scholarly journals Impact of the Method Used to Select Gas Exchange Data for Estimating the Resting Metabolic Rate, as Supplied by Breath-by-Breath Metabolic Carts

Nutrients ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 487
Author(s):  
Juan M.A. Alcantara ◽  
Guillermo Sanchez-Delgado ◽  
Francisco J. Amaro-Gahete ◽  
Jose E. Galgani ◽  
Jonatan R. Ruiz
Keyword(s):  
Gas Exchange ◽  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Time Interval ◽  
Metabolic Cart ◽  
Coefficients Of Variation ◽  
Human Energy ◽  
The Mean ◽  
Middle Aged Adults ◽  
Exchange Data

The method used to select representative gas exchange data from large datasets influences the resting metabolic rate (RMR) returned. This study determines which of three methods yields the lowest RMR (as recommended for use in human energy balance studies), and in which method the greatest variance in RMR is explained by classical determinants of this variable. A total of 107 young and 74 middle-aged adults underwent a 30 min RMR examination using a breath-by-breath metabolic cart. Three gas exchange data selection methods were used: (i) steady state (SSt) for 3, 4, 5, or 10 min, (ii) a pre-defined time interval (TI), i.e., 6–10, 11–15, 16–20, 21–25, 26–30, 6–25, or 6–30 min, and (iii) “filtering”, setting thresholds depending on the mean RMR value obtained. In both cohorts, the RMRs yielded by the SSt and filtering methods were significantly lower (p < 0.021) than those yielded by the TI method. No differences in RMR were seen under the different conditions of the SSt method, or of the filtering method. No differences were seen between the methods in terms of the variance in RMR explained by its classical determinants. In conclusion, the SSt and filtering methods return the lowest RMRs and intra-measurement coefficients of variation when using breath-by-breath metabolic carts.

scholarly journals Two Novel Models Evaluating the Determinants of Resting Metabolic Rate in Indian Children

2021 ◽  
Author(s):  
Sandra Aravind Areekal ◽  
Anuradha Khadilkar ◽  
Veena Ekbote ◽  
Neha Kajale ◽  
Arun S. Kinare ◽  
...  
Keyword(s):  
Body Composition ◽  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Childhood Development ◽  
Relative Mass ◽  
Kidney Volume ◽  
Indian Children ◽  
Cross Sectional ◽  
Multi Centre Study ◽  
The Mean

Abstract Resting metabolic rate (RMR) quantifies the minimal energy required to sustain vital body functions and is a crucial component of childhood development. While inter-individual variations in RMR have been studied for over a century they are poorly understood. Wang (Am. J. Hum., 2012) has modelled mean RMR per unit body mass (RMR/BM) in children grouped into age classes one year apart; this model is able to explain the variation in RMR/BM very accurately in a reference Caucasian dataset based on the relative masses of four major organs (liver, kidney, brain, heart) and the residual mass. However, it is not clear if it applies to other ethnicities, especially when the variation in the RMR is observed to be large in a population. Here we address the extent to which such a model can be adapted to explain RMR/BM in Indian children. Here we present two novel phenomenological models that describe the mean RMR/BM stratified by age in Indian children and adolescents, using data from the Multi-Centre Study (MCS) and RMR-USG. MCS is a cross-sectional dataset on 495 (235 girls) children aged 9 to 19 years with anthropometric, body composition and RMR measurements. RMR-USG consists of anthropometric data, RMR, and liver and kidney volume measured through ultrasonography in nine girls and nine boys aged 6 to 8 years. The mean RMR/BM in Indian children is observed to be significantly lower compared to their Caucasian counterparts, except in boys in the age groups 9 to 11 years and 12 to 13 years. The first is a modified Wang model in which the relative masses of four major organs are assumed to be uniformly lowered for Indian children. Theoretical predictions of size are not uniformly borne out in a pilot validation study, however, the relative mass of the kidney is indeed found to be significantly lower. We then present another version of the Wang model to demonstrate that changes in body composition alone can also explain the Indian data. Either model can be thus used phenomenologically to estimate mean RMR/BM by age in Indian children; however, understanding the mechanistic basis of variation in RMR/BM remains an open problem.

Comparison of Association Between Physical Activity and Resting Metabolic Rate on Korean Young and Middle‐Aged Adults

2020 ◽  
Vol 34 (S1) ◽  
pp. 1-1
Author(s):  
HYEJUNG HWANG ◽  
Wonsang Jung ◽  
Jisu Kim ◽  
Hun-young Park ◽  
Kiwon Lim
Keyword(s):  
Physical Activity ◽  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Middle Aged ◽  
Middle Aged Adults

scholarly journals Resting Metabolic Rate in Monozygotic and Dizygotic Twins

1985 ◽  
Vol 34 (1-2) ◽  
pp. 41-47 ◽  
Author(s):  
E. Fontaine ◽  
R. Savard ◽  
A. Tremblay ◽  
J.P. Després ◽  
E. Poehlman ◽  
...  
Keyword(s):  
Energy Balance ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Open Circuit ◽  
Dizygotic Twins ◽  
Free Weight ◽  
Human Energy ◽  
Mz Twins ◽  
Male Twin

AbstractIn order to study the influence of heredity on resting metabolic rate (RMR), 20 monozygotic and 19 dizygotic male twin pairs aged 20.6 (SD 2.9) and 21.4 (SD 3.1) years, gave their consent to participate in the experiment. Fat free weight (FFW) was estimated from underwater weighing. RMR was measured by indirect calorimetry using an open circuit system. RMR was expressed as kJ · min−1, kJ/m2 · h−1, kJ/kg · h−1 and kJ/kgFFW · h−1. Significant intraclass coefficients were observed in MZ twins for the different expressions of RMR. The values ranged from r = 0.45 (P < 0.05) to r = 0.81 (P < 0.01). However, DZ twins demonstrated lower intraclass coefficients for RMR, with a range from r = 0.21 to r = 0.44. Significant (P < 0.05) DZ resemblance was revealed only when RMR was expressed as kJ · min−1 and kJ/kg · h−1. Results of the present study suggest that variations in RMR may have a genetic component. Implications for human energy balance and body fat are discussed.

scholarly journals Metabolic Adaptations to Weight Loss: Relative Changes in Resting Metabolic Rate and Energy Expenditure for Physical Activity and Association With Weight Loss Maintenance

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 526-526
Author(s):  
Rachel Silver ◽  
Sai Das ◽  
Michael Lowe ◽  
Susan Roberts
Keyword(s):  
Physical Activity ◽  
Weight Loss ◽  
Linear Regression ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Fat Mass ◽  
Weight Regain ◽  
Resting Metabolic Rate ◽  
Fat Free Mass ◽  
The Mean

Abstract Objectives There is persistent controversy over the extent to which different components of energy expenditure disproportionately decrease after weight loss and contribute to weight regain through decreased energy requirements. We conducted a secondary analysis of the CALERIE I study to test the hypothesis that decreased resting metabolic rate (RMR) and energy expenditure for physical activity (EEPA) after a 6-month calorie restriction intervention would predict weight regain at 12 months, with a greater decrease in RMR than EEPA. Methods Participants (n = 46) received all food and energy-containing beverages for 6 months. Outcome measures included total energy expenditure by doubly labeled water, RMR by indirect calorimetry, and body composition by BOD POD. Predictions for RMR and EEPA were derived from baseline linear regression models including age, sex, fat mass, and fat free mass. Baseline regression coefficients were used to calculate the predicted RMR and EEPA at 6 months. Residuals were calculated as the difference between measured and predicted values and were adjusted for body weight. The presence of metabolic adaptation was evaluated by a paired t-test comparing measured and predicted RMR at 6 months. Differences between 6-month RMR and EEPA residuals were evaluated by the same method. Linear regression was used to assess the association between 6-month residuals and weight loss maintenance (% weight change, 6 to 12 months). Results Mean weight loss was 6.9% at 6 months with 2.1% regain from 6 to 12 months. No adaptation in RMR was observed at 6 months (mean residual: 19 kcal; 95% confidence interval: −9, 48; P = 0.18). However, significant adaptation was observed in EEPA (mean residual: −199 kcal; −126, −272; P &lt; 0.0001). In addition, the mean 6-month RMR residual was significantly greater than the mean 6-month EEPA residual (218 kcal; 133, 304; P &lt; 0.0001). There was no significant association between 6-month RMR or EEPA residuals and weight regain at 12 months (P = 0.56, 0.34). Conclusions There was no measurable decrease in RMR with weight loss after adjusting for changes in fat free mass and fat mass, but there was a decrease in EEPA. Changes in RMR and EEPA with weight loss over 6 months did not predict weight regain at 12 months. Funding Sources Jean Mayer USDA Human Nutrition Research Center on Aging Doctoral Scholarship; USDA agreement #8050–51000-105–01S

The Ventilation-Corrected ParvoMedics TrueOne 2400 Provides a Valid and Reliable Assessment of Resting Metabolic Rate (RMR) in Athletes Compared With the Douglas Bag Method

2016 ◽  
Vol 26 (5) ◽  
pp. 454-463 ◽  
Author(s):  
Amy L. Woods ◽  
Laura A. Garvican-Lewis ◽  
Anthony J. Rice ◽  
Kevin G. Thompson
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Regression Equation ◽  
Reliable Measurement ◽  
Metabolic Cart ◽  
Typical Error ◽  
Reliable Assessment ◽  
Douglas Bag ◽  
Douglas Bag Method ◽  
The Difference

The aim of the current study was to determine if a single ParvoMedics TrueOne 2400 metabolic cart provides valid and reliable measurement of RMR in comparison with the criterion Douglas Bag method (DB). Ten endurance-trained participants completed duplicate RMR measurements on 2 consecutive days using the ParvoMedics system in exercise mode, with the same expirate analyzed using DB. Typical error (TE) in mean RMR between the systems was 578.9 kJ or 7.5% (p = .01). In comparison with DB, the ParvoMedics system over-estimated RMR by 946.7 ± 818.6 kJ. The bias between systems resulted from ParvoMedics VE(STPD) values. A regression equation was developed to correct the bias, which reduced the difference to -83.3 ± 631.9 kJ. TE for the corrected ParvoMedics data were 446.8 kJ or 7.2% (p = .70). On Day 1, intraday reliability in mean RMR for DB was 286.8 kJ or 4.3%, (p = .54) and for ParvoMedicsuncorrected, 359.3 kJ or 4.4%, (p = .35), with closer agreement observed on Day 2. Interday reliability for DB was 455.3 kJ or 6.6% (p = .61) and for ParvoMedicsuncorrected, 390.2 kJ or 6.3% (p = .54). Similar intraday and interday TE was observed between ParvoMedicsuncorrected and ParvoMedicscorrected data. The ParvoMedics TrueOne 2400 provided valid and reliable RMR values compared with DB when the VE(STPD) error was corrected. This will enable widespread monitoring of RMR using the ParvoMedics system in a range of field-based settings when DB is not available.

scholarly journals Evaluation of a Thermal-Based Flow Meter for Assessment of Mobile Resting Metabolic Rate Measures

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Nai-Yuan Liu ◽  
Yue Deng ◽  
Francis Tsow ◽  
Devon Bridgeman ◽  
Xiaojun Xian ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Consumption Rate ◽  
Resting Metabolic Rate ◽  
Exhaled Breath ◽  
Thermal Flow ◽  
Exhalation Rate ◽  
Flow Rate Measurement ◽  
Flow Meter ◽  
Metabolic Cart ◽  
In Series

This work evaluates the use of a new flow meter to assess exhalation rate. A mobile indirect calorimeter (MIC) was designed and used to measure resting metabolic rate (RMR), which relies on the measure of O2 consumption rate (VO2) and CO2 production rate (VCO2). The device was produced from a commercially available and well-established indirect calorimeter and implemented with a new flow meter for the purpose of this study. VO2 and VCO2 were assessed by measuring exhalation rates using the new flow meter and O2 and CO2 concentrations in breath using the original colorimetric sensors of the indirect calorimeter. The new flow meter was based on a thermal flow meter (TFM) affixed to an orifice with a diameter of 6.8 mm used as a passage for exhaled breath from 16 subjects. The results were compared with a metabolic cart (Medical Graphics), which was connected in series to the modified device. We found that 69% of the results had more than a 10% difference between the modified MIC device and the reference instrument, suggesting that the sensitivity of the thermal flow meter changed over time, which precluded its use as a flow meter for breath flow rate measurement.

Aquatic thermoregulation of captive and free-ranging beavers (Castor canadensis)

1990 ◽  
Vol 68 (11) ◽  
pp. 2409-2416 ◽  
Author(s):  
Robert A. MacArthur ◽  
Alvin P. Dyck
Keyword(s):  
Metabolic Rate ◽  
Cold Water ◽  
Castor Canadensis ◽  
Resting Metabolic Rate ◽  
Whole Body ◽  
Passive Cooling ◽  
Metabolic Rates ◽  
The Mean ◽  
Free Ranging ◽  
Skin Temperatures

Abdominal cooling occurred in 91% of all aquatic excursions documented in free-ranging beavers during fall and winter. Kits aged 4–7 months cooled faster and spent less time foraging in 1–12 °C water than did animals > 1 year old. All beavers tested in the laboratory displayed abdominal cooling in 2–20 °C water, with maximal cooling rates recorded in a 5- to 7-week-old kit. Immersion in cold water induced strong peripheral cooling, though skin temperatures beneath the pelage remained within 4–5 °C of abdominal measurements. The resting metabolic rate of beavers > 1 year old was independent of water temperature between 19 and 31 °C, but increased proportionately at lower temperatures. Whole-body conductance of resting animals was on average 1.6–3.0 times higher in water than in air. Maximum testing metabolic rates in water varied from 1.8 to 2.4 times the mean resting thermoneutral rate in air. Our results suggest that beavers mitigate the thermogenic effort required in water by adopting a thermoregulatory strategy which combines avoidance of prolonged immersion with a tolerance to passive cooling.

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