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Risk factors for long COVID: analyses of 10 longitudinal studies and electronic health records in the UK
Ellen J. Thompson; Dylan M. Williams; Alex J. Walker; Ruth E. Mitchell; Claire L. Niedzwiedz; Tiffany C. Yang; Charlotte Huggins; Alex S. F. Kwong; Richard Silverwood; Giorgio Di Gessa; Ruth C. E. Bowyer; Kate Northstone; Bo Hou; Michael J. Green; Brian Dodgeon; Katie J. Doores; Emma Duncan; Frances M. K. Williams; - OpenSAFELY Collaborative; Andrew Steptoe; David J. Porteous; Rosemary R. C. McEachan; Laurie Tomlinson; Ben Goldacre; Praveetha Patalay; George B. Ploubidis; Srinivasa Vittal Katikireddi; Kate Tilling; Christopher T. Rentsch; Nicholas J. Timpson; Nishi Chaturvedi; Claire J. Steves.
Affiliation
  • Ellen J. Thompson; King's College London
  • Dylan M. Williams; University College London
  • Alex J. Walker; University of Oxford
  • Ruth E. Mitchell; University of Bristol
  • Claire L. Niedzwiedz; University of Glasgow
  • Tiffany C. Yang; Bradford Teaching Hospitals NHS Foundation Trust
  • Charlotte Huggins; University of Edinburgh
  • Alex S. F. Kwong; University of Bristol
  • Richard Silverwood; University College London
  • Giorgio Di Gessa; University College London
  • Ruth C. E. Bowyer; King's College London
  • Kate Northstone; University of Bristol
  • Bo Hou; Bradford Teaching Hospitals NHS Foundation Trust
  • Michael J. Green; University of Glasgow
  • Brian Dodgeon; University College London
  • Katie J. Doores; King's College London
  • Emma Duncan; King's College London
  • Frances M. K. Williams; King's College London
  • - OpenSAFELY Collaborative;
  • Andrew Steptoe; University College London
  • David J. Porteous; University of Edinburgh
  • Rosemary R. C. McEachan; Bradford Teaching Hospitals NHS Foundation Trust
  • Laurie Tomlinson; London School of Hygiene and Tropical Medicine
  • Ben Goldacre; University of Oxford
  • Praveetha Patalay; University College London
  • George B. Ploubidis; University College London
  • Srinivasa Vittal Katikireddi; University of Glasgow
  • Kate Tilling; University of Bristol
  • Christopher T. Rentsch; London School of Hygiene and Tropical Medicine
  • Nicholas J. Timpson; University of Bristol
  • Nishi Chaturvedi; University College London
  • Claire J. Steves; King's College London
Preprint de En | PREPRINT-MEDRXIV | ID: ppmedrxiv-21259277
ABSTRACT
BackgroundThe impact of long COVID is considerable, but risk factors are poorly characterised. We analysed symptom duration and risk factor from 10 longitudinal study (LS) samples and electronic healthcare records (EHR). MethodsSamples 6907 adults self-reporting COVID-19 infection from 48,901 participants in the UK LS, and 3,327 adults with COVID-19, were assigned a long COVID code from 1,199,812 individuals in primary care EHR. Outcomes for LS included symptom duration lasting 4+ weeks (long COVID) and 12+ weeks. Association with of age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma was assessed. ResultsIn LS, symptoms impacted normal functioning for 12+ weeks in 1.2% (mean age 20 years) to 4.8% (mean age 63 y) of COVID-19 cases. Between 7.8% (mean age 28 y) and 17% (mean age 58 y) reported any symptoms for 12+ weeks, and greater proportions for 4+ weeks. Age was associated with a linear increased risk in long COVID between 20 and 70 years. Being female (LS OR=1.49; 95%CI1.24-1.79; EHR OR=1.51 [1.41-1.61]), having poor pre-pandemic mental health (LS OR=1.46 [1.17-1.83]; EHR OR=1.57 [1.47-1.68]) and poor general health (LS OR=1.62 [1.25-2.09]; EHR OR=1.26; [1.18-1.35]) were associated with higher risk of long COVID. Individuals with asthma (LS OR=1.32 [1.07-1.62]; EHR OR=1.56 [1.46-1.67]), and overweight or obesity (LS OR=1.25 [1.01-1.55]; EHR OR=1.31 [1.21-1.42]) also had higher risk. Non-white ethnic minority groups had lower risk (LS OR=0.32 [0.22-0.47]), a finding consistent in EHR. . Few participants had been hospitalised (0.8-5.2%). ConclusionLong COVID is associated with sociodemographic and pre-existing health factors. Further investigations into causality should inform strategies to address long COVID in the population.
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Texte intégral: 1 Collection: 09-preprints Base de données: PREPRINT-MEDRXIV Type d'étude: Cohort_studies / Experimental_studies / Observational_studies / Prognostic_studies / Rct Langue: En Année: 2021 Type de document: Preprint
Texte intégral: 1 Collection: 09-preprints Base de données: PREPRINT-MEDRXIV Type d'étude: Cohort_studies / Experimental_studies / Observational_studies / Prognostic_studies / Rct Langue: En Année: 2021 Type de document: Preprint