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Subtraction of subcutaneous fat to improve the prediction of visceral adiposity: exploring a new anthropometric track in overweight and obese youth

Subtraction of subcutaneous fat to improve the prediction of visceral adiposity: exploring a new anthropometric track in overweight and obese youth

Pediatric Diabetes 18(5): 399-404

ISSN/ISBN: 1399-543X

PMID: 27400675

DOI: 10.1111/pedi.12415

The efficiency of traditional anthropometric measurements such as body mass index (BMI) or waist circumference (Waist C) used to replace biomedical imaging for assessing visceral adipose tissue (VAT) is still highly controversial in youth. We evaluated the most accurate model predicting VAT in overweight/obese youth, using various anthropometric measurements and their correlation with different body fat compartments, especially by testing, for the first time in youth, the hypothesis that subtracting the anthropometric measurement the most highly correlated with subcutaneous abdominal adipose tissue (SAAT) and less correlated possible with VAT from an anthropometric abdominal measurement highly correlated with visceral and total abdominal adipose tissue (TAAT), predicts VAT with higher accuracy. VAT and SAAT data resulted from magnetic resonance imaging (MRI) analysis performed on 181 boys and girls (7-17 y) from Diabetes & Endocrinology Care Paediatrics Clinic in Luxembourg. Height, weight, abdominal diameters, waist, hip, and thigh circumferences were measured with a view to developing the anthropometric VAT predictive algorithms. In girls, subtracting proximal thigh circumference (Proximal Thigh C), the most closely correlated anthropometric measurement with SAAT, from Waist C, the most closely correlated anthropometric measurement with VAT was instrumental in improving VAT prediction, in comparison with the most accurate single VAT anthropometric surrogate. [Formula: see text] Residual analysis showed a negligible estimation error (5 cm2 ). In boys, Waist C was the best VAT predictor. Subtraction of abdominal subcutaneous fat is important to predict VAT in overweight/obese girls.

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Accession: 058927846

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