Comparison of Prediction Equations for Resting Energy Expenditure vs the KORR ReeVue Indirect Calorimeter in Obesity
Issue Date
2018-05-31Author
Petersen, Carsen
Publisher
University of Kansas
Format
67 pages
Type
Thesis
Degree Level
M.S.
Discipline
Dietetics & Nutrition
Rights
Copyright held by the author.
Metadata
Show full item recordAbstract
An increasing number of institutions and community settings are assessing resting energy expenditure (REE) to tailor weight loss interventions. Resting energy expenditure can be assessed using an indirect calorimeter or from prediction equations. Portable indirect calorimeters are not widely available and have associated equipment and operating costs, whereas assessment of REE using prediction equations is cost-effective and simple to use. Data are lacking to assess the agreement for the measurement of REE between portable indirect calorimeters and prediction equations to help inform institutions and community settings on the best option to assess REE in an obese population. The purpose of this study was to compare the seven most common prediction equations for estimation of resting energy expenditure (REE) – Mifflin St. Jeor (MSJ), Harris Benedict (HB), Owen, American College of Chest Physicians (ACCP) 21, ACCP 25, World Health Organization/Food and Agriculture Organization/United Nations University (WHO/FAO/UNU; using weight only), and WHO/FAO/UNU (using both weight and height) – to measured REE (MREE) using the KORR ReeVue indirect calorimeter in free-living obese adults. Statistical analyses were completed to understand if age, sex, race, or obesity grade influenced the agreement between the estimated REE for the prediction equations and MREE for the KORR ReeVue indirect calorimeter. The study found the prediction equations of MSJ, HB, WHO/FAO/UNU (using weight only), and WHO/FAO/UNU (using both weight and height) accurately estimated REE in obese adults within +/-150 kcal/day of MREE. Of these four equations, Harris Benedict had the least amount of contributing variables that influenced the estimation of MREE (only race contributed) and Mifflin St. Jeor had the second least amount (race and sex contributed) of contributing variables. Therefore, these prediction equations would be appropriate to use in clinical practice if an institution did not have access to an indirect calorimeter. The prediction equations of Owen and American College of Chest Physicians; however, under- and overestimated MREE, respectively, and should be avoided in clinical practice.
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