Factors Associated with Long COVID Recovery among US Adults - 28/08/24

Abstract |
Background |
While factors associated with long COVID (LC) continue to be illuminated, little is known about recovery. This study used national survey data to assess factors associated with recovery from LC.
Methods |
We used data from the 2022 National Health Interview Survey, a cross-sectional sample of noninstitutionalized US adults. Survey analysis was used to account for oversampling and nonresponse bias and to obtain nationally representative estimates. A multivariable logistic regression model was used to identify potential predictors of LC recovery.
Results |
Among those reporting ever having COVID-19, 17.7% or an estimated 17.5 million American adults reported ever having LC, and among those with LC, 48.5% or an estimated 8.5 million reported having recovered. Multivariable logistic regression analysis showed that Hispanic adults were significantly more likely than White adults to report recovery from LC. At the same time, those with severe COVID-19 symptoms and those who had more than a high school degree, were aged 40 years or older, or were female were less likely to report recovery.
Conclusion |
Significant variations in LC recovery were noted across age, sex, race and ethnicity, education, and severity of COVID-19 symptoms. Further work is needed to elucidate the causes of these differences and identify strategies to increase recovery rates.
Le texte complet de cet article est disponible en PDF.Keywords : COVID-19, Long COVID, Recovery
Plan
Funding: This study was supported in part by funds from Fred Cohen and Carolyn Klebanoff. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. |
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Conflicts of Interest: In the past 3 years, HK received options for Element Science and Identifeye and payments from F-Prime for advisory roles. He is a co-founder of, and holds equity in, Hugo Health, Refactor Health, and Ensight-AI, Inc. He is associated with research contracts through Yale University from Janssen, Kenvue, and Pfizer. AI co-founded RIGImmune, Xanadu Bio, and PanV, and is a member of the Board of Directors of Roche Holding Ltd and Genentech. The other authors have no potential conflicts of interest to report. |
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Authorship: All authors had access to the data and played a role in writing the manuscript. KMS: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing - original draft, review, & editing; RMS: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing - original draft, review, & editing; MS: Conceptualization, Investigation, Methodology, Project administration, Supervision, Validation, Writing - review & editing; YW: Methodology, Writing - review & editing; PB: Writing - review & editing; AI: Writing - review & editing; HMK: Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Validation, Writing - review & editing. |
Vol 137 - N° 9
P. 896-899 - septembre 2024 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.