Simplified equation for resting energy expenditure in a population of elderly chileans compared to indirect calorimetry

The need to accurately calculate the resting energy expenditure (REE) of a patient whose health is compromised and may be further impaired by a deficiency or overfeeding is essential; but in elderly, even if they have an adequate health state, is a risk group where the need to calculate REE as close...

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Published inNFS journal Vol. 13; pp. 23 - 29
Main Authors Segura-Badilla, Orietta, Kammar-García, Ashuin, Vera-López, Obdulia, Aguilar-Alonso, Patricia, Lazcano-Hernández, Martin, Avila-Sosa, Raúl, Navarro-Cruz, Addí Rhode
Format Journal Article
LanguageEnglish
Published Elsevier GmbH 01.11.2018
Elsevier
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Summary:The need to accurately calculate the resting energy expenditure (REE) of a patient whose health is compromised and may be further impaired by a deficiency or overfeeding is essential; but in elderly, even if they have an adequate health state, is a risk group where the need to calculate REE as close as possible is an imperative one. Keeping in mind that this type of imbalance effects on elderly has serious consequences; the aim of this study was to develop an equation according to an elderly people group by multivariate linear regression and compare with REE predicted by the most used equations and by indirect calorimetry (IC). Relationship between REE and body weight was analyzed by multivariate linear regression and derived equations were compared to predicted values using: Harris-Benedict, FAO/WHO 1985, FAO/WHO 2004, Valencia 2008, Lührmann 2002, Schofield 1985 (W) and Schofield 1985 (WH) equations. All the equations used for comparison overestimated energy expenditure between 12 and 15% with respect to REE obtained by IC. Harris-Benedict and Lührmann equations had the highest correlation (r = 0.78) with REE measured, and FAO/WHO 2004 equation with the lowest correlation (r = 0.75). We developed five equations for estimating REE for elderly, healthy Chilean population that are easily applicable in daily practice, which includes the variables sex, age, BMI, fat mass and fat free mass with higher correlation (r = 0.806–0.856).
ISSN:2352-3646
2352-3646
DOI:10.1016/j.nfs.2018.10.002