Bioimpedance patterns and bioelectrical impedance vector analysis (BIVA) of road cyclists
Deutscher übersetzter Titel: | Bioimpedanzmuster und die Vektorenanalyse des bioelektrischen Widerstands (BIVA) bei Straßenradsportlern |
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Autor: | Giorgi, Andrea; Vicini, Maurizio; Pollastri, Luca; Lombardi, Erica; Magni, Emilio; Andreazzoli, Andrea; Orsini, Marco; Bonifazi, Marco; Lukaski, Henry |
Erschienen in: | Journal of sports sciences |
Veröffentlicht: | 36 (2018), 22, S. 2608-2613, Lit. |
Format: | Literatur (SPOLIT) |
Publikationstyp: | Zeitschriftenartikel |
Medienart: | Elektronische Ressource (online) Gedruckte Ressource |
Sprache: | Englisch |
ISSN: | 0264-0414, 1466-447X |
DOI: | 10.1080/02640414.2018.1470597 |
Schlagworte: | |
Online Zugang: | |
Erfassungsnummer: | PU201810007412 |
Quelle: | BISp |
Abstract
Bioelectrical impedance vector-analysis (BIVA) describes cell-mass, cell function and hydration status of an individual or a group. The goal of the present investigation was to provide bioelectrical impedance data for 525 male road cyclists (155 professionals, 79 elite, 59 elite-youth, and 232 amateurs) at the time of their optimal performance level. Data were plotted on the resistance-reactance (R-Xc) graph to characterize cyclists group vectors using BIVA. Compared to the general male population, the mean vector position of the road cyclists indicates a higher body cell mass (BCM) and phase angle (p<0.001). The vector position of the high-performance, compared to the amateur cyclists showed similar patterns with higher BCM and phase angles and higher reactance values for the high-performance athletes (p<0.001). The bio-impedance data were used to calculate the 50%, 75%, and 95% tolerance ellipses of each group of cyclists. The characteristic vector positions of the road cyclists indicate normal hydration and greater muscle mass and function of the high-performance cyclists compared to amateur cyclists and the normal population. The cyclists specific tolerance ellipses, particularly the high-performance cyclists might be used for classifying a cyclist according to the individual vector position and to define target vector regions for lower level cyclists.