Use of body mass, height and surface area in the estimation of fat-free mass, total body water, metabolic rate, left ventricular mass, extracellular fluid volume and glomerular filtration rate: the comparison and reconciliation of diverse equation types

Burton, R. F. (2012) Use of body mass, height and surface area in the estimation of fat-free mass, total body water, metabolic rate, left ventricular mass, extracellular fluid volume and glomerular filtration rate: the comparison and reconciliation of diverse equation types. International Journal of Body Composition Research, 10(3), pp. 63-72.

Full text not currently available from Enlighten.

Abstract

Background: A profusion of regression equations exists relating surface area, fat-free mass, total body water and various clinical variables to height and body mass, directly or indirectly. Other published equations lack either the height or the mass term. Objective: The main aim is to show how algebraically different types of prediction equation are interrelated, thus facilitating the integration of research findings and future choices of equations. Another is to explore the rationales for the equations. Research methods and procedures: The treatment is largely algebraic, but illustrated numerically. Results and discussion: The most straightforward way of relating the predicted variables to height and body mass is through the linear regression function (A[height] + B[body mass] + C). The power function (heighta × TBMb) is also used, in estimating body surface area (BSA) or fat-free mass (FFM) for example, but for ordinary ranges of body size this approximates closely to the linear function. BSA and FFM are each sometimes used as intermediate variables in estimating other variables from height and body mass, but this is unnecessary if the relevant equations are, in effect, combined. For some predicted variables of the title either the height term or the mass term proves superfluous. For FFM a theoretical equation is derived that takes into account the tendency of FFM to increase with both height and fat mass. For limited ranges of height this approximates numerically to the above linear function. The analysis suggests that prediction equations obtained by linear regression are generally to be recommended.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Burton, Dr Richard
Authors: Burton, R. F.
College/School:College of Medical Veterinary and Life Sciences > School of Life Sciences
Journal Name:International Journal of Body Composition Research
Publisher:Smith-Gordon and Co. Ltd.
ISSN:1479-456X

University Staff: Request a correction | Enlighten Editors: Update this record