Journal of Endocrinological Investigation

, Volume 35, Issue 1, pp 35–41 | Cite as

Glycated hemoglobin, diabetes mellitus, and cardiovascular risk in a cross-sectional study among She Chinese population

  • Y. Lin
  • Y. Xu
  • G. ChenEmail author
  • B. Huang
  • Z. Chen
  • L. Yao
  • Z. Chen
Original Article


Objective: To determine whether glycated hemoglobin (HbA1c) could be used to diagnose Type 2 diabetes mellitus in She Chinese People and to assess the role of HbA1c in the development of cardiovascular disease. Research design and methods: An ethnically representative sample of 687 (277 males and 410 females) adults, 20 yr of age or older participated in the study, and 75-g oral glucose tolerance test was administrated. Based on receiver operating characteristic curves, various cut-off values of HbA1c were used to stratify glucose tolerance. Several indexes were used to assess the cardiovascular risk, including estimated glomerular filtration rate (eGFR), Tpeak-end, Tp-e dispersion, aVL R wave, and QTc. Results: Using World Health Organization as gold standard, the HbA1c value of 6.9% was optimal to diagnose diabetes mellitus with a sensitivity of 35.3% and specificity of 94.0%. And for impaired fasting glucose, impaired glucose tolerance, and impaired glucose regulation, the cut-off points were all 6.1%. Assessed by logistic regression model, HbA1c was an independent risk factor for the decline in eGFR; R wave in lead aVL increased significantly (p<0.05) with the increase of HbA1c values. Other indexes reflecting the cardiovascular risks were not meaningful in our study. Conclusions: HbA1c may be not a preferred method to diagnose Type2 diabetes in She Chinese people. However, more attention should be paid to subjects with HbA1c>6.1%, and their blood glucose should be tightly measured in clinical practice. In addition, we suggest that HbA1c is a predictor of cardiovascular disease.


aVL R wave diabetes mellitus eGFR glycated hemoglobin QTc Tp-e 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Yang W, Lu J, Weng J, et al; China National Diabetes and Metabolic Disorders Study Group. Prevalence of diabetes among men and women in China. N Engl J Med 2010, 362: 1090–101.PubMedCrossRefGoogle Scholar
  2. 2.
    Gu D, Reynolds K, Duan X, et al; InterASIA Collaborative Group. Prevalence of diabetes and impaired fasting glucose in the Chinese adult population: International Collaborative Study of Cardiovascular Disease in Asia (InterASIA). Diabetologia 2003, 46: 1190–8.PubMedCrossRefGoogle Scholar
  3. 3.
    Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabetes Med 1998, 15: 539–53.CrossRefGoogle Scholar
  4. 4.
    Bennett CM, Guo M, Dharmage SC. HbA(1c)asa screening tool for detection of Type 2 diabetes: a systematic review. Diabet Med 2007, 24: 333–43.PubMedCrossRefGoogle Scholar
  5. 5.
    Rohlfing CL, Little RR, Wiedmeyer HM, et al. Use of GHb (HbA1c) in screening for undiagnosed diabetes in the U.S. population. Diabetes Care 2000, 23: 187–91.PubMedCrossRefGoogle Scholar
  6. 6.
    Genuth S, Alberti KG, Bennett P, et al; Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003, 26: 3160–7.PubMedCrossRefGoogle Scholar
  7. 7.
    International Expert Committee. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 2009, 32: 1327–34.CrossRefGoogle Scholar
  8. 8.
    Zhou X, Pang Z, Gao W, et al. Performance of an A1C and fasting capillary blood glucose test for screening newly diagnosed diabetes and pre-diabetes defined by an oral glucose tolerance test in Qingdao, China. Diabetes Care 2009, 33: 545–50.PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    Selvin E, Steffes MW, Zhu H, et al. Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med 2010, 362: 800–11.PubMedCentralPubMedCrossRefGoogle Scholar
  10. 10.
    Smith HW. Diseases of the kidney and urinary tract. In: The Kidney: Structure and Function in Health and Disease. New York: Oxford Univ Pr. 1951, 836–87.Google Scholar
  11. 11.
    Levey AS, Coresh J, Balk E, et al; National Kidney Foundation. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 2003, 139: 137–47.PubMedCrossRefGoogle Scholar
  12. 12.
    Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron 1976, 16: 31–41.PubMedCrossRefGoogle Scholar
  13. 13.
    American Diabetes Association: Standards of medical care for patients with diabetes mellitus. Diabetes Care 2001, 24: S33–43.CrossRefGoogle Scholar
  14. 14.
    Go A, Chertow G, Fan D, McCulloch CE, Hsu CY. Chronic kidney disease and the risk if death, cardiovascular events, and hospitalization. N Eng J Med 2004, 351: 1296–305.CrossRefGoogle Scholar
  15. 15.
    Coresh J, Astor B, Sarnak M. Evidence for increased cardiovascular disease risk in patients with chronic kidney disesase. Curr Opin Nephrol Hypertens 2004, 13: 73–81.PubMedCrossRefGoogle Scholar
  16. 16.
    United States Renal Data system. 2001 Annual data report. Atlas of end-stage renal disease in the United States. Betheada, Md: National Institute of Diabetes and Digestive and Kidney Disease, 2001.Google Scholar
  17. 17.
    Emori T, Antzelevitch C. Cellular basis for complex T waves and arrhythmic activity following combined I(Kr) and I(Ks) block. J Cardiovasc Electrophysiol 2001, 12: 1369–78.PubMedCrossRefGoogle Scholar
  18. 18.
    Watanabe N, Kobayashi Y, Tanno K, et al. Transmural dispersion of repolarization and ventricular tachyarrhythmias. J Electrocadiol 2004, 37: 191–200.CrossRefGoogle Scholar
  19. 19.
    Yan GX, Antzelevitch C. Cellular basis for the normal T wave and the electrocardiographic manifestations of the long-QT syndrome. Circulation 1998, 98: 1928–36.PubMedCrossRefGoogle Scholar
  20. 20.
    de Bruyne MC, Hoes AW, Kors JA, Hofman A, van Bemmel JH, Grobbee DE. Prolonged QT interval predicts cardiac and all-cause mortality in the elderly. The Rotterdam Study. Eur Heart J 1999, 20: 278–84.PubMedCrossRefGoogle Scholar
  21. 21.
    Kannel WB, Gordon T, Offutt D. Left ventricular hypertrophy by electrocardiogram: prevalence, incidence and mortality in the Frmingham study. Ann Intern Med 1969, 71: 89–105.PubMedCrossRefGoogle Scholar
  22. 22.
    De Bacquer D, De Backer G, Kornitzer M, Blackburn H. Prognostic value of ECG findings for total, cardiovascular disease, and coronary heat disease death in men and women. Heart 1998, 80: 570–7.PubMedCentralPubMedGoogle Scholar
  23. 23.
    Budhwani N, Patel S, Dwyer EM Jr. Electrocardiographic diagnosis of left ventricular hypertrophy: the effect of left ventricular wall thickness, size, and mass on the specific criteria for left ventricular hypertrophy. Am Heart J 2005, 149: 709–14.PubMedCrossRefGoogle Scholar
  24. 24.
    Levy D, Garrison RJ, Savage DD, Kannel WB, Castelli WP. Prognostic implications of echocardiographically determined left ventricular mass in the Framingham Heart Study. N Engl J Med 1990, 322: 1561–6.PubMedCrossRefGoogle Scholar
  25. 25.
    Schillaci G, Verdecchia P, Porcellati C, Cuccurullo O, Cosco C, Perticone F. Continuous relation between left ventricular mass and cardiovascular risk in essential hypertension. Hypertension 2000, 35: 580–6.PubMedCrossRefGoogle Scholar
  26. 26.
    Perkiömäki JS, Koistinen MJ, Yli-Mäyry S, Huikuri HV. Dispersion of QT interval in patients with and without susceptibility to ventricular tachyarrhythmias after previous myocardial infarction. J Am Coll Cardiol 1995, 26: 174–9.PubMedCrossRefGoogle Scholar
  27. 27.
    Du Bois D, Du Bois EF. A formula to estimate the approximate surface area if height and weight be known. Arch Intern Med 1916, 17: 863–71.CrossRefGoogle Scholar
  28. 28.
    Levey AS, Coresh J, Balk E, et al; National Kidney Foundation. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 2003, 139: 137–47.PubMedCrossRefGoogle Scholar
  29. 29.
    National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002, 39(Suppl 1): S1–266.Google Scholar
  30. 30.
    Bazett HC. An analysis of time relations of the electrocardiogram. Heart 1920, 7: 353–70.Google Scholar
  31. 31.
    Kilpatrick ES, Bloomgarden ZT, Zimmet PZ. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes: response to the International Expert Committee. Diabetes Care 2009, 32: e159.PubMedCentralPubMedCrossRefGoogle Scholar
  32. 32.
    D.M. Nathan; International Expert Committee. International Expert Committee Report on the Role of the A1C Assay in the Diagnosis of Diabetes: Response to Kilpatrick, Bloomgarden, and Zimmet. Diabetes Care 2009, 32: e160.CrossRefGoogle Scholar
  33. 33.
    Bloomgarden ZT. A1C: recommendations, debates, and questions. Diabetes Care 2009, 32: e141–7.PubMedCrossRefGoogle Scholar
  34. 34.
    Mohan V, Vijayachandrika V, Gokulakrishnan K, et al. A1c cut points to define various glusoce intolerance groups in Asia Indian. Diabetes Care 2010, 33: 515–9.PubMedCentralPubMedCrossRefGoogle Scholar
  35. 35.
    American Diabetes Association. Standards of medical care in diabetes-2009. Diabetes Care 2009, 32(Suppl 1): S12–61.Google Scholar
  36. 36.
    American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2010, 33(Suppl 1): s63–9.Google Scholar
  37. 37.
    Bertoni AG, Krop JS, Anderson GF, Brancati FL. Diabetes-related morbidity and mortality in a national sample of U.S. elders. Diabetes Care 2002, 25: 471–5.PubMedCrossRefGoogle Scholar
  38. 38.
    Shara NM, Resnick HE, Lu L, et al. Decreased GFR estimated by MDRD or Cockcroft-Gault equation predicts incident CVD: the Strong Heart Study. J Nephrol 2009, 22: 373–80.PubMedGoogle Scholar
  39. 39.
    Verdecchia P, Angeli F, Cavallini C, et al. The voltage of R wave in lead aVL improves risk stratification in hypertensive patients without ECG left ventricular hypertrophy. J Hypertens 2009, 27: 1697–704.PubMedCrossRefGoogle Scholar
  40. 40.
    Feasibility of centralized measurements of glycated hemoglobin in the Diabetes Control and Complications Trial: a multicenter study. The DCCT Research Group. Clin Chem 1987, 33: 2267–71.Google Scholar
  41. 41.
    Jeppsson JO, Kobold U, Barr J, et al; International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). Approved IFCC reference method for the measurement of HbA1c in human blood. Clin Chem Lab Med 2002, 40: 78–89.PubMedCrossRefGoogle Scholar
  42. 42.
    Hoelzel W, Weykamp C, Jeppsson JO, et al; IFCC Working Group on HbA1c Standardization. IFCC reference system for measurement of hemoglobin A1c in human blood and the national standardization schemes in the United States, Japan, and Sweden: a method-comparison study. Clin Chem 2004, 50: 166–74.PubMedCrossRefGoogle Scholar

Copyright information

© Italian Society of Endocrinology (SIE) 2012

Authors and Affiliations

  • Y. Lin
    • 1
  • Y. Xu
    • 2
  • G. Chen
    • 2
    • 3
    Email author
  • B. Huang
    • 1
  • Z. Chen
    • 1
  • L. Yao
    • 1
  • Z. Chen
    • 1
  1. 1.Department of EndocrinologyNingde Municipal HospitalNingdeChina
  2. 2.Department of Endocrinology, Fujian Provincial HospitalFujian medical UniversityFuzhou, FujianChina
  3. 3.Washington University School of Medicine in St. LouisSt. LouisUSA

Personalised recommendations