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Predictors of half-marathon performance in male recreational athletes

Nikolaidis, Pantelis T; Knechtle, Beat (2023). Predictors of half-marathon performance in male recreational athletes. EXCLI Journal, 22:559-566.

Abstract

Few research has been conducted on predictors of recreational runners' performance, especially in half-marathon running. The purpose of our study was (a) to investigate the relationship of half-marathon race time with training, anthropometry and physiological characteristics, and (b) to develop a formula to predict half-marathon race time in male recreational runners. Recreational runners (n=134, age 44.2±8.7 years; half-marathon race time 104.6±16.2 min) underwent a physical fitness battery consisting of anthropometric and physiological tests. The participants were classified into five performance groups (fast, 73-92 min; above average, 93-99 min; average 100-107 min; below average, 108-117 min; slow group, 118-160 min). A prediction equation was developed in an experimental group (EXP, n=67), validated in a control group (CON, n=67) and prediction bias was estimated with 95 % confidence intervals (CI). Performance groups differed in half-marathon race time, training days, training distance, age, weight, (body mass index) BMI, body fat (BF) and maximum oxygen uptake (VO$_{2}$max) (p≤0.001, η$^{2}$≥0.132), where faster groups had better scores than the slower groups. Half-marathon race time correlated with physiological, anthropometric and training characteristics, with the faster the runner, the better the score in these characteristics (e.g., VO$_{2}$max, r=0.59; BMI, r=-0.55; weekly running distance, r=-0.53, p<0.001). Race time in EXP might be calculated (R$^{2}$=0.63, standard error of the estimate=9.9) using the equation 'Race time (min)=80.056+2.498×BMI-0.594×VO$_{2}$max-0.191×weekly training distance in km'. Validating this formula in CON, no bias was shown (difference between observed and predicted value 2.3±12.8 min, 95 % CI -0.9, 5.4, p=0.153). Half-marathon race time was related to and could be predicted by BMI, VO$_{2}$max and weekly running distance. Based on these relationships, a prediction formula for race time was developed providing a practical tool for recreational runners and professionals working with them.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Institute of General Practice
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Molecular Medicine
Life Sciences > Animal Science and Zoology
Life Sciences > Pharmacology
Life Sciences > Drug Discovery
Language:English
Date:22 June 2023
Deposited On:17 Aug 2023 17:39
Last Modified:24 Mar 2025 04:45
Publisher:IfADo - Leibniz Research Centre for Working Environment and Human Factors, Dortmund
ISSN:1611-2156
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.17179/excli2023-6198
PubMed ID:37534223
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  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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