title: Rice intake, weight change and risk of the metabolic syndrome development among Chinese adults: the Jiangsu Nutrition Study (JIN).
abstract: OBJECTIVE
  To examine the association between rice intake, staple food patterns (measured by percentage of rice in staple food (PRS)), weight change and the risk of the metabolic syndrome development.
  
  
  METHODS
  We followed 1231 adults, aged 20 and older, from 2002 to 2007. Food intake was assessed using a food frequency questionnaire. Body weight, height, waist circumference, blood pressure and fasting plasma glucose and lipids were measured. The metabolic syndrome was defined according to the International Diabetes Federation definition.
  
  
  RESULTS
  Rice consumption of >=401 g/day was associated with less weight gain (-2.08 kg, 95%CI: -2.75, -1.41, p<0.001), and 42% less risk of hypertension, as compared to rice consumption of <200 g/day (p=0.024). A strong linear association between rice intake and hyperglycemia was found: the odd ratios for incident hyperglycemia across rice intake <200, 201-400, >=401 g/day were: 1, 1.96, 2.50 (95%CI: 1.37, 4.57) (p for trend 0.005). A positive association between rice intake and incident abnormal high-density lipoprotein was observed. There was no association between rice intake and incident high triglycerides. Every 10% increase in PRS was associated with a 0.28 kg less in weight gain, 22% increase in hyperglycemia risk and 9% decrease in hypertension risk. Rice intake and PRS were not associated with the risk of the metabolic syndrome.
  
  
  CONCLUSIONS
  Rice intake and PRS were inversely associated with weight gain, and PRS was inversely associated with hypertension, but positively associated with fasting blood glucose elevation. No association between rice intake and PRS with the metabolic syndrome was found.
authors.affiliation: Department of Nutrition and Foodborne Disease Prevention, Jiangsu Provincial Centre for Disease Control and Prevention, 172 Jiangsu Road, Nanjing 210009, China. zumins@vip.sina.com
authors.forename: Zumin
authors.initials: Z
authors.lastname: Shi
authors.forename: Anne W
authors.initials: AW
authors.lastname: Taylor
authors.forename: Gang
authors.initials: G
authors.lastname: Hu
authors.forename: Tiffany
authors.initials: T
authors.lastname: Gill
authors.forename: Gary A
authors.initials: GA
authors.lastname: Wittert
mesh_terms: D000328:Adult; D000704:Analysis of Variance; D001786:Blood Glucose; D001794:Blood Pressure; D001827:Body Height; D001835:Body Weight; D002681:China / Q000453:epidemiology; D015331:Cohort Studies; D005247:Feeding Behavior; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D006943:Hyperglycemia / Q000097:blood / Q000453:epidemiology; D008055:Lipids / Q000097:blood; D008297:Male; D024821:Metabolic Syndrome / Q000097:blood / Q000453:epidemiology*; D008875:Middle Aged; D009749:Nutrition Surveys / Q000379:methods* / Q000706:statistics & numerical data; D016017:Odds Ratio; D012275:Oryza; D012307:Risk Factors; D011795:Surveys and Questionnaires; D055105:Waist Circumference; D015430:Weight Gain; D055815:Young Adult
chemical_list: D001786:Blood Glucose; D008055:Lipids