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

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.

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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

International Journal of Sport Nutrition and Exercise Metabolism ◽

10.1123/ijsnem.2015-0315 ◽

2016 ◽

Vol 26 (5) ◽

pp. 454-463 ◽

Cited By ~ 7

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.

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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 ◽

10.3390/nu12020487 ◽

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.

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Abstract 15864: Measured versus Estimated Resting Metabolic Rate in Heart Failure With Preserved Ejection Fraction

Circulation ◽

10.1161/circ.142.suppl_3.15864 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Theresa Anderson ◽

Thomas Cascino ◽

Daniel Perry ◽

Gillian Grafton ◽

Todd M Koelling ◽

...

Keyword(s):

Heart Failure ◽

Weight Loss ◽

Ejection Fraction ◽

Metabolic Rate ◽

Resting Metabolic Rate ◽

World Health ◽

Heart Catheterization ◽

Preserved Ejection Fraction ◽

Dietary Counseling ◽

Metabolic Cart

Introduction: Obesity is common in heart failure with preserved ejection fraction (HFpEF) and dietary weight loss can improve functional capacity, but sarcopenia and frailty are also frequently present. Little evidence is available regarding resting metabolic rate (RMR) or how commonly used equations to estimate RMR compare to measured RMR in HFpEF. This information is vital for counseling patients on individual caloric needs. Hypothesis: Commonly used estimation equations do not accurately reflect measured RMR in patients with HFpEF. Methods: Resting metabolic rate (RMR) was measured with a metabolic cart for consecutive patients with HFpEF (EF ≥50%) referred for right heart catheterization at the University of Michigan from 2011-2015. Patients with congenital, infiltrative, hypertrophic, or restrictive cardiomyopathy were excluded. The RMR was calculated using the Weir formula: RMR= 1440*[3.94 VO 2 (l/min) + 1.11*VCO 2 (l/min)] kcal/day. Measured RMR and estimations of RMR using the Harris Benedict Equation (HBE), Mifflin-St Jeor Equation (MSJE), and World Health Organization (WHO) equation were compared using paired t-tests and Bland-Altman plots. Results: Patients (n=43) were aged (mean ± SD) 62 ± 11.6 years, 53% female, and BMI 34.9 ± 11. Mean measured RMR from Weir equation was 1514 ± 479 kcal/day. Estimated RMR by HBE was 1784 ± 530, MSJE was 1685 ± 457, and WHO equation was 1816.8 ± 485 kcal/day. All estimations significantly overestimated RMR when compared to the Weir method (>10% difference and p<0.01 for all; Figure A-C). The MSJE had the closest range of agreement to the measured RMR. Conclusions: Estimations of resting metabolic rate in patients with HFpEF demonstrated a fixed bias towards overestimation when compared to measured RMR by metabolic cart. Given HFpEF populations are often obese and are counseled routinely on weight loss, understanding the implicit bias of equations estimating RMR is vital when providing nutritional and dietary counseling.

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Nutrient pattern of unsaturated fatty acids and vitamin E increase resting metabolic rate of overweight and obese women

International Journal for Vitamin and Nutrition Research ◽

10.1024/0300-9831/a000664 ◽

2020 ◽

pp. 1-9

Author(s):

Habib Yarizadeh ◽

Leila Setayesh ◽

Caroline Roberts ◽

Mir Saeed Yekaninejad ◽

Khadijeh Mirzaei

Keyword(s):

Vitamin E ◽

Metabolic Rate ◽

Unsaturated Fatty Acids ◽

Resting Metabolic Rate ◽

Blood Parameters ◽

Cross Sectional Study ◽

Obese Women ◽

Cross Sectional ◽

Dietary Nutrients ◽

Nutrient Patterns

Abstract. Objectives: Obesity plays an important role in the development of chronic diseases including cardiovascular disease and diabetes. A low resting metabolic rate (RMR) for a given body size and composition is a risk factor for obesity, however, there is limited evidence available regarding the association of nutrient patterns and RMR. The aim of this study was to determine the association of nutrient patterns and RMR in overweight and obese women. Study design: This cross-sectional study was conducted on 360 women who were overweight or obese. Method: Dietary intake was assessed using a semi-quantitative standard food frequency questionnaire (FFQ). Nutrient patterns were also extracted by principal components analysis (PCA). All participants were evaluated for their body composition, RMR, and blood parameters. Result: Three nutrient patterns explaining 64% of the variance in dietary nutrients consumption were identified as B-complex-mineral, antioxidant, and unsaturated fatty acid and vitamin E (USFA-vit E) respectively. Participants were categorized into two groups based on the nutrient patterns. High scores of USFA-vit E pattern was significantly associated with the increase of RMR (β = 0.13, 95% CI = 0.79 to 68.16, p = 0.04). No significant associations were found among B-complex-mineral pattern (β = −0.00, 95% CI = −49.67 to 46.03, p = 0.94) and antioxidant pattern (β = 0.03, 95% CI −41.42 to 22.59, p = 0.56) with RMR. Conclusion: Our results suggested that the “USFA-vit E” pattern (such as PUFA, oleic, linoleic, vit.E, α-tocopherol and EPA) was associated with increased RMR.

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Use of an ECAL indirect calorimeter measuring resting metabolic rate and fat burning capacity in a lifestyle medicine clinic for adults with diabetes, pre-diabetes and unwanted obesity

Obesity Abstracts ◽

10.1530/obabs.01.p28 ◽

2019 ◽

Author(s):

Sue Beckers

Keyword(s):

Metabolic Rate ◽

Resting Metabolic Rate ◽

Lifestyle Medicine ◽

Medicine Clinic

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Validation of Equations for the Prediction of Resting Metabolic Rate in Sri Lankan Adults

International Journal of Scientific and Research Publications (IJSRP) ◽

10.29322/ijsrp.9.10.2019.p9462 ◽

2019 ◽

Vol 9 (10) ◽

pp. p9462

Author(s):

Pathima Fairoosa ◽

Indu Waidyatilaka ◽

Maduka de Lanerolle-Dias ◽

Pujitha Wickramasinghe ◽

Pulani Lanerolle

Keyword(s):

Metabolic Rate ◽

Resting Metabolic Rate ◽

Sri Lankan

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High Intensity Interval Circuit Training on Resting Metabolic Rate in Overweight Adults

Case Medical Research ◽

10.31525/ct1-nct03972059 ◽

2019 ◽

Author(s):

Keyword(s):

Metabolic Rate ◽

High Intensity ◽

Resting Metabolic Rate ◽

Circuit Training ◽

High Intensity Interval ◽

Overweight Adults

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The Metabolic Theory of Ecology

10.1093/oso/9780199551668.003.0012 ◽

2017 ◽

Author(s):

Andrew Clarke

Keyword(s):

Metabolic Rate ◽

Resting Metabolic Rate ◽

Effect Of Temperature ◽

Thermal Ecology ◽

Model Data ◽

Metabolic Theory ◽

Physical Explanation ◽

Boltzmann Factor ◽

Scaling Exponents ◽

Metabolic Theory Of Ecology

The model of West, Brown & Enquist (WBE) is built on the assumption that the metabolic rate of cells is determined by the architecture of the vascular network that supplies them with oxygen and nutrients. For a fractal-like network, and assuming that evolution has minimised cardiovascular costs, the WBE model predicts that s=metabolism should scale with mass with an exponent, b, of 0.75 at infinite size, and ~ 0.8 at realistic larger sizes. Scaling exponents ~ 0.75 for standard or resting metabolic rate are observed widely, but far from universally, including in some invertebrates with cardiovascular systems very different from that assumed in the WBE model. Data for field metabolic rate in vertebrates typically exhibit b ~ 0.8, which matches the WBE prediction. Addition of a simple Boltzmann factor to capture the effects of body temperature on metabolic rate yields the central equation of the Metabolic Theory of Ecology (MTE). The MTE has become an important strand in ecology, and the WBE model is the most widely accepted physical explanation for the scaling of metabolic rate with body mass. Capturing the effect of temperature through a Boltzmann factor is a useful statistical description but too simple to qualify as a complete physical theory of thermal ecology.

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