This study characterizes respiration chambers with fully automated calibration. The system consists of two 14-m3 pull-type chambers. Care was taken to provide a friendly environment for the subjects, with the possibility of social contact during the experiment. Gas analysis was automated to correct for analyzer drift and barometric pressure variations and to provide ease of use. Methods used for checking the system's performance are described. The gas-analysis repeatability was within 0.002%. Results of alcohol combustion (50-350 ml/min CO2) show an accuracy of 0.5 +/- 2.0 (SD) % for O2 consumption and -0.3 +/- 1.6% for CO2 production for 2- to 24-h experiments. It is concluded that response time is not the main factor with respect to the smallest practical measurement interval (duration); volume, mixing, gas-analysis accuracy, and levels of O2 consumption and CO2 production are at least equally important. The smallest practical interval was 15-25 min, as also found with most chamber systems described in the literature. We chose to standardize 0.5 h as the minimum measurement interval.

The 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, P¼0·88) and in physical activity (ANOVA repeated measures, P¼0·21). 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. Reproducibility: Calorimetry: Body composition: AccelerometerBMR is the main component of average daily metabolic rate. It is defined as the daily rate of energy metabolism an individual needs to maintain and preserve the integrity of vital functions. A measurement of BMR must meet certain conditions. The subject must be awake and the measurement must be performed in a thermoneutral environment to avoid heat production or heat loss for maintenance of body temperature. Furthermore the subject must be in a fasted state (absence of diet-induced thermogenesis) and in rest (absence of activity-induced energy expenditure).Diet-induced thermogenesis is an increase in energy expenditure (EE) above BMR after eating. A 10 -12 h fast before BMR measurements is the accepted procedure followed by investigators to eliminate the thermic effect of food on basal EE. However, the time interval required to eliminate any residual effect of physical activity on BMR has not yet been described in a similar way. Some studies have observed that moderate-intensity physical activity elevates metabolic rate for only a few minutes to a few hours (Bahr et al.

2 ) and 10 lean men (mean BMI, 21.1 Ϯ 2.0 kg/m 2 ) were exposed to cold air for 1 hour, followed by 1 hour of rewarming. Body composition was determined by hydrodensitometry and deuterium dilution. Heat production and body temperatures were measured continuously by indirect calorimetry and thermistors, respectively. Muscle activity was recorded using electromyography. Results: In both groups, heat production increased significantly during cooling (lean, p ϭ 0.004; overweight, p ϭ 0.006). The increase was larger in the lean group compared with the overweight group (p ϭ 0.04). During rewarming, heat production returned to baseline in the overweight group and stayed higher compared with baseline in the lean group (p ϭ 0.003). The difference in heat production between rewarming and baseline was larger in the lean (p ϭ 0.01) than in the overweight subjects. Weighted body temperature of both groups decreased during cold exposure (lean, p ϭ 0.002; overweight, p Ͻ 0.001) and did not return to baseline during rewarming. Discussion: Overweight subjects showed a blunted mild cold-induced thermogenesis. The insulative cold response was not different among the groups. The energy-efficient response of the overweight subjects can have consequences for energy balance in the long term. The results support the concept of a dynamic heat regulation model instead of temperature regulation around a fixed set point.

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.

For over two centuries, scientists have measured gas exchange in animals and humans and linked this to energy expenditure of the body. The aim of this review is to provide a comprehensive overview of open-circuit diluted flow indirect calorimetry and to help researchers to make the optimal choice for a certain system and its application. A historical perspective shows that ‘open circuit diluted flow’ is a technique first used in the 19th century and applicable today for room calorimeters, ventilated hood systems, and facemasks. Room calorimeters are a classic example of an open-circuit diluted flow system. The broadly applied ventilated hood calorimeters follow the same principle and can be classified as a derivative of these room calorimeters. The basic principle is that the subject breathes freely in a passing airflow that is fully captured and analyzed. Oxygen and CO2 concentrations are measured in inlet ambient air and captured outlet air. The airflow, which is adapted depending on the application (e.g., rest versus exercise), is measured. For a room indirect calorimeter, the dilution in the large room volume is also taken into account, and this is the most complex application of this type of calorimeter. Validity of the systems can be tested by alcohol burns, gas infusions and by performing repeated measurements on subjects. Using the latter, the smallest CV (%) was found for repeated VO2max tests (1.2%) with an SD of approximately 1 kJ min−1. The smallest SD was found for sleeping metabolic rate (0.11 kJ min−1) with a CV (%) of 2.4%.

Omnical, 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.

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.(ABSTRACT TRUNCATED AT 250 WORDS)

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