Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model

Abstract Air pollution in China has become a major environmental problem. There is a lack of evidence on the impact of haze (especially PM2.5) on intensive care unit admission due to pneumonia (ICUp). We hypothesized that PM2.5 was independently associated with ICUp and there was a non-linear time l...

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Autores principales:	Zhongheng Zhang, Yucai Hong, Ning Liu
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4d2841bd376d4ba594ea0ef4d2057337
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spelling	oai:doaj.org-article:4d2841bd376d4ba594ea0ef4d20573372021-12-02T12:30:19ZAssociation of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model10.1038/s41598-017-08984-x2045-2322https://doaj.org/article/4d2841bd376d4ba594ea0ef4d20573372017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-08984-xhttps://doaj.org/toc/2045-2322Abstract Air pollution in China has become a major environmental problem. There is a lack of evidence on the impact of haze (especially PM2.5) on intensive care unit admission due to pneumonia (ICUp). We hypothesized that PM2.5 was independently associated with ICUp and there was a non-linear time lag effect. All ICU admissions occurred from January 1, 2014 to December 31, 2016 in Sir Run-Run Shaw hospital were included in the study. The primary reasons for admission were categorized into pneumonia and non-pneumonia. Distributed lag non-linear model (DLNM) was built to account for the effect of air quality parameters in both value and temporal lag dimensions. There was a total of 7487 ICU admissions during the study period, including 391 admissions due to pneumonia. The DLNM showed that the relative risk (RR) of ICUp increased with PM2.5 concentrations. At a PM2.5 concentration of 200 mcg/m3, the RR increased from 1.06 (95% CI: 0.57–1.95) at day 0 to 1.40 (95% CI: 1.05–1.86) at day 3, and returned normal at day 6 (RR: 1.13; 95% CI: 0.83–1.55). The study showed that PM2.5 was independently associated with the risk of ICUp, and the maximum effect occurred at 3 to 4 days after exposure.Zhongheng ZhangYucai HongNing LiuNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-7 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zhongheng Zhang Yucai Hong Ning Liu Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model
description	Abstract Air pollution in China has become a major environmental problem. There is a lack of evidence on the impact of haze (especially PM2.5) on intensive care unit admission due to pneumonia (ICUp). We hypothesized that PM2.5 was independently associated with ICUp and there was a non-linear time lag effect. All ICU admissions occurred from January 1, 2014 to December 31, 2016 in Sir Run-Run Shaw hospital were included in the study. The primary reasons for admission were categorized into pneumonia and non-pneumonia. Distributed lag non-linear model (DLNM) was built to account for the effect of air quality parameters in both value and temporal lag dimensions. There was a total of 7487 ICU admissions during the study period, including 391 admissions due to pneumonia. The DLNM showed that the relative risk (RR) of ICUp increased with PM2.5 concentrations. At a PM2.5 concentration of 200 mcg/m3, the RR increased from 1.06 (95% CI: 0.57–1.95) at day 0 to 1.40 (95% CI: 1.05–1.86) at day 3, and returned normal at day 6 (RR: 1.13; 95% CI: 0.83–1.55). The study showed that PM2.5 was independently associated with the risk of ICUp, and the maximum effect occurred at 3 to 4 days after exposure.
format	article
author	Zhongheng Zhang Yucai Hong Ning Liu
author_facet	Zhongheng Zhang Yucai Hong Ning Liu
author_sort	Zhongheng Zhang
title	Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model
title_short	Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model
title_full	Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model
title_fullStr	Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model
title_full_unstemmed	Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model
title_sort	association of ambient particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/4d2841bd376d4ba594ea0ef4d2057337
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Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model

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