Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.

<h4>Background</h4>There is limited evidence for the impacts of meteorological changes on asthma hospital admissions in adults in Shanghai, China.<h4>Objectives</h4>To quantitatively evaluate the short-term effects of daily mean temperature on asthma hospital admissions.<h...

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Autores principales:	Yue Zhang, Li Peng, Haidong Kan, Jianming Xu, Renjie Chen, Yuan Liu, Weibing Wang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bce51790a8b04af59c5cd9ee9995db65
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spelling	oai:doaj.org-article:bce51790a8b04af59c5cd9ee9995db652021-11-25T06:08:42ZEffects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.1932-620310.1371/journal.pone.0102475https://doaj.org/article/bce51790a8b04af59c5cd9ee9995db652014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25019158/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>There is limited evidence for the impacts of meteorological changes on asthma hospital admissions in adults in Shanghai, China.<h4>Objectives</h4>To quantitatively evaluate the short-term effects of daily mean temperature on asthma hospital admissions.<h4>Methods</h4>Daily hospital admissions for asthma and daily mean temperatures between January 2005 and December 2012 were analyzed. After controlling for secular and seasonal trends, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) combined with a distributed lag non-linear model were used to explore the associations between temperature and hospital admissions for asthma.<h4>Results</h4>During the study periods, there were 15,678 hospital admissions for asthma by residents of Shanghai, an average 5.6 per day. Pearson correlation analysis found a significant negative correlation (r = -0.174, P<0.001) between asthma hospitalizations and daily mean temperature (DMT). The DMT effect on asthma increased below the median DMT, with lower temperatures associated with a higher risk of hospital admission for asthma. Generally, the cold effect appeared to be relatively acute, with duration lasting several weeks, while the hot effect was short-term. The relative risk of asthma hospital admissions associated with cold temperature (the 25th percentile of temperature relative to the median temperature) was 1.20 (95% confidence interval [CI], 1.01∼1.41) at lag0-14. However, warmer temperatures were not associated with asthma hospital admissions.<h4>Conclusions</h4>Cold temperatures may trigger asthmatic attacks. Effective strategies are needed to protect populations at risk from the effects of cold.Yue ZhangLi PengHaidong KanJianming XuRenjie ChenYuan LiuWeibing WangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 7, p e102475 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yue Zhang Li Peng Haidong Kan Jianming Xu Renjie Chen Yuan Liu Weibing Wang Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
description	<h4>Background</h4>There is limited evidence for the impacts of meteorological changes on asthma hospital admissions in adults in Shanghai, China.<h4>Objectives</h4>To quantitatively evaluate the short-term effects of daily mean temperature on asthma hospital admissions.<h4>Methods</h4>Daily hospital admissions for asthma and daily mean temperatures between January 2005 and December 2012 were analyzed. After controlling for secular and seasonal trends, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) combined with a distributed lag non-linear model were used to explore the associations between temperature and hospital admissions for asthma.<h4>Results</h4>During the study periods, there were 15,678 hospital admissions for asthma by residents of Shanghai, an average 5.6 per day. Pearson correlation analysis found a significant negative correlation (r = -0.174, P<0.001) between asthma hospitalizations and daily mean temperature (DMT). The DMT effect on asthma increased below the median DMT, with lower temperatures associated with a higher risk of hospital admission for asthma. Generally, the cold effect appeared to be relatively acute, with duration lasting several weeks, while the hot effect was short-term. The relative risk of asthma hospital admissions associated with cold temperature (the 25th percentile of temperature relative to the median temperature) was 1.20 (95% confidence interval [CI], 1.01∼1.41) at lag0-14. However, warmer temperatures were not associated with asthma hospital admissions.<h4>Conclusions</h4>Cold temperatures may trigger asthmatic attacks. Effective strategies are needed to protect populations at risk from the effects of cold.
format	article
author	Yue Zhang Li Peng Haidong Kan Jianming Xu Renjie Chen Yuan Liu Weibing Wang
author_facet	Yue Zhang Li Peng Haidong Kan Jianming Xu Renjie Chen Yuan Liu Weibing Wang
author_sort	Yue Zhang
title	Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
title_short	Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
title_full	Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
title_fullStr	Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
title_full_unstemmed	Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
title_sort	effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/bce51790a8b04af59c5cd9ee9995db65
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Effects of meteorological factors on daily hospital admissions for asthma in adults: a time-series analysis.

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