ESPE2023 Poster Category 1 Fat, Metabolism and Obesity (97 abstracts)
1Unit of Pediatric Endocrinology and Metabolism 2nd Department of Pediatrics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, AHEPA University Hospital, Thessaloniki, Greece. 2Unit of Pediatric Oncology-Hematology, 2nd Department of Pediatrics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, AHEPA University Hospital, Thessaloniki, Greece
Objectives: Modern treatments lead to increased survival rates from childhood cancer. Childhood cancer survivors (CCS) are a growing population group, which is at high risk for cardiometabolic disorders including metabolic syndrome, type 2 diabetes and cardiovascular disease. Obesity is one of the major drivers of these adverse outcomes, resulted from corticosteroids, radiotherapy, sedentary behavior, and precancer obesity. Assessment of obesity could identify CCS at risk and predict cardiometabolic risk. Dual-Energy X-ray Absorptiometry (DEXA) scans incorporate measurements of adipose tissue mass but are not feasible because they require special equipment, expertised personnel and are expensive. The Tri-Ponderal Mass Index (TMI: kg/m3) has recently been validated as an accurate measure of obesity than the widely used Body Mass Index (BMI). The aim of the study was to investigate TMI as a measure of obesity versus DEXA compared with BMI z-score in CCS.
Methods: A single-center retrospective study enrolled thirty CCS (17 boys) of Caucasian origin, aged 12.38±3.99 years, was conducted. Anthropometric data were recorded and DEXA scan measurements of body composition were performed to assess obesity. TMI was calculated as weight (kg) divided by height cubic meters (m3).
Results: Participants had a mean age at diagnosis of 7.95±4.07 years, 20/30 (66.7%) had survived of acute lymphoblastic leukemia, all received chemotherapy, 46.7% had received radiotherapy and 6.7% underwent bone marrow transplantation. Recurrence was recorded in 23.3%. Cancer treatment was terminated at a mean age of 9.32±4.07. Mean BMI z-score was 0.62±1.17, weight (kg) 49.05±18.2, height (m) 1.50±0.20. Mean Fat Mass (FM)% measured by DEXA was 39.12±7.74. The mean TMI (kg/m3) was 14.18±3.18. TMI is significantly correlated with FM% measured by DEXA (r= 0.519, P-value=0.004), even after adjustment for age and gender (r= 0.368, P-value=0.05). However, BMI z-score remains largely correlated to FM% in the studied sample, after adjustments for age and gender (r= 0.641, P-value<0.001). Regression analysis, revealed that the association of TMI alone was not significant for obesity (TMI vs FM% estimated unstandardized B=0.711; P-value=0.117), however, the combination of TMI and BMI z-score could reliably predict FM% distribution among CCS (model R2=0.49, P-value<0.001; TMI unstandardized B=-2.25, P-value=0.005; BMI z-score unstandardized B=9.04, P-value< 0.001).
Conclusion: TMI constitutes a reliable, easy applicable and clinical obesity-specific index among CCS.