title: Optimal cut-off levels of obesity indices by different definitions of metabolic syndrome in a southeast rural Chinese population.
abstract: OBJECTIVE
  The aim of the present study was to compare the cut-off values and prediction effect of different obesity indices by different definitions of metabolic syndrome (MetS) in Zhejiang Province of China.
  
  
  METHODS
  We carried out a cross-sectional survey of 10,100 individuals (age 40 years and older) in Jiashan, Zhejiang Province. Receiver operating characteristic analysis was used to examine discrimination and find optimal cut off values of waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) to predict two or more non-adipose components of MetS by The National Cholesterol Education Program Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III) definition modified by the Asia-Pacific region criteria, International Diabetes Federation definition for the Chinese population and Chinese Diabetes Society definitions of MetS.
  
  
  RESULTS
  The age-standardized prevalence of MetS was 23.78% vs 28.76% vs 19.37% by The National Cholesterol Education Program Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III), International Diabetes Federation and Chinese Diabetes Society definitions, respectively. Cut-off values of BMI were approximately 24 kg/m(2) both in men and women by three definitions; the average cut-off values of WC, WHR and WHtR were 83 cm in men vs 81 cm in women, 0.89 in men vs 0.86 in women and 0.50 in men vs 0.51 in women, respectively. The area under receiver operating characteristic curve of BMI was larger than WC both in men and women (P < 0.05); in women, the area under receiver operating characteristic curve of WHtR was larger than WC, and WHR was smaller.
  
  
  CONCLUSIONS
  MetS is prevalent in Zhejiang Province of China, especially in the female population. BMI and WHtR might be more useful than WC and WHR for predicting two or more non-adipose components of MetS.
authors.affiliation: Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Pan
authors.affiliation: Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
authors.forename: Meng
authors.initials: M
authors.lastname: Wang
authors.affiliation: Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
authors.forename: Zhen
authors.initials: Z
authors.lastname: Ye
authors.affiliation: Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
authors.forename: Min
authors.initials: M
authors.lastname: Yu
authors.affiliation: Jiashan Center for Disease Control and Prevention, Jiashan, China.
authors.forename: Yuhua
authors.initials: Y
authors.lastname: Shen
authors.affiliation: Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
authors.forename: Qinfang
authors.initials: Q
authors.lastname: He
authors.affiliation: Jiashan Center for Disease Control and Prevention, Jiashan, China.
authors.forename: Naxin
authors.initials: N
authors.lastname: Cao
authors.affiliation: Department of Endocrinology and Metabolism, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China.
authors.forename: Guang
authors.initials: G
authors.lastname: Ning
authors.affiliation: Department of Endocrinology and Metabolism, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, China.
authors.forename: Yufang
authors.initials: Y
authors.lastname: Bi
authors.affiliation: Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
authors.forename: Weiwei
authors.initials: W
authors.lastname: Gong
authors.affiliation: Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
authors.forename: Ruying
authors.initials: R
authors.lastname: Hu
mesh_terms: D044466:Asian People; D015992:Body Mass Index; D049628:Body Size; D002681:China / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis* / Q000453:epidemiology; D008875:Middle Aged; D009765:Obesity / Q000175:diagnosis* / Q000453:epidemiology; D012372:ROC Curve; D012016:Reference Values; D012424:Rural Population
keywords: Body mass index; Metabolic syndrome; Waist-to-hip ratio