Risk factors for developing COVID-19: a population-based longitudinal study (COVIDENCE UK)
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Risk factors for severe COVID-19 include older age, male sex, obesity, black or Asian ethnicity and underlying medical conditions. Whether these factors also influence susceptibility to developing COVID-19 is uncertain.
Methods
We undertook a prospective, population-based cohort study (COVIDENCE UK) from 1 May 2020 to 5 February 2021. Baseline information on potential risk factors was captured by an online questionnaire. Monthly follow-up questionnaires captured incident COVID-19. We used logistic regression models to estimate multivariable-adjusted ORs (aORs) for associations between potential risk factors and odds of COVID-19.
Results
We recorded 446 incident cases of COVID-19 in 15 227 participants (2.9%). Increased odds of developing COVID-19 were independently associated with Asian/Asian British versus white ethnicity (aOR 2.28, 95% CI 1.33 to 3.91), household overcrowding (aOR per additional 0.5 people/bedroom 1.26, 1.11 to 1.43), any versus no visits to/from other households in previous week (aOR 1.31, 1.06 to 1.62), number of visits to indoor public places (aOR per extra visit per week 1.05, 1.02 to 1.09), frontline occupation excluding health/social care versus no frontline occupation (aOR 1.49, 1.12 to 1.98) and raised body mass index (BMI) (aOR 1.50 (1.19 to 1.89) for BMI 25.0–30.0 kg/m 2 and 1.39 (1.06 to 1.84) for BMI >30.0 kg/m 2 versus BMI <25.0 kg/m 2 ). Atopic disease was independently associated with decreased odds (aOR 0.75, 0.59 to 0.97). No independent associations were seen for age, sex, other medical conditions, diet or micronutrient supplement use.
Conclusions
After rigorous adjustment for factors influencing exposure to SARS-CoV-2, Asian/Asian British ethnicity and raised BMI were associated with increased odds of developing COVID-19, while atopic disease was associated with decreased odds.
Trial registration number
ClinicalTrials.gov Registry ( NCT04330599 ).
Article activity feed
-
-
SciScore for 10.1101/2021.03.27.21254452: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Sponsorship, registration, ethics and reporting: The study was sponsored by Queen Mary University of London and approved by Leicester South Research Ethics Committee (ref 20/EM/0117). Randomization not detected. Blinding not detected. Power Analysis Sample size: The sample size required to detect an odds ratio of at least 1.08 (effect size) for a binary exposure variable with maximum variability (probability = 0.50 changing to 0.52) and correlated with other variables in the model (R2 = 0.5), with a power of 90% using a one-sided test with 5% significance level was estimated as 10,721, using the ‘powerlog’ program in Stata 14.2 (College Station, TX). Sex as a … SciScore for 10.1101/2021.03.27.21254452: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Sponsorship, registration, ethics and reporting: The study was sponsored by Queen Mary University of London and approved by Leicester South Research Ethics Committee (ref 20/EM/0117). Randomization not detected. Blinding not detected. Power Analysis Sample size: The sample size required to detect an odds ratio of at least 1.08 (effect size) for a binary exposure variable with maximum variability (probability = 0.50 changing to 0.52) and correlated with other variables in the model (R2 = 0.5), with a power of 90% using a one-sided test with 5% significance level was estimated as 10,721, using the ‘powerlog’ program in Stata 14.2 (College Station, TX). Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources To produce patient-level covariates for each class of medications investigated, participant answers were mapped to drug classes listed on the British National Formulary (BNF) or the DrugBank and Electronic Medicines Compendium databases if not explicitly listed on the BNF; further details of the computational methods used to achieve this are presented in supplementary Appendix. DrugBanksuggested: (DrugBank, RRID:SCR_002700)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:One limitation of previous studies investigating ethnic variation in COVID-19 risk is that they did not adjust for behaviours influencing SARS-CoV-2 exposure, such as visits to other households and indoor public places. In our study, increased risk of developing COVID-19 in people of Asian/Asian British ethnic origin was not explained by such behaviours, nor by social deprivation, domestic overcrowding, occupation, BMI, or comorbidities. There is therefore an urgent need to explain ethnic disparities in risk of developing COVID-19 so that preventive strategies can be deployed. The association between raised BMI and increased susceptibility to COVID-19 that we found is consistent with studies identifying obesity as a risk factor for both susceptibility to, and severe outcomes of, COVID-19.4,17,18 It would appear that immune dysregulation associated with obesity may increase susceptibility to infection as well as disease severity. By contrast, a number of established risk factors for severe and fatal disease, including older age, male sex and underlying conditions such as diabetes, heart disease, COPD and hypertension, were not associated with risk of developing COVID-19 in our study. In keeping with reports from the UK7 and elsewhere,8 we found younger age to be associated with increased risk of developing COVID-19 in crude and minimally-adjusted models. However, this association did not persist after adjustment for multiple potential confounders, including behaviours related ...
Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
Identifier Status Title NCT04330599 Recruiting Longitudinal Population-based Observational Study of COVID-1… 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.
-
-