Resting Energy Expenditure Assessment in Adults with Obesity: Limitations of Commonly Used Predictive Equations

BACKGROUND: Accurate assessment of resting energy expenditure (REE) in patients with overweight and obesity is a key component of personalized dietary planning and physical activity prescription. Although indirect calorimetry (IC) is considered the gold standard for measuring resting energy expenditure, predictive equations are predominantly used in clinical practice, despite their limited and variable accuracy in individuals with obesity. AIM: To compare the accuracy of resting energy expenditure assessment using commonly applied predictive equations and indirect calorimetry in adults with overweight and obesity.

MATERIALS AND METHODS: An open cross-sectional comparative study was conducted in adults with a body mass index (BMI) ≥25 kg/m². Resting energy expenditure (REE) was measured using IC (Cosmed K5) and calculated with eight commonly used predictive equations. Body composition was assessed by bioelectrical impedance analysis InBody770. Accuracy was evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), Pearson correlation coefficient, and Bland–Altman analysis.

RESULTS: The study included 293 patients (111 men and 182 women) with a median (BMI) of 38.3 [32.9; 44.0] kg/m². The median REE measured by IC was 1964.5 [1570.8; 2370.5] kcal/day. All analyzed predictive equations demonstrated substantial individual error, with the mean absolute percentage error exceeding 15% in more than 50% of patients. The smallest mean bias relative to measured values was observed for the Roza–Shizgal, WHO (Schofield), and Harris–Benedict equations; however, even these formulas showed wide limits of agreement in Bland–Altman analysis. The accuracy of all equations declined with increasing age and obesity severity and was lowest in patients with BMI ≥40 and ≥50 kg/m². Equations based on fat-free mass systematically underestimated REE in patients with morbid obesity.

CONCLUSION: None of the commonly used predictive equations provides high individual accuracy for estimating REE in adults with obesity. Even equations with minimal mean bias are characterized by pronounced interindividual variability and reduced accuracy with increasing age and obesity severity. IC remains the most reliable method for determining energy requirements, particularly in patients with severe and morbid obesity.

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