A novel approach to calculating the thermic effect of food in a metabolic chamber

The use of accelerometers to improve estimation of the thermic effect of food in whole room calorimetry studies

We tested whether spontaneous physical activity (SPA) from accelerometers could be used in a whole room calorimeter to estimate thermic effect of food (TEF). Eleven healthy participants (n = 7 females; age: 27 ± 4 yr; body mass index: 22.8 ± 2.6 kg/m2) completed two 23-h visits in randomized order: one "fed" with meals provided and one "fasted" with no food. SPA was measured by ActivPAL and Actigraph accelerometers. Criterion TEF was calculated as the difference in total daily energy expenditure (TDEE) between fed and fasted visits and compared with three methods of estimating TEF: 1) SPA-adjusted TEF (adjTEF)-difference in TDEE without SPA between visits, 2) Wakeful TEF-difference in energy expenditure obtained from linear regression and basal metabolic rate during waking hours, 3) 24-h TEF-increase in TDEE above SPA and sleeping metabolic rate. Criterion TEF was 9.4 ± 4.5% of TDEE. AdjTEF (difference in estimated vs. criterion TEF: activPAL: -0.3 ± 3.3%; Actigraph: -1.8 ± 8.0%) and wakeful TEF (activPAL: -0.9 ± 6.1%; Actigraph: -2.8 ± 7.6%) derived from both accelerometers did not differ from criterion TEF (all P > 0.05). ActivPAL-derived 24-h TEF overestimated TEF (6.8 ± 5.4%, P = 0.002), whereas Actigraph-derived 24-h TEF was not significantly different (4.3 ± 9.4%, P = 0.156). TEF estimations using activPAL tended to show better individual-level agreement (i.e., smaller coefficients of variation). Both accelerometers can be used to estimate TEF in a whole room calorimeter; wakeful TEF using activPAL is the most viable option given strong group-level accuracy and reasonable individual agreement.NEW & NOTEWORTHY Two research-grade accelerometers can effectively estimate spontaneous physical activity and improve the estimation of thermic effect of food (TEF) in whole room calorimeters. The activPAL demonstrates strong group-level accuracy and reasonable individual-level agreement in estimating wakeful TEF, whereas a hip-worn Actigraph is an acceptable approach for estimating 24-h TEF. These results highlight the promising potential of accelerometers in advancing energy balance research by improving the assessment of TEF within whole room calorimeters.

Calculating Diet-Induced Thermogenesis in Mice

Diet-induced thermogenesis (DIT) is the increase in energy expenditure (EE) associated with food intake. Increasing DIT may lead to weight loss, so it is expected that increasing DIT will decrease body mass index and body fat mass. DIT in humans has been measured in various ways, but there is no way to calculate absolute DIT values in mice. Therefore, we developed a method to measure DIT in mice by applying a method more commonly used in humans. First, we measure the energy metabolism of mice under fasting conditions. EE is then plotted against the square root of activity, and a linear regression equation is fitted to the data. Next, we measure the energy metabolism of mice fed ad libitum and plotted EE in the same way. DIT is calculated by subtracting the predicted EE value from the EE value of mice fed at the same activity count. This method not only allows observation of the time course of the absolute value of DIT but also allows calculation of the ratio of DIT to caloric intake and the ratio of DIT to EE.

Validation of energy expenditure and macronutrient oxidation measured by two new whole-room indirect calorimeters

OBJECTIVE

The aim of this study was to validate two new whole-room indirfect calorimeters according to Room Indirect Calorimetry Operating and Reporting Standards (RICORS 1.0).

METHODS

For technical validation, 16 propane combustion tests were performed to determine accuracy and precision of energy expenditure (EE) and ventilation rates of oxygen (VO₂ ), carbon dioxide (VCO₂ ), and respiratory exchange ratio (VCO₂ /VO₂ ). For biological validation, eight participants (mean [SD], age 24.1 [2.5] years; BMI 24.3 [3.1] kg/m² ) underwent four 24-hour protocols under highly standardized conditions: (1) isocaloric sedentary, (2) fasting sedentary, (3) isocaloric active, and (4) fasting active. Reliability (coefficients of variation [CV]) and minimal detectable changes (MDC) were calculated for 24-hour EE, sleeping metabolic rate (SMR), physical activity energy expenditure (PAEE), thermic effect of food (TEF), and macronutrient oxidation rates.

RESULTS

Technical validation showed high reliability and recovery rates for VO₂ (0.75% and 100.8%, respectively), VCO₂ (0.49% and 100.6%), and EE (0.54% and 98.2%). Biological validation revealed CV and MDC for active conditions of 1.4% and 4.3% for 24-hour EE, 1.7% and 5.9% for SMR, and 30.2% and 38.4% for TEF, as well as 5.8% and 10.5% for PAEE, respectively. Mean CV and MDC for macronutrient oxidation rates were 9.9% and 22.9%, respectively.

CONCLUSIONS

The precision of 24-hour EE and SMR was high, whereas it was lower for PAEE and poor for TEF.

Room Indirect Calorimetry Operating and Reporting Standards (RICORS 1.0): A Guide to Conducting and Reporting Human Whole-Room Calorimeter Studies

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.

A novel method for measuring diet-induced thermogenesis in mice

Diet-induced thermogenesis (DIT) refers to energy expenditure (EE) related to food consumption. Enhancing DIT can lead to weight loss. Factors that increase DIT are expected to lower body mass index and body fat mass. Although various methods have been developed for measuring DIT in humans, there is currently no method available for calculating absolute DIT values in mice. Therefore, we attempted to measure DIT in mice by applying the method more commonly used for humans. Mouse energy metabolism was first measured under fasting conditions; EE was plotted against the square root of the activity count, and a linear regression equation was fit to the data. Then, energy metabolism was measured in mice that were allowed to feed ad libitum, and EE was plotted in the same way. We calculated the DIT by subtracting the predicted EE value from the fed EE value for the same activity count. The methodology for measuring DIT in mice may be helpful for researching ways of combatting obesity by increasing DIT.

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The methodology for measuring absolute DIT values in mice is developed.

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For mice, the proportion of DIT compared with calorie intake and EE are 12.3% and 21.7%, respectively.

A novel approach to calculating the thermic effect of food in a metabolic chamber

The thermic effect of food (TEF) is the well‐known concept in spite of its difficulty for measuring. The gold standard for evaluating the TEF is the difference in energy expenditure between fed and fasting states (ΔEE). Alternatively, energy expenditure at 0 activity (EE₀) is estimated from the intercept of the linear relationship between energy expenditure and physical activity to eliminate activity thermogenesis from the measurement, and the TEF is calculated as the difference between EE₀ and postabsorptive resting metabolic rate (RMR) or sleeping metabolic rate (SMR). However, the accuracy of the alternative methods has been questioned. To improve TEF estimation, we propose a novel method as our original TEF calculation method to calculate EE₀ using integrated physical activity over a specific time interval. We aimed to identify which alternative methods of TEF calculation returns reasonable estimates, that is, positive value as well as estimates close to ΔEE. Seven men participated in two sessions (with and without breakfast) of whole‐body indirect calorimetry, and physical activity was monitored with a triaxial accelerometer. Estimates of TEF by three simplified methods were compared to ΔEE. ΔEE, EE₀ above SMR, and our original method returned positive values for the TEF after breakfast in all measurements. TEF estimates of our original method was indistinguishable from those based on the ΔEE, whereas those as EE₀ above RMR and EE₀ above SMR were slightly lower and higher, respectively. Our original method was the best among the three simplified TEF methods as it provided positive estimates in all the measurements that were close to the value derived from gold standard for all measurements.

Electronic Noses for Well-Being: Breath Analysis and Energy Expenditure

The wealth of information concealed in a single human breath has been of interest for many years, promising not only disease detection, but also the monitoring of our general well-being. Recent developments in the fields of nano-sensor arrays and MEMS have enabled once bulky artificial olfactory sensor systems, or so-called "electronic noses", to become smaller, lower power and portable devices. At the same time, wearable health monitoring devices are now available, although reliable breath sensing equipment is somewhat missing from the market of physical, rather than chemical sensor gadgets. In this article, we report on the unprecedented rise in healthcare problems caused by an increasingly overweight population. We first review recently-developed electronic noses for the detection of diseases by the analysis of basic volatile organic compounds (VOCs). Then, we discuss the primary cause of obesity from over eating and the high calorific content of food. We present the need to measure our individual energy expenditure from our exhaled breath. Finally, we consider the future for handheld or wearable devices to measure energy expenditure; and the potential of these devices to revolutionize healthcare, both at home and in hospitals.