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Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed

AIM: Despite the increasing popularity of outdoor endurance running races of different distances, little information exists about the role of training and physiological characteristics of recreational runners. The aim of the present study was (a) to examine the role of training and physiological cha...

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Autores principales: Nikolaidis, Pantelis T., Rosemann, Thomas, Knechtle, Beat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280344/
https://www.ncbi.nlm.nih.gov/pubmed/34276402
http://dx.doi.org/10.3389/fphys.2021.682359
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author Nikolaidis, Pantelis T.
Rosemann, Thomas
Knechtle, Beat
author_facet Nikolaidis, Pantelis T.
Rosemann, Thomas
Knechtle, Beat
author_sort Nikolaidis, Pantelis T.
collection PubMed
description AIM: Despite the increasing popularity of outdoor endurance running races of different distances, little information exists about the role of training and physiological characteristics of recreational runners. The aim of the present study was (a) to examine the role of training and physiological characteristics on the performance of recreational marathon runners and (b) to develop a prediction equation of men’s race time in the “Athens Authentic Marathon.” METHODS: Recreational male marathon runners (n = 130, age 44.1 ± 8.6 years)—who finished the “Athens Authentic Marathon” 2017—performed a series of anthropometry and physical fitness tests including body mass index (BMI), body fat percentage (BF), maximal oxygen uptake (VO(2)max), anaerobic power, squat, and countermovement jump. The variation of these characteristics was examined by quintiles (i.e., five groups consisting of 26 participants in each) of the race speed. An experimental group (EXP, n = 65) was used to develop a prediction equation of the race time, which was verified in a control group (CON, n = 65). RESULTS: In the overall sample, a one-way ANOVA showed a main effect of quintiles on race speed on weekly training days and distance, age, body weight, BMI, BF, and VO(2)max (p ≤ 0.003, η(2) ≥ 0.121), where the faster groups outscored the slower groups. Running speed during the race correlated moderately with age (r = −0.36, p < 0.001) and largely with the number of weekly training days (r = 0.52, p < 0.001) and weekly running distance (r = 0.58, p < 0.001), but not with the number of previously finished marathons (r = 0.08, p = 0.369). With regard to physiological characteristics, running speed correlated largely with body mass (r = −0.52, p < 0.001), BMI (r = −0.60, p < 0.001), BF (r = −0.65, p < 0.001), VO(2)max (r = 0.67, p < 0.001), moderately with isometric muscle strength (r = 0.42, p < 0.001), and small with anaerobic muscle power (r = 0.20, p = 0.021). In EXP, race speed could be predicted (R(2) = 0.61, standard error of the estimate = 1.19) using the formula “8.804 + 0.111 × VO(2)max + 0.029 × weekly training distance in km −0.218 × BMI.” Applying this equation in CON, no bias was observed (difference between observed and predicted value 0.12 ± 1.09 km/h, 95% confidence intervals −0.15, 0.40, p = 0.122). CONCLUSION: These findings highlighted the role of aerobic capacity, training, and body mass status for the performance of recreational male runners in a marathon race. The findings would be of great practical importance for coaches and trainers to predict the average marathon race time in a specific group of runners.
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spelling pubmed-82803442021-07-16 Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed Nikolaidis, Pantelis T. Rosemann, Thomas Knechtle, Beat Front Physiol Physiology AIM: Despite the increasing popularity of outdoor endurance running races of different distances, little information exists about the role of training and physiological characteristics of recreational runners. The aim of the present study was (a) to examine the role of training and physiological characteristics on the performance of recreational marathon runners and (b) to develop a prediction equation of men’s race time in the “Athens Authentic Marathon.” METHODS: Recreational male marathon runners (n = 130, age 44.1 ± 8.6 years)—who finished the “Athens Authentic Marathon” 2017—performed a series of anthropometry and physical fitness tests including body mass index (BMI), body fat percentage (BF), maximal oxygen uptake (VO(2)max), anaerobic power, squat, and countermovement jump. The variation of these characteristics was examined by quintiles (i.e., five groups consisting of 26 participants in each) of the race speed. An experimental group (EXP, n = 65) was used to develop a prediction equation of the race time, which was verified in a control group (CON, n = 65). RESULTS: In the overall sample, a one-way ANOVA showed a main effect of quintiles on race speed on weekly training days and distance, age, body weight, BMI, BF, and VO(2)max (p ≤ 0.003, η(2) ≥ 0.121), where the faster groups outscored the slower groups. Running speed during the race correlated moderately with age (r = −0.36, p < 0.001) and largely with the number of weekly training days (r = 0.52, p < 0.001) and weekly running distance (r = 0.58, p < 0.001), but not with the number of previously finished marathons (r = 0.08, p = 0.369). With regard to physiological characteristics, running speed correlated largely with body mass (r = −0.52, p < 0.001), BMI (r = −0.60, p < 0.001), BF (r = −0.65, p < 0.001), VO(2)max (r = 0.67, p < 0.001), moderately with isometric muscle strength (r = 0.42, p < 0.001), and small with anaerobic muscle power (r = 0.20, p = 0.021). In EXP, race speed could be predicted (R(2) = 0.61, standard error of the estimate = 1.19) using the formula “8.804 + 0.111 × VO(2)max + 0.029 × weekly training distance in km −0.218 × BMI.” Applying this equation in CON, no bias was observed (difference between observed and predicted value 0.12 ± 1.09 km/h, 95% confidence intervals −0.15, 0.40, p = 0.122). CONCLUSION: These findings highlighted the role of aerobic capacity, training, and body mass status for the performance of recreational male runners in a marathon race. The findings would be of great practical importance for coaches and trainers to predict the average marathon race time in a specific group of runners. Frontiers Media S.A. 2021-07-01 /pmc/articles/PMC8280344/ /pubmed/34276402 http://dx.doi.org/10.3389/fphys.2021.682359 Text en Copyright © 2021 Nikolaidis, Rosemann and Knechtle. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Nikolaidis, Pantelis T.
Rosemann, Thomas
Knechtle, Beat
Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed
title Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed
title_full Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed
title_fullStr Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed
title_full_unstemmed Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed
title_short Development and Validation of Prediction Equation of “Athens Authentic Marathon” Men’s Race Speed
title_sort development and validation of prediction equation of “athens authentic marathon” men’s race speed
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280344/
https://www.ncbi.nlm.nih.gov/pubmed/34276402
http://dx.doi.org/10.3389/fphys.2021.682359
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