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Tenan, M.

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Using Statistical Simulation to Visualize and Quantify Day-to-Day Measurement Error in Indirect Calorimetry    Tenan, MS. United States Army Research Laboratory, Aberdeen Proving Ground, MD  Indirect calorimetry and oxygen consumption (VO2) is an accepted tool in exercise science.  A common study design entails VO2 testing before and after a training, nutrition or equipment intervention.  Changes in metabolic cost as small as 3% have been suggested to be “significant”; however, it is unknown if small variations in VO2 are actually able to be detected by indirect calorimetry.  PURPOSE:  Use a custom statistical simulation, specific to the ParvoMedics TrueOne 2400, which probabilistically determines if two day-to-day measurements in VO2 are different.  Specifically, the simulation will determine the probability that a VO2 of 3.66 L/min is different from 3.77 L/min (3% difference).  METHODS:  Day-to-day repeatability data and standard error for the ParvoMedics TrueOne 2400 were extracted across a continuum of volumes from previous validation study (Crouter et al., 2006).  Based on this data, multivariate normal distributions (n=2000) were simulated for the hypothetical VO2 data.  The two multivariate normal distributions for 3.66 L/min and 3.77 L/min were assessed with a fuzzy clustering analysis and the normalized Dunn’s partition coefficient was calculated to determine the probability that the measures are separate.  RESULTS:  Standardized plots of simulated data and assigned clusters (blue lines) are in the figure.  The normalized Dunn’s coefficient was 0.62, indicating a 62% probability that the two measurements are different.  CONCLUSION:  Claims that interventions can cause measurable changes in oxygen consumption need to be re-examined.  The present simulation suggests that the measurement error of indirect calorimetry is too great to make definitive claims about small changes in VO2 in response to an intervention.   

Using Statistical Simulation to Visualize and Quantify Day-to-Day Measurement Error in Indirect Calorimetry

http://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=2837&context=ijesab

Using Statistical Simulation to Visualize and Quantify Day-to-Day Measurement Error in Indirect Calorimetry

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