Literature DB >> 12196030

Methods to determine aerobic endurance.

Laurent Bosquet1, Luc Léger, Patrick Legros.   

Abstract

Physiological testing of elite athletes requires the correct identification and assessment of sports-specific underlying factors. It is now recognised that performance in long-distance events is determined by maximal oxygen uptake (V(2 max)), energy cost of exercise and the maximal fractional utilisation of V(2 max) in any realised performance or as a corollary a set percentage of V(2 max) that could be endured as long as possible. This later ability is defined as endurance, and more precisely aerobic endurance, since V(2 max) sets the upper limit of aerobic pathway. It should be distinguished from endurance ability or endurance performance, which are synonymous with performance in long-distance events. The present review examines methods available in the literature to assess aerobic endurance. They are numerous and can be classified into two categories, namely direct and indirect methods. Direct methods bring together all indices that allow either a complete or a partial representation of the power-duration relationship, while indirect methods revolve around the determination of the so-called anaerobic threshold (AT). With regard to direct methods, performance in a series of tests provides a more complete and presumably more valid description of the power-duration relationship than performance in a single test, even if both approaches are well correlated with each other. However, the question remains open to determine which systems model should be employed among the several available in the literature, and how to use them in the prescription of training intensities. As for indirect methods, there is quantitative accumulation of data supporting the utilisation of the AT to assess aerobic endurance and to prescribe training intensities. However, it appears that: there is no unique intensity corresponding to the AT, since criteria available in the literature provide inconsistent results; and the non-invasive determination of the AT using ventilatory and heart rate data instead of blood lactate concentration ([La(-)](b)) is not valid. Added to the fact that the AT may not represent the optimal training intensity for elite athletes, it raises doubt on the usefulness of this theory without questioning, however, the usefulness of the whole [La(-)](b)-power curve to assess aerobic endurance and predict performance in long-distance events.

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Year:  2002        PMID: 12196030     DOI: 10.2165/00007256-200232110-00002

Source DB:  PubMed          Journal:  Sports Med        ISSN: 0112-1642            Impact factor:   11.136


  204 in total

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2.  Time limit and time at VO2max' during a continuous and an intermittent run.

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Journal:  J Sports Med Phys Fitness       Date:  2000-06       Impact factor: 1.637

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Journal:  Int J Sports Med       Date:  1996-05       Impact factor: 3.118

Review 4.  The slow component of oxygen uptake kinetics in humans.

Authors:  G A Gaesser; D C Poole
Journal:  Exerc Sport Sci Rev       Date:  1996       Impact factor: 6.230

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Journal:  Ergonomics       Date:  1989-08       Impact factor: 2.778

6.  Oxygen deficit is related to the exercise time to exhaustion at maximal aerobic speed in middle distance runners.

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Journal:  Arch Physiol Biochem       Date:  1999-10       Impact factor: 4.076

7.  Noninvasive determination of the anaerobic threshold in swimming.

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Journal:  Int J Sports Med       Date:  1986-12       Impact factor: 3.118

8.  Running economy and distance running performance of highly trained athletes.

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Journal:  Med Sci Sports Exerc       Date:  1980       Impact factor: 5.411

9.  Relationships of the anaerobic threshold with the 5 km, 10 km, and 10 mile races.

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Journal:  Eur J Appl Physiol Occup Physiol       Date:  1982

10.  Lactate kinetics and individual anaerobic threshold.

Authors:  H Stegmann; W Kindermann; A Schnabel
Journal:  Int J Sports Med       Date:  1981-08       Impact factor: 3.118

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  43 in total

1.  Predicting maximal aerobic speed through set distance time-trials.

Authors:  Clint R Bellenger; Joel T Fuller; Maximillian J Nelson; Micheal Hartland; Jonathan D Buckley; Thomas A Debenedictis
Journal:  Eur J Appl Physiol       Date:  2015-08-05       Impact factor: 3.078

2.  Peak oxygen uptake. Myth and truth about an internationally accepted reference value.

Authors:  T Meyer; J Scharhag; W Kindermann
Journal:  Z Kardiol       Date:  2005-04

Review 3.  Training to enhance the physiological determinants of long-distance running performance: can valid recommendations be given to runners and coaches based on current scientific knowledge?

Authors:  Adrian W Midgley; Lars R McNaughton; Andrew M Jones
Journal:  Sports Med       Date:  2007       Impact factor: 11.136

4.  Vmax estimate from three-parameter critical velocity models: validity and impact on 800 m running performance prediction.

Authors:  Laurent Bosquet; Antoine Duchene; François Lecot; Grégory Dupont; Luc Leger
Journal:  Eur J Appl Physiol       Date:  2006-02-09       Impact factor: 3.078

5.  Prediction of time to exhaustion from blood lactate response during submaximal exercise in competitive cyclists.

Authors:  A Sassi; S M Marcora; E Rampinini; P Mognoni; F M Impellizzeri
Journal:  Eur J Appl Physiol       Date:  2006-03-09       Impact factor: 3.078

6.  Estimation of the lactate threshold using an electro acoustic sensor system analysing the respiratory air.

Authors:  M Folke
Journal:  Med Biol Eng Comput       Date:  2008-07-24       Impact factor: 2.602

Review 7.  Cardiac parasympathetic reactivation following exercise: implications for training prescription.

Authors:  Jamie Stanley; Jonathan M Peake; Martin Buchheit
Journal:  Sports Med       Date:  2013-12       Impact factor: 11.136

8.  Monitoring endurance running performance using cardiac parasympathetic function.

Authors:  Martin Buchheit; A Chivot; J Parouty; D Mercier; H Al Haddad; P B Laursen; S Ahmaidi
Journal:  Eur J Appl Physiol       Date:  2009-12-22       Impact factor: 3.078

9.  A comparison of modelling procedures used to estimate the power-exhaustion time relationship.

Authors:  Thierry Busso; Philippe Gimenez; Michel Chatagnon
Journal:  Eur J Appl Physiol       Date:  2009-09-24       Impact factor: 3.078

10.  Performance-related workload in alpine skiing with congenital heart disease.

Authors:  Andreas Rosenhagen; Rene Hoehn; Christian Thiel; Lutz Vogt; Roland Hofstetter; Winfried Banzer
Journal:  BMJ Case Rep       Date:  2009-06-18
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