ORIGINAL ARTICLE Additional anthropometric measures may improve the predictability of basal metabolic rate in adult subjects AM Johnstone 1 , KA Rance 1 , SD Murison 1 , JS Duncan 1 and JR Speakman 1,2 1 Aberdeen Centre for Energy Regulation and Obesity (ACERO), Division of Obesity and Metabolic Health, Rowett Research Institute, Aberdeen, UK and 2 ACERO, School of Biological Sciences, University of Aberdeen, Aberdeen, UK 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. European Journal of Clinical Nutrition advance online publication, 12 July 2006; doi:10.1038/sj.ejcn.1602477 Keywords: energy requirements; metabolism; health; body composition; anthropometry Introduction Estimates of daily energy requirements are an essential element of many aspects of public health nutrition, such as predicting national or population food requirements (FAO/WHO/UNU, 1985) or defining when individuals have chronic energy deficiency (James et al., 1988). Moreover, knowledge of daily energy needs, predicted as a multiple of basal metabolic rate (BMR), is used in the clinical setting to prescribe intakes for calorie-restricted diets as a part of dietary obesity therapy (e.g. SIGN, 1996). A well-recognized feature of dietary surveys is that individuals underreport the amounts of food that they consume (McGowan et al., 2001) leading to erroneous estimates of dietary energy require- ments. Usually, the classification of mis-reporters is based on their intakes falling below a critical multiple of BMR (Black et al., 1991). Hence, accurately predicting BMR for individuals is an important issue for public health nutrition. Measuring BMR is time consuming and requires specia- lized equipment (e.g. Stewart et al., 2005) that is generally unavailable in the clinical setting, and even if available, Received 8 September 2005; revised 24 April 2006; accepted 23 May 2006 Correspondence: Dr AM Johnstone, Division of Obesity and Metabolic Health, Rowett Research Institute, Greenburn Road, Aberdeen AB21 9SB, UK. E-mail: A.Johnstone@rowett.ac.uk Guarantor: AM Johnstone. Contributor: JRS, KAR and AMJ were responsible for the study concept and design. AMJ, JSD and SDM were responsible for the data collection and laboratory analysis of blood samples. JRS and KAR were responsible for the data analysis. JRS, KAR and AMJ were responsible for the first draft and critical revision of the manuscript for important intellectual content. None of the authors had a conflict of interest. European Journal of Clinical Nutrition (2006), 1–8 & 2006 Nature Publishing Group All rights reserved 0954-3007/06 $30.00 www.nature.com/ejcn