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Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution
Chiang Mai is one of the most known cities of Northern Thailand, representative for various cities in the East and South-East Asian region exhibiting seasonal smog crises. While a few studies have attempted to address smog crises effects on human health in that geographic region, research in this re...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9387779/ https://www.ncbi.nlm.nih.gov/pubmed/35980887 http://dx.doi.org/10.1371/journal.pone.0272995 |
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author | Varapongpisan, Tunyathron Frank, Till D. Ingsrisawang, Lily |
author_facet | Varapongpisan, Tunyathron Frank, Till D. Ingsrisawang, Lily |
author_sort | Varapongpisan, Tunyathron |
collection | PubMed |
description | Chiang Mai is one of the most known cities of Northern Thailand, representative for various cities in the East and South-East Asian region exhibiting seasonal smog crises. While a few studies have attempted to address smog crises effects on human health in that geographic region, research in this regard is still in its infancy. We exploited a unique situation based on two factors: large pollutant concentration variations due to the Chiang Mai smog crises and a relatively large sample of out-patient visits. About 216,000 out-patient visits in the area of Chiang Mai during the period of 2011 to 2014 for upper (J30-J39) and lower (J44) respiratory tract diseases were evaluated with respect to associations with particulate matter (PM(10)), ozone (O(3)), and nitrogen dioxide (NO(2)) concentrations using single-pollutant and multiple-pollutants Poisson regression models. All three pollutants were found to be associated with visits due to upper respiratory tract diseases (with relative risks RR = 1.023 at cumulative lag 05, 95% CI: 1.021–1.025, per 10 μg/m(3) PM(10) increase, RR = 1.123 at lag 05, 95% CI: 1.118–1.129, per 10 ppb O(3) increase, and RR = 1.110 at lag 05, 95% CI: 1.102–1.119, per 10 ppb NO(2) increase). Likewise, all three pollutants were found to be associated with visits due to lower respiratory tract diseases (with RR = 1.016 at lag 06, 95% CI: 1.015–1.017, per 10 μg/m(3) PM(10) increase, RR = 1.073 at lag 06, 95% CI: 1.070–1.076, per 10 ppb O(3) increase, and RR = 1.046 at lag 06, 95% CI: 1.040–1.051, per 10 ppb NO(2) increase). Multi-pollutants modeling analysis identified O(3) as a relatively independent risk factor and PM(10)-NO(2) pollutants models as promising two-pollutants models. Overall, these results demonstrate the adverse effects of all three air pollutants on respiratory morbidity and call for air pollution reduction and control. |
format | Online Article Text |
id | pubmed-9387779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-93877792022-08-19 Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution Varapongpisan, Tunyathron Frank, Till D. Ingsrisawang, Lily PLoS One Research Article Chiang Mai is one of the most known cities of Northern Thailand, representative for various cities in the East and South-East Asian region exhibiting seasonal smog crises. While a few studies have attempted to address smog crises effects on human health in that geographic region, research in this regard is still in its infancy. We exploited a unique situation based on two factors: large pollutant concentration variations due to the Chiang Mai smog crises and a relatively large sample of out-patient visits. About 216,000 out-patient visits in the area of Chiang Mai during the period of 2011 to 2014 for upper (J30-J39) and lower (J44) respiratory tract diseases were evaluated with respect to associations with particulate matter (PM(10)), ozone (O(3)), and nitrogen dioxide (NO(2)) concentrations using single-pollutant and multiple-pollutants Poisson regression models. All three pollutants were found to be associated with visits due to upper respiratory tract diseases (with relative risks RR = 1.023 at cumulative lag 05, 95% CI: 1.021–1.025, per 10 μg/m(3) PM(10) increase, RR = 1.123 at lag 05, 95% CI: 1.118–1.129, per 10 ppb O(3) increase, and RR = 1.110 at lag 05, 95% CI: 1.102–1.119, per 10 ppb NO(2) increase). Likewise, all three pollutants were found to be associated with visits due to lower respiratory tract diseases (with RR = 1.016 at lag 06, 95% CI: 1.015–1.017, per 10 μg/m(3) PM(10) increase, RR = 1.073 at lag 06, 95% CI: 1.070–1.076, per 10 ppb O(3) increase, and RR = 1.046 at lag 06, 95% CI: 1.040–1.051, per 10 ppb NO(2) increase). Multi-pollutants modeling analysis identified O(3) as a relatively independent risk factor and PM(10)-NO(2) pollutants models as promising two-pollutants models. Overall, these results demonstrate the adverse effects of all three air pollutants on respiratory morbidity and call for air pollution reduction and control. Public Library of Science 2022-08-18 /pmc/articles/PMC9387779/ /pubmed/35980887 http://dx.doi.org/10.1371/journal.pone.0272995 Text en © 2022 Varapongpisan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Varapongpisan, Tunyathron Frank, Till D. Ingsrisawang, Lily Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution |
title | Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution |
title_full | Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution |
title_fullStr | Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution |
title_full_unstemmed | Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution |
title_short | Association between out-patient visits and air pollution in Chiang Mai, Thailand: Lessons from a unique situation involving a large data set showing high seasonal levels of air pollution |
title_sort | association between out-patient visits and air pollution in chiang mai, thailand: lessons from a unique situation involving a large data set showing high seasonal levels of air pollution |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9387779/ https://www.ncbi.nlm.nih.gov/pubmed/35980887 http://dx.doi.org/10.1371/journal.pone.0272995 |
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