An Examination of Anthropometric and Laboratory Parameters of Metabolic Dysfunction-Associated Steatotic Liver Disease in Children and Adolescents with Obesity

Aim: This study aimed to investigate the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) in children and adolescents with obesity and to identify the anthropometric and laboratory parameters predictive of its development. Materials and Methods: In the study, a total of 289 children and adolescents between the ages of 8 and 18, who were diagnosed with obesity, were included. Data on anthropometric measurements, liver function tests, lipid parameters, fasting blood glucose (FBG) and fasting insulin levels, thyroid function tests, and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) were obtained from the medical records of the participants. Participants were divided into two groups according to the presence or absence of hepatic steatosis on ultrasonography (USG). Logistic regression analysis was performed to assess the ability of anthropometric and laboratory data to predict MASLD. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the performance of waist circumference (WC), waist-to-height ratio (WHtR), Tri-ponderal Mass Index (TMI), Alanine Aminotransferase (ALT), and Low-Density Lipoprotein Cholesterol (LDL-C) in predicting ultrasonographically detected MASLD. Results: Hepatic steatosis was detected in 40.4% (n = 117) of the children with obesity. The prevalence of hepatic steatosis was significantly higher in male participants than in female participants (p =0.001). In the comparison of the groups in terms of anthropometric and laboratory parameters, weight- Standard Deviation Score (SDS), Body Mass Index (BMI)-SDS, (TMI), WC, WHtR and fasting insulin, (LDL-C), Triglycerides (TG), ALT and Aspartate Aminotransferase (AST) levels were found to be significantly higher in Group 1 (p <0.05). BMI-SDS showed the best overall performance for predicting pediatric MASLD, whereas ALT was consistently identified as the strongest independent biochemical predictor. Conclusions: In children and adolescents with obesity, ALT was consistently associated with MASLD across multivariable models, while BMI-SDS was shown to bea significant predictor of MASLD when evaluated alongside biochemical parameters. TMI showed alternative discriminatory performance similar to that of BMI-SDS in ROC analysis, although both exhibited limited discriminatory ability. These findings suggest that TMI may have potential clinical utility as an easily calculated anthropometric indicator; however, further studies are needed to validate its role in MASLD screening.