MedGem hand-held indirect calorimeter is valid for resting energy expenditure measurement in healthy children

Resting energy expenditure depends on energy intake during weight loss in people with obesity: a retrospective cohort study

Objective

Resting energy expenditure (REE) decreases if there is reduced energy intake and body weight (BW). The decrease in REE could make it difficult for patients with obesity to maintain decreased BW. This study aimed to investigate the correlation among changes in REE, energy intake, and BW during the weight loss process in patients with obesity.

Materials and methods

We conducted a retrospective cohort study of patients hospitalized for the treatment of obesity in Japan. Patients received fully controlled diet during hospitalization and performed exercises if able. REE was measured once a week using a hand-held indirect calorimetry. Energy intake was determined by actual dietary intake.

Results

Of 44 inpatients with obesity, 17 were included in the analysis. Their BW decreased significantly after 1 week (-4.7 ± 2.0 kg, P < 0.001) and 2 weeks (-5.7 ± 2.2 kg, P < 0.001). The change in REE after 1 and 2 weeks was positively correlated with the energy intake/energy expenditure ratio (r = 0.66, P = 0.004 at 1 week, r = 0.71, P = 0.002 at 2 weeks). Using a regression equation (y = 0.5257x - 43.579), if the energy intake/energy expenditure ratio within the second week was 82.9%, the REE after 2 weeks was similar to the baseline level. There was no significant correlation between the change in REE and BW.

Conclusion

Our data suggest that changes in REE depend on energy intake/energy expenditure ratio and that the decrease in REE can be minimized by matching energy intake to energy expenditure, even during the weight loss process.

Feasibility of Using Bioelectrical Impedance Analysis for Assessing Youth Weight and Health Status: Preliminary Findings

Background. This study assessed the accuracy of bioimpedance analysis (BIA) for measuring body composition and resting metabolic rate (RMR) in fasted and non-fasted state and the prospect of using phase angle (PA) to indicate cellular health in youth. Methods. BIA body composition, RMR, and hydration measures were compared to dual-energy x-ray absorptiometry (DXA), MedGem metabolic analyzer, and urine specific gravity, respectively, at baseline in a fasted state using one-way ANOVAs. Repeated BIAs at 0, 30, 60, 90, and 120 min post-prandial were compared to baseline using repeated-measures ANOVA. Correlations were used to assess the relationship among PA and health (blood lipids and glucose, resting BP) and fitness (grip strength and a 3 min step test) measures. Results. BIA scans (N = 58; 11.4 ± 2.9 y) measured lower body fat % (BF%) in healthy weight youth (BMI < 85th percentile; 16.4 ± 1.1 vs. 25.1 ± 1.0%) and lower visceral adipose tissue (VAT) in males (44.5 ± 2.9 vs. 34.1 ± 6.0 cm2) than DXA and higher RMR in all youth (1244 ± 41 vs. 1104 ± 39 kcals/day), healthy weight (1231 ± 48 vs. 1049 ± 44 kcals/day), and teens (1541 ± 62 vs. 1234 ± 72 kcals/day) than MedGem. Compared to baseline, immediate post-prandial values were significantly higher for BF% (21.4 ± 1.4 vs. 22.0 ± 1.4%) and VAT (45.4 ± 6.1 vs. 46.2 ± 6.2 cm2). PA was significantly correlated with BF% (r = -0.33; p = 0.01), fat-free mass (r = 0.59; p < 0.001), grip strength (r = 0.56; p < 0.001). Conclusions. While more data are needed to confirm these preliminary findings, the results suggest caution is necessary in using BIA to assess aspects of youth health and weight status, especially in males, healthy weight, and teens. However, these preliminary findings do indicate that phase angle maybe be a valuable, non-invasive tool for identifying youth who are heading towards obesity and/or obesity-related health consequences.

Prediction of Resting Energy Expenditure in Children: May Artificial Neural Networks Improve Our Accuracy?

The inaccuracy of resting energy expenditure (REE) prediction formulae to calculate energy metabolism in children may lead to either under- or overestimated real caloric needs with clinical consequences. The aim of this paper was to apply artificial neural networks algorithms (ANNs) to REE prediction. We enrolled 561 healthy children (2-17 years). Nutritional status was classified according to World Health Organization (WHO) criteria, and 113 were obese. REE was measured using indirect calorimetry and estimated with WHO, Harris-Benedict, Schofield, and Oxford formulae. The ANNs considered specific anthropometric data to model REE. The mean absolute error (mean ± SD) of the prediction was 95.8 ± 80.8 and was strongly correlated with REE values (R² = 0.88). The performance of ANNs was higher in the subgroup of obese children (101 ± 91.8) with a lower grade of imprecision (5.4%). ANNs as a novel approach may give valuable information regarding energy requirements and weight management in children.

Indirect Calorimetry in Clinical Practice

Indirect calorimetry (IC) is considered as the gold standard to determine energy expenditure, by measuring pulmonary gas exchanges. It is a non-invasive technique that allows clinicians to personalize the prescription of nutrition support to the metabolic needs and promote a better clinical outcome. Recent technical developments allow accurate and easy IC measurements in spontaneously breathing patients as well as in those on mechanical ventilation. The implementation of IC in clinical routine should be promoted in order to optimize the cost–benefit balance of nutrition therapy. This review aims at summarizing the latest innovations of IC as well as the clinical indications, benefits, and limitations.

Handheld Indirect Calorimetry as a Clinical Tool for Measuring Resting Energy Expenditure in Children with and without Obesity

Background: Resting energy expenditure (REE) is a valuable measure in clinical management of obesity and other chronic illnesses. Gold standard methods for measuring REE (e.g., Douglas bags and metabolic cart) are too expensive and cumbersome for an outpatient clinical setting. The purpose of this study was to determine the accuracy of a handheld indirect calorimeter (HHIC) and prediction equations (PEs) for measurement of REE in youth with and without obesity. Methods: Fifty-three children and adolescents (12.8 ± 4.3 years, 50.9% female) had REE measured first with a MedGem™ HHIC for 10 minutes, followed by a reference indirect calorimeter system (ParvoMedics TrueOne 2400™) with hood canopy and dilution pump for 30 minutes. REE was also estimated using nine PEs as follows: Henry-1, Henry-2, Schofield, World Health Organization, Molnar, Muller, Herrmann, Schmelzle, and Harris-Benedict. Concordance correlation coefficients and Bland-Altman analyses were used for comparisons among PEs, MedGem HHIC, and metabolic cart. Results: The observed correlation between the HHIC and the reference system was rc = 0.89 with a mean bias of 2.27 ± 3.41 kcal/(kg·d) (9.1% ± 14.7%). Regarding PE, Molnar had the highest agreement with the reference system [rc = 0.93, bias of 2.17 ± 2.04 kcal/(kg·d); 9.8% ± 8.1%], followed by Harris-Benedict (rc = 0.89; 13.8% ± 8.9%), Henry-2 (rc = 0.89; 15% ± 7.6%), and Henry-1 (rc = 0.86; 16.7% ± 7.3%). All PEs were less accurate for children with overweight/obesity. Conclusions: Compared to PE, the HHIC provided more accurate REE estimates for children across the age and BMI spectrum, although positive bias was present throughout. Difference in positive bias between the HHIC and the Molnar equation may be clinically significant for youth with overweight/obesity.

Comparison of Resting Energy Expenditure Assessment in Pediatric Oncology Patients

BACKGROUND

Evaluation of energy requirements is an important part of the nutrition assessment of pediatric oncology patients. Adequate provision of energy in this population is of extreme importance because of the prevalence of malnutrition and its effect on growth, development, quality of life, morbidity, and mortality. Numerous methods are used in clinical practice for estimating the resting energy expenditures (REE), specifically indirect calorimetry and predictive equations. A relatively new instrument used to assess REE is the hand-held indirect calorimeter. The purpose of this quality improvement project was to compare the accuracy of REE measurements taken by a hand-held indirect calorimeter and predictive equations to that of a standard indirect calorimeter metabolic cart.

METHODS

Patients receiving therapy for pediatric cancer, aged 7-18 years, and having a weight ≥15 kg and scheduled for a REE nutrition assessment were eligible. Sequentially, the patient's REE was assessed with the cart and the hand-held indirect calorimeter along with the predictive equation calculation.

RESULTS

Post hoc pairwise comparisons revealed that all 3 methods were significantly different from one another (P < .0001). When compared with the cart, the portable hand-held calorimeter was found to underestimate REE by 11.9%, whereas predictive equations overestimated REE by 12.4%.

CONCLUSION

Our quality improvement project suggests that the hand-held indirect calorimeter underestimated REE, and predictive equations overestimated REE in pediatric oncology nutrition assessment. Therefore, we recommend that these limitations in assessment be considered when assessing REE using a hand-held indirect calorimeter or predictive equations.

Indirect calorimetry using a ventilated hood may be easier than using a facemask to achieve steady state when measuring resting energy expenditure

Previous studies have demonstrated differences in subjective comfort between different gas collecting methods during resting energy expenditure (REE) measurement. We hypothesized that gas collecting methods may have an influence on the time to achieve steady state and the optimum abbreviated period to estimate REE. Gas exchange variables were obtained using IIM-IC-100 (ventilated hood) and VO2000 (facemask) alternately among 32 healthy adults. A 10-minute test period was divided into 5-minute sliding time windows to obtain a subtle profile process of the coefficient of variation (CV) and REE. Friedman's test was used to compare the CVs during the test process. To compare the REE between abbreviated measurements and the reference, paired t test, linear regression, and Bland-Altman test were used. There were no significant differences between the CVs in each adjacent group of 5-minute intervals for IIM-IC-100 (P = .896). CV1 and CV2 were significantly higher than CV3-CV6 for VO2000 (P = .001). The proportion of subjects achieving steady state was lower with VO2000 (59.4-81.3%) than with IIM-IC-100 (84.4-91.8%). REE of the 2nd and 3rd 5-minute intervals did not differ from the reference, and they explained 94.7% (P < .001) and 94.9% (P < .001) of the last 5-minute REE variance, with the 95% limits of agreement ranging from -100.0 to 139.2 kcal/d and -139.5 to 182.5 kcal/d for IIM-IC-100 and VO2000, respectively. In conclusion, using a ventilated hood may be easier than using a facemask to achieve steady state and reduce the time required to estimate REE.

Assessing resting energy expenditure in overweight and obese adolescents in a clinical setting: validity of a handheld indirect calorimeter

BACKGROUND

Accurately determining energy requirements is key for nutritional management of pediatric obesity. Recently, a portable handheld indirect calorimeter, MedGem (MG) has become available to measure resting energy expenditure (REE). Our work aims to determine the clinical validity and usefulness of MG to measure REE in overweight and obese adolescents.

METHODS

Thirty-nine overweight and obese adolescents (16 male (M): 23 female (F), 15.2 ± 1.9 y, BMI percentile: 98.6 ± 2.2%) and 15 normal weight adolescents (7M: 8F, age 15.2 ± 2.0 y, BMI percentile: 39.2 ± 20.9%) participated. REE was measured with both MG and standard indirect calorimeter (VMax) in random order.

RESULTS

MG REE (1,600 ± 372 kcal/d) was lower than VMax REE (1,727 ± 327 kcal/) in the overweight and obese adolescents. Bland Altman analysis (MG -VMax) showed a mean bias of -127 kcal/d (95% CI = -72 to -182 kcal/d, P < 0.001), and a proportional bias existed such that lower measured REE by VMax was underestimated by MG, and higher measured REE by VMax were overestimated by MG.

CONCLUSION

MG systematically underestimates REE in the overweight and adolescent population, thus the MG portable indirect calorimeter is not recommended for routine use. Considering that it is a systematic underestimation of REE, MG may be clinically acceptable, only if used with caution.

Comparison of the GEM and the ECAL indirect calorimeters against the Deltatrac for measures of RMR and diet-induced thermogenesis

The Deltatrac™ II Metabolic Monitor (Datex-Ohmeda Inc.) is considered the standard reference machine in indirect calorimetry; however, it is no longer commercially available thus there is a need for new machines. The gas exchange measurement (GEM; GEM Nutrition Ltd) and the ECAL (Health Professional Solutions) are alternative measuring systems. The aim of this study was to compare the ECAL and GEM with Deltatrac for measures of RMR and the GEM to the Deltatrac for measures of diet-induced thermogenesis (DIT). Twenty healthy participants were tested on test day 1 (T1) and test day 2 (T2). RMR was measured in a randomised order for 30 min on the Deltatrac, the GEM and the ECAL. Following this, a 1553 kJ meal was consumed and DIT was measured on the Deltatrac and the GEM in alternating 15 min intervals for 4 h. The GEM reported consistently higher values than the Deltatrac for VO2, VCO2, RMR and fat oxidation (P < 0·005). The ECAL was significantly higher than the Deltatrac for measures of VO2, RMR, carbohydrate oxidation (T2) and respiratory quotient and fat oxidation (T1, T2) (P < 0·05). There were no significant differences within repeated RMR measures on the ECAL, the GEM or the Deltatrac. DIT measures were consistently higher on the GEM (T1) (P < 0·005); however, there were no significant differences between repeated measures. The findings suggest that while the GEM and the ECAL were not accurate alternatives to the Deltatrac, they may be reliable for repeated measures.

Energy expenditure in acute posttraumatic amputation: comparison of four methods for assessment

BACKGROUND

Adequate energy intake is a component of successful recovery after injury, yet little is known about the energy requirements in the acute period following traumatic amputation. The purpose of this study was to compare the clinical applicability of resting energy expenditure (REE) measured by a handheld calorimeter and estimated by 3 different predictive equations to that measured by the gold standard, indirect calorimetry using a metabolic cart, during the acute postamputation period of inpatient hospitalization.

MATERIALS AND METHODS

Indirect calorimetry measured using both a metabolic cart and handheld calorimeter and predicted by 3 equations were used to assess energy needs of eligible subjects admitted to Brooke Army Medical Center with traumatic amputation(s). REE measured by the handheld calorimeter and estimated using 3 predictive equations (Mifflin St. Jeor, Ireton-Jones 1992, and the American College of Chest Physicians [ACCP]) were compared to the gold standard metabolic cart. Each measure was assessed for significant differences and level of clinical acceptability defined as ± 10% REE by metabolic cart.

RESULTS

Thirteen male service members with traumatic amputation(s) were included. The majority of subject's measurements using the handheld calorimeter (n = 9, 69%) and 3 predictive equations (Mifflin St. Jeor [n = 7, 54%], Ireton-Jones 1992 [n = 8, 62%], ACCP [n = 7, 54%]) fell outside of the ± 10% range of clinical acceptability.

CONCLUSION

Use of the metabolic cart for measuring energy needs remains optimal in this population.

Accuracy and preference of measuring resting energy expenditure using a handheld calorimeter in healthy adults

BACKGROUND

Accurate estimates of energy expenditure are required in clinical nutrition in order to determine the requirements of individuals and to inform feeding regimes. Calorimetry can provide accurate measurements but is often impractical in clinical or community settings; prediction equations are widely used to estimate resting energy expenditure (REE) but have limited accuracy. A portable, self-calibrating, handheld calorimeter (HHC) may offer an alternative way of determining REE. The aim of the study was to evaluate whether estimates of REE derived using an HHC are closer to accurate measurements than values calculated using selected prediction equations.

METHODS

REE was measured in 36 healthy adults aged 21-58 years using a flow-through indirect calorimeter (FIC) and HHC. Estimated REE was calculated using three predictive equations (Harris & Benedict; Schofield; Henry). Differences in REE between the 'gold standard' values derived using the FIC and those derived using the HHC and equations were examined using paired t-tests and Bland Altman plots.

RESULTS

Mean REEHHC was significantly lower than mean REEFIC [4556 ± 1042 kJ (1089 ± 249 kcal) versus 6230 ± 895 kJ (1489 ± 214 kcal), P = 0.000] and also significantly lower than mean values calculated using all three equations. The mean difference between REEHHC and REEFIC [1674 ± 908 kJ (400 ± 217 kcal)] was significantly greater (P = 0.000) than the mean differences between the values calculated using the three prediction equations [272 ± 490 kJ (65 ± 117 kcal) (Harris-Benedict), 264 ± 510 kJ (63 ± 122 kcal) (Schofield), 84 ± 502 kJ (20 ± 120 kcal) (Henry)].

CONCLUSIONS

The HHC provides estimates of REE in healthy people that are less accurate than those calculated using the prediction equations and so does not provide a useful alternative.

An evaluation of a handheld indirect calorimeter against a standard calorimeter in obese and nonobese adults

BACKGROUND

Handheld indirect calorimetry has the potential to allow simple and inexpensive measurement of resting metabolic rate in spontaneously breathing people. However, validation work on these devices is contradictory. The purpose of the current study was to determine the bias and level of agreement of oxygen consumption and resting metabolic rate as measured by a handheld indirect calorimeter against a standard open-circuit indirect calorimetry cart.

MATERIALS AND METHODS

One hundred community-living, spontaneously breathing, ambulatory nonobese and obese adults were studied in single sessions by a single investigator. Sequential measurements were undertaken using the handheld indirect calorimeter and the standard metabolic cart. Measurement sequence was varied randomly.

RESULTS

The mean value for oxygen consumption and metabolic rate of the 2 devices was not significantly different. However, agreement between the 2 devices was only 43% in nonobese and obese participants, and there was proportional and fixed bias, with the handheld calorimeter tending to produce a higher value for oxygen consumption and resting metabolic rate. Limits of agreement for resting metabolic rate between the 2 calorimeters were -240 to +300 kcal/d.

CONCLUSIONS

Measurements of resting metabolic rate by the handheld indirect calorimeter tested in this study are not equivalent to measurements by standard indirect calorimetry.

Handheld calorimeter is a valid instrument to quantify resting energy expenditure in hospitalized cirrhotic patients: a prospective study

BACKGROUND

Nutrition management of cirrhosis in hospitalized patients is overlooked despite the clinical significance of sarcopenia or loss of muscle mass in cirrhosis. Determining optimal nutrition requirement needs precise measurement of resting energy expenditure (REE) in the cirrhotic patient. Predictive equations are not accurate, and the metabolic cart is expensive and cumbersome. The authors therefore performed a prospective study to examine the feasibility and accuracy of a handheld respiratory calorimeter (HHRC) in quantifying the REE in hospitalized cirrhotic patients not in the intensive care unit.

MATERIALS AND METHODS

The study was done in 2 phases: in the first phase, the REE of 24 consecutive healthy volunteers was measured using an HHRC in different positions. The objective of this phase was to identify the impact of body and arm position on measured REE. Subsequently, in the second phase of the study, REE was measured using the HHRC and the metabolic cart in 25 consecutive well-characterized, hospitalized cirrhotic patients. The degree of concordance was calculated.

RESULTS

Body position and arm position did not significantly affect the measured REE using HHRC. In patients with cirrhosis, the mean measured REE (kcal/d) using the HHRC was 1453.2 ± 319.3 in the hospital room, 1525.6 ± 305.2 in a quiet environment, and 1553.7 ± 270.6 with the metabolic cart (P > .1). Predicted REE using 2 widely used equations did not correlate either with each other or with the measured REE.

CONCLUSIONS

HHRC is a valid, feasible, and rapid method to determine optimal caloric needs in hospitalized cirrhotic patients.

Do handheld calorimeters have a role in assessment of nutrition needs in hospitalized patients? A systematic review of literature

BACKGROUND

Indirect calorimetry is a noninvasive and reliable means of determining resting metabolic rate in humans. Barriers to obtaining an accurate measure of resting metabolic rate (RMR) in hospitalized patients include the expense and the requirement of technical expertise for maintenance.

METHODS

A literature search on handheld calorimeters was conducted using PubMed and OVID. The search resulted in a total of 54 published articles; 23 of these specifically are about handheld calorimeter devices.

RESULTS

Results from a handheld calorimeter were similar to those obtained from metabolic cart studies. The Douglas bag method compared with the MedGem indicated a significant agreement (P = .286). The handheld device was compared with metabolic carts in 9 studies with mixed results. The predictive equations (Harris-Benedict, Mifflin-St Jeor, and FAO/WHO equations) over- and underestimated RMR compared with the MedGem. The Harris-Benedict equation overestimated the RMR by 3%-11%, the Mifflin-St Jeor equation overestimated the RMR by 1%, and the FAO/WHO equation overestimated RMR by 12%.

CONCLUSION

The present study examines the validity and reliability of handheld calorimeters for measuring resting energy expenditure based on published literature. Handheld calorimeters are more accurate than predictive equations based on gender, age, and ethnicity for determining resting metabolic rate and are therefore a viable alternative for clinical evaluation of the hospitalized patient.

Energy expenditure and enjoyment of common children's games in a simulated free-play environment

OBJECTIVE

To measure the energy expenditure and enjoyment of children's games to be used in developing a school-based intervention for preventing excessive weight gain.

STUDY DESIGN

Healthy weight (body mass index [BMI] < 85th percentile) and overweight or obese (BMI ≥ 85th percentile) third-grade children (15 boys; 13 girls) were recruited. In a large gymnasium, children performed 10 games randomly selected from 30 games used in previous interventions. Total energy expenditure was measured with a portable metabolic unit and perceived enjoyment was assessed using a 9-point Likert scale of facial expressions. Mean physical activity energy expenditure (PAEE = total energy expenditure minus resting metabolism) and enjoyment of the games were adjusted for sex and BMI classification. PAEE and enjoyment were compared using a repeated-measures ANOVA with sex, BMI classification, and games as main effects.

RESULTS

The games elicited a moderate intensity effort (mean ± standard deviation = 5.0 ± 1.3 metabolic equivalents, 123 ± 36 kcal/30 min). PAEE was higher for boys than for girls (0.12 ± 0.04 versus 0.11 ± 0.04 kcal/kg/min) and for healthy weight compared with overweight children (0.13 ± 0.04 versus 0.11 ± 0.03 kcal/kg/min). Twenty-two of the 30 games elicited a sufficiently high PAEE (≥ 100 kcal/30 min) and enjoyment (≥ neutral expression) for inclusion in future school-based interventions.

CONCLUSIONS

Not all children's games are perceived as enjoyable or resulted in an energy expenditure that was sufficiently high for inclusion in future physical activity interventions to prevent the excess weight gain associated with childhood obesity.

Measuring energy expenditure in community-dwelling older adults: are portable methods valid and acceptable?

The objective of this study was to assess the validity and acceptability of a handheld indirect calorimeter for measurement of resting energy expenditure in a sample of community-dwelling older adults. It was a measurement study involving 48 healthy community-dwelling older adults. Assessment of resting energy expenditure was performed in 48 healthy older adults under fasting conditions using the Europa Gas Exchange Monitor (GEM; ventilated hood indirect calorimeter, NutrEn Technology Ltd, Cheshire, UK) and the MedGem (handheld indirect calorimeter, HealtheTech Inc, Golden, CO). An eight-item self-administered survey was used to determine the acceptability of the two measurement devices. Bias and limits of agreement were calculated to determine the level of agreement between the two measurements. The Wilcoxon signed-ranks test was used to test for significant differences across items of the self-administered survey. Participants mean age was 80 years and mean body mass index (calculated as kg/m(2)) was 23. Mean (95% confidence interval) resting energy expenditure was 1,149 kcal/day (1,086, 1,194) and 1,489 kcal/day (1,386, 1,592) for the traditional and handheld indirect calorimeter, respectively; paired t test P<0.001. Mean bias and limits of agreement were 349 kcal (-270, 969) or 5 kcal/kg/day (-3.6, 13.2) with least products regression resulting in a slope of b(1)=1.9 (95% confidence interval 1.2, 2.7, P<0.05). The handheld indirect calorimeter was less acceptable to participants than the ventilated hood indirect calorimeter. Measurement of resting energy expenditure from the handheld indirect calorimeter used in this study is not acceptable for use in healthy older adults given the magnitude of the overestimate, the wide limits of agreement, the significant slope of the bias, and the discomfort experienced by the participants.