Validity of Predictive Equations for Resting Energy Expenditure Developed for Obese Patients: Impact of Body Composition Method

This study aimed to determine whether the measured resting energy expenditure (REE) in overweight and obese patients living in a temperate climate is lower than the predicted REE; and to ascertain which equation should be used in patients living in a temperate climate. REE (indirect calorimetry) and body composition (DXA) were measured in 174 patients (88 men and 86 women; 20–68 years old) with overweight or obesity (BMI 27–45 kg m−2). All volunteers were residents in Gran Canaria (monthly temperatures: 18–24 °C). REE was lower than predicted by most equations in our population. Age and BMI were similar in both sexes. In the whole population, the equations of Mifflin, Henry and Rees, Livingston and Owen, had similar levels of accuracy (non-significant bias of 0.7%, 1.1%, 0.6%, and −2.2%, respectively). The best equation to predict resting energy expenditure in overweight and moderately obese men and women living in a temperate climate all year round is the Mifflin equation. In men, the equations by Henry and Rees, Livingston, and by Owen had predictive accuracies comparable to that of Mifflin. The body composition-based equation of Johnston was slightly more accurate than Mifflin’s in men. In women, none of the body composition-based equations outperformed Mifflin’s.

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

Subclinical Hypothyroidism in Obese Patients: Relation to Resting Energy Expenditure, Serum Leptin, Body Composition, and Lipid Profile

Obesity Research ◽

10.1038/oby.2001.21 ◽

2001 ◽

Vol 9 (3) ◽

pp. 196-201 ◽

Cited By ~ 66

Author(s):

Mariantonella Tagliaferri ◽

Maria Elisa Berselli ◽

Giovanna Calò ◽

Alessandro Minocci ◽

Giulio Savia ◽

...

Keyword(s):

Body Composition ◽

Energy Expenditure ◽

Lipid Profile ◽

Subclinical Hypothyroidism ◽

Resting Energy Expenditure ◽

Obese Patients ◽

Serum Leptin ◽

Resting Energy

Download Full-text

The Effect of Laparoscopic Gastric Plication Surgery on Body Composition, Resting Energy Expenditure, Thyroid Hormones and Physical Activity in Morbidly Obese Patients

Journal of Obesity & Weight loss Therapy ◽

10.4172/2165-7904.1000275 ◽

2015 ◽

Vol 05 (05) ◽

Author(s):

Hasani M ◽

Mirahmadian M

Keyword(s):

Physical Activity ◽

Body Composition ◽

Energy Expenditure ◽

Thyroid Hormones ◽

Resting Energy Expenditure ◽

Morbidly Obese ◽

Gastric Plication ◽

Obese Patients ◽

Laparoscopic Gastric Plication ◽

Resting Energy

Download Full-text

Predictive Equations Based on Body Composition for Resting Energy Expenditure Estimation in Adults with Obesity

Current Diabetes Reviews ◽

10.2174/1573399815666191030085915 ◽

2020 ◽

Vol 16 (4) ◽

pp. 381-386

Author(s):

Dana El Masri ◽

Leila Itani ◽

Dima Kreidieh ◽

Hana Tannir ◽

Marwan El Ghoch

Keyword(s):

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Fat Free Mass ◽

Accurate Estimation ◽

Predictive Equations ◽

Bland Altman Method ◽

The Mean ◽

Mean Differences ◽

Resting Energy

Background and Aim: An accurate estimation of Resting Energy Expenditure (REE) in patients with obesity is crucial. Therefore, our aim was to assess the validity of REE predictive equations based on body composition variables in treatment-seeking Arab adults with obesity. Methods: Body composition and REE were measured by Tanita BC-418 bioimpedance and Vmax Encore 229 IC, respectively, and predictive equations based on fat mass and fat-free mass were used in REE estimations among 87 adults of both genders, in the Outpatient Clinic in the Department of Nutrition and Dietetics at Beirut Arab University (Lebanon). The mean differences between the measured and estimated REE values were calculated to assess the accuracy, and the Bland-Altman method was used to assess the level of agreement. Results: Ten predictive equations were included. In males, all the predictive equations gave significantly different estimates of REE when compared to that measured by IC. On the other hand, in females, the mean difference between the REE value estimated by Huang and Horie-Waitzberg equations and that measured using IC was not significant, and the agreement was confirmed using Bland-Altman plots. Conclusion: Huang and Horie-Waitzberg equations are suggested for accurate REE estimation in females; however, new validated REE estimation equations for males in this population are still needed.

Download Full-text

Resting energy expenditure is not increased in mildly hyperglycaemic obese diabetic patients

British Journal Of Nutrition ◽

10.1017/bjn20061744 ◽

2006 ◽

Vol 96 (5) ◽

pp. 945-948 ◽

Cited By ~ 15

Author(s):

M. Ryan ◽

A. Sallé ◽

G. Guilloteau ◽

M. Genaitay ◽

M. B. E. Livingstone ◽

...

Keyword(s):

Body Composition ◽

Energy Expenditure ◽

Resting Energy Expenditure ◽

Glycated Haemoglobin ◽

Fat Free Mass ◽

Diabetic Patients ◽

Obese Patients ◽

Obese People ◽

Resting Energy

Resting energy expenditure (REE) is believed to be increased in type 2 diabetes, an increase that is associated with deteriorating glucose tolerance during its development. Meanwhile, insulin resistance, a state linked to obesity and observed in all type 2 diabetic patients, is associated with reduced REE. Our aim was to compare REE in obese patients with and without diabetes. REE, body composition (total body water, density, percentage fat and fat-free mass: 3-compartment model) and metabolic control were assessed in fifty obese Caucasian patients with diabetes (glycated haemoglobin level 7·6 (sd 1·5) %) and fifty obese patients who were non-diabetic. Despite being more overweight and younger, obese non-diabetic patients had an absolute REE (7·73 (sd 1·44) v. 8·12 (sd 1·37) MJ; P=0·17) and percentage fat-free mass similar to those of obese diabetic patients. Even when adjusted for differences in body composition, REE remained similar in both groups. Furthermore, REE (absolute and adjusted) was unaffected by both glucose level and control (glycated haemoglobin), with fat-free mass being the only determinant of REE. We conclude that REE is not necessarily increased by the presence of diabetes in obese people.

Download Full-text