ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.
Accelerating the Search for Interventions Aimed at Expanding the Health Span in Humans: The Role of Epidemiology
The Journals of Gerontology: Series A | November 13, 2019 | Volume: 75 | Issue: 1 | Pages: 77-86
Abstract Background Extensive work in basic and clinical science suggests that biological mechanisms of aging are causally related to the development of disease and disability in late life. Modulation of the biological mechanisms of aging can extend both life span and health span in animal models, but translation to humans has been slow. Methods Summary of workshop proceedings from the 2018–2019 Epidemiology of Aging Workshop hosted by the Intramural Research Program at the National Institute on Aging. Results Epidemiologic studies play a vital role to progress in this field, particularly in evaluating new risk factors and measures of biologic aging that may influence health span, as well as developing relevant outcome measures that are robust and relevant for older individuals. Conclusions Appropriately designed epidemiological studies are needed to identify targets for intervention and to inform study design and sample size estimates for future clinical trials designed to promote health span.
Correction: The complex genetics of gait speed: genome-wide meta-analysis approach