Literature DB >> 31845269

Impact of temperature changes between neighboring days on COPD in a city in Northeast China.

Yuxia Ma1, Haoran Jiao2, Yifan Zhang2, Bowen Cheng2, Fengliu Feng2, Zhiang Yu2, Bingji Ma2.   

Abstract

Sudden temperature changes between neighboring days (T24h) have adverse effects on human health. In this study, we used a time series analysis to evaluate the impact of T24h on the number of hospital admissions for chronic obstructive pulmonary disease (COPD) from 2009 to 2012 in Changchun (the capital of Northeast China's Jilin province). We performed the analysis in a generalized additive model (GAM), and the controlling factors included long-term trends, day of the week effect, and the selected weather elements. We divided the entire study group into two gender subgroups (males and females) and two age subgroups (aged < 65 years and aged ≥ 65 years). T24h showed the greatest effect on the entire study group at lag 3 days. In particular, the greatest effect of T24h on females (males) occurred at lag 1 day (lag 3 days); the greatest effect of T24h on the aged ≥ 65 years (aged < 65 years) occurred at lag 1 day (lag 6 days). This indicates that temperature changes between neighboring days have a relatively more acute effect on the elderly and the females than on the younger people and the males. When T24h is less than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 4 days during the warm season (1.025, 95% CI: 0.981, 1.069) and lag 3 days during the cold season (1.019, 95% CI: 0.988, 1.051). When T24h is greater than zero, the highest RR of the number of hospital admissions for COPD occurred at lag 6 days during the warm season (1.026, 95% CI: 0.977, 1.077) and lag 5 days during the cold season (1.021, 95% CI: 0.986, 1.057). The results of this study could be provided to local health authorities as scientific guidelines for controlling and preventing COPD in Changchun, China.

Entities:  

Keywords:  COPD; Generalized additive model (GAM); Temperature changes between neighboring days (T24h)

Mesh:

Year:  2019        PMID: 31845269     DOI: 10.1007/s11356-019-07313-1

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  31 in total

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Journal:  Sci Total Environ       Date:  2015-12-10       Impact factor: 7.963

2.  Seasonal temperature variability and emergency hospital admissions for respiratory diseases: a population-based cohort study.

Authors:  Shengzhi Sun; Francine Laden; Jaime E Hart; Hong Qiu; Yan Wang; Chit Ming Wong; Ruby Siu-Yin Lee; Linwei Tian
Journal:  Thorax       Date:  2018-04-05       Impact factor: 9.139

3.  The temperature-mortality relationship in China: An analysis from 66 Chinese communities.

Authors:  Wenjun Ma; Lijun Wang; Hualiang Lin; Tao Liu; Yonghui Zhang; Shannon Rutherford; Yuan Luo; Weilin Zeng; Yewu Zhang; Xiaofeng Wang; Xin Gu; Cordia Chu; Jianpeng Xiao; Maigeng Zhou
Journal:  Environ Res       Date:  2014-12-06       Impact factor: 6.498

4.  Extremely cold and hot temperatures increase the risk of ischaemic heart disease mortality: epidemiological evidence from China.

Authors:  Yuming Guo; Shanshan Li; Yanshen Zhang; Ben Armstrong; Jouni J K Jaakkola; Shilu Tong; Xiaochuan Pan
Journal:  Heart       Date:  2012-11-13       Impact factor: 5.994

5.  Temperature variation between neighboring days and mortality: a distributed lag non-linear analysis.

Authors:  Jian Cheng; Rui Zhu; Zhiwei Xu; Xiangqing Xu; Xu Wang; Kesheng Li; Hong Su
Journal:  Int J Public Health       Date:  2014-10-04       Impact factor: 3.380

6.  Weather-induced ischemia and arrhythmia in patients undergoing cardiac rehabilitation: another difference between men and women.

Authors:  Alexandra Schneider; Angela Schuh; Friedrich-Karl Maetzel; Regina Rückerl; Susanne Breitner; Annette Peters
Journal:  Int J Biometeorol       Date:  2008-01-29       Impact factor: 3.787

7.  Effects of extremely hot days on people older than 65 years in Seville (Spain) from 1986 to 1997.

Authors:  J Díaz; R García; F Velázquez de Castro; E Hernández; C López; A Otero
Journal:  Int J Biometeorol       Date:  2002-04-25       Impact factor: 3.787

8.  Daily temperature and mortality: a study of distributed lag non-linear effect and effect modification in Guangzhou.

Authors:  Jun Yang; Chun-Quan Ou; Yan Ding; Ying-Xue Zhou; Ping-Yan Chen
Journal:  Environ Health       Date:  2012-09-14       Impact factor: 5.984

9.  Temperature changes between neighboring days and mortality in summer: a distributed lag non-linear time series analysis.

Authors:  Hualiang Lin; Yonghui Zhang; Yanjun Xu; Xiaojun Xu; Tao Liu; Yuan Luo; Jianpeng Xiao; Wei Wu; Wenjun Ma
Journal:  PLoS One       Date:  2013-06-24       Impact factor: 3.240

10.  A large change in temperature between neighbouring days increases the risk of mortality.

Authors:  Yuming Guo; Adrian G Barnett; Weiwei Yu; Xiaochuan Pan; Xiaofang Ye; Cunrui Huang; Shilu Tong
Journal:  PLoS One       Date:  2011-02-02       Impact factor: 3.240

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  2 in total

1.  Temperature Change between Neighboring Days Contributes to Years of Life Lost per Death from Respiratory Disease: A Multicounty Analysis in Central China.

Authors:  Chun-Liang Zhou; Ling-Shuang Lv; Dong-Hui Jin; Yi-Jun Xie; Wen-Jun Ma; Jian-Xiong Hu; Chun-E Wang; Yi-Qing Xu; Xing-E Zhang; Chan Lu
Journal:  Int J Environ Res Public Health       Date:  2022-05-12       Impact factor: 4.614

2.  The relationship between ambient temperature and acute respiratory and cardiovascular diseases in Shenyang, China.

Authors:  Yang Shen; Xudong Zhang; Cai Chen; Qianqian Lin; Xiyuan Li; Wenxiu Qu; Xuejian Liu; Li Zhao; Shijie Chang
Journal:  Environ Sci Pollut Res Int       Date:  2021-01-06       Impact factor: 5.190

  2 in total

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