Association between coronavirus disease 2019 (COVID-19) and long-term exposure to air pollution: Evidence from the first epidemic wave in China. (1st May 2021)

• Record Type: Journal Article
• Authors: Zheng, Pai; Chen, Zhangjian; Liu, Yonghong; Song, Hongbin; Wu, Chieh-Hsi; Li, Bingying; Kraemer, Moritz U.G.; Tian, Huaiyu; Yan, Xing; Zheng, Yuxin; Stenseth, Nils Chr.; Jia, Guang
• Is Part Of: Environmental pollution. Volume 276(2021)
• Publication Date: 2021-05-01
• Subjects: Coronavirus disease 2019 -- COVID-19 -- Air pollution -- Chronic exposure; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2021.116682
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: People with chronic obstructive pulmonary disease, cardiovascular disease, or hypertension have a high risk of developing severe coronavirus disease 2019 (COVID-19) and of COVID-19 mortality. However, the association between long-term exposure to air pollutants, which increases cardiopulmonary damage, and vulnerability to COVID-19 has not yet been fully established. We collected data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average air pollutant levels as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the period of the emergency response. Other variables included smoking prevalence, climate data, socioeconomic data, education level, and number of hospital beds for 324 cities in China. After adjusting for human mobility and socioeconomic factors, we found an increase of 37.8% (95% confidence interval [CI]: 23.8%–52.0%), 32.3% (95% CI: 22.5%–42.4%), and 14.2% (7.9%–20.5%) in the number of COVID-19 cases for every 10-μg/m 3 increase in long-term exposure to NO2, PM2.5, and PM10, respectively. However, when stratifying the data according to population size, the association became non-significant. The present results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings suggested that air pollution may be related to population vulnerability to COVID-19 infection, although the extent to which this relationship is confounded by city population density needs further exploration. Graphical abstract: Image 1 Highlights: Long-term exposure to NO2, PM2.5 or PM10 corresponded to COVID-19 case numbers. This study focused on the period in the first wave of China. The nationwide COVID-19 cases and severe infections in 324 cities of China were included. The association may be confounded by city population size and density. Abstract : This research reported a national-level association with long-term exposure to air pollutants and COVID-19 cases covering 324 cities in China.