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Abstract

Background: The most common clinical method for resting energy expenditure (REE) assessment is prediction equations. The purpose of this study was to elucidate which prediction equation is most accurate for REE assessment in extremely obese women. Methods: Fourteen extremely obese women (mean ± SD body mass index: 49.8 ± 6.2 kg/m²; age: 49 ± 10 years) were measured for height and weight and REE via indirect calorimetry (IC) by a metabolic cart system. Predicted REE was evaluated by several equations, including Harris-Benedict with actual body weight, Harris-Benedict with several adjustments to body weight, Cunningham, Mifflin-St Jeor, Owen, World Health Organization (WHO), and Bernstein equations. Accuracy was determined by mean difference data (IC REE – equation REE; Student's paired t-test), correlation coefficients, and agreement between methods by Bland-Altman plots. Accuracy was also evaluated on an individual basis, defined by the percentage of individuals within ±10% of IC REE. Results: The Mifflin-St Jeor, Harris-Benedict with actual body weight, and the WHO equations were the most accurate in terms of mean predicted REE. The mean predicted REE values by all other equations were different from the IC REE values (p < .1). According to the individual data, the Mifflin-St Jeor was most accurate (14% outside± 10% IC REE). The Harris-Benedict with actual body weight and WHO equations were less accurate on individual terms, with 29% and 42% of the predicted REE values, respectively, falling outside ±10% of IC REE. Conclusions: The Mifflin-St Jeor equation was most accurate method for REE assessment in extremely obese women.

Six published prediction equations and several body weight adjustments for obesity were validated in extremely obese women. Adjusting body weight for obesity produced inaccurate estimates. The Mifflin-St Jeor prediction equation was most accurate when compared with measured resting energy expenditure, according to mean data analyses and individual data inspection.

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Predicting Energy Expenditure in Extremely Obese Women

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