Measurement of Agreement of Resting Metabolic Rate between Indirect Calorimetery and Multiple Estimation Models in Adults Using Air Displacement Plethysmography
Year: 2013
Type: article
Study design: Observational Study
Abstract: PURPOSE: Air displacement plethysmography (ADP) is a well validated method for estimating body composition.Similarly, predictive equations derived from regression techniques based on large samples are extensively utilized in estimating resting metabolic rate (RMR).The Cos Med BOD POD System ® , which operates via ADP, utilizes a predictive equation to estimate RMR based on the Nelson (1992) model.However, the agreement of this predictive model with indirect calorimetery (IC) has come into question.The aim of this study is to investigate the agreement of RMR estimation models using ADP measures against a gas exchange IC system in addition to other predictive RMR models.METHODS: Sixty-six apparently healthy subjects (25 men, 41 women) participated in and completed the study.RMR measurements were obtained from the Parvomedics TrueOne 2400 System ® and The Cos Med BOD POD System ® within 10 minutes of one another.IC RMR estimates were tested against nine other validated models using ADP measures via ANOVA techniques with multiple comparisons testing and Bland Altman analysis.RESULTS: The Nelson (1992) model under-predicted RMR compared to IC (P<0.001).The Dore et al. (1982) model was the best predictor of RMR compared to the IC measures (p=0.907).However, by sex, the Dore et al. (1982) model significantly underpredicted RMR for men and over-predicted for women when compared to the IC measure (men: -231±87kcal, p<0.014 and women: 150±43kcal, p <0.001, respectively).iv CONCLUSIONS: The current RMR estimation model using ADP measures underpredicts total caloric needs.The Dore et al. (1982) model more accurately predicted RMR in the entire sample but significantly varied when split by sex.
Author: Brian Miller
Institution: University of Akron
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: green
Funder: University of Akron
OpenAlex ID: W2625259712