Thompson, Ellen J; Williams, Dylan M; Walker, Alex J; Mitchell, Ruth E; Niedzwiedz, Claire L; Yang, Tiffany C; Huggins, Charlotte F; Kwong, Alex SF; Silverwood, Richard J; Di Gessa, Giorgio; +22 more... Bowyer, Ruth CE; Northstone, Kate; Hou, Bo; Green, Michael J; Dodgeon, Brian; Doores, Katie J; Duncan, Emma L; Williams, Frances MK; OpenSAFELY Collaborative; Steptoe, Andrew; Porteous, David J; McEachan, Rosemary RC; Tomlinson, Laurie; Goldacre, Ben; Patalay, Praveetha; Ploubidis, George B; Katikireddi, Srinivasa Vittal; Tilling, Kate; Rentsch, Christopher T; Timpson, Nicholas J; Chaturvedi, Nishi; Steves, Claire J; (2022) Long COVID burden and risk factors in 10 UK longitudinal studies and electronic health records. Nature Communications, 13 (1). 3528-. DOI: https://doi.org/10.1038/s41467-022-30836-0
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Abstract
The frequency of, and risk factors for, long COVID are unclear among community-based individuals with a history of COVID-19. To elucidate the burden and possible causes of long COVID in the community, we coordinated analyses of survey data from 6907 individuals with self-reported COVID-19 from 10 UK longitudinal study (LS) samples and 1.1 million individuals with COVID-19 diagnostic codes in electronic healthcare records (EHR) collected by spring 2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for 12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic general and mental health, overweight/obesity, and asthma were associated with prolonged symptoms in both LS and EHR data, but findings for other factors, such as cardio-metabolic parameters, were inconclusive.
Item Type | Article |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Non-Communicable Disease Epidemiology |
Research Centre |
Covid-19 Research EHR Research Group Centre for the Mathematical Modelling of Infectious Diseases |
PubMed ID | 35764621 |
Elements ID | 181008 |