Faculty of Medicine, University of Málaga, Andalucía TECH, 29071 Málaga, Spain.
AdventHealth Translational Research Institute, AdventHealth Oralndo, Orlando, FL 32804, USA.
Int J Environ Res Public Health. 2020 Nov 9;17(21):8289. doi: 10.3390/ijerph17218289.
Physiological variables such as maximal oxygen uptake (VOmax), velocity at maximal oxygen uptake (VOmax), running economy (RE) and changes in lactate levels are considered the main factors determining performance in long-distance races. The aim of this review was to present the mathematical models available in the literature to estimate performance in the 5000 m, 10,000 m, half-marathon and marathon events. Eighty-eight articles were identified, selections were made based on the inclusion criteria and the full text of the articles were obtained. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables were also included by athletic specialty. A total of 58 studies were included, from 1983 to the present, distributed in the following categories: 12 in the 5000 m, 13 in the 10,000 m, 12 in the half-marathon and 21 in the marathon. A total of 136 independent variables associated with performance in long-distance races were considered, 43.4% of which pertained to variables derived from the evaluation of aerobic metabolism, 26.5% to variables associated with training load and 20.6% to anthropometric variables, body composition and somatotype components. The most closely associated variables in the prediction models for the half and full marathon specialties were the variables obtained from the laboratory tests (VOmax, VOmax), training variables (training pace, training load) and anthropometric variables (fat mass, skinfolds). A large gap exists in predicting time in long-distance races, based on field tests. Physiological effort assessments are almost exclusive to shorter specialties (5000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate coefficients of determination. The variables of note in the marathon category are fundamentally those associated with training and those derived from physiological evaluation and anthropometric parameters.
生理变量,如最大摄氧量(VOmax)、最大摄氧量时的速度(VOmax)、运动经济性(RE)和乳酸水平的变化,被认为是决定长距离比赛表现的主要因素。本综述的目的是介绍文献中可用的数学模型,以估计 5000 米、10000 米、半程马拉松和马拉松比赛的成绩。确定了 88 篇文章,根据纳入标准进行选择,并获得了文章的全文。根据人口统计学、人体测量学、运动生理学和现场测试变量对文章进行了回顾和分类,并按运动专项包括了变量。共纳入 58 项研究,时间跨度从 1983 年至今,分布在以下类别:5000 米 12 项、10000 米 13 项、半程马拉松 12 项、马拉松 21 项。共考虑了 136 个与长距离比赛表现相关的独立变量,其中 43.4%与有氧代谢评估相关的变量有关,26.5%与训练负荷相关的变量有关,20.6%与人体测量学变量、身体成分和体型成分有关。在半程和全程马拉松专项的预测模型中,与预测成绩最密切相关的变量是实验室测试(VOmax、VOmax)、训练变量(训练速度、训练负荷)和人体测量学变量(体脂量、皮褶厚度)获得的变量。根据现场测试,预测长距离比赛时间存在很大差距。生理努力评估几乎只适用于较短的专项(5000 米和 10000 米)。半程马拉松的预测变量主要是人体测量学的,但决定系数中等。马拉松类别的重要变量主要是与训练相关的变量,以及与生理评估和人体测量参数相关的变量。