Comorbidity Risk Factors Contributing to COVID-19 Related Deaths in Florida, March 1, 2020-January 16, 2021

  1. Ursula K. Weiss
  2. Jason D. Maynard
  3. Katherine McDaniel
  4. Alyssa Cohen
  5. Marie Bailey
  6. Scott A. Rivkees

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Abstract

Objectives

To assess the association of specific comorbid conditions to COVID-19 deaths in Florida among decedents 16 to 64 years of age.

Methods

This report uses Florida vital statistics death data over the period of March 1, 2020 through January 16, 2021, to estimate the effects of comorbid conditions on COVID-19 mortality for decedents 16 to 64 years of age. All cases of COVID-19 death occurring in Florida, regardless of resident status, were evaluated. The comorbidities, or contributing causes of death, identified in this report include Down syndrome, asthma, diabetes, pulmonary fibrosis, obesity, dementia, immunodeficiency, kidney disease, chronic obstructive pulmonary disease, hypertension, heart disease, and chronic liver disease and cirrhosis. The study uses a binary logistic regression to examine the relationship between COVID-19 and non-COVID-19 death and contributing causes of death based on information in the death record. Odds ratios were calculated as a residual of the logistic regression.

Results

Among COVID-19 deaths, Down syndrome was 15.26 times more likely to be a contributing cause of death compared to non-COVID-19 deaths followed by asthma (OR 7.74), diabetes (OR 6.11), pulmonary fibrosis (OR 5.13), obesity (OR 4.66), dementia (OR 4.51), immunodeficiency (OR 2.49), and kidney disease (OR 2.13). Chronic liver disease and cirrhosis (OR 0.95) and cancer (OR 0.79) had lower odds of being a contributing cause of death.

Conclusions

Heart disease, chronic liver disease and cirrhosis, and cancer were not risk factors for death from COVID-19 among decedents. Additional studies are needed to elucidate associations between race/ethnicity, socioeconomic status, and behavioral factors.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.14.21255434: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationA simple random sample of the non-COVID-19 group was used to create a 10:1 ratio sample size, non-COVID-19 to COVID-19, respectively.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    SAS (version 9.4; SAS Institute) was used to conduct all analyses.
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    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:
    The findings in this report are subject to some limitations. In Florida, coding of underlying and contributing causes of death are conducted by the National Center for Health Statistics. Thus, there could be a delay in the reporting of COVID-19-related deaths. Odds ratio analysis was conducted on decedents between 16-64 years or age, which might skew results to those contributing causes of death more closely associated with older decedents. Also, the 10:1 ratio used for this study produced slight over-dispersion, meaning variance was slightly higher than it would have been with a smaller ratio. Our analysis does not consider the impact of racial and ethnic disparities on contributing causes associated with COVID-19-related deaths and does not consider geographic differences such as proximity to hospitals, which could also impact contributing causes associated with COVID-19-related deaths.

    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 10.1101/2021.04.14.21255434 on medRxiv