use of bioimpedianciometer as predictor of mountain marathon performance
TRANSCRIPT
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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
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INTRODUCTION
Ultraendurance studies Antrophometry
Fat mass muscle mass Water Age
Billat et el, 2001
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INTRODUCTION
Training characteristics Volume Intensity frequency
Related to race performance
No studies in mountain races
Billat et el, 2001; Clemente, 2011
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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
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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)
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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).
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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
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RESULTS
Parameter r pAge .502 .002Fat Mass .632 .000Body Fat .754 .000Level of abdominal obesity
.482 .005
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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)
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DISCUSSION
Race time in mountain marathon was positively related to BF and negatively related to daily training volume
Sharer et al, 2009
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DISCUSSION
The race time could be predicted (R2 = .948) by daily training load, sports experience, age, FM, BF and level of abdominal obesity
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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
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GRACIAS POR SU ATENCIÓN