Long-Term Exposure to Outdoor Air Pollution and COVID-19 Mortality: an ecological analysis in England

  1. Zhiqiang Feng
  2. Mark Cherrie
  3. Chris Dibben

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Abstract

There is an urgent need to examine what individual and environmental risk factors are associated with COVID-19 mortality. This objective of this study is to investigate the association between long term exposure to air pollution and COVID-19 mortality. We conducted a nationwide, ecological study using zero-inflated negative binomial models to estimate the association between long term (2014-2018) small area level exposure to NO x , PM 2.5 , PM 10 and SO 2 and COVID-19 mortality rates in England adjusting for socioeconomic factors and infection exposure. We found that all four pollutant concentrations were positively associated with COVID-19 mortality. The increase in mortality risk ratio per inter quarter range increase was for PM 2.5 :11%, 95%CIs 6%-17%), PM 10 (5%; 95%CIs 1%-11%), NOx (11%, 95%CIs 6%-15%) and SO 2 (7%, 95%CIs 3%-11%) were respectively in adjusted models. Public health intervention may need to protect people who are in highly polluted areas from COVID-19 infections.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.13.20174227: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Nevertheless these two studies had severe limitations because of their methodologies. The paper by Ogen (2020) used two month pollution data as long term exposure measures and both failed to adjust for potential confounders. Travaglio et al. (2020) took a similar approach but control only for differences in population density and across only 7 relatively large regions. Studies based on U.S. were rigorous in terms of the data and methodology. However, their finding have been mixed. For example, while some found a positive association with PM2.5 (Wu et al 2020) others did not (Liang et al 2020; Knittel and Ozaltun, 2020). In the work by Liang et al (2020) they examined three NO2, PM2.5 and O3 and found that only NO2 showed consistent positive association with COVID-19 mortality. The strengths of this analysis include air pollution measures based on well validated approaches used in a large number of previous studies (Carey et al 2013; Dibben and Clemens, 2015). Our analysis utilised COVID-19 death data up to 31st May 2020 allowing us to capture almost the entire course of the first phase of the pandemic in England and hence much more fully than the previous studies which have examined data up to only March or early April. In addition, the analysis includes controlling for a number of socioeconomic, demographic confounders, not adjusted for in other studies. Viral exposure is also adjusted for in the analysis. Use of small areas is also an advantage because air pollution varies ...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2020.08.13.20174227v1 on medRxiv