The role of body composition, cardiometabolic parameters, and resting substrate oxidation in protecting against metabolic syndrome in adolescents with obesity

Mattia D'Alleva^1*Stefano Lazzer¹Maria De Martino¹Lara Mari¹Enrico Rejc¹Simone Zaccaron¹Jacopo Stafuzza¹Miriam Isola¹Adele Bondesan²Diana Caroli²Francesca Frigerio²Laura Abbruzzese²Enrica Ventura²Alessandro Sartorio²

• ¹University of Udine, Udine, Italy
• ²Experimental Laboratory for Auxo-Endocrinological Research, Piancavallo, Italy

The aetiology of metabolic syndrome (MetS) in young people involves a complex interplay between lifestyle, body composition, and cardiometabolic risk factors. The present study aimed to explore the relationships between anthropometric characteristics, body composition, cardiometabolic parameters and resting substrate metabolism in the development of MetS in severely adolescents with obesity.Methods: Seven hundred and thirty adolescents with obesity (mean age: 14.6 ± 2.1 years, BMI > 97 th percentile for gender and age) were included in this study. Body composition analysis was obtained using tetrapolar bioelectrical impedance analysis (BIA), while resting substrate oxidation was measured using an indirect calorimeter.Results: MetS was present in 27% of the participants. Compared to those without MetS, adolescents with MetS had significantly higher body mass (+15 kg, P<0.001), fat-free mass (FFM; +6 kg, P<0.001), fat mass (+9 kg, P<0.001), carbohydrate oxidation at rest (CHO; +0.02 g•min⁻¹, P=0.015), and Homeostasis Model Assessment for Insulin Resistance (HOMA-IR; +0.8, P<0.001).In adjusted-univariate logistic regression, HOMA-IR (OR: 1.22; 95% CI: 1.12-1.34, P<0.001) was associated with higher odds of MetS. Conversely, higher FFM percentage (OR: 0.96; 95% CI: 0.93-0.99, P=0.003) and HDL cholesterol levels (OR: 0.83; 95% CI: 0.81-0.86, P=0.003) were protective.In adolescents with severe obesity, resting carbohydrate oxidation and HOMA-IR emerged as independent risk factors for MetS, offering additional insight beyond conventional anthropometric and lipid indicators. Conversely, higher FFM and HDL cholesterol levels appeared to exert a protective effect. These findings underscore the importance of incorporating metabolic and body composition variables into MetS risk models and support the promotion of targeted interventions, such as endurance and resistance training, to address modifiable risk factors and reduce the likelihood of developing MetS.