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Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant

BACKGROUND: While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and...

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Autores principales: Ruan, Hai-Lin, Deng, Wang-Shen, Wang, Yao, Chen, Jian-Bing, Hong, Wei-Liang, Ye, Shan-Shan, Hu, Zhuo-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923450/
https://www.ncbi.nlm.nih.gov/pubmed/33648509
http://dx.doi.org/10.1186/s12919-021-00206-7
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author Ruan, Hai-Lin
Deng, Wang-Shen
Wang, Yao
Chen, Jian-Bing
Hong, Wei-Liang
Ye, Shan-Shan
Hu, Zhuo-Jun
author_facet Ruan, Hai-Lin
Deng, Wang-Shen
Wang, Yao
Chen, Jian-Bing
Hong, Wei-Liang
Ye, Shan-Shan
Hu, Zhuo-Jun
author_sort Ruan, Hai-Lin
collection PubMed
description BACKGROUND: While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and to establish a predictive model. RESULTS: CO poisoning was found to be significantly associated with meteorological and pollutant patterns: low temperatures, low wind speeds, low air concentrations of sulfur dioxide (SO(2)) and ozone (O(3)8h), and high daily temperature changes and ambient CO (r absolute value range: 0.079 to 0.232, all P values < 0.01). Based on the above factors, a predictive model was established: “logitPj = aj - 0.193 * temperature - 0.228 * wind speed + 0.221 * 24 h temperature change + 1.25 * CO - 0.0176 * SO(2) + 0.0008 *O(3)8h; j = 1, 2, 3, 4; a1 = -4.12, a2 = -2.93, a3 = -1.98, a4 = -0.92.” The proposed prediction model based on combined factors showed better predictive capacity than a model using only meteorological factors as a predictor. CONCLUSION: Low temperatures, wind speed, and SO(2) and high daily temperature changes, O(3)8h, and CO are related to CO poisoning. Using both meteorological and pollutant factors as predictors could help facilitate the prevention of CO poisoning. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12919-021-00206-7.
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spelling pubmed-79234502021-03-02 Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant Ruan, Hai-Lin Deng, Wang-Shen Wang, Yao Chen, Jian-Bing Hong, Wei-Liang Ye, Shan-Shan Hu, Zhuo-Jun BMC Proc Research BACKGROUND: While the influence of meteorology on carbon monoxide (CO) poisoning has been reported, few data are available on the association between air pollutants and the prediction of CO poisoning. Our objective is to explore meteorological and pollutant patterns associated with CO poisoning and to establish a predictive model. RESULTS: CO poisoning was found to be significantly associated with meteorological and pollutant patterns: low temperatures, low wind speeds, low air concentrations of sulfur dioxide (SO(2)) and ozone (O(3)8h), and high daily temperature changes and ambient CO (r absolute value range: 0.079 to 0.232, all P values < 0.01). Based on the above factors, a predictive model was established: “logitPj = aj - 0.193 * temperature - 0.228 * wind speed + 0.221 * 24 h temperature change + 1.25 * CO - 0.0176 * SO(2) + 0.0008 *O(3)8h; j = 1, 2, 3, 4; a1 = -4.12, a2 = -2.93, a3 = -1.98, a4 = -0.92.” The proposed prediction model based on combined factors showed better predictive capacity than a model using only meteorological factors as a predictor. CONCLUSION: Low temperatures, wind speed, and SO(2) and high daily temperature changes, O(3)8h, and CO are related to CO poisoning. Using both meteorological and pollutant factors as predictors could help facilitate the prevention of CO poisoning. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12919-021-00206-7. BioMed Central 2021-03-02 /pmc/articles/PMC7923450/ /pubmed/33648509 http://dx.doi.org/10.1186/s12919-021-00206-7 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ruan, Hai-Lin
Deng, Wang-Shen
Wang, Yao
Chen, Jian-Bing
Hong, Wei-Liang
Ye, Shan-Shan
Hu, Zhuo-Jun
Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
title Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
title_full Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
title_fullStr Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
title_full_unstemmed Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
title_short Carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
title_sort carbon monoxide poisoning: a prediction model using meteorological factors and air pollutant
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923450/
https://www.ncbi.nlm.nih.gov/pubmed/33648509
http://dx.doi.org/10.1186/s12919-021-00206-7
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