Predicting resting energy expenditure in young adults. Issue 3 (May 2016)

• Record Type: Journal Article
• Authors: Willis, Erik A.; Herrmann, Stephen D.; Ptomey, Lauren T.; Honas, Jeffery J.; Bessmer, Christopher T.; Donnelly, Joseph E.; Washburn, Richard A.
• Is Part Of: Obesity research & clinical practice. Volume 10:Issue 3(2016:May/Jun.)
• Page Start: 304
• Page End: 314
• Publication Date: 2016-05
• Subjects: Resting energy expenditure -- Indirect calorimetry -- Weight management -- Young adults; Obesity -- Research -- Periodicals; Obesity -- Treatment -- Periodicals; Obesity -- Periodicals; Obésité -- Recherche -- Périodiques; Obésité -- Traitement -- Périodiques; Obesity -- Research; Obesity -- Treatment; Electronic journals; Periodicals; 616.398
• DOI: 10.1016/j.orcp.2015.07.002
• Languages: English
• ISSNs: 1871-403X

Abstract

Summary: Purpose: To develop and validate a REE prediction equation for young adults. Methods: Baseline data from two studies were pooled ( N = 318; women = 52%) and randomly divided into development ( n = 159) and validation samples ( n = 159). REE was measured by indirect calorimetry. Stepwise regression was used to develop an equation to predict REE (University of Kansas (KU) equation). The KU equation and 5 additional REE prediction equations used in clinical practice (Mifflin–St. Jeor, Harris–Benedict, Owens, Frankenfield (2 equations)) were evaluated in the validation sample. Results: There were no significant differences between predicted and measured REE using the KU equation for either men or women. The Mifflin–St. Jeor equation showed a non-significant mean bias in men; however, mean bias was statistically significant in women. The Harris–Benedict equation significantly over-predicted REE in both men and women. The Owens equation showed a significant mean bias in both men and women. Frankenfield equations #1 and #2 both significantly over-predicted REE in non-obese men and women. We found no significant differences between measured REE and REE predicted by the Frankenfield #2 equations in obese men and women. Conclusion: The KU equation, which uses easily assessed characteristics (age, sex, weight) may offer better estimates of REE in young adults compared with the 5 other equations. The KU equation demonstrated adequate prediction accuracy, with approximately equal rates of over and under-prediction. However, enthusiasm for recommending any REE prediction equations evaluated for use in clinical weight management is damped by the highly variable individual prediction error evident with all these equations.