Literature DB >> 27385548

Predicting race time in male amateur marathon runners.

Juan J Salinero1, María L Soriano1, Beatriz Lara1, César Gallo-Salazar1, Francisco Areces1, Diana Ruiz-Vicente1, Javier Abián-Vicén1, Cristina González-Millán1, Juan Del Coso2.   

Abstract

BACKGROUND: The aim of the study was to analyze the relationship between anthropometry, training characteristics, muscular strength and effort-related cardiovascular response and marathon race time in male amateur runners.
METHODS: A total of 84 male amateur marathon runners aged between 23 and 70 years took part in this study (41.0±9.5 years). All of them competed in the 2013 edition of the Madrid Marathon with a finish time between 169.8 and 316 minutes (226.0±28.5 minutes). Age, running experience, number of marathon races finished, mean kilometers run weekly in the last three months, and previous personal best time in the 10 km, half marathon and marathon were recorded. Moreover, anthropometric characteristics, and the results from the Ruffier Test and a whole-body isometric force test were measured. After the marathon, the race time was registered.
RESULTS: Training volume (r=-0.479; P=0.001), previous running milestones (marathon r=0.756; half-marathon r=0.812; 10-km r=0.732; P<0.001), cardiovascular fitness (r=0.371; P=0.001) and anthropometric variables (body mass, Body Mass Index, body fat percentage, skinfolds and lower leg volume) were correlated to marathon performance (P<0.05). Two regression models appeared from the data with r2>0.50. The best, including body fat percentage, heart rate change during the recovery after the Ruffier Test and the half-marathon race time, was strongly correlated with real marathon performance (r=0.77; P<0.001). A second regression model was proposed replacing the half-marathon performance with the 10-km race time, reducing the correlation to 0.73 (P<0.001).
CONCLUSIONS: Marathon performance could be partially predicted by two different equations, including body fat percentage, recovery heart rate in the Ruffier Test and a half-marathon or 10-km performance.

Entities:  

Mesh:

Year:  2016        PMID: 27385548     DOI: 10.23736/S0022-4707.16.06503-8

Source DB:  PubMed          Journal:  J Sports Med Phys Fitness        ISSN: 0022-4707            Impact factor:   1.637


  11 in total

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Authors:  Tryntsje Fokkema; Ankie A D N van Damme; Maarten W J Fornerod; Robert-Jan de Vos; Sita M A Bierma-Zeinstra; Marienke van Middelkoop
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3.  ACTN3 R577X Genotype and Exercise Phenotypes in Recreational Marathon Runners.

Authors:  Juan Del Coso; Victor Moreno; Jorge Gutiérrez-Hellín; Gabriel Baltazar-Martins; Carlos Ruíz-Moreno; Millán Aguilar-Navarro; Beatriz Lara; Alejandro Lucía
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4.  Muscle Strength and Flexibility in Male Marathon Runners: The Role of Age, Running Speed and Anthropometry.

Authors:  Pantelis Theodoros Nikolaidis; Juan Del Coso; Thomas Rosemann; Beat Knechtle
Journal:  Front Physiol       Date:  2019-10-16       Impact factor: 4.566

5.  Training, Anthropometric, and Physiological Characteristics in Men Recreational Marathon Runners: The Role of Sport Experience.

Authors:  Pantelis T Nikolaidis; Vicente Javier Clemente-Suárez; Daniela Chlíbková; Beat Knechtle
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6.  Exploring the Anthropometric, Cardiorespiratory, and Haematological Determinants of Marathon Performance.

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7.  Assessment Methods of Body Fat in Recreational Marathon Runners: Bioelectrical Impedance Analysis versus Skinfold Thickness.

Authors:  Pantelis T Nikolaidis; Rodrigo Luiz Vancini; Marília Dos Santos Andrade; Claudio Andre Barbosa de Lira; Beat Knechtle
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8.  Pacing Strategies in the 'Athens Classic Marathon': Physiological and Psychological Aspects.

Authors:  Pantelis T Nikolaidis; Beat Knechtle
Journal:  Front Physiol       Date:  2018-11-02       Impact factor: 4.566

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Authors:  Katharina Wirnitzer; Mohamad Motevalli; Derrick Tanous; Gerold Wirnitzer; Claus Leitzmann; Renato Pichler; Thomas Rosemann; Beat Knechtle
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10.  Development and Validation of Prediction Equation of "Athens Authentic Marathon" Men's Race Speed.

Authors:  Pantelis T Nikolaidis; Thomas Rosemann; Beat Knechtle
Journal:  Front Physiol       Date:  2021-07-01       Impact factor: 4.566

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