Body Composition, Somatotype and Raw Bioelectrical Impedance Parameters of Adolescent Elite Tennis Players: Age and Sex Differences

Abstract

Studies analyzing tennis players’ body composition and morphological and bioelectrical characteristics are scarce, especially among adolescents. This study aimed to explore sex- and age-based differences in body composition, somatotype, and bioelectrical properties among elite young male and female tennis players aged 13–16 years. Twenty-two male (14.45 ± 1.10 years) and 20 female (14.30 ± 1.03 years) elite tennis players participated in this study and were compared according to sex (males vs. females) and, within each sex, according to age (13–14 years vs. 15–16 years). Female adolescent elite tennis players had higher body fat (BF) percentage and higher endomorphy than males. They also had lower skeletal muscle mass and total body water (TBW) percentages. Older boys had lower resistance and a higher TBW and phase angle (PhA) than younger boys, likely due to maturation and performance. No significant differences were found between younger and older girls, except for the PhA, potentially associated with better cell function and performance. This study provides valuable reference data for coaches of elite youth tennis players. Due to the few differences found in body composition and somatotype in the different age groups, the PhA may be used by practitioners as a reference for cell function and performance.

Prediction of body water compartments by raw bioelectrical impedance parameters in athletes: Comparison between series and parallel measurements

“…31 For each independent variable separately, a multiple regression analysis was used to determine its association with the dependent variables using the unstandardized beta coefficient and adjusting for FFM and age because of their influence on raw BIA parameters and because we included athletes practicing different sports with a wide range of age and FFM values. 27,32,33 The significance level was set at p < 0.05. If more than one variable was a predictor in the derived model, multicollinearity was evaluated.…”