2.50
Hdl Handle:
http://hdl.handle.net/2436/8005
Title:
Scaling physiological measurements for individuals of different body size.
Authors:
Nevill, Alan M.; Ramsbottom, Roger; Williams, Clyde
Abstract:
This paper examines how selected physiological performance variables, such as maximal oxygen uptake, strength and power, might best be scaled for subject differences in body size. The apparent dilemma between using either ratio standards or a linear adjustment method to scale was investigated by considering how maximal oxygen uptake (l.min-1), peak and mean power output (W) might best be adjusted for differences in body mass (kg). A curvilinear power function model was shown to be theoretically, physiologically and empirically superior to the linear models. Based on the fitted power functions, the best method of scaling maximum oxygen uptake, peak and mean power output, required these variables to be divided by body mass, recorded in the units kg 2/3. Hence, the power function ratio standards (ml.kg-2/3.min-1) and (W.kg-2/3) were best able to describe a wide range of subjects in terms of their physiological capacity, i.e. their ability to utilise oxygen or record power maximally, independent of body size. The simple ratio standards (ml.kg-1.min-1) and (W.kg-1) were found to best describe the same subjects according to their performance capacities or ability to run which are highly dependent on body size. The appropriate model to explain the experimental design effects on such ratio standards was shown to be log-normal rather than normal. Simply by taking logarithms of the power function ratio standard, identical solutions for the design effects are obtained using either ANOVA or, by taking the unscaled physiological variable as the dependent variable and the body size variable as the covariate, ANCOVA methods.
Citation:
European Journal of Applied Physiology, 65(2): 110-117
Publisher:
Springer Verlag
Issue Date:
1992
URI:
http://hdl.handle.net/2436/8005
DOI:
10.1007/BF00705066
PubMed ID:
1396632
Additional Links:
http://www.springerlink.com/content/g34726g217887553/
Submitted date:
2007-01-31
Type:
Article
Language:
en
ISSN:
0301-5548
Appears in Collections:
Sport, Exercise and Health Research Group; Exercise and Health; Learning and Teaching in Sport, Exercise and Performance

Full metadata record

DC FieldValue Language
dc.contributor.authorNevill, Alan M.-
dc.contributor.authorRamsbottom, Roger-
dc.contributor.authorWilliams, Clyde-
dc.date.accessioned2007-01-31T14:29:14Z-
dc.date.available2007-01-31T14:29:14Z-
dc.date.issued1992-
dc.date.submitted2007-01-31-
dc.identifier.citationEuropean Journal of Applied Physiology, 65(2): 110-117en
dc.identifier.issn0301-5548-
dc.identifier.pmid1396632-
dc.identifier.doi10.1007/BF00705066-
dc.identifier.urihttp://hdl.handle.net/2436/8005-
dc.description.abstractThis paper examines how selected physiological performance variables, such as maximal oxygen uptake, strength and power, might best be scaled for subject differences in body size. The apparent dilemma between using either ratio standards or a linear adjustment method to scale was investigated by considering how maximal oxygen uptake (l.min-1), peak and mean power output (W) might best be adjusted for differences in body mass (kg). A curvilinear power function model was shown to be theoretically, physiologically and empirically superior to the linear models. Based on the fitted power functions, the best method of scaling maximum oxygen uptake, peak and mean power output, required these variables to be divided by body mass, recorded in the units kg 2/3. Hence, the power function ratio standards (ml.kg-2/3.min-1) and (W.kg-2/3) were best able to describe a wide range of subjects in terms of their physiological capacity, i.e. their ability to utilise oxygen or record power maximally, independent of body size. The simple ratio standards (ml.kg-1.min-1) and (W.kg-1) were found to best describe the same subjects according to their performance capacities or ability to run which are highly dependent on body size. The appropriate model to explain the experimental design effects on such ratio standards was shown to be log-normal rather than normal. Simply by taking logarithms of the power function ratio standard, identical solutions for the design effects are obtained using either ANOVA or, by taking the unscaled physiological variable as the dependent variable and the body size variable as the covariate, ANCOVA methods.en
dc.format.extent830295 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.publisherSpringer Verlagen
dc.relation.urlhttp://www.springerlink.com/content/g34726g217887553/-
dc.subjectRatio standardsen
dc.subjectPhysiological capacityen
dc.subjectPerformance capacityen
dc.subjectExperimental design effectsen
dc.subjectLog-linear modelsen
dc.titleScaling physiological measurements for individuals of different body size.en
dc.typeArticleen
dc.format.digYES-

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