title: Obesity markers and estimated 10-year fatal cardiovascular risk in Switzerland.
abstract: OBJECTIVE
  There is an ongoing debate on which obesity marker better predicts cardiovascular disease (CVD). In this study, the relationships between obesity markers and high (>5%) 10-year risk of fatal CVD were assessed.
  
  
  RESULTS
  A cross-sectional study was conducted including 3047 women and 2689 men aged 35-75 years. Body fat percentage was assessed by tetrapolar bioimpedance. CVD risk was assessed using the SCORE risk function and gender- and age-specific cut points for body fat were derived. The diagnostic accuracy of each obesity marker was evaluated through receiver operating characteristics (ROC) analysis. In men, body fat presented a higher correlation (r=0.31) with 10-year CVD risk than waist/hip ratio (WHR, r=0.22), waist (r=0.22) or BMI (r=0.19); the corresponding values in women were 0.18, 0.15, 0.11 and 0.05, respectively (all p<0.05). In both genders, body fat showed the highest area under the ROC curve (AUC): in men, the AUC (95% confidence interval) were 76.0 (73.8-78.2), 67.3 (64.6-69.9), 65.8 (63.1-68.5) and 60.6 (57.9-63.5) for body fat, WHR, waist and BMI, respectively. In women, the corresponding values were 72.3 (69.2-75.3), 66.6 (63.1-70.2), 64.1 (60.6-67.6) and 58.8 (55.2-62.4). The use of the body fat percentage criterion enabled the capture of three times more subjects with high CVD risk than the BMI criterion, and almost twice as much as the WHR criterion.
  
  
  CONCLUSIONS
  Obesity defined by body fat percentage is more related with 10-year risk of fatal CVD than obesity markers based on WHR, waist or BMI.
authors.affiliation: Cardiomet, CHUV, Lausanne, Switzerland. pedro-manuel.marques-vidal@chuv.ch
authors.forename: P
authors.initials: P
authors.lastname: Marques-Vidal
authors.forename: M
authors.initials: M
authors.lastname: Bochud
authors.forename: V
authors.initials: V
authors.lastname: Mooser
authors.forename: F
authors.initials: F
authors.lastname: Paccaud
authors.forename: G
authors.initials: G
authors.lastname: Waeber
authors.forename: P
authors.initials: P
authors.lastname: Vollenweider
mesh_terms: D050154:Adiposity / Q000502:physiology; D000328:Adult; D000367:Age Factors; D000368:Aged; D000886:Anthropometry; D019540:Area Under Curve; D015415:Biomarkers; D001794:Blood Pressure / Q000502:physiology; D001823:Body Composition / Q000502:physiology; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000401:mortality*; D017097:Electric Impedance; D005260:Female; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008055:Lipids / Q000097:blood; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000097:blood / Q000453:epidemiology*; D012372:ROC Curve; D018570:Risk Assessment; D012737:Sex Factors; D013557:Switzerland / Q000453:epidemiology; D049629:Waist-Hip Ratio
chemical_list: D015415:Biomarkers; D008055:Lipids