Spurious Correlation? A review of the relationship between Vitamin D and Covid-19 infection and mortality

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

The study reviews the evidence presented in a recent study linking vitamin D levels and Covid-19 infection and mortality. It was argued that correlation alone may not be useful in establishing a relationship between vitamin D levels and Covid-19 infections and mortality. Appropriate controls need to be included for improved understanding of the relationship. We proposed life expectancy as a potential control. Including this control in a regression model, we find that vitamin D levels are not a statistically significant predictor of Covid-19 infections or mortality. Life expectancy, on the other hand, was found to be statistically significant predictor of infections and mortality at country level.

Article activity feed

  1. SciScore for 10.1101/2020.05.25.20110338: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    CovidMortality is number of deaths attributed to Covid-19 per million population in each country.
    CovidMortality
    suggested: None

    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.