Measurement Of Resting Energy Expenditure Research Articles

Accuracy of Resting Energy Expenditure Calculations in Unselected Overweight and Obese Patients

Aims: Measurements of resting energy expenditure (REE) were compared with the data of 14 equations to determine their accuracy. Methods: REE measurements by indirect calorimetry in 1,032 unselected overweight and obese men (n = 306) and women (n = 726) were compared with calculations by 14 different formulas. Results: The mean (± SD) values calculated with the Owen, Robertson and Reid and WHO-I equations were not significantly different from our measurement of 1,682 ± 441.9 kcal/24 h. The values obtained with the Livingston, Mifflin, Müller and Bernstein equations were significantly different but still within a range of ±100 kcal/24 h. For females, the best comparison was observed with the Müller equation which, however, differed substantially in males. For men, the Cunningham equation was best, but it gave the worst comparison in women. A good individual match was only obtained with the equation of Robertson and Reid in 34% of the men and with the Owen equation in 38% of the women. All other formulas were less accurate. Drug treatment for 55% of the subjects had no effect on the mismatch between calculated and measured data. Conclusion: Calculations of REE with most equations seem to be valid in a group analysis but they are not helpful for the estimation of an obese patient's individual energy expenditure.

Validating an energy expenditure prediction equation in overweight and obese Mexican patients.

The prevalence of overweight and obesity in Mexico is approximately 70%; thus, obtaining a reliable measurement of the resting energy expenditure (REE) in these patients is of extreme importance. The aim of the study was to obtain a prediction equation of REE in overweight or obese outpatients in the Mexican population. The study was conducted at The National Institute for Medical Sciences and Nutrition Salvador Zubiran (Mexico, D.F.). Consecutive outpatients (18-70 years old) at the Clinical Nutrition were evaluated between March 2010 and August 2012 after being diagnosed with overweight or obesity (body mass index [BMI] ≥ 25 kg/m2). Patients with any disease that could affect the measurement of gas exchange were excluded. Participants were evaluated by indirect calorimetry (IC), bioelectrical impedance analysis (BIA) and anthropometric measurements to design the REE prediction equation. Two groups were evaluated: one group for derivation and another group for validation. The REE was also estimated using the equations of Harris-Benedict, Mifflin St-Jeor, Ireton-Jones, Carrasco, Kleiber and Owen, assessing current weight, ideal weight and adjusted weight. A REE equation was obtained by multiple linear regression based on the evaluated variables, and those that gave the best precision to the model were selected. The real REE and the estimated REE were then compared using Student's t-test. To highlight differences, pairs of measurements were further analyzed using the Bland & Altman plot. Pearson correlation coefficients and coefficients of determination between REE values measured by IC and REE values estimated using various formulas were calculated. A total of 77 patients were included in the derivation group: 38 men (49.4%) and 39 women (50.6%). The mean age was 48.5 ± 13.9 years, and the mean BMI was 34.7 ± 5.7 kg/m2. A total of 50 participants were included in the validation group: 16 men (32%) and 34 women (68%). The mean age was 48.5 ± 15.5 years, and the mean BMI was 34.2 ± 5.2 kg/m2. The baseline characteristics of both groups were homogeneous. IC reported an average of 2001 ± 552 kcal, with a respiratory quotient (RQ) of 0.75 ± 0.04. The new REE equation that resulted from the statistical model had an R2 = 0.52 and a bias of ± 3.39 kcal. When the REE obtained from IC was compared with the REE estimated by the new formula, there was no significant difference between the results, and the correlation for all participants was 0.71 (p. <0.0001). When the equations were analyzed using the Bland-Altman method, the difference between the new formula and the REE measurement by IC was a bias of 3.39 ± 384 kcal.Furthermore, a correlation was obtained between the real and estimated REE values using different equations; the most accurate correlation with the new formula was Owen's formula (r=0.712). The new formula had an acceptable correlation with IC REE measurement in overweight and obese patients in the Mexican population. This equation may represent a useful tool for health care professionals who do not have access to IC equipment for the estimation of REE.

Accuracy of Predicted vs. Measured Resting Energy Expenditure in Patients Receiving Parenteral Nutrition

Accuracy of Predicted vs. Measured Resting Energy Expenditure in Patients Receiving Parenteral Nutrition

Validity of predictive equations for resting energy expenditure according to the body mass index in a population of 1726 patients followed in a Nutrition Unit

The resting energy expenditure (REE) predictive formulas are often used in clinical practice to adapt the nutritional intake of patients or to compare to REE measured by indirect calorimetry. We aimed to evaluate which predictive equations was the best alternative to REE measurements according to the BMI. 28 REE prediction equations were studied in a population of 1726 patients without acute or chronic high-grade inflammatory diseases followed in a Nutrition Unit for malnutrition, eating disorders or obesity. REE was measured by indirect calorimetry for 30 min after a fasting period of 12 h. Some formulas requiring fat mass and free-fat mass, body composition was measured by bioelectrical impedance analysis. The percentage of accurate prediction (±10%/REE measured) and Pearson r correlations were calculated. Original Harris & Benedict equation provided 73.0% of accurate predictions in normal BMI group but only 39.3% and 62.4% in patients with BMI < 16 kg m(-2) and BMI ≥ 40 kg m(-2), respectively. In particularly, this equation overestimated the REE in 51.74% of patients with BMI < 16 kg m(-2). Huang equation involving body composition provided the highest percent of accurate prediction, 42.7% and 66.0% in patients with BMI < 16 and >40 kg m(-2), respectively. Usual predictive equations of REE are not suitable for predicting REE in patients with extreme BMI, in particularly in patients with BMI <16 kg m(-2). Indirect Calorimetry may still be recommended for an accurate assessment of REE in this population until the development of an adapted predictive equation.

Variability of Resting Energy Expenditure in Infants and Young Children With Intestinal Failure–Associated Liver Disease

The aim of the study was to determine, in a cohort of young children with intestinal failure (IF), whether the estimates of basal metabolic rate (BMR) by standard equations can approximate measured resting energy expenditure (REE) by indirect calorimetry (IC). IC was performed using the dilutional canopy technique. REE measurements were compared with standard, age-based estimation equations (World Health Organization) for BMR. Subjects were classified as hypermetabolic (REE > 110% BMR), hypometabolic (REE < 90% BMR), or normal (REE = 90%-110% BMR). Twenty-eight IF patients (11 girls, 17 boys) had an underlying diagnosis of necrotizing enterocolitis (n = 10) or a congenital gastrointestinal defect (n = 18). Median age was 5.3 months. Median interquartile range (IQR) REE was 46 (42-58) kcal · kg · day. Median (IQR) total energy intake provided 209% (172%-257%) of REE, with parenteral nutrition providing 76% (23%) of total energy intake. REE was variable, with 39% (n = 11) of measurements hypermetabolic, 39% (n = 11) hypometabolic, and the remaining 21% (n = 6) normal. Although REE was well correlated with estimated BMR (r = 0.82, P < 0.0001), estimated BMR was not consistently an adequate predictor of REE. BMR over- or underestimated REE by >10 kcal · kg · day in 15 of 28 (54%) patients. REE was not significantly correlated with severity of liver disease, nutritional status, total energy intake, or gestational age. Energy expenditure is variable among children with IF and IF-associated liver disease, with approximately 80% of our cohort exhibiting either hypo- or hypermetabolism. Standard estimation equations frequently do not correctly predict individual REE. Longitudinal studies of energy expenditure and body composition may be needed to guide provision of nutrition regimens.

Impact of target energy intake on outcomes in septic patients : a prospective randomized controlled trial

To observe the impact of the diverse caloric energy intake on the outcomes and occurrence rate of complications in septic patients. A prospective single-blind randomized controlled trial was conducted. 158 cases of septic patients in intensive care unit (ICU) were enrolled and randomly assigned to three groups according to their different target value of nutrition: group A [measurements of resting energy expenditure ( MREE) <90% J , B ( MREE 90%-110%) and C ( MREE > 110%). The caloric intake, mechanical ventilation duration ( MVD),nosocomial infection rate, 28-day and 60-day mortality were analyzed. Daily energy intake in 7 days after ICU admission was as follows: the difference in target value of nutrition ( kJ/d: 7 075.0 ± 1 046.5, 5 667.8 ± 1 908.8,4 428.8 ± 1 377.8), calory intake ( k]/d: 4 671.6 ± 1 205.6, 5 655.3 ± 1 373.0, 6 053.0 ± 1 557.2), enteral nutrition value ( kJ/d: 2 051.1 ± 1 046.5, 3 980.9 ± 1 586.5, 5 337.1 ± 2 921.8) and average intake rate [ ( 66.0 ± 15.8 )% ,( 100.0 ± 5.7 )% , ( 134.0 ± 19.7)% J, and they were statistically significant difference among A, B, C groups (all P<0.05 ). The parenteral nutrition in group C were much higher than that in group A and group B ( kJ/d: 2 055.3 ± 273.4vs. 427.0 ± 273.4, 473.0 ± 332.0, both P<0.05 ). The calories provided by glucose and diprivan were similar among three groups. The MVD and ICU stay were shorter in group B than that in groups A and C [ MVD (days): 8.4 ± 6.3 vs.11.0 ± 8.2, 17.8 ± 13.0, P>0.05 and P<0.05; ICU stay (days): 11.0 ± 6.4 vs. 14.9 ± 9.6, 17.8 ± 13.0, respectively,P>0.05 and P<0.05]. The total hospital stay (days: 32.0 ± 22.5, 26.8 ± 7.0, 30.4 ± 21.4) and nosocomial infection rate [ 91.1% ( 51156) , 84.0% ( 42/50) , 90.4% ( 4 7/52) J were similar among A, B, C groups (all P>0.05). There was no difference in survival rate at 28 days among three groups as shown by the Kaplan-Meier survival curve ( F=3.145,P=0.076 ). The survival rate at 60 days showed a tendency of lowering in groups A and C, especially in group C (F=9.284, P=0.010). Both higher and lower caloric energy intake may be associated with an adverse impact, but appropriate caloric intake would improve the outcome and reduce the complication rate in septic patients.

Resting Energy Expenditure and Blood Pressure: Evidence of Perpetual Association

A myriad of cross-sectional and prospective studies have evaluated the interrelationship between blood pressure (BP) levels and different traditional metabolic surrogates including body mass index (BMI). In addition, clinically meaningful conditions such as hypertension and the metabolic syndrome independently of treatment for either condition have shown a prospective bidirectional association among different ethnicities and age burdens. However, along with the positive association between BP and adverse metabolic phenotypes, the exact underlying pathophysiological background has not yet been fully elucidated. Resting energy expenditure (REE), a quantitative measurement of metabolic processes at rest, was found to be correlated with BP levels in different ethnicities after adjustment for potential confounders. The arising clinical question is whether the measurement of REE might be a predictor of increasing BP levels or incident hypertension later in life independently of confounders including body adiposity and common pathophysiological pathways such as enhanced sympathetic nervous drive and subclinical inflammatory processes. To address the above clinical question, a longitudinal study has to be projected. However, it is also important to validate the reproducibility of the association over time, ie, sequential longitudinal evaluation of REE and BP levels. In the current issue of The Journal of Clinical Hypertension, Sriram and colleagues evaluated the association of systolic BP with REE in a cohort of 229 originally overweight premenopausal women without comorbidities who were recruited to participate in a weight loss program to normalize their BMI. After BMIrelated target achievement, the cohort of “newly normoweight” women was observed annually for 4 years and different adiposity surrogates were assessed in combination with BP and REE measurements during each individual investigational visit. The constant association of REE with BP at several follow-up timeframes after adjustment for confounders highlighted the consistency of the results over time. As a general comment, and beyond the purpose of the study by Sriram and colleagues, a successful weight loss intervention of limited time once again was not able to retain BMI within normal levels during the follow-up period. Indeed, the subset of women returned at the last visit had the same weight as before the intervention. However, we should point out that the rate of women who returned for follow-up visits was progressively reduced. Only 30 women returned for the last follow-up laboratory visit compared with 140 women with normalized BMI after weight loss intervention. Thus, prospective changes of body adiposity and REE in relation to BP changes could not be addressed by the design of the present study mainly as a result of reduced power for longitudinal evaluation. Curiously, only systolic BP was used as a principal outcome in the investigational approach of Sriram and colleagues. Although previous reports have demonstrated a mild relationship between REE and diastolic BP, the present study did not explain whether even this mild association persists overtime. Moreover, from a clinical point of view, diastolic BP might be more important compared with systolic BP in middle-aged patients. Additionally, bias regarding the exact methodology for measuring laboratory BP should not be neglected. It would be interesting to know the 24-hour profile of BP and measures of BP variability across visits. Although 24-hour BP measurements might be far different than laboratory resting BP, the former better reflects the overall hemodynamic load and may overcome eventual white-coat phenomena. A step further, does variability in laboratory BP correlate with REE variability across the 3 days of each individual followup laboratory visit? The answer to this question might enable us to better understand the reciprocal temporal changes of BP and REE. Although the procedure of REE assessment seems adequate because it is performed in laboratory conditions of “complete quiescence” after an overnight stay at a general clinical research center, neither the duration nor the quality of sleep the night before testing are reported. Under the hypothesis that participants did not demonstrate respiratory disorders during sleep, REE at awaking could be modulated by sleep characteristics. The role of the sympathetic nervous system in the pathophysiology of obesity-related hypertension is well established. We believe that a more sophisticated measurement of sympathetic nervous system activity, namely muscle nerve sympathetic activity, might better define its confounding effect compared with the measurement of urinary catecholamines alone. Over and under the above methodological remarks, the study by Sriram and colleagues set the basis for the prospective evaluation of REE either on BP levels or on Address for correspondence: Costas Thomopoulos, MD, 2, Helena Venizelou sqr, 11521 Athens, Greece E-mail: thokos@otenet.gr

Effect of a dietary intervention on growth and energy expenditure in children with cystic fibrosis

BackgroundThe study aim was to determine the effect of a dietary intervention on growth, body composition and resting energy expenditure (REE) in children with cystic fibrosis (CF) and pancreatic insufficiency (PI) in a randomized, double blind, placebo-controlled trial. MethodsSubjects (5 to 17yrs) participated in a 12-month trial of the organized lipid matrix LYM-X-SORB™ (LXS) vs. placebo dietary supplements with similar calories, total fat and fatty acids. Dietary intake was assessed using 3-day weighed food records. Height (HAZ), weight (WAZ), BMI (BMIZ), mid-upper arm muscle (UAMAZ) and fat area (UAFAZ) Z-scores were calculated. Fat mass (FM) and fat-free mass (FFM) were obtained by whole body DXA. REE (kcal/d) was evaluated by indirect calorimetry at baseline, 3 and 12months and %REE calculated using Schofield equations. No growth or REE differences were observed between LXS and placebo groups so data were pooled for analysis. Results63 children (57% males, age 10.6±2.9yr, 43% receiving LXS) completed REE measurements. Caloric intake increased from a median of 2502 [1478, 4909] to 2616 [1660, 4125] kcal/d at 12months. HAZ, WAZ and UAMAZ increased (p<0.05) over 12months. Mean REE was 109±8% predicted at baseline and 107±9% at 12months (p<0.05). REE (kcal/d) adjusted for FFM and FM decreased over 12months ([mean±SE] −31±12kcals, p<0.01), significant only in males (−49±16kcals, p<0.01). ConclusionsOver a 12month nutrition intervention with either LXS or placebo, the growth status, muscle stores and REE improved. Sustained increased energy intake improved energy metabolism, growth and nutritional status in school age children with CF, PI and mild lung disease.

Predicted vs. Actual Resting Energy Expenditure and Activity Coefficients: Post-Gastric Bypass, Lean and Obese Women

Total Energy Expenditure (TEE) and energy requirements are commonly estimated from equations predicting Resting Energy Expenditure (REE) multiplied by a Physical Activity (PA) coefficient that accounts for both PA energy expenditure and the thermogenic effect of food. PA coefficients based on PA self-reports are a potential source of error that has not been evaluated. Therefore, in this study we compared: 1) the Harris-Benedict (HB), Mifflin-St. Jeor (MSJ), and the Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU) REE equations with REE measured (REE-m) with indirect calorimetry; 2) PA coefficients determined with PA self-reports vs. objectively assessed PA; and 3) TEE estimates in post-Gastric Bypass (GB = 13), lean (LE = 7), and obese (OB = 12) women. REE was measured in the morning after an overnight fast with participants resting supine for 30 min. Self-reported PA was evaluated with a questionnaire and objectively measured with accelerometers worn for 5-7 days. Nutritional intake was evaluated with a food frequency questionnaire. Anthropometry included DEXA, and abdominal CT scans. Eligible GB had surgery ≥ 12 months before the study, and had ≥ 10 kg of body weight loss. All participants were 18-45 years of age, able to engage in ambulatory activities, and not taking part in exercise training programs. One-way ANOVA was used to detect differences in REE and TEE. Accuracy of REE prediction equations were determined by cases within 10% of REE-m, and agreement analyses. REE predictions were not different than REE-m, but agreements were better with HB and MSJ, particularly in the GB and LE groups. Discrepancies in the PA coefficients determined with self-report vs. objectively assessed PA resulted in TEE overestimates (approximately 200-300 Kcal/day) using HB and MSJ equations. FAO/WHO/UNU overestimated TEE in all groups regardless of the PA assessment method (approximately 300-900 kcal/day). These results suggest that: 1) HB and MSJ equations are good predictors of REE among GB and LE, but not among OB women, 2) PA coefficients used to estimate TEE must be determined with objective PA assessment, and 3) TEE estimates using PA coefficients with the FAO/WHO/UNU equation must be used with caution.

Agreement between prediction equations and indirect calorimetry to estimate resting energy expenditure in elderly patients on hemodialysis

Summary Background/aims Prediction equations are often applied to estimate the resting energy expenditure (REE) of end-stage renal disease patients. The accuracy of these equations in elderly on hemodialysis (HD) has not been investigated. We aimed to evaluate the agreement between the REE obtained by indirect calorimetry and three prediction equations in elderly patients on HD. Methods The REE of 72 elderly individuals (57 on HD and 15 with normal renal function), was measured by indirect calorimetry and compared to the prediction equations of Harris & Benedict, Schofield and the World Health Organization 1985 (WHO). The agreement was assessed by the intraclass correlation coefficient (ICC) and by Bland–Altman plot analysis. The ratio predicted/measured REE was used for classifying the agreement as acceptable (ratio: 0.90 to 1.10) or overestimated (ratio: >1.11). Results The REE estimated by the three equations was significantly higher than that obtained by indirect calorimetry (Harris & Benedict: 1339 ± 245 kcal/day; Schofield: 1358 ± 203 kcal/day; WHO: 1385 ± 225 kcal/day vs. indirect calorimetry: 1245 ± 283 kcal/day; P r = 0.70 (95% confidence interval: 0.54; 0.81); Schofield: r = 0.64 (0.46; 0.77) and WHO: r = 0.62 (0.43; 0.75). Acceptable agreement between the equations and indirect calorimetry was observed in 35% of patients, while overestimation was observed in 50%. Similar results were found in the elderly control group. Conclusion The three equations showed a moderate degree of agreement with indirect calorimetry and overestimation was the main error observed. These results suggest that these equations do not provide accurate measurements of REE in elderly on HD.

Bach music in preterm infants: no ‘Mozart effect’ on resting energy expenditure

To study whether Johan Sebastian Bach music has a lowering effect on resting energy expenditure (REE) similar to that of Wolfgang Amadeus Mozart music. Prospective, randomized clinical trial with cross-over in 12 healthy, appropriate weights for gestational age (GA), gavage fed, metabolically stable, preterm infants. Infants were randomized to a 30-min period of either Mozart or Bach music or no music over 3 consecutive days. REE was measured every minute by indirect calorimetry. Three REE measurements were performed in each of 12 infants at age 20±15.8 days. Mean GA was 30.17±2.44 weeks and mean birthweight was 1246±239 g. REE was similar during the first 10-min of all three randomization periods. During the next 10-min period, infants exposed to music by Mozart had a trend toward lower REE than when not exposed to music. This trend became significant during the third 10-min period. In contrast, music by Bach or no music did not affect significantly REE during the whole study. On average, the effect size of Mozart music upon REE was a reduction of 7.7% from baseline. Mozart music significantly lowers REE in preterm infants, whereas Bach music has no similar effect. We speculate that 'Mozart effect' must be taken into account when incorporating music in the therapy of preterm infants, as not all types of music may have similar effects upon REE and growth.

Favorable survival and metabolic outcome for children with diencephalic syndrome using a radiation-sparing approach

Diencephalic syndrome (DS) is a clinical disorder of metabolism associated with poor outcome in children with low-grade gliomas (LGGs). Since survival has been primarily reported with aggressive therapy, we report outcome data for these patients using a current, contrasting chemotherapy-driven approach. We performed a population-based review of DS patients treated with chemotherapy from 1997-2012. Metabolic rate was assessed in selected cases using open-circuit calorimetry to generate resting energy expenditure (REE) data. Tumor tissue was analyzed for BRAF alterations. Survival was compared with an age-related, radiotherapy naïve cohort of non-DS children with location-matched LGGs. Nine children (1.7% of 520 LGG diagnoses) fulfilled DS criteria. The median diagnostic age was 1.49 years (0.55-2.69 years), although neurofibromatosis Type-I patients were older (p = 0.005). All tumors analyzed exhibited either NF1 mutation or BRAF fusion. Seven tumors were histologically confirmed as low grade astrocytomas, one demonstrated neurocytic features, and one NF1 case was diagnosed using imaging and clinical criteria. All patients received chemotherapy, with seven cases also receiving initial nutritional supplementation. All nine gained weight after only 6 months of treatment. Two DS patients had serial REE measurements, revealing a hypermetabolic state (over 200% of predicted REE) at diagnosis which reduced to normal range with therapy. First-line chemotherapy treatment resulted in one minor response, stable disease in four cases, with progression in the remaining four patients. Although DS patients demonstrated inferior initial progression-free survival when compared to non-DS counterparts (5 years: 22 versus 60%, p = 0.015), all DS children remain alive at a median follow up of 5.3 years (1.2-14.9 years) with none requiring radiotherapy. Long-term sequelae included pituitary and visual dysfunction, learning difficulties and paradoxical, inappropriate weight gain. DS can be managed with non-aggressive chemotherapeutic, radiation-sparing strategies supplemented by temporary nutritional support. Multiple lines of therapy may be required to overcome disease progression but excellent survival and metabolic outcomes can be achieved. Continued surveillance is mandatory to prevent significant weight gain and support affected children with clinical sequelae.

Accuracy of predictive equations for the measurement of resting energy expenditure in older subjects

The measurement of resting energy expenditure (REE) is important to assess individual total energy requirements in older subjects. The validity of REE prediction equations in this population has not been thoroughly evaluated and therefore the main aim of this analysis was to assess the accuracy of REE prediction equations in older subjects. Weight, height and body mass index (BMI) were measured. REE was measured by indirect calorimetry (IC) in 68 older subjects (age: 60-94 years, M/F: 13/55, BMI: 26.3 ± 5.0 kg/m(2)). Measured REE was compared to 14 equations for the calculation of REE estimates. In addition, two novel approaches (Aggregate model and meta-regression equations) for the prediction of REE were evaluated. Paired t test and Bland-Altman method were used to assess the agreement of the equations. The average measured REE was 1298 ± 264 kcal/day. The equation with the smallest bias was proposed by Muller (Bias ± 2SD = +3 ± 294 kcal/day) whereas the Mifflin equation was associated with the largest error (Bias ± 2SD = -172 ± 282 kcal/day). The Aggregate, Muller, Harris-Benedict and Fredrix equations were characterised by a prediction within ±10% of measured REE in more than 60% of subjects. Of the four algorithms, only the Aggregate equation did not show a significant association of the measurement bias with age, BMI and gender. The Aggregate algorithm was characterised by a higher, overall accuracy for the prediction of REE in older subjects and its use should be advocated in older subjects. However, due to the large variability of the estimates, the measurement of REE by IC is still recommended for an accurate assessment of individual REE.

Resting energy expenditure values assessed by a multi-sensor armband show a low accuracy in obese subjects

Summary Background & aims Resting energy expenditure (REE) values computed upon estimation equations often show an insufficient accuracy in obese subjects. The multi-sensor SenseWear Pro Armband™ (SWA) may provide more accurate REE values. Here, we tested the accuracy of the SWA based REE measurements with reference to REE values obtained by indirect calorimetry (IC) in obese subjects. Methods A total of 188 obese women (BMI: 41.4 ± 6.1 kg/m 2 , age: 41.2 ± 12.7 years) and 76 obese men (BMI: 43.9 ± 6.5 kg/m 2 , age: 44.7 ± 12.5 years) underwent an IC for REE assessment and simultaneously wore the SWA. Results Mean REE-SWA values were not significantly different from REE-IC in women ( p = 0.066) and men ( p = 0.782) and were significantly correlated with REE-IC values (women: r = 0.58, p r = 0.73, p Conclusions The SWA does not provide more accurate REE values than established estimation equations in obese subjects. Therefore, the SWA does not present a reliable alternative to IC for measuring REE in this population.

Comparison of Energy Assessment Methods in Overweight Individuals

Practical methods of assessing resting energy expenditure (REE) could be useful in large populations of overweight and obese individuals during phases of weight loss and weight-loss maintenance to address weight regain. We compared predicted and measured REE using the MedGem handheld device and a traditional, indirect calorimeter in middle-aged men and women who were overweight and obese (body mass index ≥25.0 and <40.0). Each subject (n=88) completed traditional, indirect calorimetry and handheld calorimetry in random order. A subset of participants (n=10) completed each of these assessments at three different time points to examine their test-retest reliability. We found that MedGem estimates of REE were significantly greater than estimates with the traditional, indirect calorimeter and the predicted REE using the Harris-Benedict equation (P<0.01). Intra-class correlations were .70 (P=0.15) for repeated recordings with the MedGem and .84 (P=0.65) for traditional indirect calorimetry. The MedGem can overestimate REE in middle-aged overweight/obese individuals and has moderate test-retest reliability. Indirect calorimetry is the preferred measurement of REE in this population.

Comparison of Predictive Equations and Measured Resting Energy Expenditure Among Obese Youth Attending a Pediatric Healthy Weight Clinic

The Academy of Nutrition and Dietetics recommends the use of indirect calorimetry for calculating caloric targets for weight loss in obese youth. Practitioners typically use predictive equations since indirect calorimetry is often not available. The objective of this study was to compare measured resting energy expenditure (MREE) with that estimated using published predictive equations in obese pediatric patients. Youth aged 7 to 18 years (n = 80) who were referred to a university-based healthy weight clinic and who were greater than the 95th percentile BMI for age and gender participated. MREE was measured via a portable indirect calorimeter. Predicted energy expenditure (pEE) was estimated using published equations including those commonly used in children. pEE was compared to the MREE for each subject. Absolute mean difference between MREE and pEE, mean percentage accuracy, and mean error were determined. Mean percentage accuracy of pEE compared with MREE varied widely, with the Harris-Benedict, Lazzer, and Molnar equations providing the greatest accuracy (65%, 61%, and 60%, respectively). Mean differences between MREE and equation-estimated caloric targets varied from 197.9 kcal/day to 307.7 kcal/day. The potential to either overestimate or underestimate calorie needs in the clinical setting is significant when comparing EE derived from predictive equations with that measured using portable indirect calorimetry. While our findings suggest that the Harris-Benedict equation has improved accuracy relative to other equations in severely obese youth, the potential for error remains sufficiently great to suggest that indirect calorimetry is preferred.

Advances in the understanding of specific metabolic rates of major organs and tissues in humans

To present recent evidence on organ and tissue metabolic rates in humans to explain the variance in resting energy expenditure (REE). In humans, present knowledge on specific metabolic activities (i.e. ki-values) refers to seven organs and tissues - brain, heart, liver, kidneys, skeletal muscle, adipose tissue and residual mass - with ki-values of 240, 440, 200, 440, 13, 4.5 and 12 kcal/kg/day, provided by Elia in 1992. Detailed body composition data, as derived from whole body MRI together with measurements of whole body REE, were used to validate ki-values in nonobese, healthy and middle-aged adults. There is no sex difference, but minor, that is 2 and 3% deviations are found for age above 55 years and obesity, respectively. By contrast, in adolescents, differences of about 100 kcal/day or 7.3% of measured REE were observed. There is first evidence for changes in ki-values with either weight loss or weight regain after weight loss. Altogether these data suggest that in adolescence and at age above 55 years, in the obese and with weight change, organ and tissue masses differ in cellularity and/or their specific metabolic rates. Presently, direct assessment of specific organ and tissue metabolic rates in humans by either NMR spectroscopy or PET, together with detailed body composition analysis, has not been performed systematically. We need to become more skilled in methods and models used for detailed body composition analysis together with detailed assessment of energy expenditure in humans.

Free fatty acid flux in African‐American and caucasian adults—effect of sex and race

ObjectiveObesity, insulin resistance and diabetes disproportionately affect African American (AA) women. Abnormal adipose tissue free fatty acid (FFA) release is associated with these conditions. Resting energy expenditure (REE) and sex predict FFA release in Caucasians, but whether this is true in AA is unknown. We sought to understand the sex-specific relationships between FFA release, REE and race.Design and Methods100 adults (47% AA, 50% male, age 32±8y (mean ± SD)) from 3 different centers underwent duplicate measures of FFA release ([U-13C] palmitate) and REE (indirect calorimetry). Body composition was determined by DXA and abdominal imaging.ResultsAA participants had lower REE, but similar FFA concentrations and flux compared with Caucasian participants. The significant predictors of palmitate release were REE, sex, and race. REE and FFA flux were correlated in both sexes and both races. In a multiple-linear regression analysis with palmitate flux as the dependent variable and REE, sex, race, total fat mass, fat free mass, and insulin as independent variables, REE was the only independent predictor of FFA release in men. Both REE and race predicted palmitate flux in women.ConclusionsFFA flux is related to REE, but the relationship differs in AA and Caucasian women.

Estimated vs. actual resting energy expenditure and physical activity factor in post‐gastric bypass, lean and obese adults

Resting energy expenditure (REE) equations multiplied by a predetermined physical activity factor (PAF) are commonly used to determine energy requirements However, estimated vs. actual REE and PAF among post‐gastric‐bypass surgery (GBS), obese (Ob) and lean (L) adults have not been compared. We hypothesized that GBS, Ob and L adults will have: 1) actual REE lower than estimated and 2) actual PAF lower than estimated. A group of 13 GB, 15 Ob and 11 L adults completed REE measurements by indirect calorimetry following standard clinical procedures. The Harris‐Benedict equation (HB) and pre‐determined PAF were used to estimate energy requirements. Physical activity energy expenditure (PAEE) was determined with accelerometry and PAF with the equation: (Actual REE + accelerometry PAEE)/Actual REE. Two‐way ANOVAs were used to detect differences by group and method, and agreement between methods using Bland &amp; Altman plots. Group differences in actual REE (1631±174, 1830±290, 1441±151 kcal/day, respectively; P&lt;0.01) and HB REE (1600±131, 1970±274, 1542±225 kcal/day, respectively, P&lt;0.01) were observed, with no differences by method. Actual PAEE (269±70, 365±98, 228±112 kcal/day, respectively, P=0.002) yielded PAF ranging from 1.1 to 1.3, while HB PAF ranged from 1.2 to 1.7; causing higher predicted vs. actual energy requirement in all groups. While HB REE appeared adequate, predetermined PAF are not recommended.

Practical utility and reliability of whole-room calorimetry in young children

The use of whole-room calorimetry (WRC) in young children can increase our understanding of children's energy balance. However, studies using WRC in young children are rare due to concerns about its feasibility. To assess the feasibility of WRC in young children, forty children, aged 4–6 years, were asked to follow a graded activity protocol while in a WRC. In addition, six children participated in two additional resting protocols to examine the effect of diet-induced thermogenesis on resting energy expenditure (REE) measures and the reliability of REE measurement. Refusals to participate and data loss were quantified as measures of practical utility, and REE measured after an overnight fast and after a 90-min fast were compared. In addition, both were compared to predicted BMR values using the Schofield equation. Our results showed that thirty (78·9 %) participants had acceptable data for all intensities of the activity protocol. The REE values measured after a 90-min fast (5·07 (SD 1·04) MJ/d) and an overnight fast (4·73 (SD 0·61) MJ/d) were not significantly different from each other (P= 0·472). However, both REE after an overnight fast and a 90-min fast were significantly higher than predicted BMR (3·96 (SD 0·18) MJ/d) using the Schofield equation (P= 0·024 and 0·042, respectively). We conclude that, with a developmentally sensitive approach, WRC is feasible and can be standardised adequately even in 4- to 6-year-old children. In addition, the effect of a small standardised breakfast, approximately 90 min before REE measurements, is likely to be small.