Millions Dead: How Do We Know and What Does It Mean? Methods Used in the Comparative Risk Assessment of Household Air Pollution
TL;DR: It is estimated that in 2010 HAP was responsible for 3.9 million premature deaths and ∼4.8% of lost healthy life years (DALYs), ranking it highest among environmental risk factors examined and one of the major risk factors of any type globally.
Abstract: In the Comparative Risk Assessment (CRA) done as part of the Global Burden of Disease project (GBD-2010), the global and regional burdens of household air pollution (HAP) due to the use of solid cookfuels, were estimated along with 60+ other risk factors. This article describes how the HAP CRA was framed; how global HAP exposures were modeled; how diseases were judged to have sufficient evidence for inclusion; and how meta-analyses and exposure-response modeling were done to estimate relative risks. We explore relationships with the other air pollution risk factors: ambient air pollution, smoking, and secondhand smoke. We conclude with sensitivity analyses to illustrate some of the major uncertainties and recommendations for future work. We estimate that in 2010 HAP was responsible for 3.9 million premature deaths and ∼4.8% of lost healthy life years (DALYs), ranking it highest among environmental risk factors examined and one of the major risk factors of any type globally.
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Mohammad H. Forouzanfar1, Lily Alexander, H. Ross Anderson, Victoria F Bachman1 +733 more•Institutions (289)
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as discussed by the authors provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.
5,668 citations
01 Jan 2016
TL;DR: The comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study 2015 was used to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational risks or clusters of risks from 1990 to 2015.
Abstract: BACKGROUND
The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context.
METHODS
We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI).
FINDINGS
Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6-58·8) of global deaths and 41·2% (39·8-42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa.
INTERPRETATION
Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden.
FUNDING
Bill & Melinda Gates Foundation.
3,920 citations
Icahn School of Medicine at Mount Sinai1, Pure Earth2, World Bank3, University of Arizona4, McGill University5, Indian Ministry of Environment and Forests6, Qatar Airways7, University of Health Sciences Antigua8, Ludwig Maximilian University of Munich9, Johns Hopkins University10, Boston College11, Chulabhorn Research Institute12, University of Maryland, College Park13, University of Ghana14, Centro Nacional de Investigaciones Cardiovasculares15, University of Chicago16, University of London17, University of Oxford18, Indian Institute of Technology Delhi19, Simon Fraser University20, Consortium of Universities for Global Health21, University of Ottawa22, Columbia University23, Stockholm Resilience Centre24, Massachusetts Institute of Technology25, University of Queensland26, University of California, Berkeley27, New York University28, National Institutes of Health29, Public Health Research Institute30, United Nations Industrial Development Organization31, Renmin University of China32
TL;DR: This book is dedicated to the memory of those who have served in the armed forces and their families during the conflicts of the twentieth century.
2,628 citations
Mohammad H. Forouzanfar1, Lily Alexander1, H. Ross Anderson2, Victoria F Bachman1 +718 more•Institutions (295)
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as mentioned in this paper provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.
1,656 citations
Health Canada1, Brigham Young University2, Imperial College London3, University of Washington4, Institute for Health Metrics and Evaluation5, Harvard University6, Research Triangle Park7, University of British Columbia8, King's College London9, University of California, Berkeley10, University of California, San Francisco11, University of Liverpool12, Fudan University13, World Health Organization14, University of Ottawa15, American Cancer Society16, Health Effects Institute17
TL;DR: A fine particulate mass–based RR model that covered the global range of exposure by integrating RR information from different combustion types that generate emissions of particulate matter is developed.
Abstract: Background: Estimating the burden of disease attributable to long-term exposure to fine particulate matter (PM2.5) in ambient air requires knowledge of both the shape and magnitude of the relative ...
1,468 citations
Cites background from "Millions Dead: How Do We Know and W..."
...Smith et al. (2014) conducted a meta-analysis of studies examining COPD and LC incidence rates among men and women exposed to air pollution from burning coal or biomass for cooking....
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References
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TL;DR: In this paper, the authors estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010.
9,324 citations
Health Canada1, Brigham Young University2, Imperial College London3, University of Washington4, Institute for Health Metrics and Evaluation5, Harvard University6, Research Triangle Park7, University of British Columbia8, King's College London9, University of California, Berkeley10, University of California, San Francisco11, University of Liverpool12, Fudan University13, World Health Organization14, University of Ottawa15, American Cancer Society16, Health Effects Institute17
TL;DR: A fine particulate mass–based RR model that covered the global range of exposure by integrating RR information from different combustion types that generate emissions of particulate matter is developed.
Abstract: Background: Estimating the burden of disease attributable to long-term exposure to fine particulate matter (PM2.5) in ambient air requires knowledge of both the shape and magnitude of the relative ...
1,468 citations
Harvard University1, University of Queensland2, Johns Hopkins University3, ICF International4, Centre for Mental Health5, Boston University6, University of Sydney7, University of Melbourne8, Imperial College London9, University of New South Wales10, University of California, San Diego11, Emory University12, University of Pennsylvania13, Autonomous University of Barcelona14, University of London15, National Institutes of Health16, French Institute of Health and Medical Research17, Medical Research Council18, Auckland University of Technology19, Federal University of São Paulo20, National Institute of Population and Social Security Research21, Howard University22, Flinders University23, Erasmus University Rotterdam24, King's College London25, Karolinska Institutet26, University of California, San Francisco27, All India Institute of Medical Sciences28, Nova Southeastern University29, University of Miami30, Swansea University31, Tehran University of Medical Sciences32, Queen Mary University of London33, Allen Institute for Brain Science34, University of Cape Town35, Columbia University36, Watford General Hospital37, Centro Studi GISED38, University of Oxford39, Deakin University40, University of British Columbia41, University of Toronto42, Box Hill Hospital43, Vanderbilt University44, University of Washington45, Brandeis University46, University of Tokyo47, The Queen's Medical Center48, Norwegian University of Science and Technology49, China Medical Board50, University of Cambridge51, Royal Cornwall Hospital52, Cedars-Sinai Medical Center53, Shanghai Jiao Tong University54
TL;DR: In this paper, a comprehensive re-estimation of disability weights for the Global Burden of Disease Study 2010 through a large-scale empirical investigation in which judgments about health losses associated with many causes of disease and injury were elicited from the general public in diverse communities through a new, standardised approach.
1,130 citations
TL;DR: The conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines are discussed.
Abstract: Reliable and comparable analysis of risks to health is key for preventing disease and injury. Causal attribution of morbidity and mortality to risk factors has traditionally been conducted in the context of methodological traditions of individual risk factors, often in a limited number of settings, restricting comparability.In this paper, we discuss the conceptual and methodological issues for quantifying the population health effects of individual or groups of risk factors in various levels of causality using knowledge from different scientific disciplines. The issues include: comparing the burden of disease due to the observed exposure distribution in a population with the burden from a hypothetical distribution or series of distributions, rather than a single reference level such as non-exposed; considering the multiple stages in the causal network of interactions among risk factor(s) and disease outcome to allow making inferences about some combinations of risk factors for which epidemiological studies have not been conducted, including the joint effects of multiple risk factors; calculating the health loss due to risk factor(s) as a time-indexed "stream" of disease burden due to a time-indexed "stream" of exposure, including consideration of discounting; and the sources of uncertainty.
778 citations