title: Linking definition of childhood and adolescent obesity to current health outcomes.
abstract: OBJECTIVE
  To evaluate the ability of body mass index (BMI) and fat location indices to predict clustering of risk factors for cardiovascular and metabolic disorders in children and adolescents.
  
  
  METHODS
  A total of 2 835 children in the 3(rd) (8.2-11.3 years) and 9(th) (14-17.3 years) grade were randomly selected from Denmark, Estonia and Portugal. BMI, waist-circumference (WC) and waist-to-height ratio (WHt) were evaluated. Children were considered to have clustering of risk factors if >or=3 risk factors were present: high levels of total cholesterol, triglyceride, glucose, insulin, blood pressure and low levels of aerobic fitness and HDL-C. The diagnostic accuracy for detecting children at risk was evaluated through receiver operating characteristics analyses, performed separately for boys and girls in the four age groups: 8.2-9.5; 9.5-11.3; 14.0-15.5 and 15.5-17.3 years. Cut-offs producing equal sensitivity and specificity and minimizing misclassifications were derived. Children were classified as overweight and obese based on BMI cut-offs producing equal sensitivity and specificity and minimizing misclassifications, respectively.
  
  
  RESULTS
  The diagnostic accuracy for identifying children at risk, measured by the area under the curve (AUC), of all anthropometric indices were significantly higher than what would be expected by chance (AUC >0.5). BMI cut-offs for overweight had similar sensitivity (58.8% to 75%) and specificity (60% to 71.2%) values, whereas specificity (94.4% to 99.7%) was markedly higher than sensitivity (9.3% to 52.6%) for obesity cut-offs.
  
  
  CONCLUSIONS
  BMI, WC and WHt can be used to identify children and adolescents aged 8.2-17.3 years with a clustering of cardiovascular risk factors.
authors.affiliation: Research Unit for Dietary Studies, Institute of Preventive Medicine, Copenhagen University Hospital, Copenhagen, Denmark. AAR@ipm.regionh.dk
authors.forename: A R A
authors.initials: AR
authors.lastname: Adegboye
authors.forename: L B
authors.initials: LB
authors.lastname: Andersen
authors.forename: K
authors.initials: K
authors.lastname: Froberg
authors.forename: L B
authors.initials: LB
authors.lastname: Sardinha
authors.forename: B L
authors.initials: BL
authors.lastname: Heitmann
mesh_terms: D000293:Adolescent; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure; D001827:Body Height; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000209:etiology; D002648:Child; D002784:Cholesterol / Q000097:blood; D016000:Cluster Analysis; D003718:Denmark; D004957:Estonia; D005260:Female; D006801:Humans; D007328:Insulin / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000209:etiology; D009765:Obesity / Q000150:complications* / Q000175:diagnosis*; D050177:Overweight / Q000150:complications / Q000175:diagnosis; D010809:Physical Fitness; D011174:Portugal; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors; D012680:Sensitivity and Specificity; D014280:Triglycerides / Q000097:blood; D055105:Waist Circumference
chemical_list: D001786:Blood Glucose; D007328:Insulin; D014280:Triglycerides; D002784:Cholesterol