Long COVID and Incident Multimorbidity in the United States: Evidence from a Nationally Representative Longitudinal Study

Background/Objectives: Long COVID has been associated with elevated risks of individual chronic conditions, but its association with the transition to multimorbidity remains unclear. This study aims to examine whether retrospective COVID-19 status was associated with incident multimorbidity among U.S. adults. Methods: We analyzed Panel 24 of the Medical Expenditure Panel Survey (MEPS; 2019–2022), including 4356 individuals free of multimorbidity at baseline. COVID-19 exposure was classified as Long COVID, COVID-19-recovered, or no COVID-19. Survey-weighted logistic regression estimated associations between retrospective COVID-19 status and incident cross-domain multimorbidity, and generalized estimating equations assessed healthcare expenditures, health-related quality of life, and inpatient utilization. Results: Incident MM occurred in 106 participants: 17 with Long COVID, 41 COVID-19-recovered, and 48 with no COVID-19. In the primary model (4239 participants; 105 events), Long COVID was associated with higher odds of incident MM than no COVID-19 (OR 2.34; 95% CI, 1.14–4.79); the estimate for COVID-19-recovered participants was OR 1.71 (95% CI, 1.01–2.92). Fully adjusted and Firth estimates were directionally consistent. Cardiometabolic plus respiratory MM predominated (79/106). COVID-status-by-year interactions were not significant for total expenditures, out-of-pocket expenditures, physical or mental health scores, or inpatient stays. Conclusions: Retrospectively classified Long COVID was associated with incident cross-domain MM recorded during follow-up, but temporal ordering cannot be established, and sparse events limit precision. Replication with prospectively timed exposure and diagnosis data is needed.

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Publication Details

Journal
Healthcare
Published
2026-10-14
DOI
https://doi.org/10.3390/healthcare14203427
Primary Topic
Long-Term Effects of COVID-19
Type
article
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article

Long COVID and Incident Multimorbidity in the United States: Evidence from a Nationally Representative Longitudinal Study

Logan Cowan, Timothy Kizza, Gulzar H. Shah, Emmanuel U. Azu et al.
Healthcare
Long-Term Effects of COVID-19
article

Long COVID and Incident Multimorbidity in the United States: Evidence from a Nationally Representative Longitudinal Study

Logan Cowan, Timothy Kizza, Gulzar H. Shah, Emmanuel U. Azu, Ibrahim Alliu, Subash Thapa
article en

Abstract

Background/Objectives: Long COVID has been associated with elevated risks of individual chronic conditions, but its association with the transition to multimorbidity remains unclear. This study aims to examine whether retrospective COVID-19 status was associated with incident multimorbidity among U.S. adults. Methods: We analyzed Panel 24 of the Medical Expenditure Panel Survey (MEPS; 2019–2022), including 4356 individuals free of multimorbidity at baseline. COVID-19 exposure was classified as Long COVID, COVID-19-recovered, or no COVID-19. Survey-weighted logistic regression estimated associations between retrospective COVID-19 status and incident cross-domain multimorbidity, and generalized estimating equations assessed healthcare expenditures, health-related quality of life, and inpatient utilization. Results: Incident MM occurred in 106 participants: 17 with Long COVID, 41 COVID-19-recovered, and 48 with no COVID-19. In the primary model (4239 participants; 105 events), Long COVID was associated with higher odds of incident MM than no COVID-19 (OR 2.34; 95% CI, 1.14–4.79); the estimate for COVID-19-recovered participants was OR 1.71 (95% CI, 1.01–2.92). Fully adjusted and Firth estimates were directionally consistent. Cardiometabolic plus respiratory MM predominated (79/106). COVID-status-by-year interactions were not significant for total expenditures, out-of-pocket expenditures, physical or mental health scores, or inpatient stays. Conclusions: Retrospectively classified Long COVID was associated with incident cross-domain MM recorded during follow-up, but temporal ordering cannot be established, and sparse events limit precision. Replication with prospectively timed exposure and diagnosis data is needed.

HealthcareVol. 14(20)
Georgia Southern University (US)
Good health and well-being
Openalex Percentile: Top 14%
Long-Term Effects of COVID-19
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