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Risk factors for positive and negative COVID-19 tests: a cautious and in-depth analysis of UK biobank data.
Chadeau-Hyam, Marc; Bodinier, Barbara; Elliott, Joshua; Whitaker, Matthew D; Tzoulaki, Ioanna; Vermeulen, Roel; Kelly-Irving, Michelle; Delpierre, Cyrille; Elliott, Paul.
  • Chadeau-Hyam M; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
  • Bodinier B; MRC Centre for Environment and Health, Imperial College, London, UK.
  • Elliott J; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
  • Whitaker MD; MRC Centre for Environment and Health, Imperial College, London, UK.
  • Tzoulaki I; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
  • Vermeulen R; MRC Centre for Environment and Health, Imperial College, London, UK.
  • Kelly-Irving M; Royal Surrey County Hospital, Guildford, Surrey, UK.
  • Delpierre C; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
  • Elliott P; MRC Centre for Environment and Health, Imperial College, London, UK.
Int J Epidemiol ; 49(5): 1454-1467, 2020 10 01.
Article in English | MEDLINE | ID: covidwho-1066329
ABSTRACT

BACKGROUND:

The recent COVID-19 outbreak has generated an unprecedented public health crisis, with millions of infections and hundreds of thousands of deaths worldwide. Using hospital-based or mortality data, several COVID-19 risk factors have been identified, but these may be confounded or biased.

METHODS:

Using SARS-CoV-2 infection test data (n = 4509 tests; 1325 positive) from Public Health England, linked to the UK Biobank study, we explored the contribution of demographic, social, health risk, medical and environmental factors to COVID-19 risk. We used multivariable and penalized logistic regression models for the risk of (i) being tested, (ii) testing positive/negative in the study population and, adopting a test negative design, (iii) the risk of testing positive within the tested population.

RESULTS:

In the fully adjusted model, variables independently associated with the risk of being tested for COVID-19 with odds ratio >1.05 were male sex; Black ethnicity; social disadvantage (as measured by education, housing and income); occupation (healthcare worker, retired, unemployed); ever smoker; severely obese; comorbidities; and greater exposure to particulate matter (PM) 2.5 absorbance. Of these, only male sex, non-White ethnicity and lower educational attainment, and none of the comorbidities or health risk factors, were associated with testing positive among tested individuals.

CONCLUSIONS:

We adopted a careful and exhaustive approach within a large population-based cohort, which enabled us to triangulate evidence linking male sex, lower educational attainment and non-White ethnicity with the risk of COVID-19. The elucidation of the joint and independent effects of these factors is a high-priority area for further research to inform on the natural history of COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Confounding Factors, Epidemiologic / COVID-19 Testing / COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Limits: Female / Humans / Male / Middle aged Country/Region as subject: Europa Language: English Journal: Int J Epidemiol Year: 2020 Document Type: Article Affiliation country: Ije

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Confounding Factors, Epidemiologic / COVID-19 Testing / COVID-19 Type of study: Cohort study / Diagnostic study / Observational study / Prognostic study Limits: Female / Humans / Male / Middle aged Country/Region as subject: Europa Language: English Journal: Int J Epidemiol Year: 2020 Document Type: Article Affiliation country: Ije