Statistical analysis was performed using SPSS version 25.0 for Windows (SPSS Inc., IBM, Armonk, NY, United States). Data were tested for normal distribution (Shapiro-Wilk Test) and homogeneity of variance (Levene-Test for equality of variances). Mean differences of anthropometric and performance parameters between groups (normal weight vs. overweight vs. obese) were tested using a one-way analysis of variance (ANOVA) (Bortz, 1999). Differences between means were considered meaningful if p < 0.05 and partial eta-squared (ηp2) > 0.15 (Richardson, 2011). Alpha level is reported as exact p values and was not set dichotomously as significant or non-significant as recommended by Hurlbert et al. (2019). Post hoc pairwise comparisons were conducted using Bonferroni corrected T-tests. Due to the relatively small number of cases in each age group (n = 11) and in order to avoid an overestimation of mean differences, interpretation of results was primarily based on ηp2. For clarity, magnitude of group differences were interpreted using the following criteria: 0.02, a small difference; 0.13, a moderate difference; 0.26, a large difference. The effect size (d) (the mean difference of scores divided by the pooled SD) was calculated for each parameter (Hartmann et al., 1992), as is interpreted as trivial (<0.20), small (≥0.20–0.49), moderate (≥0.50–0.79), and large (≥0.80). Pearson’s product moment correlations were calculated and used to determine the relationship between anthropometric and performance (physical and academic) parameters. A magnitude of correlation (r) between the measures of <0.1, 0.1–0.3, 0.3–0.5, 0.5–0.7, and 0.7–0.9, >0.9, were considered trivial, small, moderate, large, very large, and almost perfect, respectively.

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