ESPE Abstracts (2018) 89 P-P2-174

CAN Triponderal Mass Index be a New Indicator in the Predicting Cardiometabolic Risk in Obese Adolescents?

Gülten Cingöza, Berna Eroğlu Filibelib, Bumin Nuri Dündarc & Gönül Çatlıc

aDepartment of Pediatrics, Tepecik Training and Research Hospital, Izmir, Turkey; bDepartment of Pediatric Endocrinology, Tepecik Training and Research Hospital, Izmir, Turkey; cDepartment of Pediatric Endocrinology, Katip Celebi University, Izmir, Turkey

Introduction: BMI is claimed to be unreliable in the determination of body fat rate and cardiometabolic risk. Troublesome and reproducibility low measurements like waist circumference, waist circumference/height rate are used in the evaluation of cardiometabolic risk. Triponderal mass index (TMI; weight/height3), however, is suggested to be superior BMI in determining body fat rate and obesity.

Purpose: In this study TMI’s relationship with body mass rate and metabolic parameters and its superiority to other indexes in the determination of cardiometabolic risk were examined.

Method: Obese adolescents over BMI>95% according to the data of Turkish children were involved in the study. Anthropometric parameters, blood pressures, fasting glucose, lipid levels of cases were measured. Body fat rate was evaluated with bioelectric impedance. Metabolic syndrome (MS) was described according to International Diabetes Federation (IDF) criteria.

Results: Of 247 obese adolescents (14.8±1.5 years, 158 female, 105 MS) involved in the study, BMI 34.1±.47 kg/m2; BMI SDS 3.03±0.6; TMI 20.8±2.9 kg/m3, waist circumference/height rate 0.63±0.06 and body fat rate was established as 40.1±7.4%. BMI, BMI-SDS, TMI, waist circumference/height rates in cases diagnosed with MS (n=105) were determined significantly high. BMI, BMI SDS, waist circumference/height rate and TMI’s connection with anthropometric and metabolic parameters were summarized in Table 2. It was identified that BMI showed a potent relationship with BMI SDS and TMI and moderate positive relationship with waist circumference/height rate and BMI. It was displayed that TMI had only low connection with HDL-K, fasting insulin and HOMA-IR out of metabolic parameters. In the prediction of MS diagnosis, when diagnostic susceptibility and authenticity of TMI, BMI, BMI SDS, waist circumference/height rate were evaluated with ROC analysis, those below the curve were determined as similar and significantly high.

Conclusion: While TMI shows body fat rate more accurately compared to BMI and waist circumference/height rate, it has no superiority to BMI SDS. Nevertheless, since TMI can be calculated more practically compared to BMI SDS, it has made us think that it can be used in determining body fat rate. In addition, it cannot be shown that TMI has superiority to BMI, BMI SDS, waist circumference/height rate in displaying cardiometabolic risk.

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