Scaling maximal oxygen uptake to predict cycling time-trial performance in the field: a non-linear approach.

2.50
Hdl Handle:
http://hdl.handle.net/2436/7755
Title:
Scaling maximal oxygen uptake to predict cycling time-trial performance in the field: a non-linear approach.
Authors:
Nevill, Alan M.; Jobson, Simon A.; Palmer, G.S.; Olds, Tim
Abstract:
The purpose of the present article is to identify the most appropriate method of scaling VO2max for differences in body mass when assessing the energy cost of time-trial cycling. The data from three time-trial cycling studies were analysed (N = 79) using a proportional power-function ANCOVA model. The maximum oxygen uptake-to-mass ratio found to predict cycling speed was VO2max(m)(-0.32) precisely the same as that derived by Swain for sub-maximal cycling speeds (10, 15 and 20 mph). The analysis was also able to confirm a proportional curvilinear association between cycling speed and energy cost, given by (VO2max(m)(-0.32))0.41. The model predicts, for example, that for a male cyclist (72 kg) to increase his average speed from 30 km h(-1) to 35 km h(-1), he would require an increase in VO2max from 2.36 l min(-1) to 3.44 l min(-1), an increase of 1.08 l min(-1). In contrast, for the cyclist to increase his mean speed from 40 km h(-1) to 45 km h(-1), he would require a greater increase in VO2max from 4.77 l min(-1) to 6.36 l min(-1), i.e. an increase of 1.59 l min(-1). The model is also able to accommodate other determinants of time-trial cycling, e.g. the benefit of cycling with a side wind (5% faster) compared with facing a predominately head/tail wind (P<0.05). Future research could explore whether the same scaling approach could be applied to, for example, alternative measures of recording power output to improve the prediction of time-trial cycling performance.
Citation:
European Journal of Applied Physiology, 94(5-6): 705-710
Publisher:
Springer Berlin / Heidelberg
Issue Date:
2005
URI:
http://hdl.handle.net/2436/7755
DOI:
10.1007/s00421-005-1321-8
PubMed ID:
15906080
Additional Links:
http://www.springerlink.com/content/j863561v70228548/
Type:
Article
Language:
en
ISSN:
1439-6319
Appears in Collections:
Sport, Exercise and Health Research Group; Sport Performance; Learning and Teaching in Sport, Exercise and Performance

Full metadata record

DC FieldValue Language
dc.contributor.authorNevill, Alan M.-
dc.contributor.authorJobson, Simon A.-
dc.contributor.authorPalmer, G.S.-
dc.contributor.authorOlds, Tim-
dc.date.accessioned2007-01-25T16:03:07Z-
dc.date.available2007-01-25T16:03:07Z-
dc.date.issued2005-
dc.identifier.citationEuropean Journal of Applied Physiology, 94(5-6): 705-710en
dc.identifier.issn1439-6319-
dc.identifier.pmid15906080-
dc.identifier.doi10.1007/s00421-005-1321-8-
dc.identifier.urihttp://hdl.handle.net/2436/7755-
dc.description.abstractThe purpose of the present article is to identify the most appropriate method of scaling VO2max for differences in body mass when assessing the energy cost of time-trial cycling. The data from three time-trial cycling studies were analysed (N = 79) using a proportional power-function ANCOVA model. The maximum oxygen uptake-to-mass ratio found to predict cycling speed was VO2max(m)(-0.32) precisely the same as that derived by Swain for sub-maximal cycling speeds (10, 15 and 20 mph). The analysis was also able to confirm a proportional curvilinear association between cycling speed and energy cost, given by (VO2max(m)(-0.32))0.41. The model predicts, for example, that for a male cyclist (72 kg) to increase his average speed from 30 km h(-1) to 35 km h(-1), he would require an increase in VO2max from 2.36 l min(-1) to 3.44 l min(-1), an increase of 1.08 l min(-1). In contrast, for the cyclist to increase his mean speed from 40 km h(-1) to 45 km h(-1), he would require a greater increase in VO2max from 4.77 l min(-1) to 6.36 l min(-1), i.e. an increase of 1.59 l min(-1). The model is also able to accommodate other determinants of time-trial cycling, e.g. the benefit of cycling with a side wind (5% faster) compared with facing a predominately head/tail wind (P<0.05). Future research could explore whether the same scaling approach could be applied to, for example, alternative measures of recording power output to improve the prediction of time-trial cycling performance.en
dc.format.extent282770 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.publisherSpringer Berlin / Heidelbergen
dc.relation.urlhttp://www.springerlink.com/content/j863561v70228548/en
dc.subjectPower outputen
dc.subjectAllometric modellingen
dc.subjectCyclingen
dc.subjectBody massen
dc.subjectWind resistanceen
dc.subjectPerformance measurement-
dc.subjectSports Medicine-
dc.titleScaling maximal oxygen uptake to predict cycling time-trial performance in the field: a non-linear approach.en
dc.typeArticleen
dc.format.digYES-

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