title: Impaired glucose tolerance and its relationship to ECG-indicated coronary heart disease and risk factors among Chinese. Da Qing IGT and diabetes study.
abstract: OBJECTIVE
  To determine the prevalence of IGT and diabetes and identify the occurrence of CVD and its risk factors.
  
  
  METHODS
  This study was a population-based, cross-sectional study of 110,660 residents, 25-74 yr of age of DaQing, Hei Long Jiang Province, China.
  
  
  RESULTS
  Using 1985 WHO criteria, 577 (5.5/1000) subjects with IGT and 630 (6.0/1000) with newly diagnosed diabetes were identified. In addition, 190 (1.7/1000) with previously known diabetes were identified. Hypertension, obesity, and abnormal albumin excretion were twice as frequent in those with IGT as in 279 men and 240 women of similar age and sex distribution who had normal OGTTs. Plasma cholesterol and TGs were higher, and HDL cholesterol was lower in subjects with IGT than in nondiabetic subjects. Those with IGT had a prevalence of electrocardiographically recognized CHD 9.5-fold greater than the normoglycemic subjects. Subjects with IGT had higher plasma insulin concentrations, but the 1-h insulin-glucose ratio after the 75-g glucose load was lower. In a forward stepwise multiple logistic regression analysis, IGT itself remained an independent factor associated with CHD after adjustment for age, sex, cigarette smoking, plasma cholesterol, BP, and obesity.
  
  
  CONCLUSIONS
  Therefore, in China, IGT may occur with almost as high a frequency as diabetes and is accompanied by an increased frequency of CVD and its risk factors. Estimates from this study indicate that > 12.0% of all ECG-indicated CHD in the Da Qing population occurs in individuals with IGT and NIDDM. The IGT subjects identified in this survey form the cohort for a long-term follow-up and intervention study.
authors.affiliation: Department of Endocrinology, China Japanese Friendship Hospital, Beijing, China.
authors.forename: X R
authors.initials: XR
authors.lastname: Pan
authors.forename: Y H
authors.initials: YH
authors.lastname: Hu
authors.forename: G W
authors.initials: GW
authors.lastname: Li
authors.forename: P A
authors.initials: PA
authors.lastname: Liu
authors.forename: P H
authors.initials: PH
authors.lastname: Bennett
authors.forename: B V
authors.initials: BV
authors.lastname: Howard
mesh_terms: D000328:Adult; D000368:Aged; D000419:Albuminuria; D001055:Apolipoproteins B / Q000097:blood; D001786:Blood Glucose / Q000378:metabolism*; D001794:Blood Pressure; D002681:China / Q000453:epidemiology; D002784:Cholesterol / Q000097:blood; D008076:Cholesterol, HDL / Q000097:blood; D003327:Coronary Disease / Q000175:diagnosis / Q000453:epidemiology* / Q000209:etiology; D048909:Diabetes Complications; D003920:Diabetes Mellitus / Q000453:epidemiology* / Q000503:physiopathology; D004562:Electrocardiography; D005260:Female; D005951:Glucose Tolerance Test; D006801:Humans; D006943:Hyperglycemia / Q000150:complications / Q000453:epidemiology* / Q000503:physiopathology; D007328:Insulin / Q000097:blood; D008297:Male; D008875:Middle Aged; D012016:Reference Values; D012044:Regression Analysis; D012307:Risk Factors; D012907:Smoking; D014280:Triglycerides / Q000097:blood
chemical_list: D001055:Apolipoproteins B; D001786:Blood Glucose; D008076:Cholesterol, HDL; D007328:Insulin; D014280:Triglycerides; D002784:Cholesterol