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Validity of predictive equations for resting energy expenditure according to the body mass index in a population of 1726 patients followed in a Nutrition Unit.
Clin Nutr. 2015 Jun; 34(3):529-35.CN

Abstract

BACKGROUND & AIMS

The resting energy expenditure (REE) predictive formulas are often used in clinical practice to adapt the nutritional intake of patients or to compare to REE measured by indirect calorimetry. We aimed to evaluate which predictive equations was the best alternative to REE measurements according to the BMI.

METHODS

28 REE prediction equations were studied in a population of 1726 patients without acute or chronic high-grade inflammatory diseases followed in a Nutrition Unit for malnutrition, eating disorders or obesity. REE was measured by indirect calorimetry for 30 min after a fasting period of 12 h. Some formulas requiring fat mass and free-fat mass, body composition was measured by bioelectrical impedance analysis. The percentage of accurate prediction (±10%/REE measured) and Pearson r correlations were calculated.

RESULTS

Original Harris & Benedict equation provided 73.0% of accurate predictions in normal BMI group but only 39.3% and 62.4% in patients with BMI < 16 kg m(-2) and BMI ≥ 40 kg m(-2), respectively. In particularly, this equation overestimated the REE in 51.74% of patients with BMI < 16 kg m(-2). Huang equation involving body composition provided the highest percent of accurate prediction, 42.7% and 66.0% in patients with BMI < 16 and >40 kg m(-2), respectively.

CONCLUSION

Usual predictive equations of REE are not suitable for predicting REE in patients with extreme BMI, in particularly in patients with BMI <16 kg m(-2). Indirect Calorimetry may still be recommended for an accurate assessment of REE in this population until the development of an adapted predictive equation.

Authors+Show Affiliations

INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.Rouen University Hospital, Nutrition Unit, Rouen, France.Rouen University Hospital, Nutrition Unit, Rouen, France.INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France. Electronic address: moise.coeffier@univ-rouen.fr.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't
Validation Study

Language

eng

PubMed ID

25016971

Citation

Jésus, Pierre, et al. "Validity of Predictive Equations for Resting Energy Expenditure According to the Body Mass Index in a Population of 1726 Patients Followed in a Nutrition Unit." Clinical Nutrition (Edinburgh, Scotland), vol. 34, no. 3, 2015, pp. 529-35.
Jésus P, Achamrah N, Grigioni S, et al. Validity of predictive equations for resting energy expenditure according to the body mass index in a population of 1726 patients followed in a Nutrition Unit. Clin Nutr. 2015;34(3):529-35.
Jésus, P., Achamrah, N., Grigioni, S., Charles, J., Rimbert, A., Folope, V., Petit, A., Déchelotte, P., & Coëffier, M. (2015). Validity of predictive equations for resting energy expenditure according to the body mass index in a population of 1726 patients followed in a Nutrition Unit. Clinical Nutrition (Edinburgh, Scotland), 34(3), 529-35. https://doi.org/10.1016/j.clnu.2014.06.009
Jésus P, et al. Validity of Predictive Equations for Resting Energy Expenditure According to the Body Mass Index in a Population of 1726 Patients Followed in a Nutrition Unit. Clin Nutr. 2015;34(3):529-35. PubMed PMID: 25016971.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Validity of predictive equations for resting energy expenditure according to the body mass index in a population of 1726 patients followed in a Nutrition Unit. AU - Jésus,Pierre, AU - Achamrah,Najate, AU - Grigioni,Sébastien, AU - Charles,Jocelyne, AU - Rimbert,Agnès, AU - Folope,Vanessa, AU - Petit,André, AU - Déchelotte,Pierre, AU - Coëffier,Moïse, Y1 - 2014/06/28/ PY - 2014/02/14/received PY - 2014/05/26/revised PY - 2014/06/11/accepted PY - 2014/7/15/entrez PY - 2014/7/16/pubmed PY - 2016/2/24/medline KW - Body mass index KW - Indirect calorimetry KW - Resting energy expenditure KW - predictive equation SP - 529 EP - 35 JF - Clinical nutrition (Edinburgh, Scotland) JO - Clin Nutr VL - 34 IS - 3 N2 - BACKGROUND & AIMS: The resting energy expenditure (REE) predictive formulas are often used in clinical practice to adapt the nutritional intake of patients or to compare to REE measured by indirect calorimetry. We aimed to evaluate which predictive equations was the best alternative to REE measurements according to the BMI. METHODS: 28 REE prediction equations were studied in a population of 1726 patients without acute or chronic high-grade inflammatory diseases followed in a Nutrition Unit for malnutrition, eating disorders or obesity. REE was measured by indirect calorimetry for 30 min after a fasting period of 12 h. Some formulas requiring fat mass and free-fat mass, body composition was measured by bioelectrical impedance analysis. The percentage of accurate prediction (±10%/REE measured) and Pearson r correlations were calculated. RESULTS: Original Harris & Benedict equation provided 73.0% of accurate predictions in normal BMI group but only 39.3% and 62.4% in patients with BMI < 16 kg m(-2) and BMI ≥ 40 kg m(-2), respectively. In particularly, this equation overestimated the REE in 51.74% of patients with BMI < 16 kg m(-2). Huang equation involving body composition provided the highest percent of accurate prediction, 42.7% and 66.0% in patients with BMI < 16 and >40 kg m(-2), respectively. CONCLUSION: Usual predictive equations of REE are not suitable for predicting REE in patients with extreme BMI, in particularly in patients with BMI <16 kg m(-2). Indirect Calorimetry may still be recommended for an accurate assessment of REE in this population until the development of an adapted predictive equation. SN - 1532-1983 UR - https://www.unboundmedicine.com/medline/citation/25016971/Validity_of_predictive_equations_for_resting_energy_expenditure_according_to_the_body_mass_index_in_a_population_of_1726_patients_followed_in_a_Nutrition_Unit_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0261-5614(14)00173-3 DB - PRIME DP - Unbound Medicine ER -