title: Six-compartment body composition model: inter-method comparisons of total body fat measurement.
abstract: OBJECTIVE
  To compare 16 currently used total body fat methods to a six-compartment criterion model based on in vivo neutron activation analysis.
  
  
  METHODS
  Observational, inter-method comparison study.
  
  
  METHODS
  Twenty-three healthy subjects (17 male and 6 female).
  
  
  METHODS
  Total body water (TBW) was measured by tritium dilution; body volume by underwater weighing (UWW); total body fat and bone mineral by dual-energy X-ray absorptiometry (DXA), total body potassium (TBK) by whole-body 40K counting; total body carbon, nitrogen, calcium, phosphorus, sodium and chlorine by in vivo neutron activation analysis; skinfolds/circumferences by anthropometry (Anth); and resistance by single-frequency bioimpedance analysis (BIA).
  
  
  RESULTS
  The average of total body fat mass measurements by the six-compartment neutron activation model was 19.7+/-10.2kg (mean+/-s.d.) and comparable estimates by other methods ranged from 17.4-24.3 kg. Although all 16 methods were highly correlated with the six-compartment criterion model, three groups emerged based on their comparative characteristics (technical error, coefficient of reliability, Bland-Altman analysis) relative to criterion fat estimates, in decreasing order of agreement: 1. multi-compartment model methods of Baumgartner (19.5+/-9.9 kg), Heymsfield (19.6+/-9.9 kg), Selinger (19.7+/-10.2 kg) and Siri-3C (19.6+/-9.9 kg); 2. DXA (20.0+/-10.8 kg), Pace-TBW (18.8+/-10.1 kg), Siri-2C (20.0+/-9.9 kg), and Brozek-UWW (19.4+/-9.2 kg) methods; and 3. Segal-BIA (17.4+/-7.2 kg), Forbes-TBN (21.8+/-10.5 kg), Durnin-Anth (22.1+/-9.5 kg), Forbes-TBK (22.9+/-11.9 kg), and Steinkamp-Anth (24.3+/-9.5 kg) methods.
  
  
  CONCLUSIONS
  Relative to criterion fat estimates, body composition methods can be organized into three groups based on inter-method comparisons including technical error, coefficient of reliability and Bland-Altman analysis. These initial groupings may prove useful in establishing the clinical and research role of the many available fat estimation methods.
authors.affiliation: Obesity Research Center, St Luke's-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York, NY, USA.
authors.forename: Z M
authors.initials: ZM
authors.lastname: Wang
authors.forename: P
authors.initials: P
authors.lastname: Deurenberg
authors.forename: S S
authors.initials: SS
authors.lastname: Guo
authors.forename: A
authors.initials: A
authors.lastname: Pietrobelli
authors.forename: J
authors.initials: J
authors.lastname: Wang
authors.forename: R N
authors.initials: RN
authors.lastname: Pierson
authors.forename: S B
authors.initials: SB
authors.lastname: Heymsfield
mesh_terms: D015502:Absorptiometry, Photon; D000273:Adipose Tissue / Q000033:anatomy & histology*; D000328:Adult; D000368:Aged; D001823:Body Composition; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009501:Neutron Activation Analysis / Q000379:methods; D012044:Regression Analysis; D014915:Whole-Body Counting