Modelling 5-km Running Performance on Level and Hilly Terrains in Recreational Runners

SIMPLE SUMMARY: In the last decades, performance models have helped to comprehend the mechanisms involved in long-term physical performance. In addition, predictive models have aided in the evaluation and prescription of physical training. Here, we tested the hypothesis that physiological assessments under inclined conditions would better explain hilly running performance. We also checked the predictive role of running biomechanical, anthropometric, and neuromuscular factors. Velocity associated with maximal oxygen consumption was more predictive when assessed in inclined conditions (7%) than testing at level. Secondarily, ventilatory thresholds submaximal heart rate improved the performance models at hilly and level conditions. Spatiotemporal, strength, and anthropometric factors were not determinants of performance. Physiological assessments in inclined conditions predict 5-km running performance at hilly terrains in higher degree than evaluations at level in endurance runners. ABSTRACT: Incline and level running on treadmills have been extensively studied due to their different cardiorespiratory and biomechanical acute responses. However, there are no studies examining the performance determinants of outdoor running on hilly terrains. We aimed to investigate the influence of anthropometrics, muscle strength, and cardiorespiratory and gait spatiotemporal parameters during level (0%) and inclined (+7%) running on performance in level and hilly 5-km races. Twenty male recreational runners completed two 5-km outdoor running tests (0% vs. +7% and −7%), and two submaximal (10 km·h(−1)) and incremental treadmill tests at 0 and 7% slopes, after complete laboratory evaluations. The velocity at maximal oxygen consumption (VO(2)max) evaluated at 7% incline and level treadmill running were the best performance predictors under both hilly (R(2) = 0.72; p < 0.05) and level (R(2) = 0.85; p < 0.01) conditions, respectively. Inclusion of ventilatory and submaximal heart rate data improved the predictive models up to 100%. Conversely, none of the parameters evaluated in one condition contributed to the other condition. The spatiotemporal parameters and the runners’ strength levels were not associated to outdoor performances. These results indicate that the vVO(2)max evaluated at similar slopes in the lab can be used to predict 5-km running performances on both level and hilly terrains.