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Obes Res Clin Pract. 2016 May-Jun;10(3):304-14. doi: 10.1016/j.orcp.2015.07.002. Epub 2015 Jul 22.

Predicting resting energy expenditure in young adults.

Author information

1
University of Kansas Medical Center, Kansas City, KS, USA. Electronic address: ewillis@ku.edu.
2
Center for Health Outcomes & Prevention Research, Sanford Health, Sioux Falls, SD, USA.
3
University of Kansas Medical Center, Kansas City, KS, USA.

Abstract

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.

KEYWORDS:

Indirect calorimetry; Resting energy expenditure; Weight management; Young adults

PMID:
26210376
PMCID:
PMC5867535
DOI:
10.1016/j.orcp.2015.07.002
[Indexed for MEDLINE]
Free PMC Article

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