supported in part by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences; KM reports personal fees from Mitsubishi Tanabe Pharma, Kyowa Hakko Kirin, and MSD outside the submitted work; WM is program analyst at the UNFPA country office in Peru, which does not necessarily endorse the study; FC-L is partially supported by the PROMETEOII 2015 program/Conselleria d'Educació, Investigació, Cultura i Esport, Generalitat Valenciana and the CIBERSAM/Institute of Health Carlos III, Spanish Ministry of Science and Innovation; DM reports ad-hoc honoraria or consulting from Bunge, Haas Avocado Board, Nutrition Impact, Amarin, Astra Zeneca, Boston Heart Diagnostics, and Life Sciences Research Organization; and is on the scientific advisory board for Unilever North America; UM gratefully acknowledges funding from the German National Cohort Consortium; CDP, in the past 3 years has received consultancy payments from Pfizer and from Nutricia; DAQ was supported by The Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under award number 5T32HD057822; KR was funded by the UK NIHR Oxford BRC and NIHR CDF; IR is required to include the following statement: The authors alone are responsible for the views expressed in this Article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated; JR received additional funding from the WHO for the work on alcohol as a risk factor; SS received a research support grant from NIH and the National Research Foundation and has received pharmaceutical sponsorship from Pfizer, AstraZeneca, Servier, and Dr Reddy's, speakers honoraria from Pfizer and Lundbeck, and honoraria from the Discovery Foundation and Cambridge University Press; DJS, in the past 3 years, has received research grants and/or consultancy honoraria from AMBRF, Biocodex, Cipla, Lundbeck, National Responsible Gambling Foundation, Novartis, Servier, and Sun; AGT acknowledges a senior research fellowship from the National Health & Medical Research Council (Australia; 1042600); and GDT was supported by a Center Grant from the National Institutes of Environmental Health Sciences (ES00260).
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.