Weight and body composition changes affect resting energy expenditure predictive equations during a 12‐month weight‐loss intervention

Abstract Background Evidence in humans is equivocal in regards to whether resting energy expenditure (REE) decreases to a greater extent than predicted for the loss of body mass with weight loss, and whether this disproportionate decrease in REE persists with weight-loss maintenance. Objectives We aimed to1) determine if a lower-than-predicted REE is present in a sample of successful weight-loss maintainers (WLMs) and 2) determine if amount of weight loss or duration of weight-loss maintenance are correlated with a lower-than-predicted REE in WLMs. Design Participants (18–65 y old) were recruited in 3 groups: WLMs (maintaining ≥13.6 kg weight loss for ≥1 y, n = 34), normal-weight controls [NCs, body mass index (BMI; in kg/m2) similar to current BMI of WLMs, n = 35], and controls with overweight/obesity (OCs, BMI similar to pre–weight-loss maximum BMI of WLMs, n = 33). REE was measured (REEm) with indirect calorimetry. Predicted REE (REEp) was determined via 1) a best-fit linear regression developed with the use of REEm, age, sex, fat-free mass, and fat mass from our control groups and 2) three standard predictive equations. Results REEm in WLMs was accurately predicted by equations developed from NCs and OCs (±1%) and by 3 standard predictive equations (±3%). In WLMs, individual differences between REEm and REEp ranged from −257 to +163 kcal/d. A lower REEm compared with REEp was correlated with amount of weight lost (r = 0.36, P < 0.05) but was not correlated with duration of weight-loss maintenance (r = 0.04, P = 0.81). Conclusions We found no consistent evidence of a significantly lower REE than predicted in a sample of long-term WLMs based on predictive equations developed from NCs and OCs as well as 3 standard predictive equations. Results suggest that sustained weight loss may not always result in a substantial, disproportionately low REE. This trial was registered at clinicaltrials.gov as NCT03422380.

Download Full-text

Effects of the Curves® fitness & weight loss program in women with medically‐managed conditions: body composition and resting energy expenditure

The FASEB Journal ◽

10.1096/fasebj.23.1_supplement.lb462 ◽

2009 ◽

Vol 23 (S1) ◽

Author(s):

C Rasmussen ◽

J Culbertson ◽

R Li ◽

M Ferreira ◽

A Parker ◽

...

Keyword(s):

Weight Loss ◽

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Weight Loss Program ◽

Resting Energy

Download Full-text

Accuracy of predictive equations for evaluation of resting energy expenditure in Brazilian patients with type 2 diabetes.

10.21203/rs.3.rs-25229/v1 ◽

2020 ◽

Author(s):

Thaiciane Grassi ◽

Francesco Pinto Boeno ◽

Mauren Minuzzo de Freitas ◽

Tatiana Pedroso de Paula ◽

Luciana Vercoza Viana ◽

...

Keyword(s):

Type 2 Diabetes ◽

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Fat Free Mass ◽

Composition Analysis ◽

Cross Sectional ◽

Predictive Equations ◽

Resting Energy

Abstract Background Evaluation of the resting energy expenditure (REE) is essential to ensure an appropriate dietary prescription for patients with type 2 diabetes. The aim of this study was to evaluate the accuracy of predictive equations for REE estimation in patients with type 2 diabetes, considering indirect calorimetry (IC) as the reference method.Methods A cross-sectional study was conducted in 62 patients (31 men and 31 women) with type 2 diabetes. Clinical and laboratory variables were evaluated, as well as body composition by electrical bioimpedance. The REE was measured by IC (QUARK RMR, Cosmed, Rome, Italy) and estimated by predictive equations. Data were analyzed using Bland–Altman plots, paired t-tests, and Pearson’s correlation coefficients.Results Patients in the sample had a mean age of 63.1 ± 5.2 years, median diabetes duration of 11 (1–36) years, and mean A1C of 7.6 ± 1.2%. Body composition analysis revealed a mean fat free mass of 35.2 ± 11.8 kg and fat mass of 29.1 ± 8.8 kg. There was wide variation in the accuracy of REE values predicted by equations when compared to those measured by IC. For women, the FAO/WHO/UNO equation provided the best REE prediction in comparison to measured REE (-1.8% difference). For men, the Oxford equation yielded values closest to those measured by IC (-1.3% difference).Conclusions In this sample of the patients with type 2 diabetes, the best predictive equations to estimate REE were FAO/WHO/UNO and Oxford for women and men, respectively.

Download Full-text

Resting Energy Expenditure during Breastfeeding: Body Composition Analysis vs. Predictive Equations Based on Anthropometric Parameters

Nutrients ◽

10.3390/nu12051274 ◽

2020 ◽

Vol 12 (5) ◽

pp. 1274

Author(s):

Agnieszka Bzikowska-Jura ◽

Adriana Szulińska ◽

Dorota Szostak-Węgierek

Keyword(s):

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Accurate Estimation ◽

Composition Analysis ◽

Anthropometric Parameters ◽

Predictive Equations ◽

Body Composition Analysis ◽

Mathematical Equations ◽

Resting Energy

Accurate estimation of energy expenditure in a breastfeeding woman is crucial for maintaining the proper nutritional status of the woman and healthy development of the infant. The current literature does not contain data regarding resting energy expenditure (REE) in breastfeeding women. Using mathematical equations is the most common method of REE assessment. However, due to changes in metabolism and body composition during pregnancy and lactation, the mathematical equations used among the general population may not apply. The aim of this study was to evaluate the resting energy expenditure of exclusively breastfeeding women by using body composition analysis–estimated REE (eREE) and to provide the most appropriate predictive equations–predicted REE (pREE) based on anthropometric parameters to estimate it. This was a pilot study with 40 exclusively breastfeeding women. Height and weight were measured and body composition analysis was performed. We predicted REE using fourteen self-selected equations, based on anthropometric parameters and/or age, and/or sex. The median eREE was 1515.0 ± 68.4 kcal (95% Cl, 1477–1582 kcal) and the pREE ranged from 1149.7 kcal (95% Cl, 1088.7–1215.0) by Bernstein et al., to 1576.8 kcal (95% Cl, 1479.9–1683.4), by Müller et al. Significant differences between eREE and all pREE were observed (p < 0.001, except Korth et al. equations). The Müller et al. equation was the most accurate with the smallest individual variation. All predictive equations showed low agreement, and in most cases, the results were underestimated. These findings indicate the need for further studies to propose more suitable methods to determine the energy requirements for breastfeeding women.

Download Full-text