Insight Centre for Data Analytics, University College Dublin, Ireland; School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland.
Insight Centre for Data Analytics, University College Dublin, Ireland; School of Public Health, Physiotherapy and Population Science, University College Dublin, Dublin, Ireland.
J Sci Med Sport. 2020 Feb;23(2):182-188. doi: 10.1016/j.jsams.2019.09.013. Epub 2019 Oct 18.
Marathoners rely on expert-opinion and the anecdotal advice of their peers when devising their training plans for an upcoming race. The accumulation of results from multiple scientific studies has the potential to clarify the precise training requirements for the marathon. The purpose of the present study was to perform a systematic review, meta-analysis and meta-regression of available literature to determine if a dose-response relationship exists between a series of training behaviours and marathon performance.
Systematic review, meta-analysis and meta-regression.
A systematic search of multiple literature sources was undertaken to identify observational and interventional studies of elite and recreational marathon (42.2km) runners.
Eighty-five studies which included 137 cohorts of runners (25% female) were included in the meta-regression, with average weekly running distance, number of weekly runs, maximum running distance completed in a single week, number of runs ≥32km completed in the pre-marathon training block, average running pace during training, distance of the longest run and hours of running per week used as covariates. Separately conducted univariate random effects meta-regression models identified a negative statistical association between each of the above listed training behaviours and marathon performance (R 0.38-0.81, p<0.001), whereby increases in a given training parameter coincided with faster marathon finish times. Meta-analysis revealed the rate of non-finishers in the marathon was 7.27% (95% CI 6.09%-8.65%).
These data can be used by athletes and coaches to inform the development of marathon training regimes that are specific to a given target finish time.
马拉松运动员在制定即将到来的比赛的训练计划时,依赖专家意见和同行的轶事建议。多项科学研究的结果积累有可能阐明马拉松的精确训练要求。本研究的目的是对现有文献进行系统回顾、荟萃分析和荟萃回归,以确定一系列训练行为与马拉松成绩之间是否存在剂量反应关系。
系统回顾、荟萃分析和荟萃回归。
对多个文献来源进行了系统搜索,以确定精英和休闲马拉松(42.2 公里)跑者的观察性和干预性研究。
共有 85 项研究纳入了 137 个跑者队列(25%为女性),进行了荟萃回归,其中包括每周平均跑步距离、每周跑步次数、单周最大跑步距离、马拉松前训练阶段完成的≥32 公里跑步次数、训练期间的平均跑步速度、最长跑步距离和每周跑步时间。单独进行的单变量随机效应荟萃回归模型确定了上述训练行为中的每一项与马拉松成绩之间存在负统计关联(R 0.38-0.81,p<0.001),即给定训练参数的增加与马拉松完赛时间的加快相对应。荟萃分析显示马拉松比赛的完赛率为 7.27%(95%CI 6.09%-8.65%)。
运动员和教练可以使用这些数据来制定针对特定目标完赛时间的马拉松训练计划。