| Title: | Psychosocial predictors of COVID-19 infection in UK biobank (N = 104 201) |
| Journal: | Journal of Public Health |
| Published: | 12 Apr 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37144429/ |
| DOI: | https://doi.org/10.1093/pubmed/fdad009 |
| URL: | https://academic.oup.com/jpubhealth/advance-article-pdf/doi/10.1093/pubmed/fdad009/49865080/fdad009.pdf |
Publication 11328
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Abstract
BACKGROUND: Since the outbreak of COVID-19, data on its psychosocial predictors are limited. We therefore aimed to explore psychosocial predictors of COVID-19 infection at the UK Biobank (UKB).</p>
METHODS: This was a prospective cohort study conducted among UKB participants.</p>
RESULTS: The sample size was N = 104 201, out of which 14 852 (14.3%) had a positive COVID-19 test. The whole sample analysis showed significant interactions between sex and several predictor variables. Among females, absence of college/university degree [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.45-1.66] and socioeconomic deprivation (OR 1.16 95% CI 1.11-1.21) were associated with higher odds of COVID-19 infection, while history of psychiatric consultation (OR 0.85 95% CI 0.77-0.94) with lower odds. Among males, absence of college/university degree (OR 1.56, 95% CI 1.45-1.68) and socioeconomic deprivation (OR 1.12, 95% CI 1.07-1.16) were associated with higher odds, while loneliness (OR 0.87, 95% CI 0.78-0.97), irritability (OR 0.91, 95% CI 0.83-0.99) and history of psychiatric consultation (OR 0.85, 95% CI 0.75-0.97) were associated with lower odds.</p>
CONCLUSION: Sociodemographic factors predicted the odds of COVID-19 infection equally among male and female participants, while psychological factors had differential impacts.</p>
3 Authors
- Victor M Wauye
- Frederick K Ho
- Donald M Lyall
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