Percent relative cumulative frequency analysis in indirect calorimetry: application to studies of transgenic mice

2004 ◽  
Vol 82 (12) ◽  
pp. 1075-1083 ◽  
Author(s):  
Marc Riachi ◽  
Jean Himms-Hagen ◽  
Mary-Ellen Harper
Keyword(s):  
Oxygen Consumption ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Uncoupling Protein ◽  
Resting Metabolic Rate ◽  
Large Data ◽  
Cumulative Frequency ◽  
And Control ◽  
Deficient Mice

Indirect calorimetry is commonly used in research and clinical settings to assess characteristics of energy expenditure. Respiration chambers in indirect calorimetry allow measurements over long periods of time (e.g., hours to days) and thus the collection of large sets of data. Current methods of data analysis usually involve the extraction of only a selected small proportion of data, most commonly the data that reflects resting metabolic rate. Here, we describe a simple quantitative approach for the analysis of large data sets that is capable of detecting small differences in energy metabolism. We refer to it as the percent relative cumulative frequency (PRCF) approach and have applied it to the study of uncoupling protein-1 (UCP1) deficient and control mice. The approach involves sorting data in ascending order, calculating their cumulative frequency, and expressing the frequencies in the form of percentile curves. Results demonstrate the sensitivity of the PRCF approach for analyses of oxygen consumption ([Formula: see text]02) as well as respiratory exchange ratio data. Statistical comparisons of PRCF curves are based on the 50th percentile values and curve slopes (H values). The application of the PRCF approach revealed that energy expenditure in UCP1-deficient mice housed and studied at room temperature (24 °C) is on average 10% lower (p < 0.0001) than in littermate controls. The gradual acclimation of mice to 12 °C caused a near-doubling of [Formula: see text] in both UCP1-deficient and control mice. At this lower environmental temperature, there were no differences in [Formula: see text] between groups. The latter is likely due to augmented shivering thermogenesis in UCP1-deficient mice compared with controls. With the increased availability of murine models of metabolic disease, indirect calorimetry is increasingly used, and the PRCF approach provides a novel and powerful means for data analysis.Key words: thermogenesis, oxygen consumption, metabolic rate, uncoupling protein, UCP.

scholarly journals Indirect Calorimetry Protocol Development for Measuring Resting Metabolic Rate as a Component of Total Energy Expenditure in Free-Living Postmenopausal Women

2001 ◽  
Vol 131 (8) ◽  
pp. 2215-2218 ◽  
Author(s):  
Neilann K. Horner ◽  
Johanna W. Lampe ◽  
Ruth E. Patterson ◽  
Marian L. Neuhouser ◽  
Shirley A. Beresford ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Total Energy ◽  
Postmenopausal Women ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Total Energy Expenditure ◽  
Free Living ◽  
Protocol Development

scholarly journals The Energy Expenditure of Free-Living Physical Activities in Primary Schoolchildren

2016 ◽  
Vol 13 (s1) ◽  
pp. S57-S61 ◽  
Author(s):  
Alison L. Innerd ◽  
Liane B. Azevedo
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Physical Activities ◽  
Free Living ◽  
Metabolic Equivalent ◽  
Primary Schoolchildren ◽  
Vigorous Intensity

Background:The aim of this study is to establish the energy expenditure (EE) of a range of child-relevant activities and to compare different methods of estimating activity MET.Methods:27 children (17 boys) aged 9 to 11 years participated. Participants were randomly assigned to 1 of 2 routines of 6 activities ranging from sedentary to vigorous intensity. Indirect calorimetry was used to estimate resting and physical activity EE. Activity metabolic equivalent (MET) was determined using individual resting metabolic rate (RMR), the Harrell-MET and the Schofield equation.Results:Activity EE ranges from 123.7± 35.7 J/min/Kg (playing cards) to 823.1 ± 177.8 J/min/kg (basketball). Individual RMR, the Harrell-MET and the Schofield equation MET prediction were relatively similar at light and moderate but not at vigorous intensity. Schofield equation provided a better comparison with the Compendium of Energy Expenditure for Youth.Conclusion:This information might be advantageous to support the development of a new Compendium of Energy Expenditure for Youth.

scholarly journals Comparison of Conventional and Individualized 1-MET Values for Expressing Maximum Aerobic Metabolic Rate and Habitual Activity Related Energy Expenditure

Nutrients ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 458 ◽  
Author(s):  
Juliane Heydenreich ◽  
Yves Schutz ◽  
Katarina Melzer ◽  
Bengt Kayser
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Healthy Controls ◽  
Metabolic Capacity ◽  
Men And Women ◽  
Habitual Activity ◽  
The Individual ◽  
Activity Energy

The maximum aerobic metabolic rate can be expressed in multiple metabolically equivalent tasks (MET), i.e., METmax. The purpose was to quantify the error when the conventional (3.5 mL∙kg−1∙min−1) compared to an individualized 1-MET-value is used for calculating METmax and estimating activity energy expenditure (AEE) in endurance-trained athletes (END) and active healthy controls (CON). The resting metabolic rate (RMR, indirect calorimetry) and aerobic metabolic capacity (spiroergometry) were assessed in 52 END (46% male, 27.9 ± 5.7 years) and 53 CON (45% male, 27.3 ± 4.6 years). METmax was calculated as the ratio of VO2max over VO2 during RMR (METmax_ind), and VO2max over the conventional 1-MET-value (METmax_fix). AEE was estimated by multiplying published MET values with the individual and conventional 1-MET-values. Dependent t-tests were used to compare the different modes for calculating METmax and AEE (α = 0.05). In women and men CON, men END METmax_fix was significantly higher than METmax_ind (p < 0.01), whereas, in women END, no difference was found (p > 0.05). The conventional 1-MET-value significantly underestimated AEE in men and women CON, and men END (p < 0.05), but not in women END (p > 0.05). The conventional 1-MET-value appears inappropriate for determining the aerobic metabolic capacity and AEE in active and endurance-trained persons.

scholarly journals Estimation of Activity Related Energy Expenditure and Resting Metabolic Rate in Freely Moving Mice from Indirect Calorimetry Data

PLoS ONE ◽  
2012 ◽  
Vol 7 (5) ◽  
pp. e36162 ◽  
Author(s):  
Jan Bert Van Klinken ◽  
Sjoerd A. A. van den Berg ◽  
Louis M. Havekes ◽  
Ko Willems Van Dijk
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Related Energy ◽  
Freely Moving ◽  
Calorimetry Data

Resistance Training and Energy Balance

1998 ◽  
Vol 8 (2) ◽  
pp. 143-159 ◽  
Author(s):  
Eric T. Poehlman ◽  
Christopher Melby
Keyword(s):  
Oxygen Consumption ◽  
Energy Balance ◽  
Resistance Training ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Resistance Exercise ◽  
Resting Metabolic Rate ◽  
Substrate Oxidation ◽  
Daily Energy Expenditure ◽  
Daily Energy

In this brief review we examine the effects of resistance training on energy expenditure. The components of daily energy expenditure are described, and methods of measuring daily energy expenditure are discussed. Cross-sectional and exercise intervention studies are examined with respect to their effects on resting metabolic rate, physical activity energy expenditure, postexercise oxygen consumption, and substrate oxidation in younger and older individuals. Evidence is presented to suggest that although resistance training may elevate resting metabolic rate, il does not substantially enhance daily energy expenditure in free-living individuals. Several studies indicate that intense resistance exercise increases postexercise oxygen consumption and shifts substrate oxidation toward a greater reliance on fat oxidation. Preliminary evidence suggests that although resistance training increases muscular strength and endurance, its effects on energy balance and regulation of body weight appear to be primarily mediated by its effects on body composition (e.g., increasing fat-free mass) rather than by the direct energy costs of the resistance exercise.

scholarly journals Predictive equations for resting metabolic rate are not appropriate to use in Brazilian male adolescent football athletes

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244970
Author(s):  
Taillan M. Oliveira ◽  
Paula A. Penna-Franca ◽  
Christian H. Dias-Silva ◽  
Victor Z. Bittencourt ◽  
Fabio F. L. C. Cahuê ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Indirect Calorimetry ◽  
Resting Metabolic Rate ◽  
Primary Component ◽  
Accurate Information ◽  
Male Adolescent ◽  
Adolescent Athletes ◽  
Cross Sectional ◽  
Predictive Equations

High accuracy in estimating energy expenditure is essential for enhancing sports performance. The resting metabolic rate (RMR), as a primary component of total energy expenditure (TEE), is commonly estimated using predictive equations. However, these references may not be applicable to adolescent athletes. The purpose of this cross-sectional study was to analyse the differences between predicted RMR in relation to energy expenditure measured by indirect calorimetry (IC) among 45 Brazilian male adolescent football athletes. Indirect calorimetry (IC) and anthropometric (bioimpedance) measurements were recorded at a single visit to the laboratory after fasting overnight. The mean age was 15.6 ± 1.14 years, body mass was 63.05 ± 7.8 kg, and height was 172 ± 7.5 cm. The RMR values predicted by equations proposed by the Food and Agriculture Organization (FAO) (United Nations), Henry and Rees (HR), Harris Benedict (HB), and Cunningham (CUN) were compared with IC RMR values, by correlation analysis. The FAO and HR predictive equations yielded different values from IC (IC: 1716.26 ± 202.58, HR: 1864.87 ± 147.78, FAO: 1854.28 ± 130.19, p = 0.001). A moderate correlation of 0.504 was found between the results of HB and IC. In the survival-agreement model, the CUN equation showed low disagreement with the IC RMR, with error values between 200 and 300 kcal/day. The results showed that HB and CUN yielded similar values as IC, with the CUN equation showing low disagreement with IC; hence, adolescent athletes should undergo evaluation with precise laboratory methods to ensure that accurate information about RMR is recorded.

Determination of total energy expenditure, resting metabolic rate and physical activity in lean and overweight people

1997 ◽  
Vol 36 (4) ◽  
pp. 310-312 ◽  
Author(s):  
F. Thielecke ◽  
J. Möseneder ◽  
A. Kroke ◽  
K. Klipstein-Grobusch ◽  
H. Boeing ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Total Energy ◽  
Resting Metabolic Rate ◽  
Total Energy Expenditure ◽  
Overweight People

Energy Expenditure of Level Overground Walking in Young Adults: Comparison With Prediction Equations

2021 ◽  
pp. 1-8
Author(s):  
Jingjing Xue ◽  
Shuo Li ◽  
Rou Wen ◽  
Ping Hong
Keyword(s):  
Young Adults ◽  
Energy Expenditure ◽  
Metabolic Rate ◽  
Energy Cost ◽  
Sports Medicine ◽  
Resting Metabolic Rate ◽  
Prediction Equations ◽  
Overground Walking ◽  
All Speeds ◽  
Walking Energy Cost

Background: The purpose of this study was to investigate the accuracy of the published prediction equations for determining level overground walking energy cost in young adults. Methods: In total, 148 healthy young adults volunteered to participate in this study. Resting metabolic rate and energy expenditure variables at speeds of 4, 5, and 6 km/h were measured by indirect calorimetry, walking energy expenditure was estimated by 3 published equations. Results: The gross and net metabolic rate per mile of level overground walking increased with increased speed (all P < .01). Females were less economical than males. The present findings revealed that the American College of Sports Medicine and Pandolf et al equations significantly underestimated the energy cost of overground walking at all speeds (all P < .01) in young adults. The percentage mean bias for American College of Sports Medicine, Pandolf et al, and Weyand et al was 12.4%, 16.8%, 1.4% (4 km/h); 21.6%, 15.8%, 7.1% (5 km/h); and 27.6%, 12%, 6.6% (6 km/h). Bland–Altman plots and prediction error analysis showed that the Weyand et al was the most accurate in 3 existing equations. Conclusions: The Weyand et al equation appears to be the most suitable for the prediction of overground walking energy expenditure in young adults.

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