ArticleObesity research & clinical practice
Predicting resting energy expenditure in young adults.
Article in Obesity research & clinical practice. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Sum of Skinfold-Corrected Girths Correlates with Resting Energy Expenditure: Development of the NRGNutrients · 2024Article
- Development of a new equation and validation of earlier resting energy expenditure predicting equations in adults living in Tehran.Health promotion perspectives · 2024Article
- New predictive equations to estimate resting energy expenditure of non-dialysis dependent chronic kidney disease patients.Journal of nephrology · 2021Article
- Article
- Predicting Equations and Resting Energy Expenditure Changes in Overweight Adults.Zdravstveno varstvo · 2020Article
- Predictive equations for estimating resting energy expenditure in women with overweight and obesity at three postpartum stages.Journal of nutritional science · 2020Article
- Congruent Validity of Resting Energy Expenditure Predictive Equations in Young Adults.Nutrients · 2019Article
- Accuracy and Validity of Resting Energy Expenditure Predictive Equations in Middle-Aged Adults.Nutrients · 2018Article
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Authors and funding
7 authors.
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Abstract
purposeTo develop and validate a REE prediction equation for young adults.
methodsBaseline 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.
resultsThere 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.
conclusionThe 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.
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