Use of bioimpedianciometer as predictor of mountain marathon performance

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