scholarly journals Comparison of Predictive Equations for Resting Energy Expenditure in Overweight and Obese Adults

2011 ◽  
Vol 2011 ◽  
pp. 1-5 ◽  
Author(s):  
Erick Prado de Oliveira ◽  
Fábio Lera Orsatti ◽  
Okesley Teixeira ◽  
Nailza Maestá ◽  
Roberto Carlos Burini
Keyword(s):  
Body Mass Index ◽  
Energy Expenditure ◽  
Systematic Error ◽  
Indirect Calorimetry ◽  
Intraclass Correlation ◽  
Resting Energy Expenditure ◽  
Obese Adults ◽  
Predictive Equations ◽  
New Equation ◽  
Resting Energy

Objective. To compare values from predictive equations of resting energy expenditure (REE) with indirect calorimetry (IC) in overweight and obese adults.Methods. Eighty-two participants aged 30 to 60 years old were retrospectively analyzed. The persons had a body mass index ≥25 kg/m2. REE was estimated by IC and other five equations of the literature (Harris and Benedict, WHO1, WHO2, Owen, Mifflin).Results. All equations had different values when compared to those of IC. The best values were found by Harris and Benedict, WHO1, and WHO2, with high values of intraclass correlation coefficient and low values of mean difference. Furthermore, WHO1 and WHO2 showed lower systematic error and random.Conclusion. No predictive equations had the same values of REE as compared to those of indirect calorimetry, and those which least underestimated REE were the equations of WHO1, WHO2, and Harris and Benedict. The next step would be to validate the new equation proposed.

scholarly journals Resting energy expenditure in obese women: comparison between measured and estimated values

2016 ◽  
Vol 116 (7) ◽  
pp. 1306-1313 ◽  
Author(s):  
Vanessa Fadanelli Schoenardie Poli ◽  
Ricardo Badan Sanches ◽  
Amanda dos Santos Moraes ◽  
João Pedro Novo Fidalgo ◽  
Maythe Amaral Nascimento ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Intraclass Correlation ◽  
Resting Energy Expenditure ◽  
Fat Free Mass ◽  
Interdisciplinary Therapy ◽  
Obese Women ◽  
Predictive Equations ◽  
Before And After ◽  
Resting Energy

AbstractAssessing energy requirements is a fundamental activity in clinical dietetic practice. The aim of this study was to investigate which resting energy expenditure (REE) predictive equations are the best alternatives to indirect calorimetry before and after an interdisciplinary therapy in Brazilian obese women. In all, twelve equations based on weight, height, sex, age, fat-free mass and fat mass were tested. REE was measured by indirect calorimetry. The interdisciplinary therapy consisted of nutritional, physical exercise, psychological and physiotherapy support during the course of 1 year. The average differences between measured and predicted REE, as well as the accuracy at the ±10 % level, were evaluated. Statistical analysis included paired t tests, intraclass correlation coefficients and Bland–Altman plots. Validation was based on forty obese women (BMI 30–39·9 kg/m2). Our major findings demonstrated a wide variation in the accuracy of REE predictive equations before and after weight loss in non-morbid, obese women. The equations reported by Harris–Benedict and FAO/WHO/United Nations University (UNU) were the only ones that did not show significant differences compared with indirect calorimetry and presented a bias <5 %. The Harris–Benedict equation provided 40 and 47·5 % accurate predictions before and after therapy, respectively. The FAO equation provided 35 and 47·5 % accurate predictions. However, the Bland–Altman analysis did not show good agreement between these equations and indirect calorimetry. Therefore, the Harris–Benedict and FAO/WHO/UNU equations should be used with caution for obese women. The need to critically re-assess REE data and generate regional and more homogeneous REE databases for the target population is reinforced.

scholarly journals Accuracy and Validity of Resting Energy Expenditure Predictive Equations in Middle-Aged Adults

Nutrients ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1635 ◽  
Author(s):  
Francisco Amaro-Gahete ◽  
Lucas Jurado-Fasoli ◽  
Alejandro De-la-O ◽  
Ángel Gutierrez ◽  
Manuel Castillo ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Prediction Accuracy ◽  
Weight Status ◽  
Resting Energy Expenditure ◽  
Normal Weight ◽  
Middle Aged ◽  
Predictive Equations ◽  
Middle Aged Adults ◽  
Resting Energy

Indirect calorimetry (IC) is considered the reference method to determine the resting energy expenditure (REE), but its use in a clinical context is limited. Alternatively, there is a number of REE predictive equations to estimate the REE. However, it has been shown that the available REE predictive equations could either overestimate or underestimate the REE as measured by IC. Moreover, the role of the weight status in the accuracy and validity of the REE predictive equations requires further attention. Therefore, this study aimed to determine the accuracy and validity of REE predictive equations in normal-weight, overweight, and obese sedentary middle-aged adults. A total of 73 sedentary middle-aged adults (53% women, 40–65 years old) participated in the study. We measured REE by indirect calorimetry, strictly following the standard procedures, and we compared it with the values obtained from 33 predictive equations. The most accurate predictive equations in middle-aged sedentary adults were: (i) the equation of FAO/WHO/UNU in normal-weight individuals (50.0% of prediction accuracy), (ii) the equation of Livingston in overweight individuals (46.9% of prediction accuracy), and (iii) the equation of Owen in individuals with obesity (52.9% of prediction accuracy). Our study shows that the weight status plays an important role in the accuracy and validity of different REE predictive equations in middle-aged adults.

ENERGY EXPENDITURE IN 21-HYDROXYLASE CONGENITAL ADRENAL HYPERPLASIA PATIENTS AND COMPARISON WITH PREDICTIVE EQUATIONS

2020 ◽  
Vol 26 (4) ◽  
pp. 388-398
Author(s):  
Daniel Minutti de Oliveira ◽  
Ana Carolina Junqueira Vasques ◽  
Ezequiel Moreira Gonçalves ◽  
Sofia Helena Valente de Lemos-Marini ◽  
Gil Guerra-Junior ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Weight ◽  
Energy Expenditure ◽  
Congenital Adrenal Hyperplasia ◽  
Body Mass ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
Adrenal Hyperplasia ◽  
Predictive Equations ◽  
17 Hydroxyprogesterone

Objective: To characterize resting energy expenditure (REE) in patients with classic 21-hydroxylase congenital adrenal hyperplasia (21-OH CAH) using indirect calorimetry and compare it to the most commonly used REE predictive equations. Methods: This case-control study comprised 29 post-pubertal 21-OH CAH patients regularly followed at the University of Campinas. Elevated serum 17-hydroxyprogesterone and CYP21 gene molecular analysis confirmed the diagnosis. A healthy control group paired by age, gender, and body mass index was examined. Dual-energy X-ray absorptiometry (DEXA) measured body compositions. A bioimpedance analyzer determined fat-free mass, and indirect calorimetry using a metabolic cart measured REE. Results: Unlike our initial hypothesis, REE was similar between the groups (18.7 ± 3.1 kcal/kg/day in CAH vs. 20.3 ± 3.5 kcal/kg/day in controls; P = .728). No predictive equations reached the stipulated accuracy criteria, thus lacking validity in REE assessment in adults with the characteristics of the group studied. DEXA analysis revealed higher body fat and diminished nonbone lean mass in 21-OH CAH. Anthropometric and bioelectrical impedance parameters were not significantly different. Conclusion: Classic 21-OH CAH is generally followed in reference centers, which may facilitate indirect calorimetry use for REE measurement. Alternatively, considering our REE findings in adult 21-OH CAH patients, nutrition management based on 25 kcal/body weight/day (measured REE × activity factor 1.2 to 1.3) may be reasonable for current body weight maintenance in these patients. Abbreviations: 17-OHP = 17-hydroxyprogesterone; 21-OH CAH = classic 21-hydroxylase deficiency congenital adrenal hyperplasia; BMI = body mass index; REE = resting energy expenditure; VO2 = volume of oxygen; VCO2 = volume of carbon dioxide

scholarly journals New Predictive Equations for Resting Energy Expenditure in Normal to Overweight and Obese Population (P16-048-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Ali Almajwal ◽  
Mahmoud Abulmeaty
Keyword(s):  
Regression Analysis ◽  
Energy Expenditure ◽  
Linear Regression Analysis ◽  
Resting Energy Expenditure ◽  
Accurate Prediction ◽  
Future Research ◽  
Predictive Equations ◽  
Men And Women ◽  
New Equation ◽  
Resting Energy

Abstract Objectives The unique demographic and dietary characteristics of our population require the development of a new equation to estimate the resting energy expenditure (REE). This study presented new equations characteristic to our population. Methods A set of predictive equations for REE was derived for 427 healthy male and female subjects (aged 18–57 ± 14 years). Measurement of REE (REEm) was done by the indirect calorimetry (IC) and its prediction (REEp) by using nine equations. REEp was compared with REEm to determine the predictive accuracy of these equations. Using IC and anthropometrics for stepwise linear regression analysis, a new equation to predict REE of Saudi men and women was developed. Results Using a number of parameters (bias, underprediction, overprediction, % accurate prediction), our results suggested that almost all (9/9 in men and 7/9 in women) equations either underpredicted or overpredicted (2/9) REE. None of the already existing equations showed an acceptable REEp/REEm difference as low as 5%, and an accurate prediction (∼55%) at the individual level. Based on these findings, a new prediction equation (hereafter referred to as Almajwal–Abulmeaty [AA] equation) was developed using this study's data, after a rigorous stepwise regression analysis using the following formula: REE = 3832.955 + BW [Kg] × 48.037 − Ht [Cm] × 30.642 + gender × 141.268 − age [years] × 4.525. The regression model accounted for about 70% of the variance in REEm (R2 = 0.702). Conclusions Previous equations likely over- or underpredicted REE. Therefore, the new predictive “AA equation” developed in this study is recommended for the estimation of REE in young to middle-aged Saudi men and women with different body mass index. Future research is also required for further clinical and cross-validation of this new equation. Funding Sources This study was supported by the King Abdulaziz City for Science and Technology (grant number 11 – MED 1966 – 02). Supporting Tables, Images and/or Graphs

Resting Energy Expenditure in Overweight and Obese Adults: Agreement Between Indirect Calorimetry and Prediction Formulas

2008 ◽  
Vol 108 (9) ◽  
pp. A49
Author(s):  
J.E. Ziegler ◽  
P. Rothpletz-Puglia ◽  
R. Touger-Decker ◽  
L. Byham-Gray ◽  
J. O'Sullivan-Maillet ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
Obese Adults ◽  
Resting Energy

MON-P154: Role of Predictive Equations for Estimating Resting Energy Expenditure in Obese Adults Females

2016 ◽  
Vol 35 ◽  
pp. S210
Author(s):  
M. Marra ◽  
I. Cioffi ◽  
R. Sammarco ◽  
L. Santarpia ◽  
E. Silvestri ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Obese Adults ◽  
Predictive Equations ◽  
Resting Energy

scholarly journals Resting Energy Expenditure in CrossFit® Participants: Predictive Equations versus Indirect Calorimetry

2021 ◽  
Vol 9 (2) ◽  
pp. 7
Author(s):  
Maraline Santos Sena ◽  
Marcio Leandro Ribeiro de Souza ◽  
Valden Luis Matos Capistrano Junior
Keyword(s):  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
World Health ◽  
Predictive Equations ◽  
Portable Ultrasound ◽  
Significant Difference ◽  
Health Organization ◽  
Functional Movements ◽  
Resting Energy

Background: CrossFit® involves high-intensity functional movements and research has shown that the program increases metabolic rates in participants. Objective: To measure resting energy expenditure (REE) in CrossFit® participants using indirect calorimetry (IC) and to verify the most appropriate predictive equation to estimate REE. Methods: Overall, 142 CrossFit® participants (18–59 years; 91 [64.1%], women) underwent weight, height, waist circumference, and body mass index (BMI) measurements. Body composition was evaluated using a portable ultrasound system (BodyMetrix®). REEs were measured (mREE) by IC and predicted by six different equations (pREE): Harris-Benedict, World Health Organization (WHO), Henry and Rees, Cunningham (1980 and 1991), and Mifflin–St. Jeor. Results: The mean age was 33.0 (6.3) years, with no significant difference between men and women; mean mREE, 1583.2(404.4) kcal/d; and pREE, 1455.5(230.9) to 1711.3(285.5) kcal/d. The best REE predictive equations for this population were Cunningham (1991) (P=0.338), WHO (P=0.494), and Harris-Benedict (P=0.705) equations. The Harris-Benedict equation presented a smaller difference compared with IC [12.9(307.6) kcal], the Cunningham (1991) equation showed improved adequacy (102.5%), and the WHO equation presented highest accuracy (59.9%). The equations that were closest to the mREE were the Harris-Benedict for women and the WHO equation for men. Conclusion: Therefore, for CrossFit® participants, the REE can accurately be predicted with the Cunningham (1991), WHO, and Harris-Benedict equations.

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