New equations to estimate resting energy expenditure in obese adults from body composition
- 123 Downloads
The aims of this study were: to develop new equations for predicting resting energy expenditure (REE) in obese Italian subjects according to body composition parameters; to compare them with predicted values estimated by other REE prediction equations; and to cross-validate our equations using a validation set cohort.
Four hundred patients were enrolled and divided into three groups. Besides anthropometry and REE (indirect calorimetry), total body fat and lean were evaluated by dual X-ray absorptiometry, and fat mass and fat-free mass by bioelectrical impedance analysis.
The subjects eligible to participate were 330. Group 1 (n = 174) was used to develop (R2 = 0.79) and (R2 = 0.77). Group 2 (n = 115) was used to generate (R2 = 0.85) and (R2 = 0.81). Group 3 (n = 41) was used to cross-validate the equations.
Equations 1 and 3 are reliable to measure REE from calorimetry and better than other equations that use anthropometric variables as predictors of REE. Further analysis in different populations is required before it can be applied in clinical practice.
KeywordsPrediction equation Resting energy expenditure Body composition Obese Adults
We are beholden to all the subjects who volunteered in the study. We also thank the entire medical team from the Section of Clinical Nutrition and Nutrigenomic, University of Rome Tor Vergata, Rome. This study was supported by grants from Ministry of Agriculture, Food and Forestry (D.M.; 2017188).
De Lorenzo A conceived, designed the experiments and drafted the manuscript; Di Renzo L, Morini P, Romano L contributed to the interpretation of the data and drafted the manuscript; Romano L collected the data and performed the experiments; de Miranda RC analyzed the data; Colica C had primary responsibility for the final content. All the authors read and approved the final manuscript.
Compliance with ethical standards
Conflict of interest
All authors declare no conflict of interest.
All procedures performed were in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.
Informed consent was obtained from all participants included in this study.
- 1.Deed G, Barlow J, Kawol D, Kilov G, Sharma A, Hwa LY (2015) Diet and diabetes. Aust Fam Phys 44(5):192–196Google Scholar
- 4.Foster GD, McGuckin BG (2001) Estimating resting energy expenditure in obesity. Obes Res 5:367S–372S (discussion 373S–374S) Google Scholar
- 8.Fullmer S, Benson-Davies S, Earthman CP, Frankenfield DC, Gradwell E, Lee PS et al (2015) Evidence analysis library review of best practices for performing indirect calorimetry in healthy and non-critically ill individuals. J Acad Nutr Diet 115(9):1417–1446. doi:10.1016/j.jand.2015.04.003 CrossRefPubMedGoogle Scholar
- 28.Di Renzo L, Carbonelli MG, Bianchi A, Domino E, Migliore MR, Rillo G et al (2012) Impact of the −174 G > C IL-6 polymorphism on bioelectrical parameters in obese subjects after laparoscopic adjustable gastric banding. J Obes 2012:208953. doi:10.1155/2012/208953 CrossRefPubMedPubMedCentralGoogle Scholar
- 29.Altman DG (1996) Relation between two continuous variables. Practical statistics for medical research. Chapman & Hall, London, pp 277–324Google Scholar