Abad Cesar C C, Barros Ronaldo V, Bertuzzi Romulo, Gagliardi João F L, Lima-Silva Adriano E, Lambert Mike I, Pires Flavio O
Department of Physical Education, Senac University Centre, São Paulo, Brazil.
School of Physical Education and Sport, University of São Paulo, Brazil.
J Hum Kinet. 2016 Jul 2;51:193-200. doi: 10.1515/hukin-2015-0182. eCollection 2016 Jun 1.
The aim of this study was to verify the power of VO, peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO and PTV; 2) a constant submaximal run at 12 km·h on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO, PTV and RE) and adjusted variables (VO, PTV and RE) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO. Significant correlations (p < 0.01) were found between 10 km running time and adjusted and unadjusted RE and PTV, providing models with effect size > 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV and RE and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.
本研究的目的是验证未经调整或经体质量指数调整的摄氧量（VO）、峰值跑步机跑步速度（PTV）和跑步经济性（RE）在预测10公里跑步成绩方面的效能。18名男性耐力跑者进行了以下测试：1）递增负荷至疲劳测试以确定VO和PTV；2）在室外跑道上以12公里·小时的速度进行恒定亚极量跑步以测定RE；3）一场10公里跑步比赛。通过独立多元回归模型研究未经调整的变量（VO、PTV和RE）和经调整的变量（VO、PTV和RE），以预测10公里跑步比赛时间。10公里跑步时间与未经调整或经调整的VO之间均无显著相关性。在10公里跑步时间与经调整和未经调整的RE及PTV之间发现显著相关性（p < 0.01），所构建模型的效应量> 0.84，效能> 0.88。经体质量指数调整的预测模型由PTV和RE组成，可解释10公里跑步时间方差的83%，估计标准误（SEE）为1.5分钟。由单一PVT组成的未经调整模型可解释10公里跑步时间方差的72%（SEE为1.9分钟）。两个回归模型均能对10公里跑步时间进行有效估计；然而，未经调整的PTV可能提供一种简单的估计方法。
