• Diana A Santos, Analiza M Silva, Catarina N Matias, João P Magalhães, Cláudia S Minderico, Diana M Thomas, and Luís B Sardinha.
• Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal.
• Nutrition. 2015 Jul 1; 31 (7-8): 948-54.

ObjectiveRecently, new body indices, including body adiposity (BAI), a body shape (ABSI), and body roundness (BRI) indices have been developed to estimate adiposity. The aim of this study was to compare percent fat mass (%FM) with novel indices in an elite athlete population.MethodsUsing a cross-sectional design, %FM in 159 male and 50 female athletes using a four-component model was assessed. The %FM was compared with body mass index (BMI), BAI, ABSI, BRI, and with other %FM field methods (bioimpedance spectroscopy and skinfold prediction equation). These associations were determined using multilinear regression analysis, which resulted in predictive models of %FM in athletes. Cross-validation was performed using the prediction residual error sum of squares (PRESS) statistics method.ResultsAlthough higher associations than other indices were observed, BRI still presented low coefficients of determination (men: R(2) = 0.36; women: R(2) = 0.25) when comparing with other field methods (R(2) range, 0.33-0.75). Using BAI as the independent variable, the R(2) was 0.07 for men and 0.14 for women. ABSI did not result in a significant association with %FM in women (R(2) = 0.05) while in men a significant association was found (R(2) = 0.22). The BMI model resulted in a R(2) = 0.20 for men and R(2) = 0.22 for women. Waist circumference and the sum of skinfolds were the anthropometric variables with the highest association with adiposity. New alternatives were presented with higher coefficients of determination (PRESS R(2) ranged from 0.47 to 0.71).ConclusionsThe newly developed body indices are limited in predicting %FM in elite athletes, particularly when compared with other commonly and readily available field methods like bioimpedance analysis or skinfold prediction models.Copyright © 2015 Elsevier Inc. All rights reserved.

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