Abstract
Background: To improve research and care for patients with post-COVID-19 condition more insight into different subtypes of post-COVID-19 condition and their risk factors is urgently needed. We aimed to identify risk factors of post-COVID-19 condition in general and for specific symptom profiles.
Methods: This study is based on data collected within the Lifelines Coronavirus disease 2019 (COVID-19) cohort (N = 76 503). Mean pre- and post-SARS-CoV-2 infection symptom scores were compared to classify post-COVID-19 condition. Latent Profile Analysis was used to identify symptom profiles. Logistic and multinomial regression analyses were used to examine the association between demographic, lifestyle and health-related risk factors and post-COVID-19 condition, and symptom profiles, respectively.
Results: Of the 3465 participants having had COVID-19, 18.5% (n = 642) classified for post-COVID-19 condition. Four symptom profiles were identified: muscle pain, fatigue, cardiorespiratory and ageusia/anosmia. Female sex was a risk factor for the muscle pain and fatigue profiles. Being overweight or obese increased risk for all profiles, except the fatigue profile. Having a chronic disease increased the risk for all profiles except the ageusia/anosmia profile, with the cardiorespiratory profile being only significant in case of multimorbidity. Being unvaccinated increased risk of the ageusia/anosmia profile.
Conclusions: Findings from this study suggest that Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may trigger different pathophysiological mechanisms that may result in different subtypes of post-COVID-19 condition. These subtypes have shared and unique risk factors. Further characterization of symptom profiles and quantification of the individual and societal impact of specific symptom profiles are pressing challenges for future research.
Methods: This study is based on data collected within the Lifelines Coronavirus disease 2019 (COVID-19) cohort (N = 76 503). Mean pre- and post-SARS-CoV-2 infection symptom scores were compared to classify post-COVID-19 condition. Latent Profile Analysis was used to identify symptom profiles. Logistic and multinomial regression analyses were used to examine the association between demographic, lifestyle and health-related risk factors and post-COVID-19 condition, and symptom profiles, respectively.
Results: Of the 3465 participants having had COVID-19, 18.5% (n = 642) classified for post-COVID-19 condition. Four symptom profiles were identified: muscle pain, fatigue, cardiorespiratory and ageusia/anosmia. Female sex was a risk factor for the muscle pain and fatigue profiles. Being overweight or obese increased risk for all profiles, except the fatigue profile. Having a chronic disease increased the risk for all profiles except the ageusia/anosmia profile, with the cardiorespiratory profile being only significant in case of multimorbidity. Being unvaccinated increased risk of the ageusia/anosmia profile.
Conclusions: Findings from this study suggest that Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may trigger different pathophysiological mechanisms that may result in different subtypes of post-COVID-19 condition. These subtypes have shared and unique risk factors. Further characterization of symptom profiles and quantification of the individual and societal impact of specific symptom profiles are pressing challenges for future research.
| Original language | English |
|---|---|
| Pages (from-to) | 1163–1170 |
| Number of pages | 8 |
| Journal | European Journal of Public Health |
| Volume | 33 |
| Issue number | 6 |
| Early online date | 22-Aug-2023 |
| DOIs | |
| Publication status | Published - Dec-2023 |