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Population Response to Air Pollution and the Risk of Coronavirus Disease in Chinese Cities during the Early Pandemic Period

Author

Listed:
  • Miryoung Yoon

    (Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Korea)

  • Jong-Hun Kim

    (Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Korea)

  • Jisun Sung

    (Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Korea)

  • Ah-Young Lim

    (Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Korea)

  • Myung-Jae Hwang

    (Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Korea)

  • Eun-Hye Kim

    (Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Korea)

  • Hae-Kwan Cheong

    (Department of Social and Preventive Medicine, Sungkyunkwan University School of Medicine, Suwon 16419, Korea)

Abstract

Health behavior is a critical measure in controlling the coronavirus disease 2019 (COVID-19) pandemic. We estimated the effect of health behaviors against air pollution on reducing the risk of COVID-19 during the initial phase of the pandemic. The attack rates of COVID-19 in 159 mainland Chinese cities during the first 2 weeks after the closure of major cities was estimated; air pollution level as a surrogate indicator of the mask-wearing rate. Data on air pollution levels and meteorologic factors 2 weeks prior to the closure were obtained. The attack rate was compared with the level of air pollution using a generalized linear model after adjusting for confounders. When fine particulates (PM 2.5 ) and nitrogen dioxide (NO 2 ) levels increased by one unit of air quality index (AQI), the infection risk decreased by 0.7% and 3.4%, respectively. When PM 2.5 levels exceeded 150 (level 4), the infection risk decreased (relative risk, RR = 0.635, 95% confidence interval, CI: 0.442 to 0.912 for level 4; RR = 0.529, 95% CI: 0.337 to 0.830 for level 5; respectively). After controlling for the number of high-speed railway routes, when PM 2.5 and NO 2 levels increased by one AQI, relative risk for PM 2.5 and NO 2 was 0.990 (95% CI, 0.984 to 0.997) and 0.946 (95% CI, 0.911 to 0.982), respectively, demonstrating a consistently negative association. It is postulated that, during the early phase of the pandemic, the cities with higher air pollution levels may represent the higher practice of mask-wearing to protect from air pollution, which could have acted as a barrier to the transmission of the virus. This study highlights the importance of health behaviors, including mask-wearing for preventing infections.

Suggested Citation

  • Miryoung Yoon & Jong-Hun Kim & Jisun Sung & Ah-Young Lim & Myung-Jae Hwang & Eun-Hye Kim & Hae-Kwan Cheong, 2021. "Population Response to Air Pollution and the Risk of Coronavirus Disease in Chinese Cities during the Early Pandemic Period," IJERPH, MDPI, vol. 18(5), pages 1-12, February.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:5:p:2248-:d:505239
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    References listed on IDEAS

    as
    1. Zhang, Junjie & Mu, Quan, 2018. "Air pollution and defensive expenditures: Evidence from particulate-filtering facemasks," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 517-536.
    2. Sun, Cong & Kahn, Matthew E. & Zheng, Siqi, 2017. "Self-protection investment exacerbates air pollution exposure inequality in urban China," Ecological Economics, Elsevier, vol. 131(C), pages 468-474.
    3. Guojun He & Yuhang Pan & Takanao Tanaka, 2020. "The short-term impacts of COVID-19 lockdown on urban air pollution in China," Nature Sustainability, Nature, vol. 3(12), pages 1005-1011, December.
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