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.

The validity of resting energy expenditure predictive equations in adults with central obesity: A sub-sample of the RaNCD cohort study

2019 ◽  
Vol 25 (3) ◽  
pp. 217-224 ◽  
Author(s):  
Yahya Pasdar ◽  
Shima Moradi ◽  
Behrooz Hamzeh ◽  
Farid Najafi ◽  
Seyed Mostafa Nachvak ◽  
...  
Keyword(s):  
Cohort Study ◽  
Energy Expenditure ◽  
Central Obesity ◽  
Pearson Correlation ◽  
Resting Energy Expenditure ◽  
World Health ◽  
Predictive Equations ◽  
Significant Difference ◽  
Health Organization ◽  
Resting Energy

Background: There are different equations for estimating Resting Energy Expenditure (REE). However, these equations were mainly developed based on populations of western countries. Aim: The present study was conducted to determine the validity of REE predictive equations in adults with central obesity. Methods: This study was conducted with 129 adults with central obesity aged 35–65 years, a sub-sample from a large cohort study (Western Iran), Kurdish population. REE was measured by indirect calorimetry (IC) and REE predictive equations. Data were analysed using Pearson correlation, paired t-test, concordance correlation coefficient (CCC), mean squared deviation (MSD), level of agreement (LOA) and Bland-Altman plot. Results: All REE predictive equations had low CCC and high LOA. Although there was no statistically significant difference in the REE measured with IC and the REE predicted with the Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU), FAO/WHO/UNU (Height), Muller and revised Harris-Benedict equations ( P = 0.874, 0.113, 0.619, 0.143 and P = 0.121), other equations had statistically significant differences with IC ( P<0.001). In addition, the highest correlation was found between the IC (r = 0.682). The least difference was related to the FAO/WHO/UNU equation, with an agreement limit of -507.96 to 500.79 Kcal/day, with a 95% confidence interval. Conclusions: The results of this study showed that the FAO/WHO/UNU, Muller, revised Harris-Benedict equations and Mifflin St Jeor equations are relatively acceptable for estimating REE. However, these prediction equations are not good at predicting REE; more precise equations are needed to apply for different ethnic groups.

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.

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 Methods for Estimating Resting Energy Expenditure Using Indirect Calorimetry in Adults with Overweight and Obesity (P13-030-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Collin Popp ◽  
Paige Illiano ◽  
Margaret Curran ◽  
Mary Ann Sevick ◽  
David St-Jules
Keyword(s):  
Energy Expenditure ◽  
Indirect Calorimetry ◽  
Resting Energy Expenditure ◽  
Heart Association ◽  
Overweight And Obesity ◽  
Group Setting ◽  
Minute Period ◽  
Significant Difference ◽  
Resting Period ◽  
Resting Energy

Abstract Objectives Standard procedures to estimate resting energy expenditure (REE) using indirect calorimetry are time-consuming, and may be unnecessary. Indeed, the guidelines recommend a pre-test resting period of 30-minutes, followed by a 5-minute stabilization period, and then waiting until the first steady state period (SS), defined as a 5-minute period with a coefficient of variance (CV) of <10% for VO2 and VCO2, to estimate REE. The aim of the study was to evaluate alternative procedures for estimating REE in adults with overweight and obesity. Methods Indirect calorimetry was performed in 37 adults enrolled in a weight loss trial using a metabolic cart (Quark RMR, COSMED). The volume of oxygen (VO2) and volume of carbon dioxide (VCO2) were collected every 10 sec for ≥20-minutes following pre-test resting (10-mins) and stabilization (5-mins) periods. The measurement period was segmented into five-minute (REE6–10, REE11–15, REE16–20, and REE21–25) and rolling (REE6–15, REE6–20, and REE6–25) periods, and VO2, VCO2, and CV were calculated for each period. REE was calculated using standard criteria (REESS). Alternative SS periods of 3- and 4-minutes (REE3 and REE4) were applied to those who did not achieve REESS. REESS estimates were compared to the other estimates of REE using paired t-tests. Results Participants were 51 ± 14SD yo, primarily women (78%), and had a BMI of 35.4 ± 5.5SD kg/m2. REESS was achieved by 81% (n = 30) of all participants, and 54% (n = 20) achieved REESS during the first 5-minute period (REE6–10) following stabilization. Applying REE3 and REE4 criteria, those who did not reach REESS increased to 92% (n = 34). There were no significant differences between REESS, and REE3 (P = 0.21), REE4 (P = 0.40), REE6–10 (P = 0.38), REE6–15 (P = 0.15) or REE6–20 (P = 0.05). Conclusions The majority of adults with overweight and obesity met the standard criteria for SS following a reduced pre-test resting period. However, the non-significant difference between REESS and rolling averages suggest the standard criteria may be unnecessary in a group setting. Funding Sources American Heart Association.

Resting Energy Expenditure Early after Cardiac Surgery and Validity of Predictive Equations: A Prospective Observational Study

2021 ◽  
pp. 1-8
Author(s):  
Huijuan Ruan ◽  
Qingya Tang ◽  
Qi Yang ◽  
Fangwen Hu ◽  
Wei Cai
Keyword(s):  
Cardiac Surgery ◽  
Energy Expenditure ◽  
Observational Study ◽  
Prospective Observational Study ◽  
Heart Surgery ◽  
Resting Energy Expenditure ◽  
Predictive Equations ◽  
First Choice ◽  
Significant Difference ◽  
Resting Energy

<b><i>Objective:</i></b> Several predictive equations have been used to estimate patients’ energy expenditure. The study aimed to describe the characteristics of resting energy expenditure (REE) in patients undergoing mechanical ventilation during early postoperative stage after cardiac surgery and evaluate the validity of 9 REE predictive equations. <b><i>Methods:</i></b> This was a prospective observational study. Patients aged 18–80 years old, undergone open-heart surgery, were enrolled between January 2017 and 2018. The measured REE (mREE) was evaluated via indirect calorimetry (IC). The predictive resting energy expenditure (pREE) was suggested by 9 predictive equations, including Harris-Benedict (HB), HB coefficient method, Ireton-Jones, Owen, Mifflin, Liu, 25 × body weight (BW), 30 × BW, and 35 × BW. The association between mREE and pREE was assessed by Pearson’s correlation, paired <i>t</i> test, Bland-Altman method, and the limits of agreement (LOA). <b><i>Results:</i></b> mREE was related to gender, BMI, age, and body temperature. mREE was significantly correlated with pREE, as calculated by 9 equations (all <i>p</i> &#x3c; 0.05). There was no significant difference between pREE and mREE, as calculated by 30 × BW kcal/kg/day (<i>t</i> = 0.782, <i>p</i> = 0.435), while significant differences were noted between mREE and pREE calculated by other equations (all <i>p</i> &#x3c; 0.05). Taking the 30 × BW equation as a suitable candidate, most of the data points were within LOA, and the percentage was 95.6% (129/135). Considering the rationality of clinical use, accurate predictions (%) were calculated, and only 40.74% was acceptable. <b><i>Conclusions:</i></b> The 30 × BW equation is relatively acceptable for estimating REE in 9 predictive equations in the early stage after heart surgery. However, the IC method should be the first choice if it is feasible.

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.

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