Sex differences in the prospective associations of long COVID with incident cardiometabolic and respiratory diseases from a population-based longitudinal study in Michigan
Year: 2026
Type: article
Study design: Observational Study
Abstract: Aim: To evaluate longitudinal associations of Long COVID with incident cardiometabolic and respiratory outcomes among adults. Methods: We used the Michigan COVID-19 Recovery Surveillance Study, a population-based longitudinal study of adults with PCR-confirmed COVID-19 in Michigan. We included adults with COVID-19 who responded to the baseline (data collection: 06/2020-12/2022) and follow-up survey (data collection: 01/2022-11/2023) and were free of each outcome at baseline. Long COVID was defined as recovery taking ≥90 days after infection or no recovery. We evaluated four self-reported incident outcomes: 1) diabetes, 2) hypertension, 3) heart disease, and 4) asthma. We conducted modified Poisson models to examine longitudinal exposures-outcomes association separately, overall and stratified by sex. Results: Long COVID was associated with higher past-year incidence of heart disease and asthma in multivariable models, when we stratified the models by sex, we observed statistically significant associations for females only between Long COVID and all measured outcomes, except hypertension (Females = diabetes: Incidence Risk Ratio (IRR) = 2.33 95% CI 1.15,4.73; heart disease: IRR = 1.98 95% CI 1.10,3.57; asthma: IRR = 2.99 95% CI 1.60,5.57). Conclusion: Study findings reinforce the importance of preventing Long COVID and to monitor sequelae including incident disease outcomes for those who are experiencing Long COVID.
Source: Preventive Medicine Reports
Institutions: University of Michigan, CDC Foundation
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,610
Funders: U.S. Department of Health and Human Services, University of Michigan, Michigan Department of Health and Human Services, Centers for Disease Control and Prevention Foundation, Centers for Disease Control and Prevention, Michigan Institute for Data Science, University of Michigan, Rogel Cancer Center, University of Michigan
Award: G1589624531
OpenAlex ID: W7135390064