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Whole-room indirect calorimeters have been used to study human metabolism for more than a century. These studies have contributed substantial knowledge to the assessment of nutritional needs and the regulation of energy expenditure and substrate oxidation in humans. However, comparing results from studies conducted at different sites is challenging because of a lack of consistency in reporting technical performance, study design, and results. In May 2019, an expert panel was convened to consider minimal requirements for conducting and reporting the results of human whole-room indirect calorimeter studies. We propose Room Indirect Calorimetry Operating and Reporting Standards, version 1.0 (RICORS 1.0) to provide guidance to ensure consistency and facilitate meaningful comparisons of human energy metabolism studies across publications, laboratories, and clinical sites.

BackgroundSeveral indirect calorimetry (IC) instruments are commercially available, but comparative validity and reliability data are lacking. Existing data are limited by inconsistencies in protocols, subject characteristics, or single-instrument validation comparisons. The aim of this study was to compare accuracy and reliability of metabolic carts using methanol combustion as the cross-laboratory criterion.MethodsEight 20-minute methanol burn trials were completed on 12 metabolic carts. Respiratory exchange ratio (RER) and percent O-2 and CO2 recovery were calculated.ResultsFor accuracy, 1 Omnical, Cosmed Quark CPET (Cosmed), and both Parvos (Parvo Medics trueOne 2400) measured all 3 variables within 2% of the true value; both DeltaTracs and the Vmax Encore System (Vmax) showed similar accuracy in measuring 1 or 2, but not all, variables. For reliability, 8 instruments were shown to be reliable, with the 2 Omnicals ranking best (coefficient of variation [CV] ConclusionsOmnical, Parvo, Cosmed, and DeltaTrac had greater accuracy and reliability. The small number of instruments tested and expected differences in gas calibration variability limits the generalizability of conclusions. Finally, humidity and temperature could be modified in the laboratory to optimize IC conditions.

Body mass, body composition and sleeping metabolic rate before, during and after endurance training.Westerterp KR, Meijer GA, Schoffelen P, Janssen EM.Department of Human Biology, University of Limburg, Maastricht, The Netherlands.Metabolic rate, more specifically resting metabolic rate (RMR) or sleeping metabolic rate (SMR), of an adult subject is usually expressed as a function of the fat-free mass (FFM). Chronic exercise is thought to increase FFM and thus to increase RMR and SMR. We determined body mass (BM), body composition, and SMR before, during, and after an endurance training programme without interfering with energy intake. The subjects were 11 women and 12 men, aged 37 (SD 3) years and body mass index 22.3 (SD 1.5) kg.m-2. The endurance training prepared subjects to run a half marathon competition after 44 weeks. The SMR was measured overnight in a respiration chamber. Body composition was measured by hydrostatic weighing. Measurements were performed at 0, 8, 20, 40, and 90 weeks after the start of the training. The BM had decreased from a mean value of 66.6 (SD 6.9) to 65.6 (SD 6.7) kg (P < 0.01), fat mass (FM) had decreased from 17.1 (SD 3.9) to 13.5 (SD 3.6) kg (P < 0.001), and FFM had increased from 49.5 (SD 7.3) to 52.2 (SD 7.6) kg (P < 0.001) at 40 weeks. Mean SMR before and after 40 weeks training was 6.5 (SD 0.7) and 6.2 (SD 0.6) MJ.day-1 (P < 0.05). The decrease in SMR was related to the decrease in BM (r = 0.62, P = 0.001). At 90 weeks, when most subjects had not trained for nearly a year, BM and SMR were not significantly different from the initial value while FM and FFM had not changed since week 40 of training

There is a growing tendency to estimate energy requirements by means of the assessment of resting energy expenditure (REE) by indirect calorimetry. In this study a computerized open-circuit ventilated hood system is described that was constructed for assessing REE in a clinical setting. Measurement error of the device, tested by ethanol combustion was +2% for VO2 and VCO2 and less than 1% for respiratory quotient. To assess the within-patient variability of REE measurements performed in a daily clinical routine, we studied the following aspects of the measurements in several groups of patients with chronic obstructive pulmonary disease: (1) reproducibility, (2) the influence of routine physical activities before the measurement, (3) measurement duration, and (4) difference between measurements using a ventilated hood or a mouthpiece. Reproducibility of measurements with a 2-month interval in 12 weight-stable patients was good (1415 +/- 128 and 1398 +/- 138 kcal/day). Variations due to limited activities and different measurement durations (between 10 and 30 minutes) were not significant. Variations between measurements with a mouthpiece and ventilated hood were larger in patients than in healthy control subjects, but for both groups no systematic difference was established. REE can be assessed reliably by short-term measurements with a ventilated hood in stable chronic obstructive pulmonary disease patients on an outpatient basis, provided a short rest is taken before the measurement.

After 4 weeks of dieting, 4 weeks of frequent exercise training (6h/wk) were added to a low energy diet of 3.0 MJ/day in 6 out of 12 healthy obese female subjects (aged 30–46 years) in order to compare changes in sleeping metabolic rate (SMR) and glucose induced thermogenesis (GIT). On the basis of BMI and percentage of body fat a diet group (D) and a diet-exercise group were formed (DE). SMR and GIT were both measured during a 36-h stay in a respiration chamber. Weight loss and changes in body composition were similar after 4 weeks of dieting. Adding 4 weeks of physical training for the DE group after 4 weeks of dieting did not result in significant differences between D and DE. SMR decreased significantly after 4 weeks of dieting (D 13%; DE 12%, P

The shape of the cumulative food intake curve of normal weight and obese women was studied during solid food lunches, artificially prolonged meals, and energetically enriched meals eaten in a laboratory setting. Subjects (86 normal weight, 50 obese) displayed consistent eating behaviour over 3–6 repeated meals, with marked differences between individuals. Aspects of eating behaviour were reflected in decelerated and nondecelerated (or linear) cumulative intake curves depending on changes or no changes in eating rate during the course of a meal, respectively. A change in eating rate was generally related to a decrease in bite size, with bite rate remaining constant, from the third temporal quarter of the meal onwards, resulting in a decelerated cumulative intake curve. The nondecelerated (linear) cumulative intake curve does not show this change in eating rate: in the first three temporal quarters bite size and bite rate were constant, whereas in the fourth temporal quarter bite size decreased slightly, compensated by a small increase in bite rate. Intraindividual ranges for meal parameters such as chewing time per bite, bite interval and initial eating rate indicated consistency of individual eating behaviour. In manipulation experiments with a subset of 21 subjects in which meals were artificially prolonged by an interval of 8 min, the cumulative intake curves did not differ significantly from the original cumulative intake curves in 10 nondecelerated (linear) eaters, but showed a change towards nondecelerated curves in 8 out of 11 decelerated eaters. In manipulation experiments with a subset of 34 subjects, who consumed similar meals, but energetically enriched by addition of either fat, protein, or carbohydrates, 25 of these subjects showed no change in the shape of their cumulative intake curves.

The largest component of daily energy expenditure is resting energy expenditure as reflected in overnight metabolic rate (OMR) and sleeping metabolic rate (SMR). Here, we determined the variation in OMR (24:00-6:00 h) and SMR values (3 h intervals) as affected by physical activity (PA) during the day and the night. Subjects were 32 females and 17 males, age 18-52 years. Energy expenditure (EE) was measured for 36 h in a whole room calorimeter (14 m3), starting in the evening, providing values before and after behavioral limitation. The mean intra-individual coefficient of variation was 1.8+/-1.4% for SMRmin (minimum EE), 2.8+/-2.0% for SMRact (minimum PA), 2.4+/-2.5% for SMRres (minimum residual EE, residual calculated from 24 h relationship between EE and PA) and 2.8+/-2.2% for OMR (n=49). Mean clock time for SMR ranged from 3:15 till 4:13 h. EE and PA increased in the hour before awakening. Surprisingly, OMR showed a significant 2.7% increase (P

Intra-individual variation of basal metabolic rate and the influence of daily habitual physical activity before testing.Adriaens MP, Schoffelen PF, Westerterp KR.Department of Human Biology, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands. M.adriaens@HB.Unimaas.nlThe present study determined the intra-individual variation of BMR measurements, using a standard out-patient protocol, with the subjects transporting themselves to the laboratory for the BMR measurements after spending the night at home. The effect of a non-fasting state and variation in daily habitual physical activity the day before testing was evaluated. Eight male and eleven female subjects participated in three BMR measurements with 2-week intervals. Physical activity was estimated with a tri-axial accelerometer for movement registration, during the 3 d before each BMR measurement. There were no significant differences in estimated BMR (ANOVA repeated measures, P=0.88) and in physical activity (ANOVA repeated measures, P=0.21). Mean within-subject CV in BMR was found to be 3.3 (SD 2.1) %, ranging from 0.4 to 7.2 %. Differences between BMR measurements could not be explained by differences in physical activity the day before; however the mean within-subject CV in BMR changed from 5.7 to 5.2 % after correcting for within-machine variability and from 5.2 to 3.3 % after excluding five measurements because of non-compliance to the protocol including fasting. In conclusion, BMR values measured with a standard out-patient protocol are sufficiently reproducible for most practical purposes despite the within-subject variability in physical activity the day before the measurement. For this purpose, however, non-fasting subjects must be excluded and a regular function check of the ventilated-hood system is recommendable

Introduction Hypocretin deficiency causes narcolepsy, a condition characterized by excessive daytime sleepiness, cataplexy, and fragmented nocturnal sleep. Co-morbid overweight is present in two thirds of narcolepsy patients. Moreover one third of them is obese. Why narcolepsy patients gain weight is not known. They do not seem to eat and/or sleep more during 24 h than controls. This study was performed to detect a possible decrease in energy expenditure that could be the cause for the overweight in narcolepsy. This is the first study using a respiration chamber to measure Energy Expenditure in narcolepsy. Materials and methods Nine hypocretin deficient male patients with narcolepsy-cataplexy, and nine sex, age and body mass index (BMI) matched controls were enrolled. Energy Expenditure was measured for 24 h in a respiration chamber. Spontaneous physical activity was measured by a radar system based on Doppler principle. Subjects were given a diet to maintain energy balance based on the Harris–Benedict equation. Total Energy Expenditure (TEE), Overnight Metabolic Rate (OMR) and lowest Sleeping Metabolic Rate (SMRmin) were calculated. In addition, measured SMR was compared with SMR calculated with a prediction equation based on body composition. Results Narcolepsy patients did not differ from controls in BMI (27.4 ± 3.9 vs. 27.5 ± 4.2; P = 9.4) or age (38.1 ± 16.0 vs. 36.8 ± 15.2; P = .86) respectively. There were no differences in TEE (10.6 ± 1.2 vs. 10.6 ± .80 MJ/d; P = .99) OMR (5.7 ± .73 vs. 6.0 ± .55 MJ/d; P = .35), SMRmin (5.4 ± .76 vs. 5.4 ± .51 MJ/d; P = .99) and spontaneous activity between narcolepsy patients and matched controls (2862 ± 514 vs. 2732 ± 245 counts/d; P = .50). For both groups, measured SMR was closely related to SMR predicted from body composition. Conclusion Energy expenditure in narcolepsy patients is similar to matched controls. It is conceivable that we were not close enough to onset of the disease, when patients usually gain weight, to detect a possible difference before a new metabolic set point establishes. Acknowledgement This study was supported by a grant from UCB Pharma.

Experiments were designed to test the traditional assumption that during level walking all of the energy from oxidation of fuel appears as heat and no work is done. Work is force expressed through distance, or energy transferred from a man to the environment, but not as heat. While wearing a suit calorimeter in a respiration chamber, five women and five men walked for 70 to 90 min on a level treadmill at 2.5, 4.6, and 6.7 km.h-1 and pedalled a cycle ergometer for 70 to 90 min against 53 and 92 W loads. They also walked with a weighted backpack and against a horizontal load. During cycling, energy from fuel matched heat loss plus the power measured by the ergometer. During walking, however, energy from fuel exceeded that which appeared as heat, meaning that work was done. The power increased with walking speed; values were 14, 29, and 63 W, which represented 11, 12, and 13% of the incremental cost of fuel above the resting level. Vertical and horizontal loads increased the fuel cost and heat loss of walking but did not alter the power output. This work energy did not re-appear as thermal energy during 18 h of recovery. The most likely explanation of the work done is in the inter-action between the foot and the ground, such as compressing the heel of the shoe and bending the sole. We conclude that work is done in level walking.