Smoking and the risk of COVID-19 infection in the UK Biobank Prospective Study

  1. Eo Rin Cho
  2. Prabhat Jha
  3. Arthur S. Slutsky

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Several studies suggest a lower prevalence of smoking than expected among adults with coronavirus disease (COVID-19). We conducted logistic regression analyses of the UK Biobank prospective study of 0.5 million adults followed for an average of 11 years. Compared to women, men were more likely to be tested and to test positive. In sex-stratified analyses, current smokers had higher adjusted Odds Ratios (OR) for being tested (male OR 1.60, 95%CI 1.32-1.95 and female OR 1.50,1.21-.1.86). Current smokers were more slightly more likely than never smokers to test positive for COVID-19. Further examination of smoking as a risk factor for COVID-19 is required. These must take into account reverse causality, where smokers quit to avoid disease as well as prior diseases.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.05.20092445: (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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.05.05.20092445 on medRxiv