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Yin P, Brauer M, Cohen AJ, Wang H, Li J, Burnett RT, Stanaway JD, Causey K, Larson S, Godwin W, Frostad J, Marks A, Wang L, Zhou M, Murray CJL. The effect of air pollution on deaths, disease burden, and life expectancy across China and its provinces, 1990-2017: an analysis for the Global Burden of Disease Study 2017. Lancet Planet Health 2020; 4:e386-e398. [PMID: 32818429 PMCID: PMC7487771 DOI: 10.1016/s2542-5196(20)30161-3] [Citation(s) in RCA: 224] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 06/17/2020] [Accepted: 06/17/2020] [Indexed: 05/15/2023]
Abstract
BACKGROUND Air pollution is an important public health concern in China, with high levels of exposure to both ambient and household air pollution. To inform action at provincial levels in China, we estimated the exposure to air pollution and its effect on deaths, disease burden, and loss of life expectancy across all provinces in China from 1990 to 2017. METHODS In all 33 provinces, autonomous regions, municipalities, and special administrative regions in China, we estimated exposure to air pollution, including ambient particulate matter pollution (defined as the annual gridded concentration of PM2·5), household air pollution (defined as the percentage of households using solid cooking fuels and the corresponding exposure to PM2·5), and ozone pollution (defined as average gridded ozone concentrations). We used the methods of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 to estimate deaths and disability-adjusted life-years (DALYs) attributable to air pollution, and what the life expectancy would have been if air pollution levels had been less than the minimum level causing health loss. FINDINGS The average annual population-weighted PM2·5 exposure in China was 52·7 μg/m3 (95% uncertainty interval [UI] 41·0-62·8) in 2017, which is 9% lower than in 1990 (57·8 μg/m3, 45·0-67·0). We estimated that 1·24 million (95% UI 1·08-1·40) deaths in China were attributable to air pollution in 2017, including 851 660 (712 002-990 271) from ambient PM2·5 pollution, 271 089 (209 882-346 561) from household air pollution from solid fuels, and 178 187 (67 650-286 229) from ambient ozone pollution. The age-standardised DALY rate attributable to air pollution was 1513·1 per 100 000 in China in 2017, and was higher in males (1839·8 per 100 000) than in females (1198·3 per 100 000). The age-standardised death rate attributable to air pollution decreased by 60·6% (55·7-63·7) for China overall between 1990 and 2017, driven by an 85·4% (83·2-87·3) decline in household air pollution and a 12·0% (1·4-22·1) decline in ambient PM2·5 pollution. 40·0% of DALYs for COPD were attributable to air pollution, as were 35·6% of DALYs for lower respiratory infections, 26·1% for diabetes, 25·8% for lung cancer, 19·5% for ischaemic heart disease, and 12·8% for stroke. We estimated that if the air pollution level in China was below the minimum causing health loss, the average life expectancy would have been 1·25 years greater. The DALY rate per 100 000 attributable to air pollution varied across provinces, ranging from 482·3 (371·1-604·1) in Hong Kong to 1725·6 (720·4-2653·1) in Xinjiang for ambient pollution, and from 18·7 (9·1-34·0) in Shanghai to 1804·5 (1339·5-2270·1) in Tibet for household pollution. Although the overall mortality attributable to air pollution decreased in China between 1990 and 2017, 12 provinces showed an increasing trend during the past 27 years. INTERPRETATION Pollution from ambient PM2·5 and household burning of solid fuels decreased markedly in recent years in China, after extensive efforts to control emissions. However, PM2·5 concentrations still exceed the WHO Air Quality Guideline for the entire population of China, with 81% living in regions exceeding the WHO Interim Target 1, and air pollution remains an important risk factor. Sustainable development policies should be implemented and enforced to reduce the impact of air pollution on long-term economic development and population health. FUNDING Bill & Melinda Gates Foundation; and China National Key Research and Development Program.
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Affiliation(s)
- Peng Yin
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia, Vancouver, BC, Canada; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Aaron J Cohen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Health Effects Institute, Boston, MA, USA
| | - Haidong Wang
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jie Li
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | | | - Jeffrey D Stanaway
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Kate Causey
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Samantha Larson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - William Godwin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Ashley Marks
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Lijun Wang
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Maigeng Zhou
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
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Shaffer RM, Sellers SP, Baker MG, de Buen Kalman R, Frostad J, Suter MK, Anenberg SC, Balbus J, Basu N, Bellinger DC, Birnbaum L, Brauer M, Cohen A, Ebi KL, Fuller R, Grandjean P, Hess JJ, Kogevinas M, Kumar P, Landrigan PJ, Lanphear B, London SJ, Rooney AA, Stanaway JD, Trasande L, Walker K, Hu H. Improving and Expanding Estimates of the Global Burden of Disease Due to Environmental Health Risk Factors. Environ Health Perspect 2019; 127:105001. [PMID: 31626566 PMCID: PMC6867191 DOI: 10.1289/ehp5496] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 08/20/2019] [Accepted: 09/25/2019] [Indexed: 05/22/2023]
Abstract
BACKGROUND The Global Burden of Disease (GBD) study, coordinated by the Institute for Health Metrics and Evaluation (IHME), produces influential, data-driven estimates of the burden of disease and premature death due to major risk factors. Expanded quantification of disease due to environmental health (EH) risk factors, including climate change, will enhance accuracy of GBD estimates, which will contribute to developing cost-effective policies that promote prevention and achieving Sustainable Development Goals. OBJECTIVES We review key aspects of the GBD for the EH community and introduce the Global Burden of Disease-Pollution and Health Initiative (GBD-PHI), which aims to work with IHME and the GBD study to improve estimates of disease burden attributable to EH risk factors and to develop an innovative approach to estimating climate-related disease burden-both current and projected. METHODS We discuss strategies for improving GBD quantification of specific EH risk factors, including air pollution, lead, and climate change. We highlight key methodological challenges, including new EH risk factors, notably evidence rating and global exposure assessment. DISCUSSION A number of issues present challenges to the scope and accuracy of current GBD estimates for EH risk factors. For air pollution, minimal data exist on the exposure-risk relationships associated with high levels of pollution; epidemiological studies in high pollution regions should be a research priority. For lead, the GBD's current methods do not fully account for lead's impact on neurodevelopment; innovative methods to account for subclinical effects are needed. Decisions on inclusion of additional EH risk-outcome pairs need to be guided by findings of systematic reviews, the size of exposed populations, feasibility of global exposure estimates, and predicted trends in exposures and diseases. Neurotoxicants, endocrine-disrupting chemicals, and climate-related factors should be high priorities for incorporation into upcoming iterations of the GBD study. Enhancing the scope and methods will improve the GBD's estimates and better guide prevention policy. https://doi.org/10.1289/EHP5496.
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Affiliation(s)
- Rachel M. Shaffer
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Samuel P. Sellers
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | - Marissa G. Baker
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Rebeca de Buen Kalman
- Evans School of Public Policy and Governance, University of Washington, Seattle, Washington, USA
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
- Department of Health Metrics Sciences, University of Washington, Seattle, Washington, USA
| | - Megan K. Suter
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Susan C. Anenberg
- Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - John Balbus
- Office of the Director, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada
| | - David C. Bellinger
- Department of Neurology, Harvard Medical School, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Linda Birnbaum
- Office of the Director, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
| | - Michael Brauer
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Aaron Cohen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
- Health Effects Institute, Boston, Massachusetts, USA
| | - Kristie L. Ebi
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | | | - Philippe Grandjean
- Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Jeremy J. Hess
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | | | - Pushpam Kumar
- United Nations Programme on the Environment, Nairobi, Kenya
| | - Philip J. Landrigan
- Program in Global Public Health and the Common Good, Boston College, Chestnut Hill, Massachusetts, USA
- Global Observatory on Pollution and Health, Boston College, Chestnut Hill, Massachusetts, USA
| | - Bruce Lanphear
- Simon Fraser University, Vancouver, British Columbia, Canada
| | - Stephanie J. London
- Epidemiology Branch, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
| | - Andrew A. Rooney
- Division of the National Toxicology Program, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
| | - Jeffrey D. Stanaway
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
| | - Leonardo Trasande
- Department of Pediatrics, New York University School of Medicine, New York, New York, USA
- NYU Global Institute of Public Health, New York University, New York, New York, USA
| | - Katherine Walker
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Howard Hu
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
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3
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Reiner RC, Welgan CA, Casey DC, Troeger CE, Baumann MM, Nguyen QP, Swartz SJ, Blacker BF, Deshpande A, Mosser JF, Osgood-Zimmerman AE, Earl L, Marczak LB, Munro SB, Miller-Petrie MK, Rodgers Kemp G, Frostad J, Wiens KE, Lindstedt PA, Pigott DM, Dwyer-Lindgren L, Ross JM, Burstein R, Graetz N, Rao PC, Khalil IA, Davis Weaver N, Ray SE, Davis I, Farag T, Brady OJ, Kraemer MUG, Smith DL, Bhatt S, Weiss DJ, Gething PW, Kassebaum NJ, Mokdad AH, Murray CJL, Hay SI. Identifying residual hotspots and mapping lower respiratory infection morbidity and mortality in African children from 2000 to 2017. Nat Microbiol 2019; 4:2310-2318. [PMID: 31570869 PMCID: PMC6877470 DOI: 10.1038/s41564-019-0562-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 08/15/2019] [Indexed: 12/13/2022]
Abstract
Lower respiratory infections (LRIs) are the leading cause of death in children under the age of 5, despite the existence of vaccines against many of their aetiologies. Furthermore, more than half of these deaths occur in Africa. Geospatial models can provide highly detailed estimates of trends subnationally, at the level where implementation of health policies has the greatest impact. We used Bayesian geostatistical modelling to estimate LRI incidence, prevalence and mortality in children under 5 subnationally in Africa for 2000–2017, using surveys covering 1.46 million children and 9,215,000 cases of LRI. Our model reveals large within-country variation in both health burden and its change over time. While reductions in childhood morbidity and mortality due to LRI were estimated for almost every country, we expose a cluster of residual high risk across seven countries, which averages 5.5 LRI deaths per 1,000 children per year. The preventable nature of the vast majority of LRI deaths mandates focused health system efforts in specific locations with the highest burden. Geospatial modelling shows an overall decline in morbidity and mortality due to lower respiratory infections in Africa from 2000 to 2017, but also identifies subnational areas with residual high risk.
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Affiliation(s)
- Robert C Reiner
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. .,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
| | - Catherine A Welgan
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Daniel C Casey
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Christopher E Troeger
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Mathew M Baumann
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - QuynhAnh P Nguyen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Scott J Swartz
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Brigette F Blacker
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Aniruddha Deshpande
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Jonathan F Mosser
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | | | - Lucas Earl
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Laurie B Marczak
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Sandra B Munro
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Molly K Miller-Petrie
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Grant Rodgers Kemp
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Michigan State University, East Lansing, MI, USA
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Kirsten E Wiens
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Paulina A Lindstedt
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - David M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Laura Dwyer-Lindgren
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer M Ross
- Department of Global Health, University of Washington, Seattle, WA, USA
| | - Roy Burstein
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Nicholas Graetz
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Puja C Rao
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Ibrahim A Khalil
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Nicole Davis Weaver
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Sarah E Ray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Ian Davis
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Tamer Farag
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - Oliver J Brady
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Moritz U G Kraemer
- Department of Zoology, University of Oxford, Oxford, UK.,Harvard Medical School, University of Harvard, Boston, MA, USA
| | - David L Smith
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | | | | | | | - Nicholas J Kassebaum
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA
| | - Ali H Mokdad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Christopher J L Murray
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA. .,Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
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4
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Roth GA, Johnson CO, Abate KH, Abd-Allah F, Ahmed M, Alam K, Alam T, Alvis-Guzman N, Ansari H, Ärnlöv J, Atey TM, Awasthi A, Awoke T, Barac A, Bärnighausen T, Bedi N, Bennett D, Bensenor I, Biadgilign S, Castañeda-Orjuela C, Catalá-López F, Davletov K, Dharmaratne S, Ding EL, Dubey M, Faraon EJA, Farid T, Farvid MS, Feigin V, Fernandes J, Frostad J, Gebru A, Geleijnse JM, Gona PN, Griswold M, Hailu GB, Hankey GJ, Hassen HY, Havmoeller R, Hay S, Heckbert SR, Irvine CMS, James SL, Jara D, Kasaeian A, Khan AR, Khera S, Khoja AT, Khubchandani J, Kim D, Kolte D, Lal D, Larsson A, Linn S, Lotufo PA, Magdy Abd El Razek H, Mazidi M, Meier T, Mendoza W, Mensah GA, Meretoja A, Mezgebe HB, Mirrakhimov E, Mohammed S, Moran AE, Nguyen G, Nguyen M, Ong KL, Owolabi M, Pletcher M, Pourmalek F, Purcell CA, Qorbani M, Rahman M, Rai RK, Ram U, Reitsma MB, Renzaho AMN, Rios-Blancas MJ, Safiri S, Salomon JA, Sartorius B, Sepanlou SG, Shaikh MA, Silva D, Stranges S, Tabarés-Seisdedos R, Tadele Atnafu N, Thakur JS, Topor-Madry R, Truelsen T, Tuzcu EM, Tyrovolas S, Ukwaja KN, Vasankari T, Vlassov V, Vollset SE, Wakayo T, Weintraub R, Wolfe C, Workicho A, Xu G, Yadgir S, Yano Y, Yip P, Yonemoto N, Younis M, Yu C, Zaidi Z, Zaki MES, Zipkin B, Afshin A, Gakidou E, Lim SS, Mokdad AH, Naghavi M, Vos T, Murray CJL. The Burden of Cardiovascular Diseases Among US States, 1990-2016. JAMA Cardiol 2019; 3:375-389. [PMID: 29641820 PMCID: PMC6145754 DOI: 10.1001/jamacardio.2018.0385] [Citation(s) in RCA: 235] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Question How does the total burden of cardiovascular diseases vary across US states? Findings In this study using the Global Burden of Disease methodology, large disparities in total burden of CVD were found between US states despite marked improvements in CVD burden. Meaning These estimates can provide a benchmark for states working to focus on key risk factors, improve health care quality, and lower health care costs. Importance Cardiovascular disease (CVD) is the leading cause of death in the United States, but regional variation within the United States is large. Comparable and consistent state-level measures of total CVD burden and risk factors have not been produced previously. Objective To quantify and describe levels and trends of lost health due to CVD within the United States from 1990 to 2016 as well as risk factors driving these changes. Design, Setting, and Participants Using the Global Burden of Disease methodology, cardiovascular disease mortality, nonfatal health outcomes, and associated risk factors were analyzed by age group, sex, and year from 1990 to 2016 for all residents in the United States using standardized approaches for data processing and statistical modeling. Burden of disease was estimated for 10 groupings of CVD, and comparative risk analysis was performed. Data were analyzed from August 2016 to July 2017. Exposures Residing in the United States. Main Outcomes and Measures Cardiovascular disease disability-adjusted life-years (DALYs). Results Between 1990 and 2016, age-standardized CVD DALYs for all states decreased. Several states had large rises in their relative rank ordering for total CVD DALYs among states, including Arkansas, Oklahoma, Alabama, Kentucky, Missouri, Indiana, Kansas, Alaska, and Iowa. The rate of decline varied widely across states, and CVD burden increased for a small number of states in the most recent years. Cardiovascular disease DALYs remained twice as large among men compared with women. Ischemic heart disease was the leading cause of CVD DALYs in all states, but the second most common varied by state. Trends were driven by 12 groups of risk factors, with the largest attributable CVD burden due to dietary risk exposures followed by high systolic blood pressure, high body mass index, high total cholesterol level, high fasting plasma glucose level, tobacco smoking, and low levels of physical activity. Increases in risk-deleted CVD DALY rates between 2006 and 2016 in 16 states suggest additional unmeasured risks beyond these traditional factors. Conclusions and Relevance Large disparities in total burden of CVD persist between US states despite marked improvements in CVD burden. Differences in CVD burden are largely attributable to modifiable risk exposures.
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Affiliation(s)
| | - Gregory A Roth
- Institute for Health Metrics and Evaluation, University of Washington, Seattle.,Division of Cardiology, Department of Medicine, University of Washington, Seattle
| | - Catherine O Johnson
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | | | | | - Khurshid Alam
- The University of Western Australia, Perth, Western Australia, Australia
| | - Tahiya Alam
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | | | | | | | - Ashish Awasthi
- Indian Institute of Public Health Gandhinagar, Public Health Foundation of India, Gandhinagar, Gujarat, India
| | | | | | | | | | | | | | | | | | - Ferrán Catalá-López
- INCLIVA Health Research Institute, Centro de Investigación Biomédica en Red Salud Mental, University of Valencia, Valencia, Spain
| | - Kairat Davletov
- Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
| | | | - Eric L Ding
- Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Manisha Dubey
- International Institute for Population Sciences, Mumbai, India
| | | | - Talha Farid
- University of Louisville, Louisville, Kentucky
| | - Maryam S Farvid
- Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Valery Feigin
- Auckland University of Technology, Auckland, New Zealand
| | | | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | | | | | - Max Griswold
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | - Graeme J Hankey
- School of Medicine and Pharmacology, University of Western Australia, Perth, Western Australia, Australia
| | | | | | - Simon Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Susan R Heckbert
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | - Spencer Lewis James
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Dube Jara
- Debre Markos University, Debre Markos, Ethiopia
| | - Amir Kasaeian
- Hematology, Oncology, and Stem Cell Transplantation Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | | | | | - Abdullah T Khoja
- Al Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia
| | | | - Daniel Kim
- Northeastern University, Boston, Massachusetts
| | | | - Dharmesh Lal
- Public Health Foundation of India, New Delhi, India
| | - Anders Larsson
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | | | - Paulo A Lotufo
- Clinical Research Center, University Hospital, University of São Paulo, São Paulo, São Paulo, Brazil
| | | | - Mohsen Mazidi
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Chaoyang, Beijing
| | - Toni Meier
- Martin Luther University of Halle-Wittenberg, Halle, Germany
| | | | | | - Atte Meretoja
- University of Melbourne, Melbourne, Victoria, Australia
| | | | | | | | | | - Grant Nguyen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Minh Nguyen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Kanyin Liane Ong
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Mayowa Owolabi
- Department of Medicine, University of Ibadan, Ibadan, Oyo State, Nigeria
| | - Martin Pletcher
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | - Caroline A Purcell
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Mostafa Qorbani
- Noncommunicable Diseases Research Center, Alborz University of Medical Sciences, Hassan Abad, Karaj, Iran
| | | | - Rajesh Kumar Rai
- Society for Health and Demographic Surveillance, West Bengal, India
| | - Usha Ram
- International Institute for Population Sciences, Mumbai, India
| | | | | | | | - Saeid Safiri
- Maragheh University of Medical Sciences, East Azerbaijan Province, Iran
| | | | | | | | | | - Diego Silva
- Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Saverio Stranges
- Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada
| | - Rafael Tabarés-Seisdedos
- INCLIVA Health Research Institute, Centro de Investigación Biomédica en Red Salud Mental, University of Valencia, Valencia, Spain
| | | | - J S Thakur
- Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | | | | | | | - Stefanos Tyrovolas
- Hospital Sant Joan de Déu Barcelona, Sant Joan de Déu Research Foundation, Centro de Investigación Biomédica en Red Salud Mental, Universitat de Barcelona, Barcelona, Spain
| | - Kingsley Nnanna Ukwaja
- Department of Internal Medicine, Federal Teaching Hospital, Abakaliki, Ebonyi State, Nigeria
| | - Tommi Vasankari
- UKK Institute for Health Promotion Research, Tampere, Finland
| | - Vasiliy Vlassov
- National Research University Higher School of Economics, Moscow, Russia
| | | | | | | | | | | | - Gelin Xu
- Nanjing University School of Medicine, Nanjing, China
| | - Simon Yadgir
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Yuichiro Yano
- The University of Mississippi Medical Center, Jackson
| | - Paul Yip
- University of Hong Kong, Pokfulam, Hong Kong
| | | | | | | | | | | | - Ben Zipkin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Ashkan Afshin
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Emmanuela Gakidou
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Stephen S Lim
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Ali H Mokdad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Mohsen Naghavi
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Theo Vos
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
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5
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Balakrishnan K, Dey S, Gupta T, Dhaliwal RS, Brauer M, Cohen AJ, Stanaway JD, Beig G, Joshi TK, Aggarwal AN, Sabde Y, Sadhu H, Frostad J, Causey K, Godwin W, Shukla DK, Kumar GA, Varghese CM, Muraleedharan P, Agrawal A, Anjana RM, Bhansali A, Bhardwaj D, Burkart K, Cercy K, Chakma JK, Chowdhury S, Christopher DJ, Dutta E, Furtado M, Ghosh S, Ghoshal AG, Glenn SD, Guleria R, Gupta R, Jeemon P, Kant R, Kant S, Kaur T, Koul PA, Krish V, Krishna B, Larson SL, Madhipatla K, Mahesh PA, Mohan V, Mukhopadhyay S, Mutreja P, Naik N, Nair S, Nguyen G, Odell CM, Pandian JD, Prabhakaran D, Prabhakaran P, Roy A, Salvi S, Sambandam S, Saraf D, Sharma M, Shrivastava A, Singh V, Tandon N, Thomas NJ, Torre A, Xavier D, Yadav G, Singh S, Shekhar C, Vos T, Dandona R, Reddy KS, Lim SS, Murray CJL, Venkatesh S, Dandona L. The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study 2017. Lancet Planet Health 2019; 3:e26-e39. [PMID: 30528905 PMCID: PMC6358127 DOI: 10.1016/s2542-5196(18)30261-4] [Citation(s) in RCA: 260] [Impact Index Per Article: 52.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 10/18/2018] [Accepted: 11/02/2018] [Indexed: 05/19/2023]
Abstract
BACKGROUND Air pollution is a major planetary health risk, with India estimated to have some of the worst levels globally. To inform action at subnational levels in India, we estimated the exposure to air pollution and its impact on deaths, disease burden, and life expectancy in every state of India in 2017. METHODS We estimated exposure to air pollution, including ambient particulate matter pollution, defined as the annual average gridded concentration of PM2.5, and household air pollution, defined as percentage of households using solid cooking fuels and the corresponding exposure to PM2.5, across the states of India using accessible data from multiple sources as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three Socio-demographic Index (SDI) levels as calculated by GBD 2017 on the basis of lag-distributed per-capita income, mean education in people aged 15 years or older, and total fertility rate in people younger than 25 years. We estimated deaths and disability-adjusted life-years (DALYs) attributable to air pollution exposure, on the basis of exposure-response relationships from the published literature, as assessed in GBD 2017; the proportion of total global air pollution DALYs in India; and what the life expectancy would have been in each state of India if air pollution levels had been less than the minimum level causing health loss. FINDINGS The annual population-weighted mean exposure to ambient particulate matter PM2·5 in India was 89·9 μg/m3 (95% uncertainty interval [UI] 67·0-112·0) in 2017. Most states, and 76·8% of the population of India, were exposed to annual population-weighted mean PM2·5 greater than 40 μg/m3, which is the limit recommended by the National Ambient Air Quality Standards in India. Delhi had the highest annual population-weighted mean PM2·5 in 2017, followed by Uttar Pradesh, Bihar, and Haryana in north India, all with mean values greater than 125 μg/m3. The proportion of population using solid fuels in India was 55·5% (54·8-56·2) in 2017, which exceeded 75% in the low SDI states of Bihar, Jharkhand, and Odisha. 1·24 million (1·09-1·39) deaths in India in 2017, which were 12·5% of the total deaths, were attributable to air pollution, including 0·67 million (0·55-0·79) from ambient particulate matter pollution and 0·48 million (0·39-0·58) from household air pollution. Of these deaths attributable to air pollution, 51·4% were in people younger than 70 years. India contributed 18·1% of the global population but had 26·2% of the global air pollution DALYs in 2017. The ambient particulate matter pollution DALY rate was highest in the north Indian states of Uttar Pradesh, Haryana, Delhi, Punjab, and Rajasthan, spread across the three SDI state groups, and the household air pollution DALY rate was highest in the low SDI states of Chhattisgarh, Rajasthan, Madhya Pradesh, and Assam in north and northeast India. We estimated that if the air pollution level in India were less than the minimum causing health loss, the average life expectancy in 2017 would have been higher by 1·7 years (1·6-1·9), with this increase exceeding 2 years in the north Indian states of Rajasthan, Uttar Pradesh, and Haryana. INTERPRETATION India has disproportionately high mortality and disease burden due to air pollution. This burden is generally highest in the low SDI states of north India. Reducing the substantial avoidable deaths and disease burden from this major environmental risk is dependent on rapid deployment of effective multisectoral policies throughout India that are commensurate with the magnitude of air pollution in each state. FUNDING Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
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Cai S, Ma Q, Wang S, Zhao B, Brauer M, Cohen A, Martin RV, Zhang Q, Li Q, Wang Y, Hao J, Frostad J, Forouzanfar MH, Burnett RT. Impact of air pollution control policies on future PM 2.5 concentrations and their source contributions in China. J Environ Manage 2018; 227:124-133. [PMID: 30172931 DOI: 10.1016/j.jenvman.2018.08.052] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 08/10/2018] [Accepted: 08/11/2018] [Indexed: 05/09/2023]
Abstract
To investigate the impact of air pollutant control policies on future PM2.5 concentrations and their source contributions in China, we developed four future scenarios for 2030 based on a 2013 emission inventory, and conducted air quality simulations for each scenario using the chemical transport model GEOS-Chem (version 9.1.3). Two energy scenarios i.e., current legislation (CLE) and with additional measures (WAM), were developed to project future energy consumption, reflecting, respectively, existing legislation and implementation status as of the end of 2012, and new energy-saving policies that would be released and enforced more stringently. Two end-of-pipe control strategies, i.e., current control technologies (until 2017) and more stringent control technologies (until 2030), were also developed. The combinations of energy scenarios and end-of-pipe control strategies constitute four emission scenarios (2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM) evaluated in simulations. PM2.5 concentrations at national level were estimated to be 57 μg/m3 in the base year 2013, and 58 μg/m3, 42 μg/m3, 42 μg/m3, and 30 μg/m3 under the 2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM scenarios in 2030, respectively. Large PM2.5 reductions between 2013 and 2030 were estimated for heavily polluted regions (Sichuan Basin, Middle Yangtze River, North China). The energy-saving policies show similar effects to the end-of-pipe emission control measures, but the relative importance of these two groups of policies varies in different regions. Absolute contributions to PM2.5 concentrations from most major sources declined from 2017-CLE to 2030-WAM. With respect to fractional contributions, most coal-burning sectors (including power plant, industrial and residential coal burning) increased from 2017-CLE to 2030-WAM, due to larger reductions from non-coal sources, including transportation and biomass open burning. Residential combustion and open burning had much lower fractional contribution to ambient PM2.5 concentrations in the 2017-WAM/2030-WAM compared to the 2017-CLE/2030-CLE scenarios. Fractional contributions from transportation were reduced dramatically in 2030-CLE and 2030-WAM compared to 2017-CLE/2017-WAM, due to the enforcement of stringent end-of-pipe emission controls. Across all scenarios, coal combustion remained the single largest contributor to PM2.5 concentrations in 2030. Reducing PM2.5 emissions from coal combustion remains a strategic priority for air quality management in China.
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Affiliation(s)
- Siyi Cai
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Qiao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; School of Energy and Power Engineering, Shandong University, Jinan, 250061, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China.
| | - Bin Zhao
- Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, 90095, USA
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia V6T1Z3, Canada
| | - Aaron Cohen
- Health Effects Institute, Boston, MA, 02110, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, B3H 4R2, Canada
| | - Qianqian Zhang
- National Satellite Meteorological Center, Beijing, 100089, China
| | - Qinbin Li
- Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, 90095, USA
| | - Yuxuan Wang
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
| | - Jiming Hao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA
| | - Mohammad H Forouzanfar
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA
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Shupler M, Godwin W, Frostad J, Gustafson P, Arku RE, Brauer M. Global estimation of exposure to fine particulate matter (PM 2.5) from household air pollution. Environ Int 2018; 120:354-363. [PMID: 30119008 DOI: 10.1016/j.envint.2018.08.026] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 08/08/2018] [Accepted: 08/09/2018] [Indexed: 05/22/2023]
Abstract
BACKGROUND Exposure to household air pollution (HAP) from cooking with dirty fuels is a leading health risk factor within Asia, Africa and Central/South America. The concentration of particulate matter of diameter ≤ 2.5 μm (PM2.5) is an important metric to evaluate HAP risk, however epidemiological studies have demonstrated significant variation in HAP-PM2.5 concentrations at household, community and country levels. To quantify the global risk due to HAP exposure, novel estimation methods are needed, as financial and resource constraints render it difficult to monitor exposures in all relevant areas. METHODS A Bayesian, hierarchical HAP-PM2.5 global exposure model was developed using kitchen and female HAP-PM2.5 exposure data available in peer-reviewed studies from an updated World Health Organization Global HAP database. Cooking environment characteristics were selected using leave-one-out cross validation to predict quantitative HAP-PM2.5 measurements from 44 studies. Twenty-four hour HAP-PM2.5 kitchen concentrations and male, female and child exposures were estimated for 106 countries in Asia, Africa and Latin America. RESULTS A model incorporating fuel/stove type (traditional wood, improved biomass, coal, dung and gas/electric), urban/rural location, wet/dry season and socio-demographic index resulted in a Bayesian R2 of 0.57. Relative to rural kitchens using gas or electricity, the mean global 24-hour HAP-PM2.5 concentrations were 290 μg/m3 higher (range of regional averages: 110, 880) for traditional stoves, 150 μg/m3 higher (range of regional averages: 50, 290) for improved biomass stoves, 850 μg/m3 higher (range of regional averages: 310, 2600) for animal dung stoves, and 220 μg/m3 higher (range of regional averages: 80, 650) for coal stoves. The modeled global average female/kitchen exposure ratio was 0.40. Average modeled female exposures from cooking with traditional wood stoves were 160 μg/m3 in rural households and 170 μg/m3 in urban households. Average male and child rural area exposures from traditional wood stoves were 120 μg/m3 and 140 μg/m3, respectively; average urban area exposures were identical to average rural exposures among both sub-groups. CONCLUSIONS A Bayesian modeling approach was used to generate unique HAP-PM2.5 kitchen concentrations and personal exposure estimates for all countries, including those with little to no available quantitative HAP-PM2.5 exposure data. The global exposure model incorporating type of fuel-stove combinations can add specificity and reduce exposure misclassification to enable an improved global HAP risk assessment.
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Affiliation(s)
- Matthew Shupler
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.
| | - William Godwin
- Institute for Health Metrics & Evaluation, University of Washington, Seattle, WA, United States of America
| | - Joseph Frostad
- Institute for Health Metrics & Evaluation, University of Washington, Seattle, WA, United States of America
| | - Paul Gustafson
- Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Raphael E Arku
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada; School of Public Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, United States of America
| | - Michael Brauer
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada; Institute for Health Metrics & Evaluation, University of Washington, Seattle, WA, United States of America
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Burnett R, Chen H, Szyszkowicz M, Fann N, Hubbell B, Pope CA, Apte JS, Brauer M, Cohen A, Weichenthal S, Coggins J, Di Q, Brunekreef B, Frostad J, Lim SS, Kan H, Walker KD, Thurston GD, Hayes RB, Lim CC, Turner MC, Jerrett M, Krewski D, Gapstur SM, Diver WR, Ostro B, Goldberg D, Crouse DL, Martin RV, Peters P, Pinault L, Tjepkema M, van Donkelaar A, Villeneuve PJ, Miller AB, Yin P, Zhou M, Wang L, Janssen NAH, Marra M, Atkinson RW, Tsang H, Quoc Thach T, Cannon JB, Allen RT, Hart JE, Laden F, Cesaroni G, Forastiere F, Weinmayr G, Jaensch A, Nagel G, Concin H, Spadaro JV. Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter. Proc Natl Acad Sci U S A 2018; 115:9592-9597. [PMID: 30181279 PMCID: PMC6156628 DOI: 10.1073/pnas.1803222115] [Citation(s) in RCA: 906] [Impact Index Per Article: 151.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
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Affiliation(s)
- Richard Burnett
- Population Studies Division, Health Canada, Ottawa, ON K1A 0K9, Canada
| | - Hong Chen
- Population Studies Division, Health Canada, Ottawa, ON K1A 0K9, Canada
- Department of Environmental and Occupational Health, Public Health Ontario, Toronto, ON M5G 1V2, Canada
| | | | - Neal Fann
- Risk and Benefits Group, Office of Air Quality Planning and Standards, US Environmental Protection Agency, Washington, DC 20460
| | - Bryan Hubbell
- Office of Research and Development, US Environmental Protection Agency, Washington, DC 20460
| | - C Arden Pope
- Department of Economics, Brigham Young University, Provo, UT 84602
| | - Joshua S Apte
- Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78712
| | - Michael Brauer
- School of Population and Public Health, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Aaron Cohen
- Health Effects Institute, Boston, MA 02110-1817
| | - Scott Weichenthal
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC H3A 0G4, Canada
- Gerald Bronfman Department of Oncology, McGill University, Montreal, QC H3A 0G4, Canada
| | - Jay Coggins
- Department of Applied Economics, University of Minnesota, Minneapolis, MN 55455
| | - Qian Di
- Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Universiteit Utrecht, 3512 JE Utrecht, The Netherlands
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195
| | - Stephen S Lim
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195
| | - Haidong Kan
- School of Public Health, Fudan University, Shanghai 200433, China
| | | | - George D Thurston
- Environmental Medicine and Population Health, Program in Human Exposures and Health Effects, New York University School of Medicine, New York, NY 10016
| | - Richard B Hayes
- Department of Population Health, NYU Langone Medical Center, New York, NY 10016
| | - Chris C Lim
- Department of Environmental Medicine, New York University School of Medicine, New York, NY 10016
| | - Michelle C Turner
- ISGlobal, Barcelona Institute for Global Health, 08036 Barcelona, Spain
| | - Michael Jerrett
- Department of Environmental Health Sciences, Fielding School of Public Health, University of California, Los Angeles, CA 90095
| | - Daniel Krewski
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, ON K1N 6N5, Canada
| | - Susan M Gapstur
- Epidemiology Research Program, American Cancer Society, Inc., Atlanta, GA 30303
| | - W Ryan Diver
- Epidemiology Research Program, American Cancer Society, Inc., Atlanta, GA 30303
| | - Bart Ostro
- Department of Civil and Environmental Engineering, University of California, Davis, CA 95616
| | - Debbie Goldberg
- Cancer Prevention Institute of California, Fremont, CA 94538
| | - Daniel L Crouse
- Department of Sociology, University of New Brunswick, Fredericton, NB E3B 5A3, Canada
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada
| | - Paul Peters
- Department of Health Sciences, Carleton University, Ottawa, ON K1S 5B6, Canada
- Department of Geography and Environment, Carleton University, Ottawa, ON K1S 5B6, Canada
- New Brunswick Institute for Research, Data and Training, University of New Brunswick, Fredericton, NB E3B 5A3, Canada
| | - Lauren Pinault
- Health Analysis Division, Statistics Canada, Ottawa, ON K1A 0T6, Canada
| | - Michael Tjepkema
- Health Analysis Division, Statistics Canada, Ottawa, ON K1A 0T6, Canada
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS B3H 4R2, Canada
| | - Paul J Villeneuve
- Department of Health Sciences, Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Anthony B Miller
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
| | - Peng Yin
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Maigeng Zhou
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Lijun Wang
- National Center for Chronic Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China
| | - Nicole A H Janssen
- National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
| | - Marten Marra
- National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
| | - Richard W Atkinson
- Population Health Research Institute, St. George's, University of London, London SW17 0RE, United Kingdom
- MRC-PHE Centre for Environment and Health, St. George's, University of London, London SW17 0RE, United Kingdom
| | - Hilda Tsang
- School of Public Health, University of Hong Kong, Hong Kong, China
| | - Thuan Quoc Thach
- School of Public Health, University of Hong Kong, Hong Kong, China
| | - John B Cannon
- Department of Economics, Brigham Young University, Provo, UT 84602
| | - Ryan T Allen
- Department of Economics, Brigham Young University, Provo, UT 84602
| | - Jaime E Hart
- Department of Environmental Health, Harvard C.T. Channing School of Public Health, Harvard University, Boston, MA 02115
| | - Francine Laden
- Department of Environmental Health, Harvard C.T. Channing School of Public Health, Harvard University, Boston, MA 02115
| | - Giulia Cesaroni
- Department of Epidemiology, Regional Health Service, ASL Roma 1, 00147 Rome, Italy
| | - Francesco Forastiere
- Department of Epidemiology, Regional Health Service, ASL Roma 1, 00147 Rome, Italy
| | - Gudrun Weinmayr
- Institute of Epidemiology and Medical Biometry, Ulm University, 89081 Ulm, Germany
| | - Andrea Jaensch
- Institute of Epidemiology and Medical Biometry, Ulm University, 89081 Ulm, Germany
| | - Gabriele Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University, 89081 Ulm, Germany
| | - Hans Concin
- Agency for Preventive and Social Medicine, 6900 Bregenz, Austria
| | - Joseph V Spadaro
- Spadaro Environmental Research Consultants (SERC), Philadelphia, PA 19142
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Shaddick G, Thomas ML, Amini H, Broday D, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Pruss-Ustun A, Simpson D, van Donkelaar A, Brauer M. Data Integration for the Assessment of Population Exposure to Ambient Air Pollution for Global Burden of Disease Assessment. Environ Sci Technol 2018; 52:9069-9078. [PMID: 29957991 DOI: 10.1021/acs.est.8b02864] [Citation(s) in RCA: 100] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Air pollution is a leading global disease risk factor. Tracking progress (e.g., for Sustainable Development Goals) requires accurate, spatially resolved, routinely updated exposure estimates. A Bayesian hierarchical model was developed to estimate annual average fine particle (PM2.5) concentrations at 0.1° × 0.1° spatial resolution globally for 2010-2016. The model incorporated spatially varying relationships between 6003 ground measurements from 117 countries, satellite-based estimates, and other predictors. Model coefficients indicated larger contributions from satellite-based estimates in countries with low monitor density. Within and out-of-sample cross-validation indicated improved predictions of ground measurements compared to previous (Global Burden of Disease 2013) estimates (increased within-sample R2 from 0.64 to 0.91, reduced out-of-sample, global population-weighted root mean squared error from 23 μg/m3 to 12 μg/m3). In 2016, 95% of the world's population lived in areas where ambient PM2.5 levels exceeded the World Health Organization 10 μg/m3 (annual average) guideline; 58% resided in areas above the 35 μg/m3 Interim Target-1. Global population-weighted PM2.5 concentrations were 18% higher in 2016 (51.1 μg/m3) than in 2010 (43.2 μg/m3), reflecting in particular increases in populous South Asian countries and from Saharan dust transported to West Africa. Concentrations in China were high (2016 population-weighted mean: 56.4 μg/m3) but stable during this period.
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Affiliation(s)
- Gavin Shaddick
- Department of Mathematics , University of Exeter , Exeter , EX4 4QF , U.K
- Department of Mathematical Sciences , University of Bath , Bath , BA2 7AY , U.K
| | - Matthew L Thomas
- Department of Mathematical Sciences , University of Bath , Bath , BA2 7AY , U.K
| | - Heresh Amini
- Department of Epidemiology and Public Health , Swiss Tropical and Public Health Institute , Basel , 4051 , Switzerland
- University of Basel , Basel , 4051 , Switzerland
- Department of Environmental Health , Harvard T. H. Chan School of Public Health , Boston , Massachusetts 02215 , United States
| | - David Broday
- Faculty of Civil and Environmental Engineering , The Technion , Haifa , 32000 , Israel
| | - Aaron Cohen
- Health Effects Institute , Boston , Massachusetts 02110 , United States
- Institute for Health Metrics and Evaluation , Seattle , Washington 98121 , United States
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation , Seattle , Washington 98121 , United States
| | - Amelia Green
- Department of Mathematical Sciences , University of Bath , Bath , BA2 7AY , U.K
| | - Sophie Gumy
- World Health Organization , Geneva , 1202 , Switzerland
| | - Yang Liu
- Department of Environmental Health , Emory University, Rollins School of Public Health , Atlanta , Georgia 30322 , United States
| | - Randall V Martin
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
- Harvard-Smithsonian Center for Astrophysics , Cambridge , Massachusetts 02138 , United States
| | | | - Daniel Simpson
- Department of Statistical Sciences , University of Toronto , Toronto , Ontario M5S 3G3 , Canada
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Michael Brauer
- Institute for Health Metrics and Evaluation , Seattle , Washington 98121 , United States
- School of Population and Public Health , The University of British Columbia , Vancouver , British Columbia V6T 1Z3 , Canada
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Venkataraman C, Brauer M, Tibrewal K, Sadavarte P, Ma Q, Cohen A, Chaliyakunnel S, Frostad J, Klimont Z, Martin RV, Millet DB, Philip S, Walker K, Wang S. Source influence on emission pathways and ambient PM 2.5 pollution over India (2015-2050). Atmos Chem Phys 2018; 18:8017-8039. [PMID: 33679902 PMCID: PMC7935015 DOI: 10.5194/acp-18-8017-2018] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015-2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 annual standard (40 μg m-3). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM2.5 in India. About 60 % of India's mean population-weighted PM2.5 concentrations come from anthropogenic source sectors, while the remainder are from "other" sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.
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Affiliation(s)
- Chandra Venkataraman
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, India
- Interdisciplinary program in Climate Studies, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia V6T1Z3, Canada
| | - Kushal Tibrewal
- Interdisciplinary program in Climate Studies, Indian Institute of Technology Bombay, Powai, Mumbai, India
| | - Pankaj Sadavarte
- Interdisciplinary program in Climate Studies, Indian Institute of Technology Bombay, Powai, Mumbai, India
- Institute for Advanced Sustainability Studies (IASS), Berliner Str. 130, 14467 Potsdam, Germany
| | - Qiao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Aaron Cohen
- Health Effects Institute, Boston, MA 02110, USA
| | - Sreelekha Chaliyakunnel
- Department of Soil, Water, and Climate, University of Minnesota, Minneapolis–Saint Paul, MN 55108, USA
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98195, USA
| | - Zbigniew Klimont
- International Institute for Applied Systems Analysis, Laxenburg, Austria
| | - Randall V. Martin
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada
| | - Dylan B. Millet
- Department of Soil, Water, and Climate, University of Minnesota, Minneapolis–Saint Paul, MN 55108, USA
| | - Sajeev Philip
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada
- NASA Ames Research Center, Moffett Field, California, USA
| | | | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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Barber RM, Fullman N, Sorensen RJD, Bollyky T, McKee M, Nolte E, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, Abdulle AM, Abdurahman AA, Abera SF, Abraham B, Abreha GF, Adane K, Adelekan AL, Adetifa IMO, Afshin A, Agarwal A, Agarwal SK, Agarwal S, Agrawal A, Kiadaliri AA, Ahmadi A, Ahmed KY, Ahmed MB, Akinyemi RO, Akinyemiju TF, Akseer N, Al-Aly Z, Alam K, Alam N, Alam SS, Alemu ZA, Alene KA, Alexander L, Ali R, Ali SD, Alizadeh-Navaei R, Alkerwi A, Alla F, Allebeck P, Allen C, Al-Raddadi R, Alsharif U, Altirkawi KA, Martin EA, Alvis-Guzman N, Amare AT, Amini E, Ammar W, Amo-Adjei J, Amoako YA, Anderson BO, Androudi S, Ansari H, Ansha MG, Antonio CAT, Ärnlöv J, Artaman A, Asayesh H, Assadi R, Astatkie A, Atey TM, Atique S, Atnafu NT, Atre SR, Avila-Burgos L, Avokpaho EFGA, Quintanilla BPA, Awasthi A, Ayele NN, Azzopardi P, Saleem HOB, Bärnighausen T, Bacha U, Badawi A, Banerjee A, Barac A, Barboza MA, Barker-Collo SL, Barrero LH, Basu S, Baune BT, Baye K, Bayou YT, Bazargan-Hejazi S, Bedi N, Beghi E, Béjot Y, Bello AK, Bennett DA, Bensenor IM, Berhane A, Bernabé E, Bernal OA, Beyene AS, Beyene TJ, Bhutta ZA, Biadgilign S, Bikbov B, Birlik SM, Birungi C, Biryukov S, Bisanzio D, Bizuayehu HM, Bose D, Brainin M, Brauer M, Brazinova A, Breitborde NJK, Brenner H, Butt ZA, Cárdenas R, Cahuana-Hurtado L, Campos-Nonato IR, Car J, Carrero JJ, Casey D, Caso V, Castañeda-Orjuela CA, Rivas JC, Catalá-López F, Cecilio P, Cercy K, Charlson FJ, Chen AZ, Chew A, Chibalabala M, Chibueze CE, Chisumpa VH, Chitheer AA, Chowdhury R, Christensen H, Christopher DJ, Ciobanu LG, Cirillo M, Coggeshall MS, Cooper LT, Cortinovis M, Crump JA, Dalal K, Danawi H, Dandona L, Dandona R, Dargan PI, das Neves J, Davey G, Davitoiu DV, Davletov K, De Leo D, Del Gobbo LC, del Pozo-Cruz B, Dellavalle RP, Deribe K, Deribew A, Des Jarlais DC, Dey S, Dharmaratne SD, Dicker D, Ding EL, Dokova K, Dorsey ER, Doyle KE, Dubey M, Ehrenkranz R, Ellingsen CL, Elyazar I, Enayati A, Ermakov SP, Eshrati B, Esteghamati A, Estep K, Fürst T, Faghmous IDA, Fanuel FBB, Faraon EJA, Farid TA, Farinha CSES, Faro A, Farvid MS, Farzadfar F, Feigin VL, Feigl AB, Fereshtehnejad SM, Fernandes JG, Fernandes JC, Feyissa TR, Fischer F, Fitzmaurice C, Fleming TD, Foigt N, Foreman KJ, Forouzanfar MH, Franklin RC, Frostad J, G/hiwot TT, Gakidou E, Gambashidze K, Gamkrelidze A, Gao W, Garcia-Basteiro AL, Gebre T, Gebremedhin AT, Gebremichael MW, Gebru AA, Gelaye AA, Geleijnse JM, Genova-Maleras R, Gibney KB, Giref AZ, Gishu MD, Giussani G, Godwin WW, Gold A, Goldberg EM, Gona PN, Goodridge A, Gopalani SV, Goto A, Graetz N, Greaves F, Griswold M, Guban PI, Gugnani HC, Gupta PC, Gupta R, Gupta R, Gupta T, Gupta V, Habtewold TD, Hafezi-Nejad N, Haile D, Hailu AD, Hailu GB, Hakuzimana A, Hamadeh RR, Hambisa MT, Hamidi S, Hammami M, Hankey GJ, Hao Y, Harb HL, Hareri HA, Haro JM, Hassanvand MS, Havmoeller R, Hay RJ, Hay SI, Hendrie D, Heredia-Pi IB, Hoek HW, Horino M, Horita N, Hosgood HD, Htet AS, Hu G, Huang H, Huang JJ, Huntley BM, Huynh C, Iburg KM, Ileanu BV, Innos K, Irenso AA, Jahanmehr N, Jakovljevic MB, James P, James SL, Javanbakht M, Jayaraman SP, Jayatilleke AU, Jeemon P, Jha V, John D, Johnson C, Johnson SC, Jonas JB, Juel K, Kabir Z, Kalkonde Y, Kamal R, Kan H, Karch A, Karema CK, Karimi SM, Kasaeian A, Kassebaum NJ, Kastor A, Katikireddi SV, Kazanjan K, Keiyoro PN, Kemmer L, Kemp AH, Kengne AP, Kerbo AA, Kereselidze M, Kesavachandran CN, Khader YS, Khalil I, Khan AR, Khan EA, Khan G, Khang YH, Khoja ATA, Khonelidze I, Khubchandani J, Kibret GD, Kim D, Kim P, Kim YJ, Kimokoti RW, Kinfu Y, Kissoon N, Kivipelto M, Kokubo Y, Kolk A, Kolte D, Kopec JA, Kosen S, Koul PA, Koyanagi A, Kravchenko M, Krishnaswami S, Krohn KJ, Defo BK, Bicer BK, Kuipers EJ, Kulkarni VS, Kumar GA, Kumsa FA, Kutz M, Kyu HH, Lager ACJ, Lal A, Lal DK, Lalloo R, Lallukka T, Lan Q, Langan SM, Lansingh VC, Larson HJ, Larsson A, Laryea DO, Latif AA, Lawrynowicz AEB, Leasher JL, Leigh J, Leinsalu M, Leshargie CT, Leung J, Leung R, Levi M, Liang X, Lim SS, Lind M, Linn S, Lipshultz SE, Liu P, Liu Y, Lo LT, Logroscino G, Lopez AD, Lorch SA, Lotufo PA, Lozano R, Lunevicius R, Lyons RA, Macarayan ERK, Mackay MT, El Razek HMA, El Razek MMA, Mahdavi M, Majeed A, Malekzadeh R, Malta DC, Mantovani LG, Manyazewal T, Mapoma CC, Marcenes W, Marks GB, Marquez N, Martinez-Raga J, Marzan MB, Massano J, Mathur MR, Maulik PK, Mazidi M, McAlinden C, McGrath JJ, McNellan C, Meaney PA, Mehari A, Mehndiratta MM, Meier T, Mekonnen AB, Meles KG, Memish ZA, Mengesha MM, Mengiste DT, Mengistie MA, Menota BG, Mensah GA, Mereta ST, Meretoja A, Meretoja TJ, Mezgebe HB, Micha R, Millear A, Mills EJ, Minnig S, Mirarefin M, Mirrakhimov EM, Mock CN, Mohammad KA, Mohammed S, Mohanty SK, Mokdad AH, Mola GLD, Molokhia M, Monasta L, Montico M, Moradi-Lakeh M, Moraga P, Morawska L, Mori R, Moses M, Mueller UO, Murthy S, Musa KI, Nachega JB, Nagata C, Nagel G, Naghavi M, Naheed A, Naldi L, Nangia V, Nascimento BR, Negoi I, Neupane SP, Newton CR, Ng M, Ngalesoni FN, Ngunjiri JW, Nguyen G, Ningrum DNA, Nolte S, Nomura M, Norheim OF, Norrving B, Noubiap JJN, Obermeyer CM, Ogbo FA, Oh IH, Okoro A, Oladimeji O, Olagunju AT, Olivares PR, Olsen HE, Olusanya BO, Olusanya JO, Opio JN, Oren E, Ortiz A, Osborne RH, Osman M, Owolabi MO, PA M, Pain AW, Pakhale S, Castillo EP, Pana A, Papachristou C, Parsaeian M, Patel T, Patton GC, Paudel D, Paul VK, Pearce N, Pereira DM, Perez-Padilla R, Perez-Ruiz F, Perico N, Pesudovs K, Petzold M, Phillips MR, Pigott DM, Pillay JD, Pinho C, Polinder S, Pond CD, Prakash V, Purwar M, Qorbani M, Quistberg DA, Radfar A, Rafay A, Rahimi K, Rahimi-Movaghar V, Rahman M, Rahman MHU, Rai RK, Ram U, Rana SM, Rankin Z, Rao PV, Rao PC, Rawaf S, Rego MAS, Reitsma M, Remuzzi G, Renzaho AMNN, Resnikoff S, Rezaei S, Rezai MS, Ribeiro AL, Roba HS, Rokni MB, Ronfani L, Roshandel G, Roth GA, Rothenbacher D, Roy NK, Sachdev PS, Sackey BB, Saeedi MY, Safiri S, Sagar R, Sahraian MA, Saleh MM, Salomon JA, Samy AM, Sanabria JR, Sanchez-Niño MD, Sandar L, Santos IS, Santos JV, Milicevic MMS, Sarmiento-Suarez R, Sartorius B, Satpathy M, Savic M, Sawhney M, Saylan MI, Schöttker B, Schutte AE, Schwebel DC, Seedat S, Seid AM, Seifu CN, Sepanlou SG, Serdar B, Servan-Mori EE, Setegn T, Shackelford KA, Shaheen A, Shahraz S, Shaikh MA, Shakh-Nazarova M, Shamsipour M, Islam SMS, Sharma J, Sharma R, She J, Sheikhbahaei S, Shen J, Shi P, Shigematsu M, Shin MJ, Shiri R, Shoman H, Shrime MG, Sibamo ELS, Sigfusdottir ID, Silva DAS, Silveira DGA, Sindi S, Singh A, Singh JA, Singh OP, Singh PK, Singh V, Sinke AH, Sinshaw AE, Skirbekk V, Sliwa K, Smith A, Sobngwi E, Soneji S, Soriano JB, Sousa TCM, Sposato LA, Sreeramareddy CT, Stathopoulou V, Steel N, Steiner C, Steinke S, Stokes MA, Stranges S, Strong M, Stroumpoulis K, Sturua L, Sufiyan MB, Suliankatchi RA, Sun J, Sur P, Swaminathan S, Sykes BL, Tabarés-Seisdedos R, Tabb KM, Taffere GR, Talongwa RT, Tarajia M, Tavakkoli M, Taveira N, Teeple S, Tegegne TK, Tehrani-Banihashemi A, Tekelab T, Tekle DY, Shifa GT, Terkawi AS, Tesema AG, Thakur JS, Thomson AJ, Tillmann T, Tiruye TY, Tobe-Gai R, Tonelli M, Topor-Madry R, Tortajada M, Troeger C, Truelsen T, Tura AK, Uchendu US, Ukwaja KN, Undurraga EA, Uneke CJ, Uthman OA, van Boven JFM, Van Dingenen R, Varughese S, Vasankari T, Venketasubramanian N, Violante FS, Vladimirov SK, Vlassov VV, Vollset SE, Vos T, Wagner JA, Wakayo T, Waller SG, Walson JL, Wang H, Wang YP, Watkins DA, Weiderpass E, Weintraub RG, Wen CP, Werdecker A, Wesana J, Westerman R, Whiteford HA, Wilkinson JD, Wiysonge CS, Woldeyes BG, Wolfe CDA, Won S, Workicho A, Workie SB, Wubshet M, Xavier D, Xu G, Yadav AK, Yaghoubi M, Yakob B, Yan LL, Yano Y, Yaseri M, Yimam HH, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Yu C, Zaidi Z, El Sayed Zaki M, Zambrana-Torrelio C, Zapata T, Zenebe ZM, Zodpey S, Zoeckler L, Zuhlke LJ, Murray CJL. Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990-2015: a novel analysis from the Global Burden of Disease Study 2015. Lancet 2017; 390:231-266. [PMID: 28528753 PMCID: PMC5528124 DOI: 10.1016/s0140-6736(17)30818-8] [Citation(s) in RCA: 307] [Impact Index Per Article: 43.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 02/26/2017] [Accepted: 02/28/2017] [Indexed: 02/08/2023]
Abstract
BACKGROUND National levels of personal health-care access and quality can be approximated by measuring mortality rates from causes that should not be fatal in the presence of effective medical care (ie, amenable mortality). Previous analyses of mortality amenable to health care only focused on high-income countries and faced several methodological challenges. In the present analysis, we use the highly standardised cause of death and risk factor estimates generated through the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) to improve and expand the quantification of personal health-care access and quality for 195 countries and territories from 1990 to 2015. METHODS We mapped the most widely used list of causes amenable to personal health care developed by Nolte and McKee to 32 GBD causes. We accounted for variations in cause of death certification and misclassifications through the extensive data standardisation processes and redistribution algorithms developed for GBD. To isolate the effects of personal health-care access and quality, we risk-standardised cause-specific mortality rates for each geography-year by removing the joint effects of local environmental and behavioural risks, and adding back the global levels of risk exposure as estimated for GBD 2015. We employed principal component analysis to create a single, interpretable summary measure-the Healthcare Quality and Access (HAQ) Index-on a scale of 0 to 100. The HAQ Index showed strong convergence validity as compared with other health-system indicators, including health expenditure per capita (r=0·88), an index of 11 universal health coverage interventions (r=0·83), and human resources for health per 1000 (r=0·77). We used free disposal hull analysis with bootstrapping to produce a frontier based on the relationship between the HAQ Index and the Socio-demographic Index (SDI), a measure of overall development consisting of income per capita, average years of education, and total fertility rates. This frontier allowed us to better quantify the maximum levels of personal health-care access and quality achieved across the development spectrum, and pinpoint geographies where gaps between observed and potential levels have narrowed or widened over time. FINDINGS Between 1990 and 2015, nearly all countries and territories saw their HAQ Index values improve; nonetheless, the difference between the highest and lowest observed HAQ Index was larger in 2015 than in 1990, ranging from 28·6 to 94·6. Of 195 geographies, 167 had statistically significant increases in HAQ Index levels since 1990, with South Korea, Turkey, Peru, China, and the Maldives recording among the largest gains by 2015. Performance on the HAQ Index and individual causes showed distinct patterns by region and level of development, yet substantial heterogeneities emerged for several causes, including cancers in highest-SDI countries; chronic kidney disease, diabetes, diarrhoeal diseases, and lower respiratory infections among middle-SDI countries; and measles and tetanus among lowest-SDI countries. While the global HAQ Index average rose from 40·7 (95% uncertainty interval, 39·0-42·8) in 1990 to 53·7 (52·2-55·4) in 2015, far less progress occurred in narrowing the gap between observed HAQ Index values and maximum levels achieved; at the global level, the difference between the observed and frontier HAQ Index only decreased from 21·2 in 1990 to 20·1 in 2015. If every country and territory had achieved the highest observed HAQ Index by their corresponding level of SDI, the global average would have been 73·8 in 2015. Several countries, particularly in eastern and western sub-Saharan Africa, reached HAQ Index values similar to or beyond their development levels, whereas others, namely in southern sub-Saharan Africa, the Middle East, and south Asia, lagged behind what geographies of similar development attained between 1990 and 2015. INTERPRETATION This novel extension of the GBD Study shows the untapped potential for personal health-care access and quality improvement across the development spectrum. Amid substantive advances in personal health care at the national level, heterogeneous patterns for individual causes in given countries or territories suggest that few places have consistently achieved optimal health-care access and quality across health-system functions and therapeutic areas. This is especially evident in middle-SDI countries, many of which have recently undergone or are currently experiencing epidemiological transitions. The HAQ Index, if paired with other measures of health-system characteristics such as intervention coverage, could provide a robust avenue for tracking progress on universal health coverage and identifying local priorities for strengthening personal health-care quality and access throughout the world. FUNDING Bill & Melinda Gates Foundation.
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Cohen AJ, Brauer M, Burnett R, Anderson HR, Frostad J, Estep K, Balakrishnan K, Brunekreef B, Dandona L, Dandona R, Feigin V, Freedman G, Hubbell B, Jobling A, Kan H, Knibbs L, Liu Y, Martin R, Morawska L, Pope CA, Shin H, Straif K, Shaddick G, Thomas M, van Dingenen R, van Donkelaar A, Vos T, Murray CJL, Forouzanfar MH. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015. Lancet 2017; 389:1907-1918. [PMID: 28408086 PMCID: PMC5439030 DOI: 10.1016/s0140-6736(17)30505-6] [Citation(s) in RCA: 2708] [Impact Index Per Article: 386.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Revised: 01/07/2017] [Accepted: 01/24/2017] [Indexed: 02/07/2023]
Abstract
BACKGROUND Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels. METHODS We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure-response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure-response functions spanning the global range of exposure. FINDINGS Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000-422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015. INTERPRETATION Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction. FUNDING Bill & Melinda Gates Foundation and Health Effects Institute.
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Affiliation(s)
| | | | | | | | - Joseph Frostad
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | - Kara Estep
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | | | | | - Lalit Dandona
- Institute for Health Metrics and Evaluation, Seattle, WA, USA; Public Health Foundation of India, New Delhi, India
| | | | - Valery Feigin
- Auckland University of Technology, Auckland, New Zealand
| | - Greg Freedman
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | - Bryan Hubbell
- United States Environmental Protection Agency, Washington, DC, USA
| | | | - Haidong Kan
- Fudan University, Yangpu Qu, Shanghai, China
| | - Luke Knibbs
- University of Queensland, St Lucia, QLD, Australia
| | - Yang Liu
- Emory University, Atlanta, GA, USA
| | | | - Lidia Morawska
- Queensland University of Technology, Brisbane, QLD, Australia
| | | | | | - Kurt Straif
- International Agency for Research on Cancer, Lyon, France
| | | | | | | | | | - Theo Vos
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
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Ericson B, Landrigan P, Taylor MP, Frostad J, Caravanos J. The Global Burden of Lead Toxicity Attributable to Informal Used
Lead-Acid Battery Sites. Ann Glob Health 2017; 82:686-699. [DOI: 10.1016/j.aogh.2016.10.015] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
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Lim SS, Allen K, Bhutta ZA, Dandona L, Forouzanfar MH, Fullman N, Gething PW, Goldberg EM, Hay SI, Holmberg M, Kinfu Y, Kutz MJ, Larson HJ, Liang X, Lopez AD, Lozano R, McNellan CR, Mokdad AH, Mooney MD, Naghavi M, Olsen HE, Pigott DM, Salomon JA, Vos T, Wang H, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, Abdulle AM, Abraham B, Abubakar I, Abu-Raddad LJ, Abu-Rmeileh NME, Abyu GY, Achoki T, Adebiyi AO, Adedeji IA, Afanvi KA, Afshin A, Agarwal A, Agrawal A, Kiadaliri AA, Ahmadieh H, Ahmed KY, Akanda AS, Akinyemi RO, Akinyemiju TF, Akseer N, Al-Aly Z, Alam K, Alam U, Alasfoor D, AlBuhairan FS, Aldhahri SF, Aldridge RW, Alemu ZA, Ali R, Alkerwi A, Alkhateeb MAB, Alla F, Allebeck P, Allen C, Al-Raddadi R, Alsharif U, Altirkawi KA, Martin EA, Alvis-Guzman N, Amare AT, Amberbir A, Amegah AK, Amini H, Ammar W, Amrock SM, Andersen HH, Anderson BO, Anderson GM, Antonio CAT, Anwari P, Ärnlöv J, Artaman A, Asayesh H, Asghar RJ, Atique S, Avokpaho EFGA, Awasthi A, Quintanilla BPA, Azzopardi P, Bacha U, Badawi A, Balakrishnan K, Banerjee A, Barac A, Barber R, Barker-Collo SL, Bärnighausen T, Barrero LH, Barrientos-Gutierrez T, Basu S, Bayou TA, Bazargan-Hejazi S, Beardsley J, Bedi N, Beghi E, Béjot Y, Bell ML, Bello AK, Bennett DA, Bensenor IM, Benzian H, Berhane A, Bernabé E, Bernal OA, Betsu BD, Beyene AS, Bhala N, Bhatt S, Biadgilign S, Bienhoff KA, Bikbov B, Binagwaho A, Bisanzio D, Bjertness E, Blore J, Bourne RRA, Brainin M, Brauer M, Brazinova A, Breitborde NJK, Broday DM, Brugha TS, Buchbinder R, Butt ZA, Cahill LE, Campos-Nonato IR, Campuzano JC, Carabin H, Cárdenas R, Carrero JJ, Carter A, Casey D, Caso V, Castañeda-Orjuela CA, Rivas JC, Catalá-López F, Cavalleri F, Cecílio P, Chang HY, Chang JC, Charlson FJ, Che X, Chen AZ, Chiang PPC, Chibalabala M, Chisumpa VH, Choi JYJ, Chowdhury R, Christensen H, Ciobanu LG, Cirillo M, Coates MM, Coggeshall M, Cohen AJ, Cooke GS, Cooper C, Cooper LT, Cowie BC, Crump JA, Damtew SA, Dandona R, Dargan PI, Neves JD, Davis AC, Davletov K, de Castro EF, De Leo D, Degenhardt L, Del Gobbo LC, Deribe K, Derrett S, Des Jarlais DC, Deshpande A, deVeber GA, Dey S, Dharmaratne SD, Dhillon PK, Ding EL, Dorsey ER, Doyle KE, Driscoll TR, Duan L, Dubey M, Duncan BB, Ebrahimi H, Endries AY, Ermakov SP, Erskine HE, Eshrati B, Esteghamati A, Fahimi S, Farid TA, Farinha CSES, Faro A, Farvid MS, Farzadfar F, Feigin VL, Felicio MM, Fereshtehnejad SM, Fernandes JG, Fernandes JC, Ferrari AJ, Fischer F, Fitchett JRA, Fitzmaurice C, Foigt N, Foreman K, Fowkes FGR, Franca EB, Franklin RC, Fraser M, Friedman J, Frostad J, Fürst T, Gabbe B, Garcia-Basteiro AL, Gebre T, Gebrehiwot TT, Gebremedhin AT, Gebru AA, Gessner BD, Gillum RF, Ginawi IAM, Giref AZ, Giroud M, Gishu MD, Giussani G, Godwin W, Gona P, Goodridge A, Gopalani SV, Gotay CC, Goto A, Gouda HN, Graetz N, Greenwell KF, Griswold M, Gugnani H, Guo Y, Gupta R, Gupta R, Gupta V, Gutiérrez RA, Gyawali B, Haagsma JA, Haakenstad A, Hafezi-Nejad N, Haile D, Hailu GB, Halasa YA, Hamadeh RR, Hamidi S, Hammami M, Hankey GJ, Harb HL, Haro JM, Hassanvand MS, Havmoeller R, Heredia-Pi IB, Hoek HW, Horino M, Horita N, Hosgood HD, Hoy DG, Htet AS, Hu G, Huang H, Iburg KM, Idrisov BT, Inoue M, Islami F, Jacobs TA, Jacobsen KH, Jahanmehr N, Jakovljevic MB, James P, Jansen HAFM, Javanbakht M, Jayaraman SP, Jayatilleke AU, Jee SH, Jeemon P, Jha V, Jiang Y, Jibat T, Jin Y, Jonas JB, Kabir Z, Kalkonde Y, Kamal R, Kan H, Kandel A, Karch A, Karema CK, Karimkhani C, Karunapema P, Kasaeian A, Kassebaum NJ, Kaul A, Kawakami N, Kayibanda JF, Keiyoro PN, Kemmer L, Kemp AH, Kengne AP, Keren A, Kesavachandran CN, Khader YS, Khan AR, Khan EA, Khan G, Khang YH, Khoja TAM, Khosravi A, Khubchandani J, Kieling C, Kim CI, Kim D, Kim S, Kim YJ, Kimokoti RW, Kissoon N, Kivipelto M, Knibbs LD, Kokubo Y, Kolte D, Kosen S, Kotsakis GA, Koul PA, Koyanagi A, Kravchenko M, Krueger H, Defo BK, Kuchenbecker RS, Kuipers EJ, Kulikoff XR, Kulkarni VS, Kumar GA, Kwan GF, Kyu HH, Lal A, Lal DK, Lalloo R, Lam H, Lan Q, Langan SM, Larsson A, Laryea DO, Latif AA, Leasher JL, Leigh J, Leinsalu M, Leung J, Leung R, Levi M, Li Y, Li Y, Lind M, Linn S, Lipshultz SE, Liu PY, Liu S, Liu Y, Lloyd BK, Lo LT, Logroscino G, Lotufo PA, Lucas RM, Lunevicius R, El Razek MMA, Magis-Rodriguez C, Mahdavi M, Majdan M, Majeed A, Malekzadeh R, Malta DC, Mapoma CC, Margolis DJ, Martin RV, Martinez-Raga J, Masiye F, Mason-Jones AJ, Massano J, Matzopoulos R, Mayosi BM, McGrath JJ, McKee M, Meaney PA, Mehari A, Mekonnen AB, Melaku YA, Memiah P, Memish ZA, Mendoza W, Mensink GBM, Meretoja A, Meretoja TJ, Mesfin YM, Mhimbira FA, Micha R, Miller TR, Mills EJ, Mirarefin M, Misganaw A, Mitchell PB, Mock CN, Mohammadi A, Mohammed S, Monasta L, de la Cruz Monis J, Hernandez JCM, Montico M, Moradi-Lakeh M, Morawska L, Mori R, Mueller UO, Murdoch ME, Murimira B, Murray J, Murthy GVS, Murthy S, Musa KI, Nachega JB, Nagel G, Naidoo KS, Naldi L, Nangia V, Neal B, Nejjari C, Newton CR, Newton JN, Ngalesoni FN, Nguhiu P, Nguyen G, Le Nguyen Q, Nisar MI, Pete PMN, Nolte S, Nomura M, Norheim OF, Norrving B, Obermeyer CM, Ogbo FA, Oh IH, Oladimeji O, Olivares PR, Olusanya BO, Olusanya JO, Opio JN, Oren E, Ortiz A, Osborne RH, Ota E, Owolabi MO, PA M, Park EK, Park HY, Parry CD, Parsaeian M, Patel T, Patel V, Caicedo AJP, Patil ST, Patten SB, Patton GC, Paudel D, Pedro JM, Pereira DM, Perico N, Pesudovs K, Petzold M, Phillips MR, Piel FB, Pillay JD, Pinho C, Pishgar F, Polinder S, Poulton RG, Pourmalek F, Qorbani M, Rabiee RHS, Radfar A, Rahimi-Movaghar V, Rahman M, Rahman MHU, Rahman SU, Rai RK, Rajsic S, Raju M, Ram U, Rana SM, Ranabhat CL, Ranganathan K, Rao PC, Refaat AH, Reitsma MB, Remuzzi G, Resnikoff S, Ribeiro AL, Blancas MJR, Roba HS, Roberts B, Rodriguez A, Rojas-Rueda D, Ronfani L, Roshandel G, Roth GA, Rothenbacher D, Roy A, Roy N, Sackey BB, Sagar R, Saleh MM, Sanabria JR, Santos JV, Santomauro DF, Santos IS, Sarmiento-Suarez R, Sartorius B, Satpathy M, Savic M, Sawhney M, Sawyer SM, Schmidhuber J, Schmidt MI, Schneider IJC, Schutte AE, Schwebel DC, Seedat S, Sepanlou SG, Servan-Mori EE, Shackelford K, Shaheen A, Shaikh MA, Levy TS, Sharma R, She J, Sheikhbahaei S, Shen J, Sheth KN, Shey M, Shi P, Shibuya K, Shigematsu M, Shin MJ, Shiri R, Shishani K, Shiue I, Sigfusdottir ID, Silpakit N, Silva DAS, Silverberg JI, Simard EP, Sindi S, Singh A, Singh GM, Singh JA, Singh OP, Singh PK, Skirbekk V, Sligar A, Soneji S, Søreide K, Sorensen RJD, Soriano JB, Soshnikov S, Sposato LA, Sreeramareddy CT, Stahl HC, Stanaway JD, Stathopoulou V, Steckling N, Steel N, Stein DJ, Steiner C, Stöckl H, Stranges S, Strong M, Sun J, Sunguya BF, Sur P, Swaminathan S, Sykes BL, Szoeke CEI, Tabarés-Seisdedos R, Tabb KM, Talongwa RT, Tarawneh MR, Tavakkoli M, Taye B, Taylor HR, Tedla BA, Tefera W, Tegegne TK, Tekle DY, Shifa GT, Terkawi AS, Tessema GA, Thakur JS, Thomson AJ, Thorne-Lyman AL, Thrift AG, Thurston GD, Tillmann T, Tobe-Gai R, Tonelli M, Topor-Madry R, Topouzis F, Tran BX, Truelsen T, Dimbuene ZT, Tura AK, Tuzcu EM, Tyrovolas S, Ukwaja KN, Undurraga EA, Uneke CJ, Uthman OA, van Donkelaar A, Varakin YY, Vasankari T, Vasconcelos AMN, Veerman JL, Venketasubramanian N, Verma RK, Violante FS, Vlassov VV, Volkow P, Vollset SE, Wagner GR, Wallin MT, Wang L, Wanga V, Watkins DA, Weichenthal S, Weiderpass E, Weintraub RG, Weiss DJ, Werdecker A, Westerman R, Whiteford HA, Wilkinson JD, Wiysonge CS, Wolfe CDA, Wolfe I, Won S, Woolf AD, Workie SB, Wubshet M, Xu G, Yadav AK, Yakob B, Yalew AZ, Yan LL, Yano Y, Yaseri M, Ye P, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Yu C, Zaidi Z, El Sayed Zaki M, Zambrana-Torrelio C, Zapata T, Zegeye EA, Zhao Y, Zhou M, Zodpey S, Zonies D, Murray CJL. Measuring the health-related Sustainable Development Goals in 188 countries: a baseline analysis from the Global Burden of Disease Study 2015. Lancet 2016; 388:1813-1850. [PMID: 27665228 PMCID: PMC5055583 DOI: 10.1016/s0140-6736(16)31467-2] [Citation(s) in RCA: 250] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2016] [Revised: 08/13/2016] [Accepted: 08/16/2016] [Indexed: 02/05/2023]
Abstract
BACKGROUND In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). METHODS We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. FINDINGS In 2015, the median health-related SDG index was 59·3 (95% uncertainty interval 56·8-61·8) and varied widely by country, ranging from 85·5 (84·2-86·5) in Iceland to 20·4 (15·4-24·9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r2=0·88) and the MDG index (r2=0·92), whereas the non-MDG index had a weaker relation with SDI (r2=0·79). Between 2000 and 2015, the health-related SDG index improved by a median of 7·9 (IQR 5·0-10·4), and gains on the MDG index (a median change of 10·0 [6·7-13·1]) exceeded that of the non-MDG index (a median change of 5·5 [2·1-8·9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. INTERPRETATION GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs. FUNDING Bill & Melinda Gates Foundation.
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Wang H, Naghavi M, Allen C, Barber RM, Bhutta ZA, Carter A, Casey DC, Charlson FJ, Chen AZ, Coates MM, Coggeshall M, Dandona L, Dicker DJ, Erskine HE, Ferrari AJ, Fitzmaurice C, Foreman K, Forouzanfar MH, Fraser MS, Fullman N, Gething PW, Goldberg EM, Graetz N, Haagsma JA, Hay SI, Huynh C, Johnson CO, Kassebaum NJ, Kinfu Y, Kulikoff XR, Kutz M, Kyu HH, Larson HJ, Leung J, Liang X, Lim SS, Lind M, Lozano R, Marquez N, Mensah GA, Mikesell J, Mokdad AH, Mooney MD, Nguyen G, Nsoesie E, Pigott DM, Pinho C, Roth GA, Salomon JA, Sandar L, Silpakit N, Sligar A, Sorensen RJD, Stanaway J, Steiner C, Teeple S, Thomas BA, Troeger C, VanderZanden A, Vollset SE, Wanga V, Whiteford HA, Wolock T, Zoeckler L, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, Abera SF, Abreu DMX, Abu-Raddad LJ, Abyu GY, Achoki T, Adelekan AL, Ademi Z, Adou AK, Adsuar JC, Afanvi KA, Afshin A, Agardh EE, Agarwal A, Agrawal A, Kiadaliri AA, Ajala ON, Akanda AS, Akinyemi RO, Akinyemiju TF, Akseer N, Lami FHA, Alabed S, Al-Aly Z, Alam K, Alam NKM, Alasfoor D, Aldhahri SF, Aldridge RW, Alegretti MA, Aleman AV, Alemu ZA, Alexander LT, Alhabib S, Ali R, Alkerwi A, Alla F, Allebeck P, Al-Raddadi R, Alsharif U, Altirkawi KA, Martin EA, Alvis-Guzman N, Amare AT, Amegah AK, Ameh EA, Amini H, Ammar W, Amrock SM, Andersen HH, Anderson BO, Anderson GM, Antonio CAT, Aregay AF, Ärnlöv J, Arsenijevic VSA, Artaman A, Asayesh H, Asghar RJ, Atique S, Avokpaho EFGA, Awasthi A, Azzopardi P, Bacha U, Badawi A, Bahit MC, Balakrishnan K, Banerjee A, Barac A, Barker-Collo SL, Bärnighausen T, Barregard L, Barrero LH, Basu A, Basu S, Bayou YT, Bazargan-Hejazi S, Beardsley J, Bedi N, Beghi E, Belay HA, Bell B, Bell ML, Bello AK, Bennett DA, Bensenor IM, Berhane A, Bernabé E, Betsu BD, Beyene AS, Bhala N, Bhalla A, Biadgilign S, Bikbov B, Abdulhak AAB, Biroscak BJ, Biryukov S, Bjertness E, Blore JD, Blosser CD, Bohensky MA, Borschmann R, Bose D, Bourne RRA, Brainin M, Brayne CEG, Brazinova A, Breitborde NJK, Brenner H, Brewer JD, Brown A, Brown J, Brugha TS, Buckle GC, Butt ZA, Calabria B, Campos-Nonato IR, Campuzano JC, Carapetis JR, Cárdenas R, Carpenter DO, Carrero JJ, Castañeda-Orjuela CA, Rivas JC, Catalá-López F, Cavalleri F, Cercy K, Cerda J, Chen W, Chew A, Chiang PPC, Chibalabala M, Chibueze CE, Chimed-Ochir O, Chisumpa VH, Choi JYJ, Chowdhury R, Christensen H, Christopher DJ, Ciobanu LG, Cirillo M, Cohen AJ, Colistro V, Colomar M, Colquhoun SM, Cooper C, Cooper LT, Cortinovis M, Cowie BC, Crump JA, Damsere-Derry J, Danawi H, Dandona R, Daoud F, Darby SC, Dargan PI, das Neves J, Davey G, Davis AC, Davitoiu DV, de Castro EF, de Jager P, Leo DD, Degenhardt L, Dellavalle RP, Deribe K, Deribew A, Dharmaratne SD, Dhillon PK, Diaz-Torné C, Ding EL, dos Santos KPB, Dossou E, Driscoll TR, Duan L, Dubey M, Duncan BB, Ellenbogen RG, Ellingsen CL, Elyazar I, Endries AY, Ermakov SP, Eshrati B, Esteghamati A, Estep K, Faghmous IDA, Fahimi S, Faraon EJA, Farid TA, Farinha CSES, Faro A, Farvid MS, Farzadfar F, Feigin VL, Fereshtehnejad SM, Fernandes JG, Fernandes JC, Fischer F, Fitchett JRA, Flaxman A, Foigt N, Fowkes FGR, Franca EB, Franklin RC, Friedman J, Frostad J, Fürst T, Futran ND, Gall SL, Gambashidze K, Gamkrelidze A, Ganguly P, Gankpé FG, Gebre T, Gebrehiwot TT, Gebremedhin AT, Gebru AA, Geleijnse JM, Gessner BD, Ghoshal AG, Gibney KB, Gillum RF, Gilmour S, Giref AZ, Giroud M, Gishu MD, Giussani G, Glaser E, Godwin WW, Gomez-Dantes H, Gona P, Goodridge A, Gopalani SV, Gosselin RA, Gotay CC, Goto A, Gouda HN, Greaves F, Gugnani HC, Gupta R, Gupta R, Gupta V, Gutiérrez RA, Hafezi-Nejad N, Haile D, Hailu AD, Hailu GB, Halasa YA, Hamadeh RR, Hamidi S, Hancock J, Handal AJ, Hankey GJ, Hao Y, Harb HL, Harikrishnan S, Haro JM, Havmoeller R, Heckbert SR, Heredia-Pi IB, Heydarpour P, Hilderink HBM, Hoek HW, Hogg RS, Horino M, Horita N, Hosgood HD, Hotez PJ, Hoy DG, Hsairi M, Htet AS, Htike MMT, Hu G, Huang C, Huang H, Huiart L, Husseini A, Huybrechts I, Huynh G, Iburg KM, Innos K, Inoue M, Iyer VJ, Jacobs TA, Jacobsen KH, Jahanmehr N, Jakovljevic MB, James P, Javanbakht M, Jayaraman SP, Jayatilleke AU, Jeemon P, Jensen PN, Jha V, Jiang G, Jiang Y, Jibat T, Jimenez-Corona A, Jonas JB, Joshi TK, Kabir Z, Kamal R, Kan H, Kant S, Karch A, Karema CK, Karimkhani C, Karletsos D, Karthikeyan G, Kasaeian A, Katibeh M, Kaul A, Kawakami N, Kayibanda JF, Keiyoro PN, Kemmer L, Kemp AH, Kengne AP, Keren A, Kereselidze M, Kesavachandran CN, Khader YS, Khalil IA, Khan AR, Khan EA, Khang YH, Khera S, Khoja TAM, Kieling C, Kim D, Kim YJ, Kissela BM, Kissoon N, Knibbs LD, Knudsen AK, Kokubo Y, Kolte D, Kopec JA, Kosen S, Koul PA, Koyanagi A, Krog NH, Defo BK, Bicer BK, Kudom AA, Kuipers EJ, Kulkarni VS, Kumar GA, Kwan GF, Lal A, Lal DK, Lalloo R, Lallukka T, Lam H, Lam JO, Langan SM, Lansingh VC, Larsson A, Laryea DO, Latif AA, Lawrynowicz AEB, Leigh J, Levi M, Li Y, Lindsay MP, Lipshultz SE, Liu PY, Liu S, Liu Y, Lo LT, Logroscino G, Lotufo PA, Lucas RM, Lunevicius R, Lyons RA, Ma S, Machado VMP, Mackay MT, MacLachlan JH, Razek HMAE, Magdy M, Razek AE, Majdan M, Majeed A, Malekzadeh R, Manamo WAA, Mandisarisa J, Mangalam S, Mapoma CC, Marcenes W, Margolis DJ, Martin GR, Martinez-Raga J, Marzan MB, Masiye F, Mason-Jones AJ, Massano J, Matzopoulos R, Mayosi BM, McGarvey ST, McGrath JJ, McKee M, McMahon BJ, Meaney PA, Mehari A, Mehndiratta MM, Mejia-Rodriguez F, Mekonnen AB, Melaku YA, Memiah P, Memish ZA, Mendoza W, Meretoja A, Meretoja TJ, Mhimbira FA, Micha R, Millear A, Miller TR, Mirarefin M, Misganaw A, Mock CN, Mohammad KA, Mohammadi A, Mohammed S, Mohan V, Mola GLD, Monasta L, Hernandez JCM, Montero P, Montico M, Montine TJ, Moradi-Lakeh M, Morawska L, Morgan K, Mori R, Mozaffarian D, Mueller UO, Murthy GVS, Murthy S, Musa KI, Nachega JB, Nagel G, Naidoo KS, Naik N, Naldi L, Nangia V, Nash D, Nejjari C, Neupane S, Newton CR, Newton JN, Ng M, Ngalesoni FN, de Dieu Ngirabega J, Nguyen QL, Nisar MI, Pete PMN, Nomura M, Norheim OF, Norman PE, Norrving B, Nyakarahuka L, Ogbo FA, Ohkubo T, Ojelabi FA, Olivares PR, Olusanya BO, Olusanya JO, Opio JN, Oren E, Ortiz A, Osman M, Ota E, Ozdemir R, PA M, Pain A, Pandian JD, Pant PR, Papachristou C, Park EK, Park JH, Parry CD, Parsaeian M, Caicedo AJP, Patten SB, Patton GC, Paul VK, Pearce N, Pedro JM, Stokic LP, Pereira DM, Perico N, Pesudovs K, Petzold M, Phillips MR, Piel FB, Pillay JD, Plass D, Platts-Mills JA, Polinder S, Pope CA, Popova S, Poulton RG, Pourmalek F, Prabhakaran D, Qorbani M, Quame-Amaglo J, Quistberg DA, Rafay A, Rahimi K, Rahimi-Movaghar V, Rahman M, Rahman MHU, Rahman SU, Rai RK, Rajavi Z, Rajsic S, Raju M, Rakovac I, Rana SM, Ranabhat CL, Rangaswamy T, Rao P, Rao SR, Refaat AH, Rehm J, Reitsma MB, Remuzzi G, Resnikoff S, Ribeiro AL, Ricci S, Blancas MJR, Roberts B, Roca A, Rojas-Rueda D, Ronfani L, Roshandel G, Rothenbacher D, Roy A, Roy NK, Ruhago GM, Sagar R, Saha S, Sahathevan R, Saleh MM, Sanabria JR, Sanchez-Niño MD, Sanchez-Riera L, Santos IS, Sarmiento-Suarez R, Sartorius B, Satpathy M, Savic M, Sawhney M, Schaub MP, Schmidt MI, Schneider IJC, Schöttker B, Schutte AE, Schwebel DC, Seedat S, Sepanlou SG, Servan-Mori EE, Shackelford KA, Shaddick G, Shaheen A, Shahraz S, Shaikh MA, Shakh-Nazarova M, Sharma R, She J, Sheikhbahaei S, Shen J, Shen Z, Shepard DS, Sheth KN, Shetty BP, Shi P, Shibuya K, Shin MJ, Shiri R, Shiue I, Shrime MG, Sigfusdottir ID, Silberberg DH, Silva DAS, Silveira DGA, Silverberg JI, Simard EP, Singh A, Singh GM, Singh JA, Singh OP, Singh PK, Singh V, Soneji S, Søreide K, Soriano JB, Sposato LA, Sreeramareddy CT, Stathopoulou V, Stein DJ, Stein MB, Stranges S, Stroumpoulis K, Sunguya BF, Sur P, Swaminathan S, Sykes BL, Szoeke CEI, Tabarés-Seisdedos R, Tabb KM, Takahashi K, Takala JS, Talongwa RT, Tandon N, Tavakkoli M, Taye B, Taylor HR, Ao BJT, Tedla BA, Tefera WM, Have MT, Terkawi AS, Tesfay FH, Tessema GA, Thomson AJ, Thorne-Lyman AL, Thrift AG, Thurston GD, Tillmann T, Tirschwell DL, Tonelli M, Topor-Madry R, Topouzis F, Towbin JA, Traebert J, Tran BX, Truelsen T, Trujillo U, Tura AK, Tuzcu EM, Uchendu US, Ukwaja KN, Undurraga EA, Uthman OA, Dingenen RV, van Donkelaar A, Vasankari T, Vasconcelos AMN, Venketasubramanian N, Vidavalur R, Vijayakumar L, Villalpando S, Violante FS, Vlassov VV, Wagner JA, Wagner GR, Wallin MT, Wang L, Watkins DA, Weichenthal S, Weiderpass E, Weintraub RG, Werdecker A, Westerman R, White RA, Wijeratne T, Wilkinson JD, Williams HC, Wiysonge CS, Woldeyohannes SM, Wolfe CDA, Won S, Wong JQ, Woolf AD, Xavier D, Xiao Q, Xu G, Yakob B, Yalew AZ, Yan LL, Yano Y, Yaseri M, Ye P, Yebyo HG, Yip P, Yirsaw BD, Yonemoto N, Yonga G, Younis MZ, Yu S, Zaidi Z, Zaki MES, Zannad F, Zavala DE, Zeeb H, Zeleke BM, Zhang H, Zodpey S, Zonies D, Zuhlke LJ, Vos T, Lopez AD, Murray CJL. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388:1459-1544. [PMID: 27733281 PMCID: PMC5388903 DOI: 10.1016/s0140-6736(16)31012-1] [Citation(s) in RCA: 4031] [Impact Index Per Article: 503.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. METHODS We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). FINDINGS Globally, life expectancy from birth increased from 61·7 years (95% uncertainty interval 61·4-61·9) in 1980 to 71·8 years (71·5-72·2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11·3 years (3·7-17·4), to 62·6 years (56·5-70·2). Total deaths increased by 4·1% (2·6-5·6) from 2005 to 2015, rising to 55·8 million (54·9 million to 56·6 million) in 2015, but age-standardised death rates fell by 17·0% (15·8-18·1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14·1% (12·6-16·0) to 39·8 million (39·2 million to 40·5 million) in 2015, whereas age-standardised rates decreased by 13·1% (11·9-14·3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42·1%, 39·1-44·6), malaria (43·1%, 34·7-51·8), neonatal preterm birth complications (29·8%, 24·8-34·9), and maternal disorders (29·1%, 19·3-37·1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. INTERPRETATION At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. FUNDING Bill & Melinda Gates Foundation.
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Kassebaum NJ, Arora M, Barber RM, Bhutta ZA, Brown J, Carter A, Casey DC, Charlson FJ, Coates MM, Coggeshall M, Cornaby L, Dandona L, Dicker DJ, Erskine HE, Ferrari AJ, Fitzmaurice C, Foreman K, Forouzanfar MH, Fullman N, Gething PW, Goldberg EM, Graetz N, Haagsma JA, Hay SI, Johnson CO, Kemmer L, Khalil IA, Kinfu Y, Kutz MJ, Kyu HH, Leung J, Liang X, Lim SS, Lozano R, Mensah GA, Mikesell J, Mokdad AH, Mooney MD, Naghavi M, Nguyen G, Nsoesie E, Pigott DM, Pinho C, Rankin Z, Reinig N, Salomon JA, Sandar L, Smith A, Sorensen RJD, Stanaway J, Steiner C, Teeple S, Troeger C, Truelsen T, VanderZanden A, Wagner JA, Wanga V, Whiteford HA, Zhou M, Zoeckler L, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, Abraham B, Abubakar I, Abu-Raddad LJ, Abu-Rmeileh NME, Achoki T, Ackerman IN, Adebiyi AO, Adedeji IA, Adsuar JC, Afanvi KA, Afshin A, Agardh EE, Agarwal A, Agarwal SK, Ahmed MB, Kiadaliri AA, Ahmadieh H, Akseer N, Al-Aly Z, Alam K, Alam NKM, Aldhahri SF, Alegretti MA, Aleman AV, Alemu ZA, Alexander LT, Ali R, Alkerwi A, Alla F, Allebeck P, Allen C, Alsharif U, Altirkawi KA, Martin EA, Alvis-Guzman N, Amare AT, Amberbir A, Amegah AK, Amini H, Ammar W, Amrock SM, Anderson GM, Anderson BO, Antonio CAT, Anwari P, Ärnlöv J, Arsenijevic VSA, Artaman A, Asayesh H, Asghar RJ, Avokpaho EFGA, Awasthi A, Quintanilla BPA, Azzopardi P, Bacha U, Badawi A, Balakrishnan K, Banerjee A, Barac A, Barker-Collo SL, Bärnighausen T, Barregard L, Barrero LH, Basu S, Bayou TA, Beardsley J, Bedi N, Beghi E, Bell B, Bell ML, Benjet C, Bennett DA, Bensenor IM, Berhane A, Bernabé E, Betsu BD, Beyene AS, Bhala N, Bhansali A, Bhatt S, Biadgilign S, Bienhoff K, Bikbov B, Abdulhak AAB, Biryukov S, Bisanzio D, Bjertness E, Blore JD, Borschmann R, Boufous S, Bourne RRA, Brainin M, Brazinova A, Breitborde NJK, Brugha TS, Buchbinder R, Buckle GC, Butt ZA, Calabria B, Campos-Nonato IR, Campuzano JC, Carabin H, Carapetis JR, Cárdenas R, Carrero JJ, Castañeda-Orjuela CA, Rivas JC, Catalá-López F, Cavalleri F, Chang JC, Chiang PPC, Chibalabala M, Chibueze CE, Chisumpa VH, Choi JYJ, Choudhury L, Christensen H, Ciobanu LG, Colistro V, Colomar M, Colquhoun SM, Cortinovis M, Crump JA, Damasceno A, Dandona R, Dargan PI, das Neves J, Davey G, Davis AC, Leo DD, Degenhardt L, Gobbo LCD, Derrett S, Jarlais DCD, deVeber GA, Dharmaratne SD, Dhillon PK, Ding EL, Doyle KE, Driscoll TR, Duan L, Dubey M, Duncan BB, Ebrahimi H, Ellenbogen RG, Elyazar I, Endries AY, Ermakov SP, Eshrati B, Esteghamati A, Estep K, Fahimi S, Farid TA, Farinha CSES, Faro A, Farvid MS, Farzadfar F, Feigin VL, Fereshtehnejad SM, Fernandes JG, Fernandes JC, Fischer F, Fitchett JRA, Foigt N, Fowkes FGR, Franklin RC, Friedman J, Frostad J, Fürst T, Futran ND, Gabbe B, Gankpé FG, Garcia-Basteiro AL, Gebrehiwot TT, Gebremedhin AT, Geleijnse JM, Gibney KB, Gillum RF, Ginawi IAM, Giref AZ, Giroud M, Gishu MD, Giussani G, Godwin WW, Gomez-Dantes H, Gona P, Goodridge A, Gopalani SV, Gotay CC, Goto A, Gouda HN, Gugnani H, Guo Y, Gupta R, Gupta R, Gupta V, Gutiérrez RA, Hafezi-Nejad N, Haile D, Hailu AD, Hailu GB, Halasa YA, Hamadeh RR, Hamidi S, Hammami M, Handal AJ, Hankey GJ, Harb HL, Harikrishnan S, Haro JM, Hassanvand MS, Hassen TA, Havmoeller R, Hay RJ, Hedayati MT, Heredia-Pi IB, Heydarpour P, Hoek HW, Hoffman DJ, Horino M, Horita N, Hosgood HD, Hoy DG, Hsairi M, Huang H, Huang JJ, Iburg KM, Idrisov BT, Innos K, Inoue M, Jacobsen KH, Jauregui A, Jayatilleke AU, Jeemon P, Jha V, Jiang G, Jiang Y, Jibat T, Jimenez-Corona A, Jin Y, Jonas JB, Kabir Z, Kajungu DK, Kalkonde Y, Kamal R, Kan H, Kandel A, Karch A, Karema CK, Karimkhani C, Kasaeian A, Katibeh M, Kaul A, Kawakami N, Kazi DS, Keiyoro PN, Kemp AH, Kengne AP, Keren A, Kesavachandran CN, Khader YS, Khan AR, Khan EA, Khang YH, Khoja TAM, Khubchandani J, Kieling C, Kim CI, Kim D, Kim YJ, Kissoon N, Kivipelto M, Knibbs LD, Knudsen AK, Kokubo Y, Kolte D, Kopec JA, Koul PA, Koyanagi A, Defo BK, Kuchenbecker RS, Bicer BK, Kuipers EJ, Kumar GA, Kwan GF, Lalloo R, Lallukka T, Larsson A, Latif AA, Lavados PM, Lawrynowicz AEB, Leasher JL, Leigh J, Leung R, Li Y, Li Y, Lipshultz SE, Liu PY, Liu Y, Lloyd BK, Logroscino G, Looker KJ, Lotufo PA, Lucas RM, Lunevicius R, Lyons RA, Razek HMAE, Mahdavi M, Majdan M, Majeed A, Malekzadeh R, Malta DC, Marcenes W, Martinez-Raga J, Masiye F, Mason-Jones AJ, Matzopoulos R, Mayosi BM, McGrath JJ, McKee M, Meaney PA, Mehari A, Melaku YA, Memiah P, Memish ZA, Mendoza W, Meretoja A, Meretoja TJ, Mesfin YM, Mhimbira FA, Millear A, Miller TR, Mills EJ, Mirarefin M, Mirrakhimov EM, Mitchell PB, Mock CN, Mohammad KA, Mohammadi A, Mohammed S, Monasta L, Hernandez JCM, Montico M, Moradi-Lakeh M, Mori R, Mueller UO, Mumford JE, Murdoch ME, Murthy GVS, Nachega JB, Naheed A, Naldi L, Nangia V, Newton JN, Ng M, Ngalesoni FN, Nguyen QL, Nisar MI, Pete PMN, Nolla JM, Norheim OF, Norman RE, Norrving B, Obermeyer CM, Ogbo FA, Oh IH, Oladimeji O, Olivares PR, Olusanya BO, Olusanya JO, Oren E, Ortiz A, Ota E, Oyekale AS, PA M, Park EK, Parsaeian M, Patten SB, Patton GC, Pedro JM, Pereira DM, Perico N, Pesudovs K, Petzold M, Phillips MR, Piel FB, Pillay JD, Pishgar F, Plass D, Polinder S, Popova S, Poulton RG, Pourmalek F, Prasad NM, Qorbani M, Rabiee RHS, Radfar A, Rafay A, Rahimi K, Rahimi-Movaghar V, Rahman M, Rahman MHU, Rahman SU, Rai D, Rai RK, Rajsic S, Raju M, Ram U, Ranganathan K, Refaat AH, Reitsma MB, Remuzzi G, Resnikoff S, Reynolds A, Ribeiro AL, Ricci S, Roba HS, Rojas-Rueda D, Ronfani L, Roshandel G, Roth GA, Roy A, Sackey BB, Sagar R, Sanabria JR, Sanchez-Niño MD, Santos IS, Santos JV, Sarmiento-Suarez R, Sartorius B, Satpathy M, Savic M, Sawhney M, Schmidt MI, Schneider IJC, Schutte AE, Schwebel DC, Seedat S, Sepanlou SG, Servan-Mori EE, Shahraz S, Shaikh MA, Sharma R, She J, Sheikhbahaei S, Shen J, Sheth KN, Shibuya K, Shigematsu M, Shin MJ, Shiri R, Sigfusdottir ID, Silva DAS, Silverberg JI, Simard EP, Singh A, Singh JA, Singh PK, Skirbekk V, Skogen JC, Soljak M, Søreide K, Sorensen RJD, Sreeramareddy CT, Stathopoulou V, Steel N, Stein DJ, Stein MB, Steiner TJ, Stovner LJ, Stranges S, Stroumpoulis K, Sunguya BF, Sur PJ, Swaminathan S, Sykes BL, Szoeke CEI, Tabarés-Seisdedos R, Tandon N, Tanne D, Tavakkoli M, Taye B, Taylor HR, Ao BJT, Tegegne TK, Tekle DY, Terkawi AS, Tessema GA, Thakur JS, Thomson AJ, Thorne-Lyman AL, Thrift AG, Thurston GD, Tobe-Gai R, Tonelli M, Topor-Madry R, Topouzis F, Tran BX, Truelsen T, Dimbuene ZT, Tsilimbaris M, Tura AK, Tuzcu EM, Tyrovolas S, Ukwaja KN, Undurraga EA, Uneke CJ, Uthman OA, van Gool CH, van Os J, Vasankari T, Vasconcelos AMN, Venketasubramanian N, Violante FS, Vlassov VV, Vollset SE, Wagner GR, Wallin MT, Wang L, Weichenthal S, Weiderpass E, Weintraub RG, Werdecker A, Westerman R, Wijeratne T, Wilkinson JD, Williams HC, Wiysonge CS, Woldeyohannes SM, Wolfe CDA, Won S, Xu G, Yadav AK, Yakob B, Yan LL, Yano Y, Yaseri M, Ye P, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Yu C, Zaidi Z, Zaki MES, Zeeb H, Zodpey S, Zonies D, Zuhlke LJ, Vos T, Lopez AD, Murray CJL. Global, regional, and national disability-adjusted life-years (DALYs) for 315 diseases and injuries and healthy life expectancy (HALE), 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 2016; 388:1603-1658. [PMID: 27733283 PMCID: PMC5388857 DOI: 10.1016/s0140-6736(16)31460-x] [Citation(s) in RCA: 1387] [Impact Index Per Article: 173.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Revised: 08/11/2016] [Accepted: 08/16/2016] [Indexed: 12/30/2022]
Abstract
BACKGROUND Healthy life expectancy (HALE) and disability-adjusted life-years (DALYs) provide summary measures of health across geographies and time that can inform assessments of epidemiological patterns and health system performance, help to prioritise investments in research and development, and monitor progress toward the Sustainable Development Goals (SDGs). We aimed to provide updated HALE and DALYs for geographies worldwide and evaluate how disease burden changes with development. METHODS We used results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015. We calculated DALYs by summing years of life lost (YLLs) and years of life lived with disability (YLDs) for each geography, age group, sex, and year. We estimated HALE using the Sullivan method, which draws from age-specific death rates and YLDs per capita. We then assessed how observed levels of DALYs and HALE differed from expected trends calculated with the Socio-demographic Index (SDI), a composite indicator constructed from measures of income per capita, average years of schooling, and total fertility rate. FINDINGS Total global DALYs remained largely unchanged from 1990 to 2015, with decreases in communicable, neonatal, maternal, and nutritional (Group 1) disease DALYs offset by increased DALYs due to non-communicable diseases (NCDs). Much of this epidemiological transition was caused by changes in population growth and ageing, but it was accelerated by widespread improvements in SDI that also correlated strongly with the increasing importance of NCDs. Both total DALYs and age-standardised DALY rates due to most Group 1 causes significantly decreased by 2015, and although total burden climbed for the majority of NCDs, age-standardised DALY rates due to NCDs declined. Nonetheless, age-standardised DALY rates due to several high-burden NCDs (including osteoarthritis, drug use disorders, depression, diabetes, congenital birth defects, and skin, oral, and sense organ diseases) either increased or remained unchanged, leading to increases in their relative ranking in many geographies. From 2005 to 2015, HALE at birth increased by an average of 2·9 years (95% uncertainty interval 2·9-3·0) for men and 3·5 years (3·4-3·7) for women, while HALE at age 65 years improved by 0·85 years (0·78-0·92) and 1·2 years (1·1-1·3), respectively. Rising SDI was associated with consistently higher HALE and a somewhat smaller proportion of life spent with functional health loss; however, rising SDI was related to increases in total disability. Many countries and territories in central America and eastern sub-Saharan Africa had increasingly lower rates of disease burden than expected given their SDI. At the same time, a subset of geographies recorded a growing gap between observed and expected levels of DALYs, a trend driven mainly by rising burden due to war, interpersonal violence, and various NCDs. INTERPRETATION Health is improving globally, but this means more populations are spending more time with functional health loss, an absolute expansion of morbidity. The proportion of life spent in ill health decreases somewhat with increasing SDI, a relative compression of morbidity, which supports continued efforts to elevate personal income, improve education, and limit fertility. Our analysis of DALYs and HALE and their relationship to SDI represents a robust framework on which to benchmark geography-specific health performance and SDG progress. Country-specific drivers of disease burden, particularly for causes with higher-than-expected DALYs, should inform financial and research investments, prevention efforts, health policies, and health system improvement initiatives for all countries along the development continuum. FUNDING Bill & Melinda Gates Foundation.
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Archer-Nicholls S, Carter E, Kumar R, Xiao Q, Liu Y, Frostad J, Forouzanfar MH, Cohen A, Brauer M, Baumgartner J, Wiedinmyer C. The Regional Impacts of Cooking and Heating Emissions on Ambient Air Quality and Disease Burden in China. Environ Sci Technol 2016; 50:9416-23. [PMID: 27479733 DOI: 10.1021/acs.est.6b02533] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Exposure to air pollution is a major risk factor globally and particularly in Asia. A large portion of air pollutants result from residential combustion of solid biomass and coal fuel for cooking and heating. This study presents a regional modeling sensitivity analysis to estimate the impact of residential emissions from cooking and heating activities on the burden of disease at a provincial level in China. Model surface PM2.5 fields are shown to compare well when evaluated against surface air quality measurements. Scenarios run without residential sector and residential heating emissions are used in conjunction with the Global Burden of Disease 2013 framework to calculate the proportion of deaths and disability adjusted life years attributable to PM2.5 exposure from residential emissions. Overall, we estimate that 341 000 (306 000-370 000; 95% confidence interval) premature deaths in China are attributable to residential combustion emissions, approximately a third of the deaths attributable to all ambient PM2.5 pollution, with 159 000 (142 000-172 000) and 182 000 (163 000-197 000) premature deaths from heating and cooking emissions, respectively. Our findings emphasize the need to mitigate emissions from both residential heating and cooking sources to reduce the health impacts of ambient air pollution in China.
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Affiliation(s)
- Scott Archer-Nicholls
- National Center for Atmospheric Research (NCAR), Boulder, Colorado 80301, United States
| | - Ellison Carter
- Institute on the Environment, University of Minnesota , St. Paul, Minnesota United States
| | - Rajesh Kumar
- National Center for Atmospheric Research (NCAR), Boulder, Colorado 80301, United States
| | - Qingyang Xiao
- Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States
| | - Yang Liu
- Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington , Seattle, Washington United States
| | - Mohammad H Forouzanfar
- Institute for Health Metrics and Evaluation, University of Washington , Seattle, Washington United States
| | - Aaron Cohen
- Health Effects Institute, Suite 500, 101 Federal Street Boston, Massachusetts 02110, United States
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia , 2206 East Mall, Vancouver, British Columbia V6T1Z3, Canada
| | - Jill Baumgartner
- Institute on the Environment, University of Minnesota , St. Paul, Minnesota United States
- Institute for Health and Social Policy and Department of Epidemiology, Biostatistics and Occupational Health, McGill University , 1130 Pine Avenue West, Montreal, Quebec H3A1A3, Canada
| | - Christine Wiedinmyer
- National Center for Atmospheric Research (NCAR), Boulder, Colorado 80301, United States
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Ericson B, Landrigan P, Taylor MP, Frostad J, Caravanos J, Keith J, Fuller R. The Global Burden of Lead Toxicity Attributable to Informal Used Lead-Acid Battery Sites. Ann Glob Health 2016. [PMID: 28283119 DOI: 10.1016/j.aogh.2016.10.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2023] Open
Abstract
BACKGROUND Prior calculations of the burden of disease from environmental lead exposure in low- and middle-income countries (LMICs) have not included estimates of the burden from lead-contaminated sites because of a lack of exposure data, resulting in an underestimation of a serious public health problem. OBJECTIVE We used publicly available statistics and detailed site assessment data to model the number of informal used lead-acid battery (ULAB) recyclers and the resulting exposures in 90 LMICs. We estimated blood lead levels (BLLs) using the US Environment Protection Agency's Integrated Exposure Uptake Biokinetic Model for Lead in Children and Adult Lead Model. Finally, we used data and algorithms generated by the World Health Organization to calculate the number of attributable disability adjusted life years (DALYs). RESULTS We estimated that there are 10,599 to 29,241 informal ULAB processing sites where human health is at risk in the 90 countries we reviewed. We further estimated that 6 to 16.8 million people are exposed at these sites and calculate a geometric mean BLL for exposed children (0-4 years of age) of 31.15 μg/dL and a geometric mean BLL for adults of 21.2 μg/dL. We calculated that these exposures resulted in 127,248 to 1,612,476 DALYs in 2013. CONCLUSIONS Informal ULAB processing is currently causing widespread lead poisoning in LMICs. There is an urgent need to identify and mitigate exposures at existing sites and to develop appropriate policy responses to minimize the creation of new sites.
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Affiliation(s)
- Bret Ericson
- Pure Earth, New York, NY; Department of Environmental Sciences, Faculty of Science and Engineering, Macquarie University, North Ryde, Sydney, Australia; City University of New York School of Public Health, New York, NY.
| | - Phillip Landrigan
- Department of Pediatrics, Mount Sinai School of Medicine, New York, NY
| | - Mark Patrick Taylor
- Department of Environmental Sciences, Faculty of Science and Engineering, Macquarie University, North Ryde, Sydney, Australia
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, Seattle, WA
| | - Jack Caravanos
- Pure Earth, New York, NY; College of Global Public Health, New York University, New York, NY
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Brauer M, Freedman G, Frostad J, van Donkelaar A, Martin RV, Dentener F, van Dingenen R, Estep K, Amini H, Apte JS, Balakrishnan K, Barregard L, Broday D, Feigin V, Ghosh S, Hopke PK, Knibbs LD, Kokubo Y, Liu Y, Ma S, Morawska L, Sangrador JLT, Shaddick G, Anderson HR, Vos T, Forouzanfar MH, Burnett RT, Cohen A. Ambient Air Pollution Exposure Estimation for the Global Burden of Disease 2013. Environ Sci Technol 2016; 50:79-88. [PMID: 26595236 DOI: 10.1021/acs.est.5b03709] [Citation(s) in RCA: 532] [Impact Index Per Article: 66.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Exposure to ambient air pollution is a major risk factor for global disease. Assessment of the impacts of air pollution on population health and evaluation of trends relative to other major risk factors requires regularly updated, accurate, spatially resolved exposure estimates. We combined satellite-based estimates, chemical transport model simulations, and ground measurements from 79 different countries to produce global estimates of annual average fine particle (PM2.5) and ozone concentrations at 0.1° × 0.1° spatial resolution for five-year intervals from 1990 to 2010 and the year 2013. These estimates were applied to assess population-weighted mean concentrations for 1990-2013 for each of 188 countries. In 2013, 87% of the world's population lived in areas exceeding the World Health Organization Air Quality Guideline of 10 μg/m(3) PM2.5 (annual average). Between 1990 and 2013, global population-weighted PM2.5 increased by 20.4% driven by trends in South Asia, Southeast Asia, and China. Decreases in population-weighted mean concentrations of PM2.5 were evident in most high income countries. Population-weighted mean concentrations of ozone increased globally by 8.9% from 1990-2013 with increases in most countries-except for modest decreases in North America, parts of Europe, and several countries in Southeast Asia.
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Affiliation(s)
- Michael Brauer
- School of Population and Public Health, The University of British Columbia , 3rd Floor-2206 East Mall, Vancouver, British Columbia V6T1Z3, Canada
| | - Greg Freedman
- Institute for Health Metrics and Evaluation, University of Washington , Seattle Washington 98195, United States
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington , Seattle Washington 98195, United States
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science, Dalhousie University , Halifax, Nova Scotia B3H 4R2, Canada
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University , Halifax, Nova Scotia B3H 4R2, Canada
| | - Frank Dentener
- European Commission, Joint Research Centre, Ispra, Italy
| | | | - Kara Estep
- Institute for Health Metrics and Evaluation, University of Washington , Seattle Washington 98195, United States
| | - Heresh Amini
- Swiss Tropical and Public Health Institute, Basel, Switzerland
| | - Joshua S Apte
- Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin , Austin Texas 78712, United States
| | - Kalpana Balakrishnan
- Department of Environmental Health Engineering, Sri Ramachandra University , Chennai, India
| | - Lars Barregard
- Department of Occupational and Environmental Health, University of Gothenburg , Gothenburg, Sweden
| | - David Broday
- Technion-Israel Institute of Technology , Civil and Environmental Engineering, Haifa, Israel
| | - Valery Feigin
- National Institute for Stroke & Applied Neurosciences, Auckland University of Technology , Aukland, New Zealand
| | - Santu Ghosh
- Department of Environmental Health Engineering, Sri Ramachandra University , Chennai, India
| | - Philip K Hopke
- Department of Chemical Engineering, Clarkson University , Potsdam, New York 13699, United States
| | - Luke D Knibbs
- School of Public Health, The University of Queensland , Brisbane, Queensland, Australia
| | - Yoshihiro Kokubo
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center , Osaka, Japan
| | - Yang Liu
- Rollins School of Public Health, Emory University , Atlanta, Georgia 30322, United States
| | - Stefan Ma
- Saw Swee Hock School of Public Health, National University of Singapore , Singapore
| | - Lidia Morawska
- School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology , Brisbane Queensland, Australia
| | | | - Gavin Shaddick
- Department of Mathematical Sciences, University of Bath , Bath, U.K
| | - H Ross Anderson
- Population Health Research Institute, St. George's University of London , London, U.K
| | - Theo Vos
- Institute for Health Metrics and Evaluation, University of Washington , Seattle Washington 98195, United States
| | - Mohammad H Forouzanfar
- Institute for Health Metrics and Evaluation, University of Washington , Seattle Washington 98195, United States
| | | | - Aaron Cohen
- Health Effects Institute , Boston, Massachusetts 02110-1817, United States
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