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Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation.
0140-6736
1223-1249
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Lee, Paul
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et al.
Abbafati, Cristiana
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Abbas, Kaja M.
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Abbasi-Kangevari, Mohsen
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Abd-Allah, Foad
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Abdelalim, Ahmed
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Abdollahi, Mohammad
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Abdollahpour, Ibrahim
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Abegaz, Kedir Hussein
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Abolhassani, Hassan
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Abushouk, Abdelrahman I.
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Adabi, Maryam
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Adekanmbi, Victor
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Akunna, Chisom Joyqueenet
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Alahdab, Fares
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Al-Aly, Ziyad
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Lee, Paul
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Abbafati, Cristiana, Abbas, Kaja M., Abbasi-Kangevari, Mohsen, Abdollahi, Mohammad and Lee, Paul , et al. (2020) Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396 (10258), 1223-1249. (doi:10.1016/S0140-6736(20)30752-2).

Record type: Article

Abstract

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation.

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More information

Published date: 17 October 2020
Additional Information: Funding Information: C A T Antonio reports personal fees from Johnson & Johnson (Philippines), outside of the submitted work. E Beghi reports grants from Italian Ministry of Health and SOBI, and personal fees from Arvelle Therapeutics, outside of the submitted work. Y Béjot reports personal fees from AstraZeneca, Bristol-Myers Squibb, Pfizer, Medtronic, Merck Sharpe & Dohme, and Amgen; grants and personal fees from Boehringer Ingelheim; personal fees and non-financial support from Servier; and non-financial support from Biogen, outside of the submitted work. M L Bell reports grants from US Environmental Protection Agency, National Institutes of Health (NIH), and from Wellcome Trust Foundation, during the conduct of the study; and Honorarium or travel reimbursement from the NIH (for review of grant proposals), American Journal of Public Health (participation as editor), Global Research Laboratory and Seoul National University, Royal Society, Ohio University, Atmospheric Chemistry Gordon Research Conference, Johns Hopkins Bloomberg School of Public Health, Arizona State University, Ministry of the Environment Japan, Hong Kong Polytechnic University, University of Illinois–Champaign, and the University of Tennessee–Knoxville, outside of the submitted work. H Christensen reports personal fees from Bristol Myers Squibb, Bayer, and Boehringer Ingelheim, outside of the submitted work. S-C Chung reports grants from GlaxoSmithKline, outside of the submitted work. L Degenhardt reports grants from Indivior and Seqirus, outside of the submitted work. S M S Islam reports grants from National Heart Foundation of Australia and Deakin University, during the conduct of the study. S L James reports grants from Sanofi Pasteur and employment from Genentech, outside of the submitted work. V Jha reports grants from Baxter Healthcare, GlaxoSmithKline, Zydus Cadilla, and Biocon and personal fees from NephroPlus, outside of the submitted work. J J Jozwiak reports personal fees from Amgen, ALAB Laboratoria, Teva, Synexus, and Boehringer Ingelheim, outside of the submitted work. S V Katikireddi reports grants from NRS Senior Clinical Fellowship, UK Medical Research Council, and the Scottish Government Chief Scientist Office, during the conduct of the study. M Kivimäki reports grants from the Medical Research Council, UK (MR/R024227/1), during the conduct of the study. S Lorkowski reports personal fees from Akcea Therapeutics, Amedes, Amgen, Berlin-Chemie, Boehringer Ingelheim Pharma, Daiichi Sankyo, Merck Sharp & Dohme, Novo Nordisk, Sanofi-Aventis, Synlab, Unilever, and Upfield, and non-financial support from Preventicus, outside of the submitted work. R V Martin reports grants from the Natural Science and Engineering Research Council of Canada, during the conduct of the study. T R Miller reports having a contract from the AB InBev Foundation, outside of the submitted work. J F Mosser reports grants from the Bill & Melinda Gates Foundation, during the conduct of the study. S Nomura reports grants from the Ministry of Education, Culture, Sports, Science, and Technology. S B Patten reports funding from the Cuthbertson & Fischer Chair in Pediatric Mental Health at the University of Calgary, during the conduct of the study. C D Pond reports personal fees from Nutricia, outside of the submitted work; and grants from the National Medical Research council in relation to dementia, and travel grants and remuneration related to education of primary care professionals in relation to dementia. M J Postma reports grants from BioMerieux, WHO, European Union, FIND, Antilope, DIKTI, LPDP, Bayer, and Budi; personal fees from Quintiles, Novartis, and Pharmerit; grants and personal fees from IQVIA, Bristol-Myers Squibb, Astra Zeneca, Seqirus, Sanofi, Merck Sharpe & Dohme, GlaxoSmithKline, Pfizer, Boehringer Ingelheim, and Novavax; stocks from Ingress Health, and PAG; and is acting as adviser to Asc Academics, all outside of the submitted work. I Rakovac reports grants from WHO, during the conduct of the study. A E Schutte reports personal fees from Omron, Servier, Takeda, Novartis, and Abbott, outside of the submitted work. J A Singh reports personal fees from Crealta/Horizon, Medisys, Fidia, UBM LLC, Trio Health, Medscape, WebMD, Clinical Care Options, Clearview Healthcare Partners, Putnam Associates, Spherix, Practice Point Communications, the NIH, and the American College of Rheumatology; personal fees from Simply Speaking; stock options in Amarin Pharmaceuticals and Viking Pharmaceuticals; membership in the steering committee of OMERACT (an international organisation that develops measures for clinical trials and receives arm's length funding from 12 pharmaceutical companies), the FDA Arthritis Advisory Committee, and the Veterans Affairs Rheumatology Field Advisory Committee; and non-financial support from UAB Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis, outside of the submitted work. S T S Skou reports personal fees from Journal of Orthopaedic & Sports Physical Therapy and Munksgaard and grants from The Lundbeck Foundation, outside of the submitted work; and being co-founder of GLA:D. GLA:D is a non-profit initiative hosted at University of Southern Denmark aimed at implementing clinical guidelines for osteoarthritis in clinical practice. J D Stanaway reports grants from the Bill & Melinda Gates Foundation, during the conduct of the study. D J Stein reports personal fees from Lundbeck, and Sun, outside of the submitted work. F Topouzis reports grants from Pfizer, Thea, Novartis, Rheon, Omikron, Pharmaten, Bayer, and Bausch & Lomb; and personal fees from Novartis, and Omikron, outside of the submitted work. R Uddin reports travel and accommodation reimbursement from Deakin University Institute for Physical Activity and Nutrition, outside of the submitted work. All other authors declare no competing interests. Publisher Copyright: © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

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Local EPrints ID: 475692
URI: http://eprints.soton.ac.uk/id/eprint/475692
ISSN: 0140-6736
PURE UUID: fd2c5b4d-95bc-4ddc-8b1f-3357b205d728
ORCID for Paul Lee: ORCID iD orcid.org/0000-0002-5729-6450

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Date deposited: 24 Mar 2023 17:57
Last modified: 14 Jun 2024 02:07

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Contributors

Author: Cristiana Abbafati
Author: Kaja M. Abbas
Author: Mohsen Abbasi-Kangevari
Author: Foad Abd-Allah
Author: Ahmed Abdelalim
Author: Mohammad Abdollahi
Author: Ibrahim Abdollahpour
Author: Kedir Hussein Abegaz
Author: Hassan Abolhassani
Author: Victor Aboyans
Author: Lucas Guimarães Abreu
Author: Michael R.M. Abrigo
Author: Ahmed Abualhasan
Author: Laith Jamal Abu-Raddad
Author: Abdelrahman I. Abushouk
Author: Maryam Adabi
Author: Victor Adekanmbi
Author: Abiodun Moshood Adeoye
Author: Olatunji O. Adetokunboh
Author: Davoud Adham
Author: Shailesh M. Advani
Author: Ashkan Afshin
Author: Gina Agarwal
Author: Seyed Mohammad Kazem Aghamir
Author: Anurag Agrawal
Author: Tauseef Ahmad
Author: Keivan Ahmadi
Author: Mehdi Ahmadi
Author: Hamid Ahmadieh
Author: Muktar Beshir Ahmed
Author: Temesgen Yihunie Akalu
Author: Rufus Olusola Akinyemi
Author: Tomi Akinyemiju
Author: Blessing Akombi
Author: Chisom Joyqueenet Akunna
Author: Fares Alahdab
Author: Ziyad Al-Aly
Author: Khurshid Alam
Author: Samiah Alam
Author: Tahiya Alam
Author: Fahad Mashhour Alanezi
Author: Turki M. Alanzi
Author: Biresaw Wassihun Alemu
Author: Peter W. Gething
Author: Md Mehedi Hasan
Author: Yang Liu
Author: Nicholas L.S. Roberts
Author: Joshua A. Salomon
Author: Yuan Pang Wang
Author: Stephen S. Lim
Author: Paul Lee ORCID iD
Corporate Author: et al.

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