Overweight in Young Athletes: New Predictive Model of Overfat Condition

Gabriele Mascherini, Cristian Petri, Elena Ermini, Vittorio Bini, Piergiuseppe Calà, Giorgio Galanti and Pietro Amedeo Modesti
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Gabriele Mascherini: Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi di Firenze, 50134 Firenze, Italy
Cristian Petri: Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi di Firenze, 50134 Firenze, Italy
Elena Ermini: Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi di Firenze, 50134 Firenze, Italy
Vittorio Bini: Dipartimento di Medicina, Università di Perugia, 06156 Perugia, Italy
Piergiuseppe Calà: Sector “Health and Safety in the Workplace and Special Processes in the Field of Prevention”, Directorate of Citizenship Rights and Social Cohesion, 50139 Firenze, Italy
Giorgio Galanti: Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi di Firenze, 50134 Firenze, Italy
Pietro Amedeo Modesti: Dipartimento di Medicina Sperimentale e Clinica, Università degli Studi di Firenze, 50134 Firenze, Italy

IJERPH, 2019, vol. 16, issue 24, 1-10

Abstract: The aim of the study is to establish a simple and low-cost method that, associated with Body Mass Index (BMI), differentiates overweight conditions due to a prevalence of lean mass compared to an excess of fat mass during the evaluation of young athletes. 1046 young athletes (620 male, 426 female) aged between eight and 18 were enrolled. Body composition assessments were performed with anthropometry, circumferences, skinfold, and bioimpedance. Overweight was established with BMI, while overfat was established with the percentage of fat mass: 3.5% were underweight, 72.8% were normal weight, 20.1% were overweight, and 3.5% were obese according to BMI; according to the fat mass, 9.5% were under fat, 63.6% were normal fat, 16.2% were overfat, and 10.8% were obese. Differences in overfat prediction were found using BMI alone or with the addition of the triceps fold (area under the receiver operating characteristics curve (AUC) for BMI = 0.867 vs. AUC for BMI + TRICEPS = 0.955, p < 0.001). These results allowed the creation of a model factoring in age, sex, BMI, and triceps fold that could provide the probability that a young overweight athlete is also in an overfat condition. The calculated probability could reduce the risk of error in establishing the correct weight status of young athletes.

Keywords: Triceps skinfold; overweight; youth; obese; child; adolescent (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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