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Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data.

ABSTRACT: Physical activity (PA) is a main determinant of total energy expenditure (TEE) and has been suggested to play a key role in body weight regulation. However, thus far it has been challenging to determine what part of the expended energy is due to activity in freely moving subjects. We developed a computational method to estimate activity related energy expenditure (AEE) and resting metabolic rate (RMR) in mice from activity and indirect calorimetry data. The method is based on penalised spline regression and takes the time dependency of the RMR into account. In addition, estimates of AEE and RMR are corrected for the regression dilution bias that results from inaccurate PA measurements. We evaluated the performance of our method based on 500 simulated metabolic chamber datasets and compared it to that of conventional methods. It was found that for a sample time of 10 minutes the penalised spline model estimated the time-dependent RMR with 1.7 times higher accuracy than the Kalman filter and with 2.7 times higher accuracy than linear regression. We assessed the applicability of our method on experimental data in a case study involving high fat diet fed male and female C57Bl/6J mice. We found that TEE in male mice was higher due to a difference in RMR while AEE levels were similar in both groups, even though female mice were more active. Interestingly, the higher activity did not result in a difference in AEE because female mice had a lower caloric cost of activity, which was likely due to their lower body weight. In conclusion, TEE decomposition by means of penalised spline regression provides robust estimates of the time-dependent AEE and RMR and can be applied to data generated with generic metabolic chamber and indirect calorimetry set-ups.

SUBMITTER: Van Klinken JB

PROVIDER: S-EPMC3344840 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data.

Van Klinken Jan Bert JB van den Berg Sjoerd A A SA van den Berg Sjoerd A A SA Havekes Louis M LM Willems Van Dijk Ko K

PloS one 20120504 5

Physical activity (PA) is a main determinant of total energy expenditure (TEE) and has been suggested to play a key role in body weight regulation. However, thus far it has been challenging to determine what part of the expended energy is due to activity in freely moving subjects. We developed a computational method to estimate activity related energy expenditure (AEE) and resting metabolic rate (RMR) in mice from activity and indirect calorimetry data. The method is based on penalised spline re ...[more]

PMID: 22574139

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Project description:Optimal energy provision, guided by measured resting energy expenditure (REE) and determined by indirect calorimetry (IC), is fundamental in Intensive Care Units (ICU). Because IC availability is limited, methods to predict REE based on carbon dioxide production (VCO2) measurements (REEVCO2) alone have been proposed as a surrogate for REE measured by IC (REEIC). The study aimed at externally and internally validating the accuracy of the REEVCO2 as an alternative to REEIC in mechanically ventilated children. A ventilator's integrated gas exchange module (E-COVX) was used to prospectively measure REEIC and predict REEVCO2 on 107 mechanically ventilated children during the first 24 h of admission. The accuracy of the REEVCO2 compared to REEIC was assessed through the calculation of bias and precision, paired median differences, linear regression, and ROC analysis. Accuracy within ±10% of the REEIC was deemed acceptable for the REEVCO2 equation. The calculated REEVCO2 based on respiratory quotient (RQ) 0.89 resulted in a mean bias of -72.7 kcal/day (95% limits of agreement -321.7 to 176.3 kcal/day) and a high coefficient of variation (174.7%), while 51.4% of the calculations fell outside the ±10% accuracy rate. REEVCO2 derived from RQ 0.80 or 0.85 did not improve accuracy. Only measured RQ (Beta 0.73, p < 0.001) and no-recorded neuromuscular blocking agents (Beta -0.13, p = 0.044) were independently associated with the REEVCO2-REEIC difference. Among the recorded anthropometric, metabolic, nutrition, or clinical variables, only measured RQ was a strong predictor of REEVCO2 inaccuracy (p < 0.001). Cutoffs of RQ = 0.80 predicted 89% of underestimated REEIC (sensitivity 0.99; specificity 0.89) and RQ = 0.82 predicted 56% of overestimated REEIC (sensitivity of 0.99; specificity 0.56). REEVCO2 cannot be recommended as an alternative to REEIC in mechanically ventilated children, regardless of the metabolic, anthropometric, or clinical status at the time of the evaluation.

Dataset Information

Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data.

Publications

Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data.

Similar Datasets

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