Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study

Background: Despite a substantial reduction in the use of solid fuels worldwide, exposure to household air pollution (HAP) from use of these fuels for cooking remains a leading risk factor for global disease burden. Among environmental risk factors, the contribution of HAP to disease burden is secon...

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Main Authors: F B Bennitt, BA, S S Wozniak, BA, K Causey, MPH, K Burkart, PhD, M Brauer, ScD
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:The Lancet Global Health
Online Access:http://www.sciencedirect.com/science/article/pii/S2214109X21001261
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spelling doaj-41be7beb060b4b3fb7dea0bcaee98f2b2021-03-13T04:22:44ZengElsevierThe Lancet Global Health2214-109X2021-03-019S18Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease StudyF B Bennitt, BA0S S Wozniak, BA1K Causey, MPH2K Burkart, PhD3M Brauer, ScD4University of Washington, Institute for Health Metrics and Evaluation, Seattle WA, USA; Correspondence to: Fiona Bennitt, Institute for Health Metrics and Evaluation, Population Health Building/Hans Rosling Center 3980 15th Avenue NE, Seattle, WA 98195, USAUniversity of Washington, Institute for Health Metrics and Evaluation, Seattle WA, USAUniversity of Washington, Institute for Health Metrics and Evaluation, Seattle WA, USAUniversity of Washington, Institute for Health Metrics and Evaluation, Seattle WA, USAUniversity of Washington, Institute for Health Metrics and Evaluation, Seattle WA, USA; University of British Columbia, School of Population and Public Health, Vancouver, BC, CanadaBackground: Despite a substantial reduction in the use of solid fuels worldwide, exposure to household air pollution (HAP) from use of these fuels for cooking remains a leading risk factor for global disease burden. Among environmental risk factors, the contribution of HAP to disease burden is second only to ambient particulate matter pollution. We present updates to our modeling methodology as well as our latest findings on attributable burden estimates. Methods: We estimated HAP-attributable burden for cataract, chronic obstructive pulmonary disease, ischaemic heart disease, lower respiratory infections, lung cancer, neonatal disorders, stroke, and type 2 diabetes for 204 countries and territories from 1990 to 2019. We used spatio-temporal Gaussian Process Regression to model data from observational surveys and censuses reporting primary cooking fuel to estimate the proportion of individuals using a specific solid-fuel type (wood, coal/charcoal, agricultural residues, or dung) by location. We converted the fuel exposure estimates to year, location, and sex/age-specific PM2·5 exposures with a regression mapping function using household air pollution measurements. Using a Bayesian meta-regression tool, we estimated relative risk as a function of PM2·5 exposure for each disease based upon a systematic review of the epidemiological literature on indoor and ambient air pollution. We then combined our exposure estimates and relative risks to estimate population attributable fractions and attributable burden for each cause. Findings: In 2019, 91·5 million global disability-adjusted life years (DALYs) (95% uncertainty interval 67·0–119) were attributable to HAP, a decline of more than 50% from 1990. We estimated 2·31 million (1·63–3·12) global deaths were attributable to HAP and accounted for over 4% of all deaths in 2019. HAP-attributable burden remains highest in sub-Saharan Africa and south Asia, with 3770·3 (2876·4–4720·2) and 2068·0 (1412·5–2799·7) age-standardised DALYs per 100 000 population, respectively. Interpretation: Although the disease burden attributable to HAP decreased considerably between 1990 and 2019, it remains a significant risk factor. Our internally consistent methodology and comprehensive approach to estimation of HAP-attributable burden provides a robust resource for global health interventions. Efforts to transition to cleaner household energy sources should be accelerated. Funding: Bill & Melinda Gates Foundation.http://www.sciencedirect.com/science/article/pii/S2214109X21001261
collection DOAJ
language English
format Article
sources DOAJ
author F B Bennitt, BA
S S Wozniak, BA
K Causey, MPH
K Burkart, PhD
M Brauer, ScD
spellingShingle F B Bennitt, BA
S S Wozniak, BA
K Causey, MPH
K Burkart, PhD
M Brauer, ScD
Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study
The Lancet Global Health
author_facet F B Bennitt, BA
S S Wozniak, BA
K Causey, MPH
K Burkart, PhD
M Brauer, ScD
author_sort F B Bennitt, BA
title Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study
title_short Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study
title_full Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study
title_fullStr Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study
title_full_unstemmed Estimating disease burden attributable to household air pollution: new methods within the Global Burden of Disease Study
title_sort estimating disease burden attributable to household air pollution: new methods within the global burden of disease study
publisher Elsevier
series The Lancet Global Health
issn 2214-109X
publishDate 2021-03-01
description Background: Despite a substantial reduction in the use of solid fuels worldwide, exposure to household air pollution (HAP) from use of these fuels for cooking remains a leading risk factor for global disease burden. Among environmental risk factors, the contribution of HAP to disease burden is second only to ambient particulate matter pollution. We present updates to our modeling methodology as well as our latest findings on attributable burden estimates. Methods: We estimated HAP-attributable burden for cataract, chronic obstructive pulmonary disease, ischaemic heart disease, lower respiratory infections, lung cancer, neonatal disorders, stroke, and type 2 diabetes for 204 countries and territories from 1990 to 2019. We used spatio-temporal Gaussian Process Regression to model data from observational surveys and censuses reporting primary cooking fuel to estimate the proportion of individuals using a specific solid-fuel type (wood, coal/charcoal, agricultural residues, or dung) by location. We converted the fuel exposure estimates to year, location, and sex/age-specific PM2·5 exposures with a regression mapping function using household air pollution measurements. Using a Bayesian meta-regression tool, we estimated relative risk as a function of PM2·5 exposure for each disease based upon a systematic review of the epidemiological literature on indoor and ambient air pollution. We then combined our exposure estimates and relative risks to estimate population attributable fractions and attributable burden for each cause. Findings: In 2019, 91·5 million global disability-adjusted life years (DALYs) (95% uncertainty interval 67·0–119) were attributable to HAP, a decline of more than 50% from 1990. We estimated 2·31 million (1·63–3·12) global deaths were attributable to HAP and accounted for over 4% of all deaths in 2019. HAP-attributable burden remains highest in sub-Saharan Africa and south Asia, with 3770·3 (2876·4–4720·2) and 2068·0 (1412·5–2799·7) age-standardised DALYs per 100 000 population, respectively. Interpretation: Although the disease burden attributable to HAP decreased considerably between 1990 and 2019, it remains a significant risk factor. Our internally consistent methodology and comprehensive approach to estimation of HAP-attributable burden provides a robust resource for global health interventions. Efforts to transition to cleaner household energy sources should be accelerated. Funding: Bill & Melinda Gates Foundation.
url http://www.sciencedirect.com/science/article/pii/S2214109X21001261
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