Li, Meng and Chen, Shengqi and Zhao, Hanqing and Tang, Chengxiang and Lai, Yunfeng and Ung, Carolina Oi Lam and Su, Jinya and Hu, Hao (2021) The short-term associations of chronic obstructive pulmonary disease hospitalizations with meteorological factors and air pollutants in Southwest China: a time-series study. Scientific Reports, 11 (1). 12914-. DOI https://doi.org/10.1038/s41598-021-92380-z
Li, Meng and Chen, Shengqi and Zhao, Hanqing and Tang, Chengxiang and Lai, Yunfeng and Ung, Carolina Oi Lam and Su, Jinya and Hu, Hao (2021) The short-term associations of chronic obstructive pulmonary disease hospitalizations with meteorological factors and air pollutants in Southwest China: a time-series study. Scientific Reports, 11 (1). 12914-. DOI https://doi.org/10.1038/s41598-021-92380-z
Li, Meng and Chen, Shengqi and Zhao, Hanqing and Tang, Chengxiang and Lai, Yunfeng and Ung, Carolina Oi Lam and Su, Jinya and Hu, Hao (2021) The short-term associations of chronic obstructive pulmonary disease hospitalizations with meteorological factors and air pollutants in Southwest China: a time-series study. Scientific Reports, 11 (1). 12914-. DOI https://doi.org/10.1038/s41598-021-92380-z
Abstract
Chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity worldwide and is projected to be the third by 2030. However, there is little evidence available on the associations of COPD hospitalizations with meteorological factors and air pollutants in developing countries/regions of Asia. In particular, no study has been done in western areas of China considering the nonlinear and lagged effects simultaneously. This study aims to evaluate the nonlinear and lagged associations of COPD hospitalizations with meteorological factors and air pollutants using time-series analysis. The modified associations by sex and age were also investigated. The distributed lag nonlinear model was used to establish the association of daily COPD hospitalizations of all 441 public hospitals in Chengdu, China from Jan/2015–Dec/2017 with the ambient meteorological factors and air pollutants. Model parameters were optimized based on quasi Akaike Information Criterion and model diagnostics was conducted by inspecting the deviance residuals. Subgroup analysis by sex and age was also performed. Temperature, relative humidity, wind and Carbon Monoxide (CO) have statistically significant and consistent associations with COPD hospitalizations. The cumulative relative risk (RR) was lowest at a temperature of 19℃ (relative humidity of 67%). Both extremely high and low temperature (and relative humidity) increase the cumulative RR. An increase of wind speed above 4 mph (an increase of CO above 1.44 mg/m3) significantly decreases (increases) the cumulative RR. Female populations were more sensitive to low temperature and high CO level; elderly (74+) populations are more sensitive to high relative humidity; younger populations (< = 74) are more susceptible to CO higher than 1.44 mg/m3. Therefore, people with COPD should avoid exposure to adverse environmental conditions of extreme temperatures and relative humidity, low wind speed and high CO level, especially for female and elderly patients who were more sensitive to extreme temperatures and relative humidity.
Item Type: | Article |
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Uncontrolled Keywords: | Humans; Pulmonary Disease, Chronic Obstructive; Disease Susceptibility; Air Pollutants; Hospitalization; Humidity; Temperature; Air Pollution; Environmental Exposure; Age Factors; Sex Factors; Aged; Aged, 80 and over; China; Female; Male; Meteorological Concepts; Public Health Surveillance |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 29 Jun 2021 13:48 |
Last Modified: | 30 Oct 2024 17:18 |
URI: | http://repository.essex.ac.uk/id/eprint/30539 |
Available files
Filename: s41598-021-92380-z.pdf
Licence: Creative Commons: Attribution 3.0