Body composition measurement and diabetes – A new perspective on development of antibodies after SARS-CoV-2 booster vaccination
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose: In patients with SARS-CoV-2 infection overweight and diabetes are associated with poor prognosis. Therefore, effectiveness and tolerance of booster vaccination against SARS-CoV-2 has to be ensured. We examined the impact of overweight and diabetes on anti-SARS-CoV-2-titers and the incidence of side effects after booster vaccination. Methods: We performed a cross-sectional study with consecutive recruitment and convenience sampling of 100 participants vaccinated three times against SARS-CoV-2. Anti-SARS-CoV-2-titers, immunological parameters and biochemical markers of glucose metabolism were measured. Prevalence of vaccination side effects was assessed by personal interview. Moreover, metabolic status was assessed by performance of body composition measurement and body impedance analysis. The glycemic and metabolic parameters were correlated with the anti-SARS-CoV-2-titers and the incidence of side effects. The results were compared between patient with and without overweight and diabetes. Results: = .28). Moreover, the investigated glycemic parameters and parameters of the body composition measurement and body impedance analysis did not present any correlation with the antibody levels. Furthermore, we could reveal that vaccination side effects are more likely to occur in participants without diabetes (OR 2.9 (95%-CI: 0.5-4.3, p.04)). Conclusions: Overweight and diabetes are not associated with lower anti-SARS-CoV-2-titers after booster vaccination. Parameters of the body composition and body impedance analysis did not reveal any further association regarding development of anti-SARS-CoV-2-titers. Vaccination side effects are more likely to occur in participants without diabetes. Supplementary Information: The online version contains supplementary material available at 10.1007/s40200-025-01699-1.
Institutions: Essen University Hospital, University of Duisburg-Essen
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,990
Funder: Universitätsklinikum Essen
OpenAlex ID: W4415535892
