title: 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.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.affiliation: INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Jésus
authors.affiliation: INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: Najate
authors.initials: N
authors.lastname: Achamrah
authors.affiliation: INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: Sébastien
authors.initials: S
authors.lastname: Grigioni
authors.affiliation: Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: Jocelyne
authors.initials: J
authors.lastname: Charles
authors.affiliation: Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: Agnès
authors.initials: A
authors.lastname: Rimbert
authors.affiliation: INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: Vanessa
authors.initials: V
authors.lastname: Folope
authors.affiliation: INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: André
authors.initials: A
authors.lastname: Petit
authors.affiliation: INSERM Unit 1073, Rouen, France; Rouen University, Institute for Innovation and Biomedical Research, Rouen, France; Rouen University Hospital, Nutrition Unit, Rouen, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Déchelotte
authors.affiliation: 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.
authors.forename: Moïse
authors.initials: M
authors.lastname: Coëffier
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001481:Basal Metabolism; D001823:Body Composition; D015992:Body Mass Index; D002153:Calorimetry, Indirect / Q000379:methods; D017097:Electric Impedance; D004734:Energy Metabolism; D005260:Female; D006801:Humans; D008297:Male; D044342:Malnutrition / Q000175:diagnosis*; D008875:Middle Aged; D009752:Nutritional Status; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D055815:Young Adult
keywords: Body mass index; Indirect calorimetry; Resting energy expenditure; predictive equation