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Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020

The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet’s ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate condition...

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Autores principales: Jainonthee, Chalita, Wang, Ying-Lin, Chen, Colin W. K., Jainontee, Karuna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696662/
https://www.ncbi.nlm.nih.gov/pubmed/36355883
http://dx.doi.org/10.3390/tropicalmed7110341
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author Jainonthee, Chalita
Wang, Ying-Lin
Chen, Colin W. K.
Jainontee, Karuna
author_facet Jainonthee, Chalita
Wang, Ying-Lin
Chen, Colin W. K.
Jainontee, Karuna
author_sort Jainonthee, Chalita
collection PubMed
description The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet’s ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM(2.5), and PM(10)). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month’s PM(2.5) and temperature (lag1) had a significant association with influenza incidence, while the previous month’s temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM(2.5) lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM(10) and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution.
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spelling pubmed-96966622022-11-26 Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020 Jainonthee, Chalita Wang, Ying-Lin Chen, Colin W. K. Jainontee, Karuna Trop Med Infect Dis Article The unfavorable effects of global climate change, which are mostly the result of human activities, have had a particularly negative effect on human health and the planet’s ecosystems. This study attempted to determine the seasonality and association of air pollution, in addition to climate conditions, with two respiratory infections, influenza and pneumonia, in Chiang Mai, Thailand, which has been considered the most polluted city on Earth during the hot season. We used a seasonal-trend decomposition procedure based on loess regression (STL) and a seasonal cycle subseries (SCS) plot to determine the seasonality of the two diseases. In addition, multivariable negative binomial regression (NBR) models were used to assess the association between the diseases and environmental variables (temperature, precipitation, relative humidity, PM(2.5), and PM(10)). The data revealed that influenza had a clear seasonal pattern during the cold months of January and February, whereas the incidence of pneumonia showed a weak seasonal pattern. In terms of forecasting, the preceding month’s PM(2.5) and temperature (lag1) had a significant association with influenza incidence, while the previous month’s temperature and relative humidity influenced pneumonia. Using air pollutants as an indication of respiratory disease, our models indicated that PM(2.5) lag1 was correlated with the incidence of influenza, but not pneumonia. However, there was a linear association between PM(10) and both diseases. This research will help in allocating clinical and public health resources in response to potential environmental changes and forecasting the future dynamics of influenza and pneumonia in the region due to air pollution. MDPI 2022-10-31 /pmc/articles/PMC9696662/ /pubmed/36355883 http://dx.doi.org/10.3390/tropicalmed7110341 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jainonthee, Chalita
Wang, Ying-Lin
Chen, Colin W. K.
Jainontee, Karuna
Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020
title Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020
title_full Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020
title_fullStr Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020
title_full_unstemmed Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020
title_short Air Pollution-Related Respiratory Diseases and Associated Environmental Factors in Chiang Mai, Thailand, in 2011–2020
title_sort air pollution-related respiratory diseases and associated environmental factors in chiang mai, thailand, in 2011–2020
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696662/
https://www.ncbi.nlm.nih.gov/pubmed/36355883
http://dx.doi.org/10.3390/tropicalmed7110341
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