Obesity, walking pace and risk of severe COVID-19 and mortality: analysis of UK Biobank

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Abstract

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  1. SciScore for 10.1101/2020.07.10.20150003: (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:
    This study has several important limitations. As testing in the UK has not been universal, it is not possible determine who in the population has been exposed to SARS-CoV-2; linkage will therefore only highlight those that have developed severe disease. Therefore the findings should be interpreted as the overall risk to date in the UK Biobank cohort of being exposed to SARS-CoV-2 and subsequently developing severe COVID-19. Nevertheless, the risk of severe COVID-19 with obesity reported in this study is within the range of early findings reported in other studies (10, 12, 13). As this is an evolving pandemic, data should be interpreted as relating to the first wave of the pandemic in England. Lastly, the risk factors included in this study were measured before the pandemic and therefore do not necessarily reflect participants current health status. However, both BMI and measures of physical fitness have been shown to be stable over time in adults, particularly over relatively short time frames such as a decade (14, 15). The current findings therefore should be interpreted as highlighting the potential importance of simple measures of physical fitness, such as self-reported waking pace, in addition to BMI as potential risk factors for severe COVID-19. In conclusion, as countries start to ease governmental restrictions to stop the spread of SARS-CoV-2 infection, identifying individuals at greatest risk of developing severe disease is crucial. This study highlights BMI and walki...

    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. SciScore for 10.1101/2020.07.10.20150003: (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

    Software and Algorithms
    SentencesResources
    Methods For this analysis, we used UK Biobank (https://www.ukbiobank.ac.uk/), a large prospective cohort of middle-aged adults designed to support health research (8).
    https://www.ukbiobank.ac.uk/
    suggested: (UK Biobank, SCR_012815)

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

    • This study has several important limitations.
    • As testing in the UK has not been universal, it is not possible determine who in the population has been exposed to SARS-CoV-2; linkage will therefore only highlight those that have developed severe disease.
    • Therefore the findings should be interpreted as the overall risk to date in the UK Biobank cohort of being exposed to SARS-CoV-2 and subsequently developing severe COVID-19.
    • Nevertheless, the risk of severe COVID-19 with obesity reported in this study is within the range of early findings reported in other studies


    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).


    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.