TY  - JOUR
AU  - Giorgi, Andrea
A2  - Giorgi, Andrea
A2  - Vicini, Maurizio
A2  - Pollastri, Luca
A2  - Lombardi, Erica
A2  - Magni, Emilio
A2  - Andreazzoli, Andrea
A2  - Orsini, Marco
A2  - Bonifazi, Marco
A2  - Lukaski, Henry
DB  - BISp
DP  - BISp
KW  - Analyse
KW  - Anthropometrie
KW  - Ausdauersport
KW  - Impedanzmessverfahren
KW  - Körperzusammensetzung
KW  - Leistungsfähigkeit
KW  - Leistungsfähigkeit, sportartspezifische
KW  - Leistungsfähigkeit, sportliche
KW  - Leistungsphysiologie
KW  - Radsport
KW  - Sportwissenschaft
KW  - Untersuchung, vergleichende
LA  - eng
TI  - Bioimpedance patterns and bioelectrical impedance vector analysis (BIVA) of road cyclists
TT  - Bioimpedanzmuster und die Vektorenanalyse des bioelektrischen Widerstands (BIVA) bei Straßenradsportlern
PY  - 2018
N2  - 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.
L2  - https://www.tandfonline.com/doi/full/10.1080/02640414.2018.1470597
L2  - https://dx.doi.org/10.1080/02640414.2018.1470597
DO  - 10.1080/02640414.2018.1470597
SP  - S. 2608-2613
SN  - 0264-0414
JO  - Journal of sports sciences
IS  - 22
VL  - 36
M3  - Elektronische Ressource (online)
M3  - Gedruckte Ressource
ID  - PU201810007412
ER  -