Abstract
Predictive equations have been specifically developed for obese patients to estimate resting energy expenditure (REE). Body composition (BC) assessment is needed for some of these equations. We assessed the impact of BC methods on the accuracy of specific predictive equations developed in obese patients. REE was measured (mREE) by indirect calorimetry and BC assessed by bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). mREE, percentages of prediction accuracy (±10% of mREE) were compared. Predictive equations were studied in 2588 obese patients. Mean mREE was 1788 ± 6.3 kcal/24 h. Only the Müller (BIA) and Harris & Benedict (HB) equations provided REE with no difference from mREE. The Huang, Müller, Horie-Waitzberg, and HB formulas provided a higher accurate prediction (>60% of cases). The use of BIA provided better predictions of REE than DXA for the Huang and Müller equations. Inversely, the Horie-Waitzberg and Lazzer formulas provided a higher accuracy using DXA. Accuracy decreased when applied to patients with BMI ≥ 40, except for the Horie-Waitzberg and Lazzer (DXA) formulas. Müller equations based on BIA provided a marked improvement of REE prediction accuracy than equations not based on BC. The interest of BC to improve REE predictive equations accuracy in obese patients should be confirmed.
Highlights
Assessment of resting energy expenditure (REE) provides information for weight management and adaptation of nutritional intakes, useful in obese patients [1]
The aim of the present study was to assess the impact of Body composition (BC) methods, either bioelectrical impedance analysis (BIA) or dual-energy X-ray absorptiometry (DXA), on the accuracy of specific predictive equations developed in obese patients
Predictive equations were studied in 2588 obese patients with 2073 women and 515 men
Summary
Assessment of resting energy expenditure (REE) provides information for weight management and adaptation of nutritional intakes, useful in obese patients [1]. Several predictive equations have been developed to estimate REE [4]. Several studies have assessed the validity of REE predictive equations in obese subjects with some controversial results [4,5,6,7]. Body composition (BC) assessment is needed for some of these predictive equations, to quantify fat free mass (FFM) which is an important determinant of REE [8]. Several studies reported that including BC data does not improve the accuracy of REE predictive equations in obese patients [6,9,10,11]
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