Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363179
Title: Modelling in physiology and human performance : the influence of body size.
Author: Batterham, Alan Mark.
Awarding Body: Manchester Metropolitan University
Current Institution: Manchester Metropolitan University
Date of Award: 1997
Availability of Full Text:
Access through EThOS:
Abstract:
This thesis examined the validity of allometric models (Y = aXbg) in scaling physiological and human performance data (Y) for differences in body size (X). 1) Anaerobic performance. External peak power output (PPO) derived from supramaximalleg ergometry was compared in young adult males and females, using a multivariate allometric model. Estimated fat free mass (FFM) and thigh muscle-and-bone cross-sectional area served as indicators of involved musculature. Male PPO was greater than female (P < 0.05), after allometric adjustment for body size differences. This finding is questionable, however, as the within-gender goodness-of-fit values for the regression models were very poor. 2) Cardiac dimensions. The proper relationships between echocardiographic dimensions [left ventricular (LV) mass, and LV internal dimensions] and various indicators of overall body size [height, body mass (BM), FFM, and body surface area (BSA)] were examined in young, apparently healthy, adult males and females. Scaling by FFM was associated with the least residual error in these samples. The obtained relationships were generally dimensionally consistent, that is, LV mass proportional to FFM to the first power, and LV internal dimensions related to the 1/3 power ofFFM. 3) Methodological issues. The multivariate allometric scaling of peak oxygen uptake by height and BM was investigated. Regression diagnostics revealed that the obtained exponents were unstable, and potentially numerically inaccurate, due to severe collinearity between height and BM in the sample. For elite weightlifting performance, detailed examination of the allometric regression residuals revealed that the model was poorly specified. Re-specification of the model using secondorder polynomials provided the optimal scaling of this data set.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.363179  DOI: Not available
Keywords: Allometry; Echocardiography; Heart size Human physiology Mathematical statistics Operations research
Share: