title: Can body mass index, waist circumference, waist-hip ratio and waist-height ratio predict the presence of multiple metabolic risk factors in Chinese subjects?
abstract: BACKGROUND
  Obesity is associated with metabolic risk factors. Body mass index (BMI), waist circumference, waist-hip ratio (WHR) and waist-height ratio (WHtR) are used to predict the risk of obesity related diseases. However, it has not been examined whether these four indicators can detect the clustering of metabolic risk factors in Chinese subjects.
  
  
  METHODS
  There are 772 Chinese subjects in the present study. Metabolic risk factors including high blood pressure, dyslipidemia, and glucose intolerance were identified according to the criteria from WHO. All statistical analyses were performed separately according to sex by using the SPSS 12.0.
  
  
  RESULTS
  BMI, waist circumference and WHtR values were all significantly associated with blood pressure, glucose, triglyceride and also with the number of metabolic risk factors in both male and female subjects (all of P < 0.05). According to receiver operating characteristic (ROC) analysis, the area under curve values of BMI, waist circumference and WHtR did not differ in male (0.682 vs. 0.661 vs. 0.651) and female (0.702 vs. 0.671 vs. 0.674) subjects, indicating that the three values could be useful in detecting the occurrence of multiple metabolic risk factors. The appropriate cut-off values of BMI, waist circumference and WHtR to predict the presence of multiple metabolic risk factors were 22.85 and 23.30 kg/m² in males and females, respectively. Those of waist circumference and WHtR were 91.3 cm and 87.1 cm, 0.51 and 0.53 in males and females, respectively.
  
  
  CONCLUSIONS
  The BMI, waist circumference and WHtR values can similarly predict the presence of multiple metabolic risk factors in Chinese subjects.
authors.affiliation: Clinical laboratory, Shengjing Hospital of China Medical University, Shenyang 110004, PR China. Liuy@sj-hospital.org
authors.forename: Yong
authors.initials: Y
authors.lastname: Liu
authors.forename: Guanghui
authors.initials: G
authors.lastname: Tong
authors.forename: Weiwei
authors.initials: W
authors.lastname: Tong
authors.forename: Liping
authors.initials: L
authors.lastname: Lu
authors.forename: Xiaosong
authors.initials: X
authors.lastname: Qin
mesh_terms: D000886:Anthropometry; D044466:Asian People; D015992:Body Mass Index; D002681:China / Q000453:epidemiology; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D050171:Dyslipidemias / Q000175:diagnosis; D005260:Female; D018149:Glucose Intolerance / Q000175:diagnosis; D006305:Health Status Indicators; D006801:Humans; D006973:Hypertension / Q000175:diagnosis; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology*; D008875:Middle Aged; D009765:Obesity / Q000378:metabolism*; D011237:Predictive Value of Tests; D012372:ROC Curve; D012307:Risk Factors; D055105:Waist Circumference; D049629:Waist-Hip Ratio