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dc.contributor.authorNevill, Alan M.
dc.contributor.authorMarkovic, G
dc.contributor.authorVucetic, V
dc.contributor.authorHolder, Roger L.
dc.date.accessioned2007-04-05T11:02:50Z
dc.date.available2007-04-05T11:02:50Z
dc.date.issued2004
dc.date.submitted2007-03-14
dc.identifier.citationAnnals of Human Biology, 31(4): 436-445
dc.identifier.issn0301-4460
dc.identifier.pmid15513694
dc.identifier.doi10.1080/03014460410001723996
dc.identifier.urihttp://hdl.handle.net/2436/11119
dc.description.abstractBACKGROUND: The power function relationship, MR = a.m(b), between metabolic rate (MR) and body mass m has been the source of much controversy amongst biologists for many years. Various studies have reported mass exponents (b) greater than the anticipated 'surface-area' exponent 0.67, often closer to 0.75 originally identified by Kleiber. AIM: The study aimed to provide a biological explanation for these 'inflated' exponents when modelling maximum oxygen uptake (max), based on the observations from this and previous studies that larger individuals develop disproportionately more muscle mass in the arms and legs. RESEARCH DESIGN AND SUBJECTS: A cross-sectional study of 119 professional soccer players from Croatia aged 18-34 was carried out. RESULTS: Here we confirm that the power function relationship between max and body mass of the professional soccer players results in an 'inflated' mass exponent of 0.75 (95% confidence interval from 0.56 to 0.93), but also the larger soccer players have disproportionately greater leg muscle girths. When the analysis was repeated incorporating the calf and thigh muscle girths rather than body mass as predictor variables, the analysis not only explained significantly more of the variance in max, but the sum of the exponents confirmed a surface-area law. CONCLUSIONS: These findings confirm the pitfalls of fitting body-mass power laws and suggest using muscle-girth methodology as a more appropriate way to scale or normalize metabolic variables such as max for individuals of different body sizes.
dc.format.extent129225 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherTaylor & Francis
dc.relation.urlhttps://www.tandfonline.com/doi/abs/10.1080/03014460410001723996
dc.subjectMuscularity
dc.subjectLarger individuals
dc.subjectMaximum oxygen uptake
dc.subjectSoccer players
dc.subjectFootball players
dc.subjectCroatia
dc.titleCan greater muscularity in larger individuals resolve the 3/4 power-law controversy when modelling maximum oxygen uptake?
dc.typeJournal article
dc.format.digYES
refterms.dateFOA2018-08-21T09:41:49Z
html.description.abstractBACKGROUND: The power function relationship, MR = a.m(b), between metabolic rate (MR) and body mass m has been the source of much controversy amongst biologists for many years. Various studies have reported mass exponents (b) greater than the anticipated 'surface-area' exponent 0.67, often closer to 0.75 originally identified by Kleiber. AIM: The study aimed to provide a biological explanation for these 'inflated' exponents when modelling maximum oxygen uptake (max), based on the observations from this and previous studies that larger individuals develop disproportionately more muscle mass in the arms and legs. RESEARCH DESIGN AND SUBJECTS: A cross-sectional study of 119 professional soccer players from Croatia aged 18-34 was carried out. RESULTS: Here we confirm that the power function relationship between max and body mass of the professional soccer players results in an 'inflated' mass exponent of 0.75 (95% confidence interval from 0.56 to 0.93), but also the larger soccer players have disproportionately greater leg muscle girths. When the analysis was repeated incorporating the calf and thigh muscle girths rather than body mass as predictor variables, the analysis not only explained significantly more of the variance in max, but the sum of the exponents confirmed a surface-area law. CONCLUSIONS: These findings confirm the pitfalls of fitting body-mass power laws and suggest using muscle-girth methodology as a more appropriate way to scale or normalize metabolic variables such as max for individuals of different body sizes.


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