use of bioimpedianciometer as predictor of mountain marathon performance
TRANSCRIPT
Use of bioimpedianciometer as predictor of mountain marathon
performance
Vicente Javier Clemente-SuarezDepartment of Sport Sciences. UEM
Pantelis Theodoros NikolaidisDepartment of Physical and Cultural Education, Hellenic Army Academy
INTRODUCTION
Ultraendurance studies Antrophometry
Fat mass muscle mass Water Age
Billat et el, 2001
INTRODUCTION
Training characteristics Volume Intensity frequency
Related to race performance
No studies in mountain races
Billat et el, 2001; Clemente, 2011
OBJETIVE
To study the association between anthropometric, training experience and race time in a mountain marathon and predict the race time in a mountain marathon
METHODS
52 participants (173.9±6.5 cm, 72.7±9.9 kg) “Pueblo de los Artesanos” mountain
marathon 42 km 2147 m cumulative altitude change Diary - training characteristics Inbody 720 – body composition Pre race evaluation (Clemente et al, 2011)
METHODS
InBody 720 is a multifrequency impedance body composition analyser, which uses an eight-point tactile electrode method to take readings from the body. It measures resistance at five specific frequencies (1 kHz, 50 kHz, 250 kHz, 500 kHz, and 1 MHz) and reactance at three specific frequencies (5 kHz, 50 kHz, and 250 kHz) on each of five segments (right arm, left arm, trunk, right leg and left leg).
METHODS
Statistical Analysis SPSS 17.0 Bivariate correlation analysis between
training and anthropometric parameters and probe time – R Pearson
Stepwise multiple regression analysis to determine the variables correlated with the race time
RESULTS
Parameter r pAge .502 .002Fat Mass .632 .000Body Fat .754 .000Level of abdominal obesity
.482 .005
RESULTS
Race time (min) = 979.79 - 0.227 (daily training, min) - 0.629 (sports practicing experience, years) - 2.716 (age, years) + 5.010 (Fat Mass, kg) + 7.292 (Body Fat, %) – 1156.903 (level of abdominal obesity)
DISCUSSION
Race time in mountain marathon was positively related to BF and negatively related to daily training volume
Sharer et al, 2009
DISCUSSION
The race time could be predicted (R2 = .948) by daily training load, sports experience, age, FM, BF and level of abdominal obesity
DISCUSSION
Runners with higher performance in the mountain marathon presented lower body mass index, level of abdominal obesity, BF, FM, body mass and a higher number of days of training per week
Use of BIA is a easy, quick and valid instrument to predict mountain race performance
Leyk et al, 2007
GRACIAS POR SU ATENCIÓN