title: Body mass index and waist circumference independently contribute to the prediction of nonabdominal, abdominal subcutaneous, and visceral fat.
abstract: BACKGROUND
  It is unknown whether the ability of waist circumference (WC) to predict health risk beyond that predicted by body mass index (BMI) alone is explained in part by the ability of WC to identify those with elevated concentrations of total or abdominal fat.
  
  
  OBJECTIVE
  We sought to determine whether BMI and WC independently contribute to the prediction of non-abdominal (total fat - abdominal fat), abdominal subcutaneous, and visceral fat.
  
  
  METHODS
  Fat distribution was measured by magnetic resonance imaging in 341 white men and women. Multiple regression analysis was performed to measure whether the combination of BMI and WC explained a greater variance in non-abdominal, abdominal subcutaneous, and visceral fat than did BMI or WC alone. These fat depots were also compared after a subdivision of the cohort into 3 BMI (normal, overweight, and class I obese) and 3 WC (low, intermediate, and high) categories according to the classification system used to identify associations between BMI, WC, and health risk.
  
  
  RESULTS
  Independent of age and sex, the combination of BMI and WC explained a greater variance in non-abdominal, abdominal subcutaneous, and visceral fat than did either BMI or WC alone (P < 0.05). For non-abdominal and abdominal subcutaneous fat, BMI was the strongest correlate; thus, by adding BMI to WC, the variance accrued was greater than when WC was added to BMI. However, when WC was added to BMI, the added variance explained for visceral fat was greater than when BMI was added to WC. Furthermore, within each of the 3 BMI categories studied, an increase in the WC category was associated with an increase in visceral fat (P < 0.05).
  
  
  CONCLUSIONS
  BMI and WC independently contribute to the prediction of non-abdominal, abdominal subcutaneous, and visceral fat in white men and women. These observations reinforce the importance of using both BMI and WC in clinical practice.
authors.affiliation: School of Physical and Health Education, Queen's University, Kingston, Ontario, Canada.
authors.forename: Ian
authors.initials: I
authors.lastname: Janssen
authors.forename: Steven B
authors.initials: SB
authors.lastname: Heymsfield
authors.forename: David B
authors.initials: DB
authors.lastname: Allison
authors.forename: Donald P
authors.initials: DP
authors.lastname: Kotler
authors.forename: Robert
authors.initials: R
authors.lastname: Ross
mesh_terms: D000005:Abdomen / Q000502:physiology*; D000273:Adipose Tissue / Q000502:physiology*; D000328:Adult; D000368:Aged; D001824:Body Constitution; D015992:Body Mass Index; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012044:Regression Analysis