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O-38 A new method for classifying athletes between powerful and endurance: physiological variables that explain their different performance in field tests
  1. Gloria Vega1,
  2. Diogenes Arrieta2,
  3. Oscar Cardona3,
  4. Mauricio Estrada-Castrillon4,
  5. Raul Narvaez-Sanchez1,
  6. Juan C Calderon1,
  7. Jaime Gallo2
  1. 1Department of Physiology, Faculty of Medicine, University of Antioquia, Medellin-Colombia
  2. 2Sports Medicine, University of Antioquia, Faculty of Medicine, Medellin-Colombia
  3. 3Indeportes Antioquia Sports Medicine Medellin-Colombia
  4. 4Pablo Tobon Uribe vHospital Radiology Medellin- Colombia

Abstract

To decide the training for an athlete, it is essential to determine if he/she has a powerful or endurance profile, based on valid and simple measurements. This work describes how to classify athletes as powerful or endurance based on their performance on field physical tests, via clusters analysis, and measures the influence of skeletal muscle fibre type composition and cardiovascular function in such performance.

Methods 51 elite athletes (20.6 ± 2.9 years, 30 women) of team sports (25% handball, 22% basketball, 21% volleyball floor, 18% softball, 8% beach volleyball, 6% indoor soccer) were evaluated in Medellin, Colombia, with the following: 1. Performance on field tests: Three jumps -free vertical (FVJ), counter movement (CMJ), and squat (SQT)-; two velocity tests −20 metres dash and shuttle sprint- and ergospirometry (VO2); 2. Noninvasive quantification of intramuscular carnosine (mM/Kg.wt) in vastus lateralis muscle (VLM), a surrogate of area occupied by type II fibres in muscle, by proton magnetic resonance spectroscopy; 3. Cardiac structure and function by echocardiography; 4. Haemodynamic and autonomic response, both at rest and at 70°, by impedance cardiography.

Results Clusters determined that best field tests to distinguish between powerful (n = 26, 51%) and endurance (n = 25, 49%) were the three jumps and the 20 metres shuttle sprint. Both groups did not differ in age, sports age or training volume, but body mass index (BMI, Kg/m2) and percentage of body fat (bf%) were lower in powerful than in endurance athletes (p < 0,05). ANCOVA adjusted for BMI, bf% and age, showed larger muscular type II fibres area in VLM in powerful than in endurance athletes (38.2% vs. 29.5%; difference between means 8.7%, IC 95%, 4.02–13.3, p = 0.01). The only cardiovascular variable with significant difference was mitral valve E/A ratio, lower in powerful compared to endurance (1.9 vs 2.4; difference between means 0.5, IC 95%, −0.1 to −0.9, p < 0.05), suggesting better diastolic function and less cardiac rigidity in the latter. In multiple linear regression analysis, introducing demography, anthropometry, cardiac structure and function, and intramuscular mM/Kg.wt of carnosine, the variability of 20 metres sprints was explained (R2 = 0.82, p < 0.05 for all cases) by bf% (ß coefficient −0.6, meaning that for each 1% rise in body fat, velocity reduces 0.6 m/s), left ventricle diastolic diameter index (ß 0.47, for each cm/m2 rise in diameter, velocity raises 0.47 m/sec), cardiac index at 70° (ß 0.9) and contractility index at 70° (ß −0.04). The variability of jumps was explained (R2 = 0.78) by bf% (ß −0.84 for CMJ) and carnosine (ß 1.9 for CMJ, which means that each 1 mM/Kg.wt rise in carnosine raises 1.9 cm the CMJ).

Conclusions The 20 metres velocity is explained essentially by body composition and cardiovascular variables and the jump is explained fundamentally by body composition and muscle composition, which can be accessed by noninvasive spectroscopy. This new methodology associates biochemical intramuscular variables such carnosine with field tests, and helps to evaluate and classify athletes, to control training and to understand variables which determine performance during a competition.

(Grant:CODI2565;Colciencias-Coldeportes FP44842-379-2014)

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