scholarly journals Resting energy expenditure measured longitudinally following hip fracture compared to predictive equations: is an injury adjustment required?

2005 ◽  
Vol 94 (6) ◽  
pp. 976-982 ◽  
Author(s):  
Michelle D. Miller ◽  
Lynne A. Daniels ◽  
Elaine Bannerman ◽  
Maria Crotty
Keyword(s):  
Hip Fracture ◽  
Energy Expenditure ◽  
Total Energy ◽  
Physiological Stress ◽  
Resting Energy Expenditure ◽  
Mean Difference ◽  
Limits Of Agreement ◽  
Predictive Equations ◽  
The Mean ◽  
Resting Energy

The present study measuring resting energy expenditure (REE; kJ/d) longitudinally using indirect calorimetry in six elderly women aged ≥70 years following surgery for hip fracture, describes changes over time (days 10, 42 and 84 post-injury) and compares measured values to those calculated from routinely applied predictive equations. REE was compared to REE predicted using the Harris Benedict and Schofield equations, with and without accounting for the theoretical increase in energy expenditure of 35 % secondary to physiological stress of injury and surgery. Mean (95 % CI) measured REE (kJ/d) was 4704 (4354, 5054), 4090 (3719, 4461) and 4145 (3908, 4382) for days 10, 42 and 84, respectively. A time effect was observed for measured REE,P=0·003. Without adjusting for stress the mean difference and 95 % limits of agreement for measured and predicted REE (kJ/kg per d) for the Harris Benedict equation were 1 (−9, 12), 10 (2, 18) and 9 (1, 17) for days 10, 42 and 84, respectively. The mean difference and 95 % limits of agreement for measured and predicted REE (kJ/kg per d) for the Schofield equation without adjusting for stress were 8 (−3, 19), 16 (6, 26) and 16 (10, 22) for days 10, 42 and 84, respectively. After adjusting for stress, REE predicted from the Harris Benedict or Schofield equations overestimated measured REE by between 38 and 69 %. Energy expenditure following fracture is poorly understood. Our data suggest REE was relatively elevated early in recovery but declined during the first 6 weeks. Using the Harris Benedict or Schofield equations adjusted for stress may lead to overestimation of REE in the clinical setting. Further work is required to evaluate total energy expenditure before recommendations can be made to alter current practice for calculating theoretical total energy requirements of hip fracture patients.

665 Reliability of Resting Energy Expenditure in Major Burns: Comparison Between Measured and Predictive Equations

2020 ◽  
Vol 41 (Supplement_1) ◽  
pp. S177-S178
Author(s):  
Jun Hur ◽  
Dohern Kym
Keyword(s):  
Energy Expenditure ◽  
Resting Energy Expenditure ◽  
Concordance Correlation Coefficient ◽  
Altman Analysis ◽  
Concordance Correlation ◽  
Predictive Equations ◽  
Severe Burns ◽  
The Mean ◽  
Poor Outcomes ◽  
Resting Energy

Abstract Introduction Poor outcomes can result from inadequate energy intake. We aimed to investigate the reliability of resting energy expenditure (REE) measured by indirect calorimetry (IC) with REE calculated using predictive equations for nutritional support in patients with major burns. Methods REE was measured using IC and compared with predictive equations in 215 adult severe burns patients from Jan 2011 to Jun 2015. Agreement between IC and predictive equations was assessed using Bland-Altman methods. Results All predictive equations were compared with REE measured using IC. The mean measured REE was 1712 kcal/d. Bland-Altman analysis showed that 1.2 times HBE, Thumb 25, and Ireton-Jones equations had higher accuracy and reliability. The concordance correlation coefficient was higher (0.49) in the Ireton-Jones equation, and root mean square error (RMSE) was lowest (471.5) in the Thumb 25 equation. The proportion of patients with predicted REE within ±10% of measured REE was highest with Thumb 25 (52.5%). Other equations for burns patients had higher mean bias and overestimated REE when compared with IC results. Conclusions This study suggests that Thumb 25 can be used as an alternative method for estimating energy requirements of patients with major burns when IC is not available or applicable. Applicability of Research to Practice Harrison-Benedict known as standard equation failed to show superiority to others in burns. Burn-specific equations are tend to overestimate ebergy requirements.

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

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.

Total Energy Expenditure and Physical Activity Measured with the Bicarbonate-Urea Method in Patients with Human Immunodeficiency Virus Infection

1996 ◽  
Vol 91 (2) ◽  
pp. 241-245 ◽  
Author(s):  
N. I. J. Paton ◽  
M. Elia ◽  
S. A. Jebb ◽  
G. Jennings ◽  
D. C. MacAllan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Total Energy ◽  
Physical Activity Level ◽  
Resting Energy Expenditure ◽  
Total Energy Expenditure ◽  
Activity Level ◽  
Hiv Positive ◽  
Urea Method ◽  
Resting Energy

1. Our objectives were to measure total energy expenditure, the daily variation in total energy expenditure and the physical activity level in a group of HIV-positive subjects using the bicarbonate-urea method. The study also aimed to assess the practicalities of using the bicarbonate-urea technique in free-living conditions. 2. Total energy expenditure was measured with the bicarbonate-urea method over 2 consecutive days (1 day in one subject) in 10 male patients with HIV infection (median CD4 count = 30). Resting energy expenditure was measured by indirect calorimetry. Physical activity level (total energy expenditure/resting energy expenditure) was calculated from these measurements and from activity diaries. 3. Resting energy expenditure was found to be 7.46 ± 0.87 MJ/day, 5% higher than predicted values. Total energy expenditure was 10.69 ± 1.95 MJ/day with an intra-individual day-to-day variation of 6 ± 6%. The measured physical activity level was 1.42 ± 0.14, higher than the diary estimate of 1.34 ± 0.16 (P = 0.029), and there were large inter-method differences in individual values. The subcutaneous infusion of bicarbonate was well tolerated and did not seem to restrict normal activities. 4. Total energy expenditure was not elevated in the group of HIV-positive subjects when compared with reference values for normal subjects. The physical activity level of the patients in this study was lower than that measured using other techniques in healthy young men, but was compatible with that expected for people leading a sedentary lifestyle. Reductions in physical activity in patients with HIV are likely to contribute to the wasting process and physical activity level may thus be a clinically useful measure. This study has also provided the first tracer estimate of the day-to-day variation in total energy expenditure. The bicarbonate-urea method represents an important new investigative tool for measuring total energy expenditure which has previously only been possible within the confines of a whole-body calorimeter or using the expensive doubly labelled water method.

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 Evaluation of Variability in Resting Energy Expenditure and Its Relationship with Macronutrients and Gestational Weight Gain During the Second Trimester of Pregnancy (P11-136-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Kiley Vander Wyst ◽  
Matthew Buman ◽  
Gabriel Shaibi ◽  
Megan Petrov ◽  
Elizabeth Reifsnider ◽  
...  
Keyword(s):  
Weight Gain ◽  
Energy Expenditure ◽  
Total Energy ◽  
Gestational Weight Gain ◽  
Early Period ◽  
Resting Energy Expenditure ◽  
Dietary Composition ◽  
Second Trimester ◽  
Gestational Weight ◽  
Resting Energy

Abstract Objectives Resting energy expenditure (REE) comprises 60% of total energy expenditure and variations may be associated with gestational weight gain (GWG). There is a paucity of research investigating the relationship between REE and GWG. We investigated variations in REE and dietary composition throughout the second trimester and their association with GWG. Methods In this controlled trial, pregnant women (N = 16, mean age of 29.9 ± 4.3 years) with a gestational age < 17 weeks used the Breezing™ device for 13 weeks. This device is a real-time metabolism tracker that measures REE via indirect calorimetry. Height, weight, REE, and dietary intake via 24-hr recall were assessed every 2 weeks. Rate of GWG was calculated as weight gain divided by number of study weeks. Early (EC, GA wks 14–21), late (LC, GA wks 21–28), and overall (OC, GA wks 14–28) changes in macronutrient composition, REE, and GWG were used to evaluate time-specific associations. Group differences were analyzed using a General Linear Model in SPSS Version 25. Results Among the 16 participants, 25% of women were normal weight, 50% were overweight, and 25% were obese at study start. Women had a total and rate of GWG of 8.1 ± 2.9 kg and 0.6 ± 0.2 kg/wk, respectively. REE increased 72 ± 211 kcals/d during the early period, 121 ± 294 kcals/d during the late period, and 200 ± 316 kcals/d overall (from 1544 ± 237 kcal/d to 1744 ± 384 kcal/d). Early changes in REE were significantly correlated with the late changes in total (r = 0.52, P = 0.04) and rate of weight gain (r = 0.54, P = 0.03). A correlation between overall changes in REE and total weight gain was moderate and approached significance, r = 0.44, P = 0.09. Changes in total energy, fat, carbohydrate, and protein intake were not correlated with changes in REE; however, a moderate relationship between early changes in REE and overall changes in energy intake approached significance, r = 0.46, P = 0.07. Changes in GWG and REE did not differ among normal, overweight, or obese women (EC: F(2,15) = 0.36, P = 0.70; LC: F(2,15) = 2.37, P = 0.13; OC: F(2.15) = 1.27, P = 0.31). Conclusions Early changes in REE demonstrated a moderate, positive correlation with total and rate of GWG suggesting that assessment of REE early in pregnancy may help understand changes in GWG. Future research that evaluates both REE and dietary composition throughout pregnancy may provide insight into appropriate GWG. Funding Sources Project HoneyBee, Arizona State University.

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.

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