Accuracy of the Common Predictive Equations for Estimating Resting Energy Expenditure among Normal and Overweight Girl University Students

2015 ◽  
Vol 35 (2) ◽  
pp. 136-142 ◽  
Author(s):  
Nazli Namazi ◽  
Soghra Aliasgharzadeh ◽  
Reza Mahdavi ◽  
Fariba Kolahdooz
Keyword(s):  
Energy Expenditure ◽  
University Students ◽  
Resting Energy Expenditure ◽  
Predictive Equations ◽  
The Common ◽  
Resting Energy

Reliability of resting energy expenditure in major burns: Comparison between measured and predictive equations

2019 ◽  
Vol 38 (6) ◽  
pp. 2763-2769 ◽  
Author(s):  
Jinwoo Jeon ◽  
Dohern Kym ◽  
Yong Suk Cho ◽  
Youngmin Kim ◽  
Jaechul Yoon ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Predictive Equations ◽  
Resting Energy

scholarly journals Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and bioelectrical impedance analysis derived phase angle

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Maurizio Marra ◽  
Olivia Di Vincenzo ◽  
Iolanda Cioffi ◽  
Rosa Sammarco ◽  
Delia Morlino ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Phase Angle ◽  
Elite Athletes ◽  
Resting Energy Expenditure ◽  
Sport Performance ◽  
Accurate Estimation ◽  
Anthropometric Parameters ◽  
Predictive Equations ◽  
Good Prediction Accuracy ◽  
Resting Energy

Abstract Background An accurate estimation of athletes’ energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations. Methods Adult elite athletes aged 18–40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas. Results One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m2) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias −0.3% (Eq. A based on anthropometric parameters) and −0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%). Conclusion In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.

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 Congruent Validity of Resting Energy Expenditure Predictive Equations in Young Adults

Nutrients ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 223 ◽  
Author(s):  
Francisco Amaro-Gahete ◽  
Guillermo Sanchez-Delgado ◽  
Juan Alcantara ◽  
Borja Martinez-Tellez ◽  
Victoria Muñoz-Hernandez ◽  
...  
Keyword(s):  
Young Adults ◽  
Energy Expenditure ◽  
United Nations ◽  
Weight Status ◽  
Resting Energy Expenditure ◽  
Normal Weight ◽  
Healthy Adults ◽  
Predictive Equations ◽  
Resting Energy

Having valid and reliable resting energy expenditure (REE) estimations is crucial to establish reachable goals for dietary and exercise interventions. However, most of the REE predictive equations were developed some time ago and, as the body composition of the current population has changed, it is highly relevant to assess the validity of REE predictive equations in contemporary young adults. In addition, little is known about the role of sex and weight status on the validity of these predictive equations. Therefore, this study aimed to investigate the role of sex and weight status in congruent validity of REE predictive equations in young adults. A total of 132 young healthy adults (67.4% women, 18–26 years old) participated in the study. We measured REE by indirect calorimetry strictly following the standard procedures, and we compared it to 45 predictive equations. The most accurate equations were the following: (i) the Schofield and the “Food and Agriculture Organization of the United Nations/World Health Organization/United Nations” (FAO/WHO/UNU) equations in normal weight men; (ii) the Mifflin and FAO/WHO/UNU equations in normal weight women; (iii) the Livingston and Korth equations in overweight men; (iv) the Johnstone and Frankenfield equations in overweight women; (v) the Owen and Bernstein equations in obese men; and (vi) the Owen equation in obese women. In conclusion, the results of this study show that the best equation to estimate REE depends on sex and weight status in young healthy adults.

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

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

Obesity ◽  
2021 ◽  
Vol 29 (10) ◽  
pp. 1596-1605
Author(s):  
Jared H. Dahle ◽  
Danielle M. Ostendorf ◽  
Zhaoxing Pan ◽  
Paul S. MacLean ◽  
Daniel H. Bessesen ◽  
...  
Keyword(s):  
Weight Loss ◽  
Body Composition ◽  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Weight Loss Intervention ◽  
Predictive Equations ◽  
Composition Changes ◽  
Resting Energy

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.

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