An evaluation of the training determinants of marathon performance: A meta-analysis with meta-regression. Issue 2 (February 2020)

• Record Type: Journal Article
• Authors: Doherty, Cailbhe; Keogh, Alison; Davenport, James; Lawlor, Aonghus; Smyth, Barry; Caulfield, Brian
• Is Part Of: Journal of science and medicine in sport. Volume 23:Issue 2(2020)
• Page Start: 182
• Page End: 188
• Publication Date: 2020-02
• Subjects: Running [MeSH] -- Exercise [MeSH] -- Physical fitness [MeSH] -- Physical endurance [MeSH] -- Endurance training [MeSH] -- Marathon; Sports sciences -- Periodicals; Sports medicine -- Periodicals; Exercise -- Physiological aspects -- Periodicals; Sports -- physiology -- Periodicals; Sports Medicine -- Periodicals; Sportgeneeskunde; 617.102705
• DOI: 10.1016/j.jsams.2019.09.013
• Languages: English
• ISSNs: 1440-2440

Abstract

Abstract: Objectives: 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. Design: Systematic review, meta-analysis and meta-regression. Methods: A systematic search of multiple literature sources was undertaken to identify observational and interventional studies of elite and recreational marathon (42.2 km) runners. Results: 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 ≥32 km 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 2 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%). Conclusions: 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.