## 4 Discussion  
The objective of this study was to define differences between biological sex and among the kinds of sports people practiced. As explained in the Results section, we did find differences in most of the anthropometric variables. Researchers such as [PERSON] et al. (2025) [20] have conducted meta-analyses on the health benefits of regular physical exercise in sedentary adults. Their findings highlight that, in addition to improving cardiovascular health, regular exercise helps to obtain better anthropometric indices and reduce the BMI. Therefore, using anthropometric measurements could be useful for evaluating health and to promote the benefits of regular physical activity, as they provide tangible indicators of improvement. Our main goal was to analyze whether there were anthropometrical differences between the sexes and among different sport modalities. We believe that these results could be very useful, since they could better explain which values are the most common for each sex and the sport modality practiced regularly. In addition, the results could also be used to establish personal training plans based on an individual's morphological characteristics, as advocated by [PERSON] et al. (2015) [21]. They could also be useful for other researchers to understand what they should be looking for when recruiting sporting talent at an early age, as demonstrated by [PERSON] et al. (2017) [22] in his research on youth volleyball players. We decided to use ISAK methodology [4] for the measurements. Additionally, in an attempt to avoid any extrinsic factor that could affect the results, we decided to follow [PERSON]'s criteria [5] to define the inclusion and exclusion criteria. We also considered the participants' diet [19] and ensured the absence of any injuries during the measurements. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{2}{c}{**Variable Analyzed**} & **Pearson** & **R2** & **Fitted R2** & \(p\)**-Value** \\ \hline \multirow{3}{*}{\%F} & T & 0.033 & 0.001 & \(-\)0.001 & \(p\) = 0.511 \\  & M & \(-\)0.036 & 0.001 & \(-\)0.003 & \(p\) = 0.578 \\  & F & 0.165 & 0.027 & 0.021 & \(p\) = 0.040 \({}^{*}\) \\ \hline \multirow{3}{*}{\%M} & T & 0.075 & 0.006 & 0.003 & \(p\) = 0.129 \\  & M & \(-\)0.103 & 0.011 & 0.007 & \(p\) = 0.106 \\  & F & 0.007 & 0.000 & \(-\)0.006 & \(p\) = 0.927 \\ \hline \multirow{3}{*}{\%B} & T & 0.054 & 0.003 & 0.000 & \(p\) = 0.278 \\  & M & 0.009 & 0.000 & \(-\)0.004 & \(p\) = 0.893 \\  & F & \(-\)0.167 & 0.028 & 0.021 & \(p\) = 0.038* \\ \hline \multirow{3}{*}{\%R} & T & 0.153 & 0.023 & 0.021 & \(p\) = 0.002 \\  & M & \(-\)0.068 & 0.005 & 0.001 & \(p\) = 0.288 \\ \cline{1-1}  & F & 0.062 & 0.004 & \(-\)0.003 & \(p\) = 0.441 \\ \hline \hline \end{tabular} \({}^{*}\)= statistically significant, T = total, M = male, F = female, \(p\) = probability value, R2 = coefficient of determination, F% = fat percentage, M% = muscle percentage, B% = bone percentage, %R = residual percentage.  
\end{table} 
Table 8: Body composition results of the participants according to age. On average, the men tended to practice more hours of physical activity per week than the women. Other studies, such as that by [PERSON] et al. (2014) [23], obtained different results, but this could be due to many reasons. This is likely to be a consequence of the size of the sample and the sociodemographic characteristics of the area where the data were collected. It is worth noting that one's sex does not affect the amount of exercise that an individual can perform. Other authors, such as [PERSON] (2020) [24], have suggested that the amount of exercise performed depends more on variables such as age, geographical location, local culture, the existence or absence of sports facilities, and the promotion of sports by government entities and media. Some authors, such as [PERSON] et al. (1993) [25], believe that men tend to practice team sports to socialize and compete among themselves. Other researchers, such as [PERSON] et al.