title: Obesity related metabolic abnormalities: distribution and geographic differences among middle-aged and older Chinese populations.
abstract: OBJECTIVE
  To investigate geographic differences in obesity related metabolic abnormalities in middle-aged and older Chinese people with different levels of adiposity.
  
  
  METHODS
  Data from 3289 individuals aged 50-70 years who participated in a cross-sectional survey in 2005 (1641 from northern [Beijing] and 1648 from southern [Shanghai] China) were analyzed. Overweight or obesity and abdominal obesity were classified as body mass index > or =24 kg/m2 and waist circumference > or =90 cm for men and > or =80 cm for women. Metabolic abnormalities (metabolic syndrome, dyslipidemia, hypertension and diabetes) were defined using the NCEP/ATPIII criteria.
  
  
  RESULTS
  The overall prevalence of overweight and obesity was 53.4%, and the prevalence of abdominal obesity was 48.0%, respectively. The prevalence of the metabolic abnormalities was significantly higher among obese individuals than their normal weight counterparts. The association between obesity and the higher prevalence of the metabolic abnormalities was more pronounced among people who were overweight or obese in the north, especially for those living in rural areas.
  
  
  CONCLUSIONS
  The prevalence of obesity and associated metabolic abnormalities varies substantially among Chinese people in different geographic region. Individuals who were overweight or obese living in rural areas in the north contribute importantly to the north-south differences in obesity-related metabolic abnormalities among Chinese populations.
authors.affiliation: Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Graduate School of the Chinese Academy of Sciences, 294 Tai-yuan Rd, Shanghai, 200031, China.
authors.forename: Zhijie
authors.initials: Z
authors.lastname: Yu
authors.forename: Xu
authors.initials: X
authors.lastname: Lin
authors.forename: Jere D
authors.initials: JD
authors.lastname: Haas
authors.forename: Oscar H
authors.initials: OH
authors.lastname: Franco
authors.forename: Kirsten L
authors.initials: KL
authors.lastname: Rennie
authors.forename: Huaixing
authors.initials: H
authors.lastname: Li
authors.forename: He
authors.initials: H
authors.lastname: Xu
authors.forename: Xinghuo
authors.initials: X
authors.lastname: Pang
authors.forename: Hong
authors.initials: H
authors.lastname: Liu
authors.forename: Zheng
authors.initials: Z
authors.lastname: Zhang
authors.forename: Shurong
authors.initials: S
authors.lastname: Zou
authors.forename: Shufang
authors.initials: S
authors.lastname: Jiao
mesh_terms: D050153:Abdominal Fat / Q000378:metabolism; D000367:Age Factors; D000368:Aged; D000428:Alcohol Drinking / Q000453:epidemiology; D002681:China / Q000453:epidemiology; D003430:Cross-Sectional Studies; D005260:Female; D005843:Geography; D015438:Health Behavior; D006306:Health Surveys; D006801:Humans; D008297:Male; D024821:Metabolic Syndrome / Q000453:epidemiology* / Q000378:metabolism*; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology* / Q000378:metabolism*; D015995:Prevalence; D012044:Regression Analysis; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology