A health impact assessment of long-term exposure to particulate air pollution in Thailand

dc.contributor.authorMueller, William
dc.contributor.authorVardoulakis, Sotiris
dc.contributor.authorSteinle, Susanne
dc.contributor.authorLoh, Miranda
dc.contributor.authorJohnston, Helinor J
dc.contributor.authorPrecha, Nopadol
dc.contributor.authorKliengchuay, W.
dc.contributor.authorSahanavin, Narut
dc.contributor.authorNakhapakorn, Kanchana
dc.contributor.authorSillaparassamee, Ratthapol
dc.contributor.authorTantrakarnapa, Kraichat
dc.contributor.authorCherrie, John W
dc.date.accessioned2024-01-22T22:53:59Z
dc.date.available2024-01-22T22:53:59Z
dc.date.issued2021
dc.date.updated2022-10-02T07:17:59Z
dc.description.abstractParticulate air pollution causes a spectrum of adverse health effects affecting the respiratory, cardiovascular, neurological, and metabolic systems that are hypothesised to be driven by inflammation and oxidative stress. Millions of premature deaths each year are attributed to exposure to ambient particulate matter (PM). We quantified health and economic impacts from long-term exposure to ambient PM2.5 in the population of Thailand for 2016. We collected data on ambient PM2.5 concentrations from automatic monitoring stations across Thailand over 1996-2016. We used historic exposure to PM2.5 to estimate the mortality in each province from lower respiratory infections (LRIs), stroke, chronic obstructive pulmonary disease, lung cancer, and ischaemic heart disease, and also assessed diabetes mortality, as well as incident cases of dementia and Parkinson's disease, in supplementary analyses. We applied risk estimates from the Global Exposure Mortality Model to calculate attributable mortality and quantify disability-adjusted life years (DALYs); we based economic costs on the value of a statistical life (VSL). We calculated 50 019 (95% confidence interval [CI]: 42 189-57 849) deaths and 508 918 (95% CI: 438 345-579 492) DALYs in 2016 attributed to long-term PM2.5 exposure in Thailand. Population attributable fractions ranged from 20% (95% CI: 10% to 29%) for stroke to 48% (95% CI: 27% to 63%) for LRIs. Based on the VSL, we calculated a cost of US$ 60.9 billion (95% CI: US$ 51.3-70.4 billion), which represents nearly 15% of Thailand's gross domestic product in 2016. While progress has been made to reduce exposure to ambient PM2.5 in Thailand, continued reductions based on stricter regulatory limits for PM2.5 and other air pollutants would help prolong life, and delay, or prevent, onset of cardiorespiratory and other diseases.en_AU
dc.description.sponsorshipThis study was funded by the Medical Research Council (MRC) (MR/R006210/1) and the Thailand Research Fund (TRF) (RDG603009). Funds to support open access were provided by Heriot-Watt University. The views expressed are those of the author(s) and not necessarily those of the MRC or TRF.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn1748-9326en_AU
dc.identifier.urihttp://hdl.handle.net/1885/311740
dc.language.isoen_AUen_AU
dc.provenanceOriginal content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.en_AU
dc.publisherIOP Publishingen_AU
dc.rights© 2021 The authorsen_AU
dc.rights.licenseCreative Commons Attribution licenceen_AU
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_AU
dc.sourceEnvironmental Research Lettersen_AU
dc.subjecthealth impact assessmenten_AU
dc.subjectparticulate matteren_AU
dc.subjectair pollutionen_AU
dc.subjectvalue of a statistical lifeen_AU
dc.titleA health impact assessment of long-term exposure to particulate air pollution in Thailanden_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Accessen_AU
local.bibliographicCitation.issue5en_AU
local.contributor.affiliationMueller, William, Institute of Occupational Medicineen_AU
local.contributor.affiliationVardoulakis, Sotiris, College of Health and Medicine, ANUen_AU
local.contributor.affiliationSteinle, Susanne, Institute of Occupational Medicineen_AU
local.contributor.affiliationLoh, Miranda, Institute of Occupational Medicineen_AU
local.contributor.affiliationJohnston, Helinor J, Heriot-Watt Universityen_AU
local.contributor.affiliationPrecha, Nopadol, Walailak Universityen_AU
local.contributor.affiliationKliengchuay, W., Mahidol Universityen_AU
local.contributor.affiliationSahanavin, Narut, Srinakharintarawiroj Universityen_AU
local.contributor.affiliationNakhapakorn, Kanchana, Mahidol Universityen_AU
local.contributor.affiliationSillaparassamee, Ratthapol, Valaya Alongkorn Rajabhat Universityen_AU
local.contributor.affiliationTantrakarnapa, Kraichat, Mahidol Universityen_AU
local.contributor.affiliationCherrie, John W, Heriot-Watt Universityen_AU
local.contributor.authoruidVardoulakis, Sotiris, u5094038en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor420200 - Epidemiologyen_AU
local.identifier.ariespublicationa383154xPUB19275en_AU
local.identifier.citationvolume16en_AU
local.identifier.doi10.1088/1748-9326/abe3baen_AU
local.identifier.scopusID2-s2.0-85105734965
local.identifier.thomsonIDWOS:000647654000001
local.publisher.urlhttps://iopscience.iop.org/en_AU
local.type.statusPublished Versionen_AU

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