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. 2023 Jun 17;401(10393):2060-2071.
doi: 10.1016/S0140-6736(23)00458-0. Epub 2023 Jun 5.

Burden of disease attributable to unsafe drinking water, sanitation, and hygiene in domestic settings: a global analysis for selected adverse health outcomes

Jennyfer Wolf  1 , Richard B Johnston  2 , Argaw Ambelu  3 , Benjamin F Arnold  4 , Robert Bain  5 , Michael Brauer  6 , Joe Brown  7 , Bethany A Caruso  8 , Thomas Clasen  9 , John M Colford Jr  10 , Joanna Esteves Mills  2 , Barbara Evans  11 , Matthew C Freeman  9 , Bruce Gordon  2 , Gagandeep Kang  12 , Claudio F Lanata  13 , Kate O Medlicott  2 , Annette Prüss-Ustün  2 , Christopher Troeger  14 , Sophie Boisson  2 , Oliver Cumming  15
Affiliations

Burden of disease attributable to unsafe drinking water, sanitation, and hygiene in domestic settings: a global analysis for selected adverse health outcomes

Jennyfer Wolf et al. Lancet. .

Abstract

Background: Assessments of disease burden are important to inform national, regional, and global strategies and to guide investment. We aimed to estimate the drinking water, sanitation, and hygiene (WASH)-attributable burden of disease for diarrhoea, acute respiratory infections, undernutrition, and soil-transmitted helminthiasis, using the WASH service levels used to monitor the UN Sustainable Development Goals (SDGs) as counterfactual minimum risk-exposure levels.

Methods: We assessed the WASH-attributable disease burden of the four health outcomes overall and disaggregated by region, age, and sex for the year 2019. We calculated WASH-attributable fractions of diarrhoea and acute respiratory infections by country using modelled WASH exposures and exposure-response relationships from two updated meta-analyses. We used the WHO and UNICEF Joint Monitoring Programme for Water Supply, Sanitation and Hygiene public database to estimate population exposure to different WASH service levels. WASH-attributable undernutrition was estimated by combining the population attributable fractions (PAF) of diarrhoea caused by unsafe WASH and the PAF of undernutrition caused by diarrhoea. Soil-transmitted helminthiasis was fully attributed to unsafe WASH.

Findings: We estimate that 1·4 (95% CI 1·3-1·5) million deaths and 74 (68-80) million disability-adjusted life-years (DALYs) could have been prevented by safe WASH in 2019 across the four designated outcomes, representing 2·5% of global deaths and 2·9% of global DALYs from all causes. The proportion of diarrhoea that is attributable to unsafe WASH is 0·69 (0·65-0·72), 0·14 (0·13-0·17) for acute respiratory infections, and 0·10 (0·09-0·10) for undernutrition, and we assume that the entire disease burden from soil-transmitted helminthiasis was attributable to unsafe WASH.

Interpretation: WASH-attributable burden of disease estimates based on the levels of service established under the SDG framework show that progress towards the internationally agreed goal of safely managed WASH services for all would yield major public-health returns.

Funding: WHO and Foreign, Commonwealth & Development Office.

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Conflict of interest statement

Declaration of interests JW reports grants from UK Foreign, Commonwealth & Development Office (FCDO), during this study. MB reports grants from Bill & Melinda Gates Foundation during this study. CFL reports non-financial support from WHO COVID-19 Vaccine Effectiveness Working Group, grants from CureVac AG, grants from PATH, grants from HilleVax, and personal fees from Valneva outside the submitted work. JB reports grants from Bill & Melinda Gates Foundation, grants from US Centers for Disease Control & Prevention, and grants from Columbia World Projects during this study. MCF reports Consulting for Rickett's Global Scientific Advisory Committee. RBJ reports grants from UK FCDO during this study, grants from Agence française de développement, grants from Australian Government Department of Foreign Affairs and Trade, grants from Austrian Development Agency, grants from Bill & Melinda Gates Foundation, grants from German Federal Ministry for Economic Development and Cooperation, grants from The Netherlands Directorate-General for International Cooperation, grants from Swiss Agency for Development and Cooperation, and grants from United States Agency for International Development outside the submitted work. All other authors declare no competing interests.

Figures

Figure 1
Figure 1
General approach for calculating the PAF and the attributable disease burden in comparative risk assessment Sources for data inputs are listed in appendix 1 (p 6). DALY=disability-adjusted life-year. PAF=population attributable fraction. n=total number of exposure levels.
Figure 2
Figure 2
Conceptual model for disease burden assessment attributable to unsafe drinking water and associated reduction in risk of diarrhoea Blue box with solid line: counterfactual minimum risk exposure used in the analysis with associated percentage reduction in risk of diarrhoea compared with the highest risk-exposure group from a meta-analysis. Blue box with dashed line: additional plausible risk reduction, which cannot currently be estimated due to a paucity of exposure or exposure–response data. SDG=Sustainable Development Goal. *Safe drinking water does not represent any substantial risk to health over a lifetime of consumption. The position of the boxes is not directly proportional to the expected health effect.
Figure 3
Figure 3
Conceptual model for disease burden assessment attributable to unsafe sanitation and associated reduction in risk of diarrhoea Blue box with solid line: counterfactual minimum risk exposure used in the analysis with associated percentage reduction in risk of diarrhoea compared with the highest risk-exposure group from Wolf and colleagues’ meta-analysis. Blue boxes with dashed lines: additional plausible risk reduction, which cannot currently be estimated due to a paucity of exposure or exposure–response data. The position of the boxes is not directly proportional to the expected health effect. SDG=Sustainable Development Goal.
Figure 4
Figure 4
Conceptual model for disease burden assessment attributable to unsafe hygiene and associated reductions in risk of diarrhoea and acute respiratory infections, Blue box with solid line: counterfactual minimum risk exposure used in the analysis with associated percentage reductions in risk of diarrhoea and risk of acute respiratory infections compared with no handwashing. Blue box with dashed line: additional plausible risk reductions that cannot currently be estimated due to a paucity of exposure or exposure–response data. The position of the boxes is not directly proportional to the expected health effect.
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References

    1. Prüss-Ustün A, Wolf J, Bartram J, et al. Burden of disease from inadequate water, sanitation and hygiene for selected adverse health outcomes: an updated analysis with a focus on low- and middle-income countries. Int J Hyg Environ Health. 2019;222:765–777. - PMC - PubMed
    1. GBD 2019 Risk Factors Collaborators Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396:1223–1249. - PMC - PubMed
    1. WHO. UNICEF Progress on household drinking water, sanitation and hygiene 2000–2020: five years into the SDGs. 2021. https://washdata.org/report/jmp-2021-wash-households
    1. Wolf J, Hubbard S, Brauer M, et al. Effectiveness of interventions to improve drinking water, sanitation, and handwashing with soap on risk of diarrhoeal disease in children in low-income and middle-income settings: a systematic review and meta-analysis. Lancet. 2022;400:48–59. - PMC - PubMed
    1. Checkley W, Buckley G, Gilman RH, et al. Multi-country analysis of the effects of diarrhoea on childhood stunting. Int J Epidemiol. 2008;37:816–830. - PMC - PubMed

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