title: Evaluation of anthropometric indices for metabolic syndrome in Chinese adults aged 40 years and over.
abstract: BACKGROUND
  The prevalence of metabolic syndrome (MetS) is increasing worldwide with a marked impact in cardiovascular disease (CVD) and diabetes risk.
  
  
  OBJECTIVE
  To evaluate the anthropometric indices for metabolic syndrome (MetS) and determine the optimal cut-off values of waist circumference (WC), body mass index (BMI), and waist height ratio (WHtR) for MetS in Chinese adults aged 40 years and over.
  
  
  METHODS
  A sample of Chinese adults aged 40 years and over including 430 men and 638 women was investigated. Blood pressure, weight, height, and WC were measured; HDL-cholesterol (HDL-C), Triglyceride (TG), and plasma glucose were examined. Receiver operating characteristics (ROC) curve analyses were used to evaluate the optimal cut-off point of WC, BMI, and WHtR for MetS.
  
  
  RESULTS
  According to the ROC curve analysis, the optimal cut-off point for WC was found to be 84.0 cm in men and 80.0 cm in women; for BMI, it was 26.0 in men and 25.0 in women; and for WHtR, it was 0.5 in both men and women. WHtR has the highest predictive value for fast plasma glucose in women, while BMI has the better prediction of dyslipidemia in men.
  
  
  CONCLUSIONS
  Anthropometric indices (WC, BMI, and WHtR) are useful screening tools for obesity, MetS, and CVD risk factors. BMI may be a better indicator than the others for screening obesity, dyslipidemia, and other risk components in Chinese men aged 40 years and over, while WHtR may be better for Chinese women, especially among those aged 70 years and over.
authors.affiliation: School of Public Health, Shanghai Jiao Tong University, 227 Chong Qing Nan Road, 200025 Shanghai, China.
authors.forename: Yan-Hong
authors.initials: YH
authors.lastname: He
authors.forename: Ying-Chun
authors.initials: YC
authors.lastname: Chen
authors.forename: Guo-Xin
authors.initials: GX
authors.lastname: Jiang
authors.forename: Hong-Er
authors.initials: HE
authors.lastname: Huang
authors.forename: Rui
authors.initials: R
authors.lastname: Li
authors.forename: Xiao-Ying
authors.initials: XY
authors.lastname: Li
authors.forename: Guang
authors.initials: G
authors.lastname: Ning
authors.forename: Qi
authors.initials: Q
authors.lastname: Cheng
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001786:Blood Glucose / Q000032:analysis; D001827:Body Height; D015992:Body Mass Index; D002681:China / Q000453:epidemiology; D050171:Dyslipidemias / Q000097:blood / Q000175:diagnosis / Q000208:ethnology / Q000473:pathology; D005260:Female; D006801:Humans; D008055:Lipids / Q000097:blood; D008297:Male; D008403:Mass Screening / Q000379:methods*; D024821:Metabolic Syndrome / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology / Q000208:ethnology; D008875:Middle Aged; D056128:Obesity, Abdominal / Q000097:blood / Q000175:diagnosis / Q000208:ethnology / Q000473:pathology; D015995:Prevalence; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012727:Sex Characteristics; D055105:Waist Circumference
chemical_list: D001786:Blood Glucose; D008055:Lipids