![2013](../../../../assets/md5images/9084fb7562a1d1178779972bc2524c05.gif)
Event Title
Physiological Parameters for the Prediction of 5k Performance for Trained, Female Runners
Start Date
31-10-2013 11:00 AM
Description
The present investigation was designed to determine which physiological variables are most important in determining 5k performance for trained, female endurance runners. Thirty-five subjects completed a incremental, treadmill test to determine maximal oxygen uptake (VO2peak), velocity at VO2peak (vVO2peak), lactate threshold (LT), velocity at lactate threshold (vLT), and running economy at lactate threshold (RE at LT). Body composition was also estimated. VO2peak, vVO2peak, vLT, RE at LT and body composition were all significantly (p < .01) correlated with 5k performance. vVO2peak, VO2peak, and body composition were used to create a multiple regression equation. vLT and RE at LT were not used in the regression analysis due to high colinearity with other predictor variables. The regression equation revealed 70.7% of the variance in 5k performance could be predicted by vVO2peak, VO2peak and body composition (p < .05). These results show that vVO2peak is the single best predictor of 5k performance in trained, female endurance runners. Coaches and distance athletes should place high emphasis on workouts designed to improve vVO2peak values due to its high predictive power regarding performance.
Physiological Parameters for the Prediction of 5k Performance for Trained, Female Runners
The present investigation was designed to determine which physiological variables are most important in determining 5k performance for trained, female endurance runners. Thirty-five subjects completed a incremental, treadmill test to determine maximal oxygen uptake (VO2peak), velocity at VO2peak (vVO2peak), lactate threshold (LT), velocity at lactate threshold (vLT), and running economy at lactate threshold (RE at LT). Body composition was also estimated. VO2peak, vVO2peak, vLT, RE at LT and body composition were all significantly (p < .01) correlated with 5k performance. vVO2peak, VO2peak, and body composition were used to create a multiple regression equation. vLT and RE at LT were not used in the regression analysis due to high colinearity with other predictor variables. The regression equation revealed 70.7% of the variance in 5k performance could be predicted by vVO2peak, VO2peak and body composition (p < .05). These results show that vVO2peak is the single best predictor of 5k performance in trained, female endurance runners. Coaches and distance athletes should place high emphasis on workouts designed to improve vVO2peak values due to its high predictive power regarding performance.