The validity of predicting the basal metabolic rate of young Australian men and women

Abstract

Objectives: To assess the accuracy of the Scho®eld, Scho®eld & James (1985) equations and those of Hayter & Henry (1994) for the prediction of the basal metabolic rate (BMR), of young Australians. Design: BMR was measured by indirect calorimetry, while fat free mass (FFM) and fat mass (FM) were measured by bioelectric impendence analysis (BIA) in 128 volunteers (39 men and 89 women), aged between 18 and 30 y. Setting: Deakin Institute of Human Nutrition, Deakin University, Melbourne, Australia. Results: The measured BMR of Australian men and women were signi®cantly lower (P 0.001) than the predicted BMR using the Scho®eld et al (1985) equation, with a mean (s.d.) bias (bias measured 7 predicted BMR) of 7406 (513) kJ/d in men and 7124 (348) kJ/d in women. The measured BMR of Australian men and women were similar to the predicted BMR using the equations of Hayter & Henry (1994) and bias was unrelated to body weight. BMR adjusted for FFM and FM was signi®cantly higher by three percent in women on oral contraceptive agents (OCA) as compared to those not on OCA. Conclusions: The Scho®eld et al (1985) equations are not valid for the prediction of BMR of young Australian men and women. The equations of Hayter & Henry (1994) for North Europeans and Americans, provide an accurate estimate of the BMR of Australian men and women at the group level. However, in young women not using OCA a correction factor of 0.97 applied to the predicted BMR provides a better estimate.

Predicting the resting metabolic rate of young Australian males

“…The regression equations of Harris & Benedict (1919) and Scho®eld (1985) all overestimated the mean RMR of our subjects by 518 ± 600 kJaday (P`0.001) and these errors were relatively constant across the range of measured RMR. The equations of Hayter & Henry (1994) and Piers et al (1997) only produced physiologically signi®cant errors at the lower end of our range of measurement. Conclusions: Equations need to be generated from a large database for the prediction of the RMR of 18 to 30-yold Australian males and FFM estimated from the regression of the sum of skinfold thicknesses on FFM via the four compartment body composition model needs to be further explored as an expedient RMR predictor.…”

“…The dependent t-test was used to determine whether our measured RMR mean was signi®cantly different (P 0.05) from those predicted by the equations of Harris & Benedict (1919), Scho®eld (1985), Hayter & Henry (1994) and Piers et al (1997). Total errors were also calculated as follows:…”

“…The RMRs predicted by the equations of Harris & Benedit (1919), Scho®eld (1985), Hayter & Henry (1994) and Piers et al (1997) will then be crossvalidated against our measured and predicted values.…”

“…More recently, Piers et al, (1997) demonstrated that the Scho®eld (1985) equations signi®cantly overpredict (P`0.001) the RMR of 18 to 30-y-old Australian males and females. The present investigation extends the work of Piers et al (1997) by using fat-free mass (FFM) as a predictor of RMR.…”

“…More recently, Piers et al, (1997) demonstrated that the Scho®eld (1985) equations signi®cantly overpredict (P`0.001) the RMR of 18 to 30-y-old Australian males and females. The present investigation extends the work of Piers et al (1997) by using fat-free mass (FFM) as a predictor of RMR. The FFM is a more valid predictor of RMR than body mass because it has a much higher rate of resting energy expenditure (Elia, 1992b: 124.3 kJ Á kg 71 Á day 71 ) than adipose tissue (Elia, 1992b: 18.8 kJ Á kg 71 Á day 71 ).…”