Skip to main content

Comparison of energy expenditure measurements by a new basic respiratory room vs. classical ventilated hood



Nutritional support is often based on predicted resting energy expenditure (REE). In patients, predictions seem invalid. Indirect calorimetry is the gold standard for measuring EE. For assessments over longer periods (up to days), room calorimeters are used. Their design makes their use cumbersome, and warrants improvements to increase utility. Current study aims to compare data on momentary EE, obtained by a basic respiration room vs. classical ventilated hood. The objective is to compare results of the basic room and to determine its 1)reliability for measuring EE and 2)sensitivity for minute changes in activity.


Two protocols (P1; P2)(n = 62; 25 men/37 women) were applied. When measured by hood, participants in both protocols were in complete rest (supine position). When assessed by room, participants in P1 were instructed to stay half-seated while performing light desk work; in P2 participants were in complete rest mimicking hood conditions. The Omnical calorimeter operated both modalities. Following data were collected/calculated: Oxygen uptake (\(\dot{\mathrm{V}}\) O2(ml/min)), carbon dioxide production (\(\dot{\mathrm{V}}\) CO2ml/min), 24h_EE (kcal/min), and respiratory exchange ratio (RER). Statistical analyses were done between modalities and between protocols. The agreement between 24h_EE, \(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2 obtained by both modalities was investigated by linear regression. Reliability analysis on 24h_EE determined ICC.


No significant differences were found for 24h_EE and \(\dot{\mathrm{V}}\) O2. \(\dot{\mathrm{V}}\) CO2 significantly differed in P1 + P2, and P2 (hood > room). RER was significantly different (hood > room) for P1 + P2 and both protocols individually. Reliability of 24h_EE between modalities was high. Modality-specific results were not different between protocols.


The room is valid for assessing momentary EE. Minute changes in activity lead to a non-significant increase in EE and significant increase in RER. The significant difference in \(\dot{\mathrm{V}}\) CO2 for hood might be related to perceived comfort. More research is necessary on determinants of RER, type (intensity) of activity, and restlessness. The design of the room facilitates metabolic measurements in research, with promising results for future clinical use.

Peer Review reports


In 1955, the nutritional needs of patients were already recognized [1] and remain a topic of interest today. For example, recently malnutrition was frequently observed in hospitalized patients with COVID-19 [2]. The urge to strive for adequate nutritional support in clinical situations continues to be of major concern [3]. Malnutrition remains underrecognized and undertreated in many patients [4,5,6]. Total energy expenditure (TEE) determines a person’s individual energy requirement, which is ideally met by total energy intake (TEI). When TEE and TEI match, an energy balance is reached. A positive (TEI > TEE) or negative (TEI < TEE) balance induces weight gain or -loss, respectively [5]. It has been reported that the presence of a disease and/or its treatment disturbs the energy balance by affecting the body’s energy expenditure (EE) (e.g. chemotoxicity during cancer treatment). If nutritional needs are not met, the resulting disbalance causes alterations in body weight (BW), seen as mass changes of the different body components (body composition (BC)). Deteriorating changes in fat mass (FM) and fat free mass (FFM), specifically skeletal muscle mass, will negatively affect general health, Quality of Life and activities of daily living [6].

Various methods have been developed to determine EE. A common tool is the predictive Harris-Benedict Equation (HBEq), which is based on anthropometric variables and easy applicable in clinical practice [7]. Predictive equations are valid in the overall healthy population [8], however, EE is often underestimated in hospitalized patients due to their condition/nature of the disease [4, 9]. Hence, accurate analysis of EE is of utmost importance to ward energy balance. Indirect calorimetry (IC) is the gold standard because of its high sensitivity and precision [10]. Newer technology and better understanding of how to interpret measurements should lead to more frequent use, consequentially improving individualized nutritional support in clinical settings as well.

To date, different indirect calorimeters are commercially available and can, depending on the setup, be used for cardiopulmonary exercise tests or the analysis of (momentary/resting) EE. For measuring EE, either a ventilated hood or respiratory room is used. A disadvantage of the hood for bedside applications is the short period (30 min) of possible measuring time due to increased build-up of arousal. Additionally, it is often more accurate and informative to measure EE under free-living conditions (e.g., during sleep), requiring prolonged periods of measuring time. Whole-room calorimeters have been designed for the latter, in which EE measurements up to several days are feasible [11, 12].

Although room calorimeters are highly accurate and referred to as gold standard, they are expensive because of their technological design, and require specialized staff. In addition, the fact that they are often located away from a patients’ whereabouts makes their use in hospital settings cumbersome. Recently, a basic version of a full respiration room has been developed (Maastricht Instruments, Maastricht, The Netherlands). This room is easy to operate by standard indirect calorimetry devices and allows bed rested patients to be measured during their hospital stay. A major advantage of this system over the use of a ventilated hood is that patients can be followed throughout the day or night resulting in more reliable measures of EE.

Therefore, the major aims of the present study were 1) to compare results of the momentary measure of the rate at which a person uses energy, further referred to as momentary energy expenditure, assessed by the basic version of a respiratory room compared to gold standard assessments with ventilated hood, and 2) to determine the room’s sensitivity for minute changes in activity under semi free-living conditions.

Materials and methods

This cross-sectional comparison study was conducted at the Multidisciplinary Metabolic Research Unit (M2RUN) of the research group Movant (University of Antwerp (BE); department of Rehabilitation Sciences and Physiotherapy). Comparison between EE measured by room and ventilated hood is done by means of two protocols (P1 and P2). In P1, minimal activity (light desk work) is performed inside the room to assess its sensitivity for minute changes in EE related to activity. In P2, EE is measured inside the room under identical resting conditions, which allows to compare its results with hood modality. The study is approved by the medical ethical committee of the University of Antwerp/Antwerp University Hospital (B300201942189).


Sixty-two subjects were recruited through social media or direct contact with the researchers and enrolled after providing a written informed consent. Between January and December 2019, 32 subjects participated in P1, between January and February 2022, 30 subjects in P2. Inclusion criteria were: adults (> 18 years), healthy (absence of (chronic) disease), no recent (< 1 month) medical treatment (e.g. surgery) or current use of pharmacological substances. Subjects were excluded when one of these criteria was not met. Demographic characteristics can be found in Table 1.

Table 1 Demographic characteristics of all participants, and comparison of subjects between protocols


For P1 and P2, two IC measurements 1) respiration room and 2) ventilated hood were consecutively performed (1.5 h in total). After arrival at the research facility, a period of relative rest (± 15 min) was set before beginning of the measurements so that the participants could acclimate. Relative rest is defined as a state of being, where tasks can be performed, albeit without physical effort (which has repercussions on the respiratory rate). Assessments were done under semi-fasting conditions and executed on the same day. Subjects were asked to refrain from heavy exercise at least 12-h before and solid meals or snacks 3-h prior the study. Water was allowed ad libitum. The order of measurements was decided by simple randomization. Flipping a coin assigned the subject to the first measuring device (head = room vs. tail = hood) after which the second device was automatically designated. After each respiratory room assessment, a 15 min washing-out time was installed to refresh the air inside, and to limit measurement errors related to build-up of respiratory gases. In addition, we predicted EE based on the HBEq for all participants in P1 and P2 to collate with hood measurements [8], so as to compare the results obtained by the room with valid hood measurements. Following HBEq was used:


Indirect calorimetry

All IC measurements were done with the same an open circuit diluted flow calorimeter (Omnical IV, Maastricht Instruments, Maastricht, The Netherlands), with the only difference in measurements was the size of the “headspace” per modality (hood: 0,03m3; room: 14m3) (average temperature (C°): 22.5 ± 3.1 C°; average humidity (%): 46.6 ± 3.3%; light: 500 lm (ambient light)). The Omnical is the fourth generation calorimeter and developed based on methods for whole‐room calorimetry [13,14,15,16]. Calibration of the device was performed automatically every 30 min with span gas (18% O2 and 0.8% CO2) and nitrogen gas (100%). Validation of the system by methanol combustion was performed weekly as described previously [15]: The theoretical value for the respiratory exchange ratio (RER;\(\dot{\mathrm{V}}\) CO2/\(\dot{\mathrm{V}}\) O2) was 0.667, based on the ratio of produced CO2 to utilized O2 from the burning of methanol from the equation: 2CH3OH + 3O2 → 2CO2. In brief, the methanol burner has been set to burn 0.2 g/min, equivalent to the production of 150mlCO2/min and a consumption of 225mlO2/min. Since an error percentage is dependent on burn-rate, the expression of the error limit in absolute ml/min is preferred, hence the limit values of 7.5 and 11 ml/min for CO2 and O2 respectively (5% of 150 ml CO2 and 5% of 225 ml O2). For validation in the range of EE, methanol (pro‐analysis, 99.8%; Merck Millipore BV, Amsterdam, The Netherlands) was burned at a target \(\dot{\mathrm{V}}\) O2 rate of 225 ml/min [15]. All measurements were normalized to standard temperature and pressure dry (STPD) values by measuring temperature, humidity, and pressure. Data of the methanol burning tests can be found in (Appendix Table 7).

Ventilated Hood

Hood measurements were performed inside the room, with open door to prevent built up of environmental CO2 concentrations. This way, subjects could remain in the same resting facilities and environmental conditions. Momentary EE was assessed after 3 h of fasting as approximation of resting EE (REE) [17]. Assessment of momentary EE by ventilated hood was identical for P1 and P2 (Fig. 1). All subjects were asked to lay still on a bed in supine position with the hood (0,03m3) placed over their heads. The hood served as reservoir collecting \(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2. A continuous flow of fresh air is directed through the hood and all in- and outgoing air is analyzed for O2 and CO2 concentrations, while the airflow through the system is measured, determining gas concentrations for in- and expired air with a representative resolution of ≤ 0.001% [15]. The flow rate was equal between P1 and P2 (Table 2). Inspired air (environment) samples were taken every 2 min, while expired air was analyzed every other 2 min as well as continuously. The measurement with ventilated hood lasted 30 min and data were provided every 5 s. Only data of the last 20 min were used to ascertain a balanced recording of gas exchange rates (\(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2) as fluctuations are often seen in the beginning of the measurement due to a slow decrease towards a resting level. From sitting or standing to resting in supine position, there is a decrease in EE which typically takes 10 min to achieve a steady state [17, 18]. The Weir equation (Weir, 1949) was used to convert \(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2 to EE values. The RER, indicative for substrate utilization, was calculated as an average over the whole selected measurement to limit errors due to intra-individual variations. Data were collected by the Omnical device to the 6th decimal as kcal/min (EEHood;kcal/min) and recalculated (1st decimal) by the researchers into kcal in 24 h (24h_EEHood;kcal). Results obtained by ventilated hood were used as gold standard [8].

Fig. 1
figure 1

Modalities used for measuring energy expenditure. Left: Ventilated hood; Right: Basic respiratory room

Table 2 Flow rate in room and hood

Respiratory room

A basic version of a respiration room (14m3) was built by using plexiglass windows in an aluminum frame (Fig. 1). The windows were made airtight with rubber seals. A ventilator was placed on the ceiling to mix the air in the room. An air inlet was placed through the ceiling while the air outlet was placed at the bottom of one of the walls. Room temperature and humidity were measured with the Rotronic probe HC2A-S (Rotronic, Basserdorf, Germany). Validation was identical as described above for the hood. An extra methanol validation was performed inside the room by burning methanol for 60 min in a fireproof bucket. The flow rate was equal between P1 and P2 (Table 2).

The room served as reservoir collecting \(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2. Because of the larger volume of the room, the measurement lasted 60 min and data were provided every minute. Only results of the last 50 min were used. \(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2 were converted by the Omnical to EE values (Weir, 1949). Data on momentary EE were collected to the 6th decimal as kcal/min (EERoom;kcal/min) and recalculated by the researchers (1st decimal) to kcal in 24 h (24h_EERoom;kcal). The RER was calculated as an average over the whole selected measurement, hence limiting errors related to intra-individual variations.

The respiratory room measurement of momentary EE was different between P1 and P2. For P1, subjects were instructed to stay in a seated position on a bed while performing light desk work on a laptop computer (minimal activity). For P2, subjects were asked to lay still imitating the subject’s position when measured by hood.

Statistical analysis

Quantitative variables are expressed as mean ± SD. All data collected during system calibration and in P1 and P2 were checked for normality with the Kolmogorov–Smirnov test, normality plot and boxplot. Validation of the system is reported by accuracy and variability (measure of precision); Accuracy is reported as mean % difference of expected vs. observed gas exchange rates (\(\dot{\mathrm{V}}\) O2, \(\dot{\mathrm{V}}\) CO2). Variability is reported as the standard deviation (SD) of the expected vs. observed % difference [19]. A variability of < 3% was selected as upper limit treshold of reliability, as previously described [20].

The independent samples T-test was used to compare subject characteristics between participants of P1 and P2 to avoid bias related to the study population. The paired-samples T-test compared the 24h_EE measured under the hood with EE_HBEq for all subjects together (Protocol 1 + 2) and for subjects of P1 and P2 individually (Table 8. in Appendix). To analyze comparability between modalities, a paired samples T-test between room and hood modality was performed on all subjects together (Protocol 1 + 2) for 24h_EE, \(\dot{\mathrm{V}}\) O2, \(\dot{\mathrm{V}}\) CO2, and RER, as well as for the subjects participating in the individual protocols (P1 or P2). Next, the independent samples T-test examined the variability of 24h_EE, \(\dot{\mathrm{V}}\) O2, \(\dot{\mathrm{V}}\) CO2, and RER between P1 and P2 for hood and room, to confirm the equal resting state of the first modality and analyze the ability of the room to detect minimal activity.

Proportional bias and equality of the range of results between room and hood for the participants of P2 was investigated by linear regression analysis for 24h_EE, \(\dot{\mathrm{V}}\) O2, and \(\dot{\mathrm{V}}\) CO2, with a Bland–Altman plot to analyze the agreement between modalities under similar resting conditions. A reliability analysis on 24h_EE between room and hood for all subjects (Protocol 1 + 2) and study samples of P1 and P2 separately was conducted to analyze the intraclass correlation coefficient (ICC; two-way mixed – absolute agreement). All statistical tests were executed two-sided (Significance: α = 0.05). Statistical analyses were performed with the use of SPSS software (SPSS v28, IBM Business Analytics, New York, USA).


General characteristics of the subjects

Sixty-two (62) subjects, 32 in P1 (10men(m)/22women(w)) and 30 in P2 (15 m/15w) were recruited. The demographic characteristics and comparison between the participants of P1 and P2 combined (Protocol 1 + 2), and P1 and P2 independently are shown in Table 1. No significant differences were found between the subjects of both protocols.

Validation of Omnical system

The mean percentage difference between expected and observed results for analyzing \(\dot{\mathrm{V}}\) O2 was 0.22% with 0.25% variability rate. For \(\dot{\mathrm{V}}\) CO2, the mean difference was -1.67% with 1.87% variability, while this was -1.86% and 1.81% respectively for RER (Table 3). Variability rate between the assessment of gas concentrations and RER by Omnical and expected values was < 3%.

Table 3 Validation of Omnical

Comparison of momentary energy expenditure, calorimetric gas measurements and respiratory exchange rate

Room vs. Hood

Momentary expenditure

24h_EE was not different between room and ventilated hood conditions for all subjects together (room vs. hood P1 + P2: p = 0.543) and for all participants in P1 (p = 0.158) and P2 (p = 0.281) independently (Table 4).

Table 4 Comparison of momentary energy expenditure based on indirect calorimetric gas analysis between room and ventilated hood

Gas analysis (\(\dot{\mathbf{V}}\) O2 and \(\dot{\mathbf{V}}\) CO2) and respiratory exchange rate

\(\dot{V}\) O2 did not differ significantly between room and hood for all subjects together (p = 0.139), and for P1 (p = 0.051) and P2 (p = 0.614) separately. \(\dot{V}\) CO2 was significantly different between room and hood in P1 + P2 (p = 0.031) and in P2 independently (p = 0.029). No significant difference was found for \(\dot{\mathrm{V}}\) CO2 in P1 (p = 0.391). The RER of all subjects together (P1 + P2) was significantly higher for the hood measurement compared to the room (p < 0.001). The same was seen in P1 (p < 0.001) and P2 (p = 0.015) independently (Table 4).

Detection of minimal activity

Protocol 1 vs. Protocol 2

Momentary energy expenditure

No significant differences were found for 24h_EE between both protocols (P1 vs. P2) used under hood (p = 0.742) or room (p = 0.487) conditions (Table 5).

Table 5 Modality-specific comparison of momentary energy expenditure based on indirect calorimetric gas analysis between protocol 1 and protocol 2

Gas analysis (\(\dot{\mathbf{V}}\) O2 and \(\dot{\mathbf{V}}\) CO2) and respiratory exchange rate

Values of V̇O2 and V̇CO2 were also not significantly different between protocols (P1 vs. P2) for both modalities (Hood: V̇O2: p = 0.707, V̇CO2: p = 0.679; Room: V̇O2: p = 0.43, V̇CO2: p = 0.796).The RER for all subjects, either measured by hood or room, did not show a significant difference between P1 and P2 (Room: p = 0.122; hood: p = 0.970) (Table 5).

Linear regression analysis and Bland–Altman plot for P2

No proportional bias was found for 24h_EE, \(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2 for all subjects in P2. Regression analysis of the mean difference between 24h_EE in room and hood (delta 24h_EE) on the average of the two methods (mean 24h_EE) showed a non-significant unstandardized coefficient of 0.076 (p = 0.412). For the mean \(\dot{\mathrm{V}}\) O2, the unstandardized coefficient was 0.086 (p = 0.310), and for mean \(\dot{\mathrm{V}}\) CO2 -0.001 (p = 0.994) (Table 6). Figure 2 shows the Bland–Altman plots of the mean differences and averages of 24h_EE, \(\dot{\mathrm{V}}\) O2 and \(\dot{\mathrm{V}}\) CO2, respectively, obtained by P2.

Table 6 Detection of proportional bias between results of P2
Fig. 2
figure 2

Bland–Altman plot of the agreement between modalities. Upper: Bland–Altman plot for 24h_EE measured by room and hood; Middle: Bland–Altman plot for VO2 measured by room and hood; Lower: Bland–Altman plot for VCO2 measured by room and hood; DELTA24h_EE: Difference between 24h_EE measured by hood and room for subjects of P1 + P2; MEAN24h_EE: Mean of 24h_EE measured by hood and room for subjects of P1 + P2; DELTA_ VO2: Difference between VO2 measured by hood and room for subjects of P1 + P2; MEAN_ VO2: Mean of VO2 measured by hood and room for subjects of P1 + P2; DELTA_ VCO2: Difference between VCO2 measured by hood and room for subjects of P1 + P2; MEAN_ VCO2: Mean of VCO2 measured by hood and room for subjects of P1 + P2; UB: Upper boundary; LB: Lower boundary

Reliability between room and hood for momentary energy expenditure and gas concentrations

A high degree of reliability was found for 24h_EE in room and hood in all subjects (P1 + P2). The average ICC for was 0.906 with a 95% confidence interval (CI) of 0.844 – 0.943. Both protocols (P1 and P2) also showed a high degree of reliability with an ICC of 0.883 (CI: 0.762 – 0.943) in P1, and 0.939 (CI: 0.873 – 0.971) in P2 (Table 6).


Respiratory rooms are the current gold standard for analyzing EE in free living conditions. To determine if the basic respiratory room is valid for assessing EE, we compared the measurement of EE (kcal/min) recalculated to 24h_EE (kcal), based on indirect calorimetric gas exchange parameters (\(\dot{\mathrm{V}}\) O2, and \(\dot{\mathrm{V}}\) CO2), between the new room and ventilated hood in healthy adults. For this purpose, we used a high-end indirect calorimeter that has been validated as measuring device [15, 20]. Secondly, we investigated if the room was sensitive to detect small changes in free-living conditions by means of two protocols (P1 and P2). In P1 the subjects were seated in an upright position in a hospital bed and were allowed to perform light deskwork on a laptop computer, whereas in P2 subjects were asked to lay still in supine position mimicking the resting condition as measured under the ventilated hood.

Comparison between the new basic respiratory room and ventilated hood

Analysis of momentary energy expenditure by calorimetric gas measurements.

Comparison between room and hood

The present study found no significant differences in 24h_EE between the respiratory room and ventilated hood measurements. A good ICC related to the measurement of EE supports this finding (all subjects, and participants of P1 and P2 separately). The same applies to V̇O2 and V̇CO2, where no significant differences between both measuring devices were discovered.

Yet in general, a higher but non-significant V̇O2 was noticed in the room compared to the hood while the V̇CO2 was higher as measured under hood conditions. The fact that the room has a larger volume might explain the higher V̇O2 generally seen in the room. For the hood, hyperventilation most likely causes an increase in V̇CO2, a finding which is not new. As the hood is in the form of a small, confined space, accepting the canopy could bring difficulties as agitation might build-up. One should realize that the aim of measured EE is to reflect the caloric need as closely as possible. Hence assessments obtained from shorter measurements (as is the case for the hood) therefore always lead to an EE that is extrapolated and not fully accounts for the true variation during one circadian cycle [21]. The conditions under the hood can possibly result in higher values for V̇CO2, as seen in our study, and might consequentially lead to a misinterpretation of EE, resulting in non-adequate nutritional strategies (especially in clinical patients). From our study, we can conclude that the basic respiratory room is a valid device for assessing EE and can therefore be used for continuous measurements over longer time intervals, consequentially ameliorating nutritional support.

Detection of minimal activity

No difference present in 24h_EE between hood assessments of P1 and P2, and for the room assessments of P1 and P2. This motivates the assumption that the subject’s conditions for hood and room were both comparable between protocols although minimal activity was performed inside the room during P1. It can be suggested that light deskwork has similar metabolic demands (reflected by EE) compared to supine position which is in accordance with previous results of Miles-Chan et al. [22] who reported that, under ventilated hood conditions, no difference between the supine and seated position were observed. Another reason could be that the room is not sensitive enough to detect a change in minimal activity. However, since 24h_EE room in P1 was higher (although not significantly) compared to P2, it might be that the type of activity was not rigorous enough to lead to a significant increase in EE, still, a minimal change was detected by the room.

Alongside the metabolic demand of the system comes substrate (nutrient) oxidation, indicated by RER, to maintain energy homeostasis. A change in the body’s physiological state (e.g. active (light desk work) vs. rest) is therefore expected to be accompanied by a change in RER [23]. While EE between modalities was similar, RER between hood and room did differ significantly (hood > room in P1 + P2, P1, and P2 separately). Looking at room and hood separately, a small non-significant difference in room-RER was seen between protocols (P1 < P2), while the hood displayed similar results on RER (P1 = P2).

The RER is a proxy measure for the oxidative capacity of muscles to get energy. When \(\dot{\mathrm{V}}\) O2 (due to activity) or \(\dot{\mathrm{V}}\) CO2 (due to agitation/hyperventilation) increase, respectively a lower and higher RER is seen [24]. Comparing room-RER with hood-RER, it can be suggested that agitation/hyperventilation underneath the hood with consequently a higher \(\dot{\mathrm{V}}\) CO2 partially explains the significant difference in RER between measurement devices. Additionally, we further hypothesize that active movements bring changes in gas concentrations forth, which can be detected by the room, affecting RER. Comparing room-\(\dot{\mathrm{V}}\) O2 of P1 and P2, higher concentrations were found in P1 (minimal activity). Consequently, the room’s RER in P1 was smaller (although not significant) compared to P2. Since the allowance of light desk work inside the respiratory room varied between both protocols, we suggest that the active movements accompanying light deskwork might have been a decisive factor for the difference between the room-RER in both protocols, as subjects were allowed to move freely with their upper torso and arms. In addition, other subject-related variabilities can contribute to differences as well, such as hormonal status (menstrual status), previous level of exercise, or food intake prior to the 3 h of fasting. Further investigation on other specific determinants is warranted [24].

Although of clinical value, respiratory rooms are sparsely available due to high costs in infrastructure and the need of experienced and trained staff, therefore mostly used in academic research settings. The technological design of the basic respiratory room improves mobility and allows for measurements of EE under semi free-living conditions on a specific ward instead of transferring patients towards a stationary calorimeter. Accurate insights in the energy requirements can eventually lead to more individualized, patient-centered nutritional support.


The findings of this study should be considered in the light of some limitations. First, we did not take BC, more specific muscle mass (cfr. FFM) into account. This might have led to possible errors related to interpretation of the results as muscle mass is a large determinant of EE. FFM should therefore always be assessed concordantly by e.g. BodPod. More, the small sample size in both P1 and P2 may have affected the results, studies on larger groups are necessary to confirm our findings. Also, we did not correct for food intake. As the minimal fasting time was set at 3 h, some participants were measured early in the morning after > 8 h of fasting. An inventory of food intake by a self-reported nutritional diary or standardized diet prior to the measurement should account for possible bias related to individual food intake. Next, we did not use any wearable movement sensors or heart rate monitor to detect minimal activity such as the postulated upper body movements. In accordance, subject’s preference or perceived comfort levels were not analyzed, as well as respiration rate to assess e.g. hyperventilation. Finally, inter-individual varieties that could have introduced aberrant results were not considered. Future research with preferably a controlled nutritional intake, general health inventory, and physiological aspects of energy metabolism (e.g. imaging data and/or markers in muscle and brown adipose tissue, menstrual phase), is needed to optimize the use of the respiratory room.


We conclude that the basic version of the respiratory room proofs to be valid to measure EE in research, and opens doors for future use in clinical practice. A minute change in activity resulted in an increase in EE, although not significant. Substrate utilization (RER) did differ significantly when the activity changed. Results of this study can be used to facilitate the implementation of IC in nutritional research, and lead to future use for developing individual nutritional programs.

Availability of data and materials

The data supporting the findings of this study are available upon reasonable request from the corresponding author. Data are not shared openly to protect privacy of study participants. Data are located in a controlled access data storage at the University of Antwerp.



Resting energy expenditure


Body composition


Body weight

CO2 :

Carbon dioxide


Energy expenditure


Fat free mass


Fat mass

HBEq :

Harris-Benedict equation


Indirect calorimetry


Intraclass correlation coefficient

O2 :


P1 :

Protocol 1

P2 :

Protocol 2


Energy expenditure (in 24 h)


Respiratory exchange ratio


Total energy expenditure


Total energy intake


  1. Kinnaman J, Browe J, Agnew E, Nelson R. Attending the nutritional needs of patients in nursing homes; theory and practice. Am J Public Health Nations Health. 1955;45(5):627–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Wierdsma N, Kruizenga H, Konings L, Krebbers D, Jorissen J, Joosten M, et al. Poor nutritional status, risk of sarcopenia and nutrition related complaints are prevalent in COVID-19 patients during and after hospital admission. Clin Nutr ESPEN. 2021;43:369–76.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Tanaka K, Tanaka S, Okazaki J, Mii S. Preoperative nutritional status is independently associated with wound healing in patients undergoing open surgery for ischemic tissue loss. Vascular. 2021;29(6):897–904.

    Article  CAS  PubMed  Google Scholar 

  4. Roza AM, Shizgal HM. The Harris Benedict equation reevaluated: resting energy requirements and the body cell mass. Am J Clin Nutr. 1984;40(1):168–82.

    Article  CAS  PubMed  Google Scholar 

  5. Saunders J, Smith T. Malnutrition: causes and consequences. Clin Med. 2010;10(6):624–7.

    Article  Google Scholar 

  6. Ahmed N, Choe Y, Mustad V, Chakraborti S, Goates S, Luo M, et al. The impact of malnutrition on survival and healthcare utilization in medicare beneficiaries with diabetes: a retrospective cohort analysis. BMJ Open Diabetes Res Care. 2018;6(1):e000471.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Sabounchi N, Rahmandad H, Ammerman A. Best fitting prediction equations for basal metabolic rate: informing obesity interventions in diverse populations. Int J Obes. 2013;37(10):1364–70.

    Article  CAS  Google Scholar 

  8. Segales Gill D. Healthy adults’ basal metabolic rate comparison measured with indirect calorimetry versus predictive formulas. Acta Sci Orthop. 2021;4(10):25–9.

    Google Scholar 

  9. Gariballa S, Forster S. Energy expenditure of acutely ill hospitalised patients. Nutr J. 2006;5:9.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Schoffelen P, Plasqui G. Utilization of different formulae to calculate energy expenditure from gas exchange and substrate oxidation; an updated equation for indirect calorimetry. In: Measurement of human energy expenditure: biological variability and technical validity. Universitaire Pers Maastricht; 2017. Available from:

  11. Lam Y, Ravussin E. Analysis of energy metabolism in humans: a review of methodologies. Mol Metab. 2016;5(11):1057–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Schoffelen P, Plasqui G. Classical experiments in whole-body metabolism: open-circuit respirometry—diluted flow chamber, hood, or facemask systems. Eur J Appl Physiol. 2018;118(1):33–49.

    Article  CAS  PubMed  Google Scholar 

  13. Schoffelen P, Westerterp K, Saris W, ten Hoor F. A dual-respiration chamber system with automated calibration. J Appl Physiol. 1997;83(6):2064–72.

    Article  CAS  PubMed  Google Scholar 

  14. Webb P, Saris W, Schoffelen P, Van Ingen Schenau G, ten Hoor F. The work of walking: a calorimetric study. Med Sci Sports Exerc. 1988;20(4):331–7.

    Article  CAS  PubMed  Google Scholar 

  15. Schoffelen P, den Hoed M, van Breda E, Plasqui G. Test-retest variability of VO2max using total-capture indirect calorimetry reveals linear relationship of VO2 and power. Scand J Med Sci Sports. 2019;29(2):213–22.

    Article  PubMed  Google Scholar 

  16. Kleinloog J, van Laar S, Schoffelen P, Plasqui G. Validity and reproducibility of VO2max testing in a respiration chamber. Scand J Med Sci Sports. 2021;31(6):1259–67.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Soares I, Vasconcellos F, Cunha F. Time to achieve steady state for an accurate assessment of resting energy expenditure in adolescents with healthy weight and obesity: a cross-sectional study. Arch Endocrinol Metab. 2022;66(2):206–13.

    PubMed  PubMed Central  Google Scholar 

  18. Schoffelen P. Measurement of human energy expenditure: biological variability and technical validity. Maastricht: Datawyse / Universitaire Pers Maastricht; 2017. Available from:

    Book  Google Scholar 

  19. Chen K, Smith S, Ravussin E, Krakoff J, Plasqui G, Tanaka S, et al. Room Indirect Calorimetry Operating and Reporting Standards (RICORS 1.0): A Guide to Conducting and Reporting Human Whole-Room Calorimeter Studies. Obesity (Silver Spring). 2020;28(9):1613–25.

  20. Kaviani S, Schoeller D, Ravussin E, Melanson E, Henes S, Dugas L, et al. Determining the accuracy and reliability of indirect calorimeters utilizing the methanol combustion technique. Nutr Clin Pract. 2018;33(2):206–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Moonen H, Beckers K, van Zanten A. Energy expenditure and indirect calorimetry in critical Illness and convalescence: current evidence and practical considerations. J Intensive Care. 2021;9:8.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Miles-Chan J, Sarafian D, Montani J, Schutz Y, Dulloo A. Sitting comfortably versus lying down: is there really a difference in energy expenditure? Clin Nutr. 2014;33(1):175–8.

    Article  CAS  PubMed  Google Scholar 

  23. Melzer K. Carbohydrate and fat utilization during rest and physical activity. ESpen Eur E J Clin Nutr Metab. 2011;6:e45–52.

    Article  Google Scholar 

  24. Ramos-Jimenez A, Hernandez-Torres R, Torres-Duran P, Romero-Gonzalez J, Mascher D, Posadas-Romero C, et al. The respiratory exchange ratio is associated with fitness indicators both in trained and untrained men: a possible application for people with reduced exercise tolerance. Clin Med Circ Respirat Pulm Med. 2008;2:1–9.

    PubMed  PubMed Central  Google Scholar 

Download references


Not applicable.


No financial or material support was received for the preparation and submission of the manuscript.

Author information

Authors and Affiliations



All authors have read the final version of the manuscript and agree with its content. Timia Van Soom: Conceptualization, methodology, data curation, formal analysis, investigation, software, validation, roles/writing - original draft. Wiebren Tjalma: writing - review & editing. Ulrike Van Daele: writing – review & editing. Nick Gebruers: Conceptualization, methodology, supervision, writing – review & editing. Eric van Breda: Conceptualization, methodology, supervision, software, validation, writing – review & editing.

Corresponding authors

Correspondence to Nick Gebruers or Eric van Breda.

Ethics declarations

Ethics approval and consent to participate

The study is approved by the medical ethical committee of the University of Antwerp/Antwerp University Hospital (Belgian registration: B300201942189). Written informed consent was provided on date of appointment.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.



Table 7 Results of methanol combustion
Table 8 Comparison between measured (hood) and predicted EE (HBeq)

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Van Soom, T., Tjalma, W., Van Daele, U. et al. Comparison of energy expenditure measurements by a new basic respiratory room vs. classical ventilated hood. Nutr J 22, 72 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: