title: Validation of prediction equations for estimating resting energy expenditure in obese Chinese children.
abstract: OBJECTIVE
  (1) To examine the validity of existing prediction equations (PREE) for estimating resting energy expenditure (REE) in obese Chinese children, (2) to correlate the measured REE (MREE) with anthropometric and biochemical parameters and (3) to derive a new PREE for local use.
  
  
  METHODS
  Cross-sectional study.
  
  
  METHODS
  100 obese children (71 boys) were studied.
  
  
  METHODS
  All subjects underwent physical examination and anthropometric measurement. Upper and central body fat distribution was signified by centrality and conicity index respectively, and REE was measured by indirect calorimetry. Fat free mass (FFM) were measured by DEXA scan. Thirteen existing prediction equations for estimating REE were compared with MREE among these obese children. Fasting blood for glucose, lipid profile and insulin were obtained.
  
  
  RESULTS
  The overall, male and female median MREEs were 7.1 mJ/d (IR 6.2-8.4), 7.3 mJ/d (IR 6.3-9.7) and 6.9 mJ/d (IR 5.6-8.1) respectively. No sex difference was noted in MREE (p=0.203). Most of the equations except Schofield equation underestimated REE of our children. By multiple linear regression, MREE was positively correlated with FFM (p<0.0001), conicity index (p<0.001) and centrality index (p=0.001). A new equation for estimating REE for local use was derived as: REE=(17.4*logFFM)+(11.4*conicity index)-(2.4*centrality index)-31.3. The mean difference of new PREE-MREE was -0.011 mJ/d (SD 1.51) with an interclass correlation coefficient of 0.91.
  
  
  CONCLUSIONS
  None of the existing prediction equations were accurate in their estimation of REE, when applied to obese Chinese children. A new prediction equation has been derived for local use.
authors.affiliation: Department of Paediatrics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong SAR. dorothychan@cuhk.edu.hk
authors.forename: Dorothy F Y
authors.initials: DF
authors.lastname: Chan
authors.forename: Albert M
authors.initials: AM
authors.lastname: Li
authors.forename: Michael H M
authors.initials: MH
authors.lastname: Chan
authors.forename: Hung Kwan
authors.initials: HK
authors.lastname: So
authors.forename: Iris H S
authors.initials: IH
authors.lastname: Chan
authors.forename: Jane A T
authors.initials: JA
authors.lastname: Yin
authors.forename: Christopher W K
authors.initials: CW
authors.lastname: Lam
authors.forename: Tai Fai
authors.initials: TF
authors.lastname: Fok
authors.forename: Edmund A S
authors.initials: EA
authors.lastname: Nelson
mesh_terms: D000293:Adolescent; D001786:Blood Glucose / Q000032:analysis; D050218:Body Fat Distribution; D015992:Body Mass Index; D002153:Calorimetry, Indirect; D002648:Child; D003430:Cross-Sectional Studies; D004734:Energy Metabolism; D005260:Female; D006801:Humans; D007328:Insulin / Q000097:blood; D016014:Linear Models; D008055:Lipids / Q000097:blood; D008297:Male; D008433:Mathematics; D009765:Obesity / Q000378:metabolism*; D012146:Rest; D055105:Waist Circumference
chemical_list: D001786:Blood Glucose; D007328:Insulin; D008055:Lipids