Literature DB >> 15809536

Can measured resting energy expenditure be estimated by formulae in daily clinical nutrition practice?

Eduardo E Moreira da Rocha1, Valéria Girard F Alves, Mônica Hissa N Silva, Carlos A Chiesa, Rosana Barcellos V da Fonseca.   

Abstract

PURPOSE OF REVIEW: To recognize the fundamental factors that alter energy expenditure on a daily basis and the impact they have on the measurement of caloric consumption by the human body, through respiratory indirect calorimetry, and thus to try to determine which predictive equation best correlates with total energy expenditure generated from energy measurements. RECENT
FINDINGS: The most important compartment of the body, for its metabolic activity and influence upon resting metabolic rate, is fat-free mass. Other variables affecting energy expenditure are sex, weight, height, age, body surface area, fat mass and ethnicity. Metabolic and activity factors such as the thermic effect of nutrients, facultative thermogenesis, anabolism/growth and physical activity, also contribute, comprising total daily energy expenditure. Following the pioneering work of Harris and Benedict for the estimation of energy expenditure, several authors turned their experimental interest to this area, and various recent predictive formulae were derived. These are useful and easy to apply in daily clinical nutrition practice. However, because of the cited variables upon energy expenditure, the final daily caloric estimates show inherent errors ranging from -23.5 to +22.5% upon measured caloric expenditure. These are particularly remarkable in critically ill patients who are exposed to medical and surgical interventions.
SUMMARY: One has to be careful in choosing, understanding and clinically applying the results from predictive equations, bearing in mind that the original population from which the equation was derived does not always correspond to that currently being evaluated.

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Year:  2005        PMID: 15809536     DOI: 10.1097/01.mco.0000165012.77567.1e

Source DB:  PubMed          Journal:  Curr Opin Clin Nutr Metab Care        ISSN: 1363-1950            Impact factor:   4.294


  13 in total

1.  Common Prediction Equations Overestimate Measured Resting Metabolic Rate in Young Hispanic Women.

Authors:  Shirley Miller; Brandy-Joe Milliron; Kathleen Woolf
Journal:  Top Clin Nutr       Date:  2013-04       Impact factor: 0.508

2.  Malnutrition in patients treated for oral or oropharyngeal cancer--prevalence and relationship with oral symptoms: an explorative study.

Authors:  Harriët Jager-Wittenaar; Pieter U Dijkstra; Arjan Vissink; Rob P van Oort; Bernard F A M van der Laan; Jan L N Roodenburg
Journal:  Support Care Cancer       Date:  2010-09-16       Impact factor: 3.603

3.  [Postoperative assessment of daily energy expenditure. Comparison of two methods].

Authors:  R Dummler; A Zittermann; M Schäfer; M Emmerich
Journal:  Anaesthesist       Date:  2013-01-16       Impact factor: 1.041

4.  Weight-adjusted resting energy expenditure is not constant in critically ill patients.

Authors:  Alexandra Zauner; Bruno Schneeweiss; Nikolaus Kneidinger; Gregor Lindner; Christian Zauner
Journal:  Intensive Care Med       Date:  2006-02-14       Impact factor: 17.440

5.  Comparison of five equations for estimating resting energy expenditure in Chinese young, normal weight healthy adults.

Authors:  Zhi-yong Rao; Xiao-ting Wu; Bin-miao Liang; Mao-yun Wang; Wen Hu
Journal:  Eur J Med Res       Date:  2012-09-01       Impact factor: 2.175

6.  Comparison of predictive equations for resting energy expenditure in overweight and obese adults.

Authors:  Erick Prado de Oliveira; Fábio Lera Orsatti; Okesley Teixeira; Nailza Maestá; Roberto Carlos Burini
Journal:  J Obes       Date:  2011-07-21

7.  Resting energy expenditure prediction in recreational athletes of 18-35 years: confirmation of Cunningham equation and an improved weight-based alternative.

Authors:  Twan ten Haaf; Peter J M Weijs
Journal:  PLoS One       Date:  2014-10-02       Impact factor: 3.240

8.  Estimation of basal metabolic rate in Chinese: are the current prediction equations applicable?

Authors:  Stefan G Camps; Nan Xin Wang; Wei Shuan Kimberly Tan; C Jeyakumar Henry
Journal:  Nutr J       Date:  2016-08-31       Impact factor: 3.271

9.  Evaluation of Factors Associated with Hypermetabolism and Hypometabolism in Critically Ill AKI Patients.

Authors:  Cassiana R de Góes; André Luis Balbi; Daniela Ponce
Journal:  Nutrients       Date:  2018-04-19       Impact factor: 5.717

10.  Predicting Equations and Resting Energy Expenditure Changes in Overweight Adults.

Authors:  Mojca Stubelj; Kaja Teraž; Tamara Poklar Vatovec
Journal:  Zdr Varst       Date:  2019-12-13
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