Tanda Giovanni, Knechtle Beat
Polytechnic School, University of Genoa, Genoa, Italy.
Gesundheitszentrum St Gallen, St Gallen, Switzerland ; Institute of Primary Care, University of Zurich, Zurich, Switzerland.
Open Access J Sports Med. 2015 Apr 28;6:129-36. doi: 10.2147/OAJSM.S80637. eCollection 2015.
Marathon (42 km) and 100 km ultramarathon races are increasing in popularity. The aim of the present study was to investigate the potential associations of anthropometric and training variables with performance in these long-distance running competitions.
Training and anthropometric data from a large cohort of marathoners and 100 km ultramarathoners provided the basis of this work. Correlations between training and anthropometric indices of subjects and race performance were assessed using bivariate and multiple regression analyses.
A combination of volume and intensity in training was found to be suitable for prediction of marathon and 100 km ultramarathon race pace. The relative role played by these two variables was different, in that training volume was more important than training pace for the prediction of 100 km ultramarathon performance, while the opposite was found for marathon performance. Anthropometric characteristics in terms of body fat percentage negatively affected 42 km and 100 km race performance. However, when this factor was relatively low (ie, less than 15% body fat), the performance of 42 km and 100 km races could be predicted solely on the basis of training indices.
Mean weekly training distance run and mean training pace were key predictor variables for both marathon and 100 km ultramarathon race performance. Predictive correlations for race performance are provided for runners with a relatively low body fat percentage.
马拉松（42公里）和100公里超级马拉松比赛越来越受欢迎。本研究的目的是调查人体测量学和训练变量与这些长跑比赛成绩之间的潜在关联。
来自大量马拉松运动员和100公里超级马拉松运动员的训练和人体测量数据为本研究提供了基础。使用双变量和多元回归分析评估受试者的训练和人体测量指标与比赛成绩之间的相关性。
发现训练中的量和强度的组合适合预测马拉松和100公里超级马拉松比赛的配速。这两个变量所起的相对作用不同，即训练量对预测100公里超级马拉松成绩比训练配速更重要，而马拉松成绩则相反。体脂百分比方面的人体测量特征对42公里和100公里比赛成绩有负面影响。然而，当这个因素相对较低（即体脂低于15%）时，42公里和100公里比赛的成绩仅根据训练指标就可以预测。
平均每周训练距离和平均训练配速是马拉松和100公里超级马拉松比赛成绩的关键预测变量。为体脂百分比相对较低的跑步者提供了比赛成绩的预测相关性。
