Additional anthropometric measures may improve the predictability of basal metabolic rate in adult subjects

Abstract

Background:The most commonly used predictive equation for basal metabolic rate (BMR) is the Schofield equation, which only uses information on body weight, age and sex to derive the prediction. However, because body composition is a key influencing factor, there will be error in calculating an individual's basal requirements based on this prediction. Objective: To investigate whether adding additional anthropometric measures to the standard measures can enhance the predictability of BMR and to cross-validate this within a separate subgroup. Design: Cross-sectional study of 150 Caucasian adults from Scotland, with a body mass index range of 16.7-49.3 kg/m 2 . All subjects underwent measurement of BMR, body composition, and 148 also had basic skinfold and circumference measures taken. The resultant equation was tested in a subgroup of 39 obese males. Results: The average difference between the predicted (Schofield equation) and measured BMR was 502 kJ/day. There was a slight systematic bias in this error, with the Schofield equation underestimating the lowest values. The average discrepancy between predicted and actual BMR was reduced to 452 kJ/day, with the addition of fat mass, fat-free mass, an overall 10% improvement on the Schofield equation (P ¼ 0.054). Using an equation derived from principal components analysis of anthropometry measurements similarly decreased the difference to 458 kJ/day (P ¼ 0.039). Testing the equation in a separate group indicated a 33% improvement in predictability of BMR, compared to the Schofield equation. Conclusions: In the absence of detailed information on body composition, utilizing anthropometric data provides a useful alternative methodology to improve the predictability of BMR beyond that achieved from the standard Schofield prediction equation. This should be confirmed in more individuals, both within the obese and normal weight category.

The mass-specific energy cost of human walking is set by stature

“…The error that results from using these equations to predict the mean basal metabolic rates of either children or adult groups was established in the original work as ±2.2-3.4% for groups of 10 subjects (Schofield et al, 1985). Similar accuracy for predicting group means has been subsequently reported by a number of other investigators (De Lorenzo et al, 2001;Piers et al, 1997;Johnstone et al, 2006;Rodriguez et al, 2000;van der Ploeg et al, 2001). …”

“…We used predictive equations rather than direct measurements for this purpose because doing so was necessary for the inclusion and consistent treatment of the 25 qualifying literature group data points used in our scaling analysis. The literature amply supports the ability of the population equations used to predict group means (De Loreonzo et al, 2001;Piers et al, 1997;Johnstone et al, 2006;Rodriguez et al, 2000;Schofield et al, 1985;van der Ploeg et al, 2001;Weyand et al, 2009), indicating an approximate accuracy of 3% for the group sizes assessed here. Indeed, for the six adult subjects on whom we took direct measurements, this was the accuracy observed; the mean predicted value was 3.2% greater than the measured value.…”

BMR in a Brazilian adult probability sample: the Nutrition, Physical Activity and Health Survey

“…Comparison of results from studies in young Brazilian women using the same protocol and calorimeter showed that BMR was not significantly different between women who lived in the tropics (Niterói, Rio de Janeiro state) (3) and women who lived below the Tropic of Capricorn in the temperate (11) 5813 (27) region of the country (Porto Alegre, Rio Grande do Sul state, at 30801 0 59 00 S, 51813 0 48 00 W) (13) . The Schofield equations have also been shown to be inadequate to estimate BMR in clinical settings of people living in Europe and North America (5,7,(39)(40)(41)(42)(43) . It has been suggested that the equations have unsolved problems in origin because they were based on a non-representative sample of the population (6) , limiting their use for prediction of BMR in different populations.…”

Estimating resting energy expenditure in patients requiring nutritional support: a survey of dietetic practice

“…An overwhelming majority (99%) of dietitians surveyed use the Schofield equation to calculate BMR. The Schofield equation does not incorporate measurements of body composition, despite its impact on BMR, which therefore limit its validity for use in individuals (Johnstone et al, 2006). The consistent use of the Schofield equation to calculate BMR is likely to be owing to its recommendation by standard clinical texts in the UK (Thomas, 2001;Todorovic and Micklewright, 2004).…”