# Bioelectrical Impedance Vector Analysis (BIVA) and Somatotype in Female Rugby Players
## 4 Discussion
Conventional BIA requires mathematical models to estimate body compartments [15], which has promoted the development of the BIVA modality and the interpretation of raw electrical variables, such as PA, to avoid this dependency. This modality does not assume considerations about body compartments, mass, geometry, or hydration, nor it is subjected to the error derived from regression models vs. reference techniques [18; 19; 50]. In our results, the study of raw electrical variables demonstrated a higher PA of the forwards (7.26\({}^{\circ}\)) vs. the backs (6.73\({}^{\circ}\)). Recently, the reference percentiles of PA for sports populations have beenpublished by [PERSON] et al. [52]. Considering these reference values for team sports, our players were situated between P50 and P85. The research group of [PERSON] documented that PA differs in each sport, according to the player's position, which is related to BC and morphological characteristics, especially in team sports [52]. The same group underlined that in male athletes from team sports, PA is positively related to the mesomorphy component and negatively related to the ectomorphy component of somatotype [53]. Although there is no study that evaluates the association between impedance vectors and somatotype in female athletes, similar results could be expected. The high PA of our players compared to other sports could be explained by the high mesomorph component in their somatotype. Prior studies have suggested that PA is positively related to muscle mass and negatively related to the ECW/ICW relationship [50; 54]. PA is also related to cellular health and hydration and muscular mass and quality. Moreover, it is suggested that PA could be a useful indicator for the study of athletes during sport season, especially if they present a low PA, in order to (1) identify changes in BC, (2) evaluate fatigue and sport performance, and (3) design specific nutritional strategies [52; 55]. However, a number of authors have reported that the study of PA in isolation could lead to misinterpretations of BC [37; 54]. It has been observed that athletes with similar PAs could differ in TBW or FM%. Since classic BIVA assesses the impedance vectors and not just PA (vector slope), it could be more useful because it also takes into account the length of the vector, which shows TBW (longer vectors are related to a lower TBW) [21; 54]. In this modality of BIVA, considering the reference values of individual impedance vector distributions for sports populations, the majority of the studied rugby players presented a similar bioelectrical behaviour to other athletes (Figure 2), despite not belonging to an elite team. There were only two players out of the ellipses at 75% (although within ellipses at 95%); one was in the right upper quadrant and the other in the left lower quadrant. The first one (number 9) is a back player with a BMI of 21.4 kg/m\({}^{2}\). They presented a greater endomorphy component than the rest of the players, so it is possible that their morphology explains their position in the BIVA graph. The second one (number 7) is a forward player with a high BMI (37.5 kg/m\({}^{2}\)), which explains their BIVA graph position. These results agree with [PERSON] et al. 's research, which documented that athletes with a high body mass could be placed in the lower area of the BIVA graph, independently of their morphology [53]. Classic BIVA did not detect differences in BC according to the player's position, which is shown by both the individual impedance vector distribution (Figure 3) and the mean impedance vector distribution of each subgroup (confidence ellipses, Figure 4a). This was an expected result, given that [PERSON] et al. [54] proved that classic BIVA detects differences in TBW but not in FM%. The two studied subgroups of players differ in fat mass but not in TBW, as is shown by the mean impedance vectors (Figure 4a) and the \(\mathrm{Z}/\mathrm{H}\) values (Table 3). Body geometry is a factor that affects bioimpedance measurements [35].