Evidence map›Paper›PMID 42227090›Full record

ArticleProblemy endokrinologii2026

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

A A Averkina, M G Rafaelyan, O V Vasyukova, R M Guseinova, P L Okorokov, Yu V Burmitskaya, V A Romanova, D A Kopytina, E P Atavina-Ermakova, N G Mokrysheva

Abstract readEnglish Abstract
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Article in Problemy endokrinologii, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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Authors and funding

10 authors.

A A AverkinaEndocrinology Research Centre.
M G RafaelyanEndocrinology Research Centre.
O V VasyukovaEndocrinology Research Centre.
R M GuseinovaEndocrinology Research Centre.
P L OkorokovEndocrinology Research Centre.
Yu V BurmitskayaEndocrinology Research Centre.
V A RomanovaEndocrinology Research Centre.
D A KopytinaEndocrinology Research Centre.
E P Atavina-ErmakovaEndocrinology Research Centre.
N G MokryshevaEndocrinology Research Centre.

Funding

Non-US Government Research Support type
6 · The paper itself

Abstract

backgroundAccurate 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.

aimTo compare the accuracy of resting energy expenditure assessment using commonly applied predictive equations and indirect calorimetry in adults with overweight and obesity. MATERIALS AND

methodsAn 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.

resultsThe 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.

conclusionNone 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.

Indexed as

Basal MetabolismEnergy MetabolismObesityAdultBody CompositionBody Mass IndexCalorimetry, IndirectCross-Sectional StudiesFemaleHumansMaleMiddle Aged

Identifiers

PMID42227090
PMCPMC13288070

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