Association between daily hospital outpatient visits for accidents and daily ambient air temperatures in an industrial city

NCUIR > College of Earth Sciences > Department of Atmospheric Sciences > journal & Dissertation > Item 987654321/100650

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Title:	Association between daily hospital outpatient visits for accidents and daily ambient air temperatures in an industrial city
Authors:	王國英;Chau, Tang-Tat;Wang, Kuo-Ying
Contributors:	地球科學學院大氣科學學系
Keywords:	Accidents;Accidents - statistics & numerical data;Adolescent;Adult;Aged;Air pollution;Air Pollution - analysis;Air temperature;Ambient temperature;Analysis;Annual reports;Carbon Monoxide - analysis;Child;Child, Preschool;Correlation;Daily temperatures;Data processing;Demographic aspects;Earth Sciences;Emergency medical care;Emissions;Engineering and Technology;Environmental aspects;Environmental factors;Female;Health aspects;Heat;Holidays & special occasions;Hospitals;Humans;Industry;Infant;Infant, Newborn;Influence;Linear Models;Male;Medical records;Medicine and Health Sciences;Meteorology;Middle Aged;Nitrogen dioxide;Nitrogen Dioxide - analysis;Normal distribution;Older people;Outpatients;Ozone - analysis;Particulate Matter - analysis;People and Places;Photochemicals;Physical Sciences;Pollutants;Pollution;Population;Professional baseball;Regression analysis;Regression models;Temperature;Temperature effects;Temperature variations;Traffic models;Vehicle emissions;Weather;Young Adult;Young adults
Date:	2016-01-01
Issue Date:	2026-04-21 14:09:38 (UTC+8)
Publisher:	Public Library of Science;United States: Public Library of Science
Abstract:	摘要： An accident is an unwanted hazard to a person. However, accidents occur. In this work, we search for correlations between daily accident rates and environmental factors. To study daily hospital outpatients who were admitted for accidents during a 5-year period, 2007-2011, we analyzed data regarding 168,366 outpatients using univariate regression models; we also used multivariable regression models to account for confounding factors. Our analysis indicates that the number of male outpatients admitted for accidents was approximately 1.31 to 1.47 times the number of female outpatients (P < 0.0001). Of the 12 parameters (regarding air pollution and meteorology) considered, only daily temperature exhibited consistent and significant correlations with the daily number of hospital outpatient visits for accidents throughout the 5-year analysis period. The univariate regression models indicate that older people (greater than 66 years old) had the fewest accidents per 1-degree increase in temperature, followed by young people (0-15 years old). Middle-aged people (16-65 years old) were the group of outpatients that were more prone to accidents, with an increase in accident rates of 0.8-1.2 accidents per degree increase in temperature. The multivariable regression models also reveal that the temperature variation was the dominant factor in determining the daily number of outpatient visits for accidents. Our further multivariable model analysis of temperature with respect to air pollution variables show that, through the increases in emissions and concentrations of CO, photochemical O3 production and NO2 loss in the ambient air, increases in vehicular emissions are associated with increases in temperatures. As such, increases in hospital visits for accidents are related to vehicular emissions and usage. This finding is consistent with clinical experience which shows about 60% to 80% of accidents are related to traffic, followed by accidents occurred in work place. 其他題名： PLoS One 出版者： United States: Public Library of Science 出版日期： 2016-01-27 出處： PloS one, 2016-01, Vol.11 (1), p.e0145003 資源來源： Directory of Open Access Journals - DOAJ (NTUSG) 版權： COPYRIGHT 2016 Public Library of Science 版權： 2016 Chau, Wang. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 版權： 2016 Chau, Wang 2016 Chau, Wang 識別號： ISSN: 1932-6203 識別號： EISSN: 1932-6203 識別號： DOI: 10.1371/journal.pone.0145003 識別號： PMID: 26815039
Appears in Collections:	[Department of Atmospheric Sciences] journal & Dissertation

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