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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
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5561234/ https://www.ncbi.nlm.nih.gov/pubmed/28819316 http://dx.doi.org/10.1038/s41598-017-08984-x |
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author | Zhang, Zhongheng Hong, Yucai Liu, Ning |
author_facet | Zhang, Zhongheng Hong, Yucai Liu, Ning |
author_sort | Zhang, Zhongheng |
collection | PubMed |
description | 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 | Online Article Text |
id | pubmed-5561234 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55612342017-08-21 Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model Zhang, Zhongheng Hong, Yucai Liu, Ning Sci Rep Article 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. Nature Publishing Group UK 2017-08-17 /pmc/articles/PMC5561234/ /pubmed/28819316 http://dx.doi.org/10.1038/s41598-017-08984-x Text en © The Author(s) 2017 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zhang, Zhongheng Hong, Yucai Liu, Ning Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model |
title | 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_short | 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 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5561234/ https://www.ncbi.nlm.nih.gov/pubmed/28819316 http://dx.doi.org/10.1038/s41598-017-08984-x |
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