The association of obesity-related traits on COVID-19 severity and hospitalization is affected by socio-economic status: a multivariable Mendelian randomization study

  1. Brenda Cabrera-Mendoza
  2. Frank R Wendt
  3. Gita A Pathak
  4. Flavio De Angelis
  5. Antonella De Lillo
  6. Dora Koller
  7. Renato Polimanti

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Abstract

Background

Due to its large impact on human health, socio-economic status (SES) could at least partially influence the established association between obesity and coronavirus disease 2019 (COVID-19) severity. To estimate the independent effect of body size and SES on the clinical manifestations of COVID-19, we conducted a Mendelian randomization (MR) study.

Methods

Applying two-sample MR approaches, we evaluated the effects of body mass index (BMI, n = 322 154), waist circumference (WC, n = 234 069), hip circumference (n = 213 019) and waist–hip ratio (n = 210 088) with respect to three COVID-19 outcomes: severe respiratory COVID-19 (cases = 8779, controls = 1 000 875), hospitalized COVID-19 (cases = 17 992, controls = 1 810 493) and COVID-19 infection (cases = 87 870, controls = 2 210 804). Applying a multivariable MR (MVMR) approach, we estimated the effect of these anthropometric traits on COVID-19 outcomes accounting for the effect of SES assessed as household income (n = 286 301).

Results

BMI and WC were associated with severe respiratory COVID-19 [BMI: odds ratio (OR) = 1.51, CI = 1.24–1.84, P = 3.01e-05; WC: OR = 1.48, 95% CI = 1.15–1.91, P = 0.0019] and hospitalized COVID-19 (BMI: OR = 1.50, 95% CI = 1.32–1.72, P = 8.83e-10; WC: OR = 1.41, 95% CI = 1.20–1.67, P = 3.72e-05). Conversely, income was associated with lower odds of severe respiratory (OR = 0.70, 95% CI = 0.53–0.93, P = 0.015) and hospitalized COVID-19 (OR = 0.78, 95% CI = 0.66–0.92, P = 0.003). MVMR analyses showed that the effect of these obesity-related traits on increasing the odds of COVID-19 negative outcomes becomes null when accounting for income. Conversely, the association of income with lower odds of COVID-19 negative outcomes is not affected when including the anthropometric traits in the multivariable model.

Conclusion

Our findings indicate that SES contributes to the effect of obesity-related traits on COVID-19 severity and hospitalization.

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  1. Version published to 10.1093/ije/dyac129
  2. ScreenIT

    SciScore for 10.1101/2021.06.08.21258587: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisOur primary MR analysis was conducted using the inverse variance weighted (IVW) approach, because it provides the highest statistical power [37].

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The MVMR analysis was conducted using the MendelianRandomization R package [39].
    MendelianRandomization
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The limitations of the present study should be acknowledged. First, this study was conducted using data generated from participants of European descent. Accordingly, the results obtained may not be generalization to populations with other ancestral origins. Further research is necessary to evaluate the effect of anthropometric and socioeconomic traits in populations with diverse ancestral background. Second, in this study we could not evaluate the presence of sex-specific effects as large-scale datasets informative of sex-specific COVID-19 susceptibility are not available at this time. There are known sex differences in the mechanisms underlying the association of SES with body size and composition [14,61]. Therefore, future sex-stratified studies are required to understand the processes linking these traits with COVID-19 outcomes. Third, although we conducted multiple sensitivity analyses, we cannot discard completely the influence of potential confounders in our results. Therefore, complementary studies are needed to confirm and further explore the findings here reported.

    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.
    • Thank you for including a protocol registration statement.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.06.08.21258587v1 on medRxiv