title: Predictive equations for basal metabolic rate in Chinese adults: a cross-validation study.
abstract: OBJECTIVE
  To develop predictive equations for basal metabolic rate (BMR) in healthy Chinese adults and to evaluate factors that may influence BMR.
  
  
  METHODS
  Measuring the BMR of Chinese adults by indirect calorimetry. Selected subjects were randomly assigned to a validation sample and a cross-validation sample. The validation sample was used to develop predictive equations that were cross-validated using the other sample.
  
  
  METHODS
  Two hundred twenty-three healthy Chinese adults (102 men and 121 women) participated in the study. Their ages ranged from 20 to 78 years old (mean = 43.8 +/- 14.3 years).
  
  
  METHODS
  BMR was measured by indirect calorimetry. Body composition was assessed by skinfold fat thicknesses, bioelectrical impedance analysis, and urinary creatinine excretion.
  
  
  METHODS
  Student's t test, Pearson correlation coefficients, linear regression analyses, and the best subset were used for statistical analyses.
  
  
  RESULTS
  The better-fitting equation for predicting BMR in Chinese adults is BMR = 13.88 x weight (kg) + 4.16 x height (cm) - 3.43 x age (years) - 112.40 x sex (men = 0; women = 1) +54.34. Men had higher BMR values than women because men had greater fat-free mass, body cell mass, and muscle mass. BMR correlated best with body composition, which correlated highly with anthropometric measurements. Therefore, accurate determination of body weight and body height are beneficial in predicting a person's BMR. All of the currently available predictive equations overestimated BMR (P = .0001) for healthy Chinese adults. The equations developed in this study predict BMR more accurately for Chinese adults.
  
  
  CONCLUSIONS
  The equations developed in this study are recommended for clinical use in healthy Chinese adults who are within normal limits for body weight.
authors.affiliation: Department of Nutrition of Taiwan University Hospital in Taipei, Republic of China.
authors.forename: H Y
authors.initials: HY
authors.lastname: Liu
authors.forename: Y F
authors.initials: YF
authors.lastname: Lu
authors.forename: W J
authors.initials: WJ
authors.lastname: Chen
mesh_terms: D000328:Adult; D000368:Aged; D044466:Asian People; D001481:Basal Metabolism; D001823:Body Composition / Q000502:physiology*; D002153:Calorimetry, Indirect; D002681:China; D003404:Creatinine / Q000652:urine; D017097:Electric Impedance; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012044:Regression Analysis; D015203:Reproducibility of Results; D012727:Sex Characteristics; D012885:Skinfold Thickness
chemical_list: D003404:Creatinine