Skip to main content

Advertisement

Log in

Prevalence of diabetic nephropathy among Chinese patients with type 2 diabetes mellitus and different categories of their estimated glomerular filtration rate based on the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation in primary care in Hong Kong: a cross-sectional study

  • Research Article
  • Published:
Journal of Diabetes & Metabolic Disorders Aims and scope Submit manuscript

Abstract

Purpose

To evaluate the prevalence of diabetic nephropathy and different categories of estimated glomerular filtration rate (eGFR) as calculated by the CKD-EPI equation among Chinese patients with type 2 diabetes in primary care in Hong Kong. The associated factors of diabetic nephropathy were also analyzed.

Methods

A cross-sectional study was conducted in 35,109 Chinese patients with type 2 diabetes followed up in all General Outpatient Clinics in a Hospital Authority cluster and had undergone comprehensive diabetic complication assessment from April 2013 to March 2016. The GFR was estimated by the CKD-EPI equation. Logistic regression was used to analyze the associated factors of diabetic nephropathy.

Results

The prevalence of diabetic nephropathy (with either or both albuminuria and impaired eGFR), impaired eGFR (with or without albuminuria) and albuminuria (with or without impaired eGFR) was 31.6%, 16.9% and 22.0% respectively. The prevalence of eGFR categories 1, 2, 3, 4 and 5 was 36.0%, 47.1%, 15.7%, 1.1% and 0.1% respectively. The comorbidity with hypertension or presence of other diabetic microvascular or macrovascular complications including diabetic retinopathy, peripheral neuropathy, peripheral vascular disease, history of stroke and history of ischemic heart disease had strong association with diabetic nephropathy. Obesity, smoking, suboptimal control of blood pressure, hemoglobin A1c and non-high density lipoprotein cholesterol were also significantly associated with diabetic nephropathy.

Conclusions

Diabetic nephropathy was common among Chinese patients with type 2 diabetes in primary care in Hong Kong. Early identification and control of the modifiable risk factors are of upmost importance in preventing the complication.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. World Health Organization. Global status report on noncommunicable diseases 2014 [article online]. 2014. Available from: http://www.who.int/nmh/publications/ncd-status-report-2014/en/. Accessed 13 Mar 2016.

  2. Whiting D, Guariguata L, Weil C, et al. IDF diabetes atlas: global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Res Clin Pract. 2011;94(3):311–21.

    Article  Google Scholar 

  3. Wong K, Wang Z. Prevalence of type 2 diabetes mellitus of Chinese populations in mainland China, Hong Kong, and Taiwan. Diabetes Res Clin Pract. 2006;73(2):126–34.

    Article  Google Scholar 

  4. Jha V, Garcia-Garcia G, Iseki K, et al. Chronic kidney disease: global dimension and perspectives. Lancet. 2013;382 North American Edition (9888):260–72.

    Article  Google Scholar 

  5. Saunders WB. KDOQI clinical practice guidelines and clinical practice recommendations for diabetes and chronic kidney disease. Am J Kidney Dis. 2007;49(2 Suppl 2):S12–154.

    Google Scholar 

  6. de Boer I, Rue T, Hall Y, Heagerty PJ, Weiss NS, Himmelfarb J. Temporal trends in the prevalence of diabetic kidney disease in the United States. JAMA. 2011;305(24):2532–9.

    Article  Google Scholar 

  7. Lou Q-L, Ouyang X-J, Liu-Bao G, et al. Chronic kidney disease and associated cardiovascular risk factors in Chinese with type 2 diabetes. Diabetes Metab J. 2012;36(6):433–42.

    Article  Google Scholar 

  8. Ho Y, Chau K, Choy B, et al. Hong Kong renal registry report 2012. Hong Kong J Nephrol. 2013;15(1):28–43.

    Article  Google Scholar 

  9. Matsushita K, van der Velde M, Astor B, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet. 2010;375 North American Edition (9731):2073–81.

    Article  Google Scholar 

  10. Gansevoort R, Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, et al. Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts. Kidney Int. 2011;80(1):93–104.

    Article  CAS  Google Scholar 

  11. Goede P, Lund-Andersen H, Parving H, et al. Effect of a multifactorial intervention on mortality in type 2 diabetes. N Engl J Med. 2008;358(6):580–91.

    Article  Google Scholar 

  12. Zoungas S, de Galan B, Ninomiya T, et al. Combined effects of routine blood pressure lowering and intensive glucose control on macrovascular and microvascular outcomes in patients with type 2 diabetes: new results from the ADVANCE trial. Diabetes Care. 2009;32(11):2068–74.

    Article  CAS  Google Scholar 

  13. Bilous R. Microvascular disease: what does the UKPDS tell us about diabetic nephropathy? Diabet Med. 2008;Suppl 2:25–9.

    Article  Google Scholar 

  14. Johnson C, Levey A, Coresh J, Levin A, Lau J, Eknoyan G. Clinical practice guidelines for chronic kidney disease in adults: part I. definition, disease stages, evaluation, treatment, and risk factors. Am Fam Physician. 2004;70(5):869–985.

    PubMed  Google Scholar 

  15. Levey A, Bosch J, Lewis J, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of diet in renal disease study group. Ann Intern Med. 1999;130(6):461–70.

    Article  CAS  Google Scholar 

  16. Stevens L, Coresh J, Feldman H, et al. Evaluation of the modification of diet in renal disease study equation in a large diverse population. J Am Soc Nephrol. 2007;18(10):2749–57.

    Article  Google Scholar 

  17. National Kidney Foundation. Frequently asked questions about GFR estimates [article online]. 2014. Available from: https://www.kidney.org/sites/default/files/12-10-4004_FAQ-ABE.pdf. Accessed 23 Nov 2018.

  18. Levey A, Stevens L, Schmid C, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–12.

    Article  Google Scholar 

  19. Inker L, Shaffi K, Levey A. Estimating glomerular filtration rate using the chronic kidney disease-epidemiology collaboration creatinine equation: better risk predictions. Circ Heart Fail. 2012;5(3):303–6.

    Article  Google Scholar 

  20. Kilbride H, Stevens P, Eaglestone G, et al. Accuracy of the MDRD (modification of diet in renal disease) study and CKD-EPI (CKD epidemiology collaboration) equations for estimation of GFR in the elderly. Am J Kidney Dis. 2013;61(1):57–66.

    Article  Google Scholar 

  21. Liao Y, Liao W, Liu J, Xu G, Zeng R. Assessment of the CKD-EPI equation to estimate glomerular filtration rate in adults from a Chinese CKD population. J Int Med Res. 2011;39(6):2273–80.

    Article  CAS  Google Scholar 

  22. Matsushita K, Selvin E, Bash L, et al. Risk implications of the new CKD epidemiology collaboration (CKD-EPI) equation compared with the MDRD study equation for estimated GFR: the atherosclerosis risk in communities (ARIC) study. Am J Kidney Dis. 2010;55(4):648–59.

    Article  Google Scholar 

  23. Matsushita K, Mahmoodi B, Woodward M, et al. Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate. JAMA. 2012;307(18):1941–51.

    Article  CAS  Google Scholar 

  24. National Institute for Health and Care Excellence. Chronic kidney disease in adults: assessment and management: clinical guideline 182 [article online]. 2014 [updated Jan 2015]. Available from: https://www.nice.org.uk/guidance/cg182. Accessed 15 Mar 2016.

  25. Retnakaran R, Cull C, Thorne K, et al. Risk factors for renal dysfunction in type 2 diabetes: U.K. prospective diabetes study 74. Diabetes. 2006;55(6):1832–9.

    Article  CAS  Google Scholar 

  26. Ravid M, Brosh D, Ravid-Safran D, Levy Z, Rachmani R. Main risk factors for nephropathy in type 2 diabetes mellitus are plasma cholesterol levels, mean blood pressure, and hyperglycemia. Arch Intern Med. 1998;158(9):998–1004.

    Article  CAS  Google Scholar 

  27. Gross J, de Azevedo M, Silveiro S, et al. Diabetic nephropathy: diagnosis, prevention, and treatment. Diabetes Care. 2005;28(1):164–76.

    Article  Google Scholar 

  28. Unnikrishnan R, Rema M, Pradeepa R, Deepa M, Shanthirani CS, Deepa R, et al. Prevalence and risk factors of diabetic nephropathy in an urban South Indian population: the Chennai urban rural epidemiology study (CURES 45). Diabetes Care. 2007;30(8):2019–24.

    Article  CAS  Google Scholar 

  29. Toth PP, Simko, et al. The impact of serum lipids on risk for microangiopathy in patients with type 2 diabetes mellitus. Cardiovasc Diabetol. 2012;11(1):109.

    Article  CAS  Google Scholar 

  30. Blomster JI, Zoungas S, Chalmers J, Li Q, Chow CK, Woodward M, et al. The relationship between alcohol consumption and vascular complications and mortality in individuals with type 2 diabetes. Diabetes Care. 2014;37(5):1353–9.

    Article  CAS  Google Scholar 

  31. UK Renal Association. Clinical Practice Guidelines for the Detection, Monitoring and Care of Patients with Chronic Kidney Disease. 5th Edition [article online]. 2009–2011. Available from: https://renal.org/detection-monitoring-care-of-patients-with-ckd-5th-edition-2/. Accessed 15 Mar 2016.

  32. Singh N, Armstrong DG, Lipsky BA. Preventing foot ulcers in patients with diabetes. JAMA. 2005;293(2):217–28.

    Article  CAS  Google Scholar 

  33. Rodriguez-Poncelas A, Garre-Olmo J, Franch-Nadal J, et al. Prevalence of chronic kidney disease in patients with type 2 diabetes in Spain: PERCEDIME2 study. BMC Nephrol. 2013;14:46.

    Article  Google Scholar 

  34. Coll-de-Tuero G, Mata-Cases M, Rodriguez-Poncelas A, Pepió JMA, Roura P, Benito B, et al. Chronic kidney disease in the type 2 diabetic patients: prevalence and associated variables in a random sample of 2642 patients of a Mediterranean area. BMC Nehrol. 2012;13:87.

    Article  Google Scholar 

  35. Thomas MC, Weekes AJ, Broadley OJ, et al. The burden of chronic kidney disease in Australian patients with type 2 diabetes (the NEFRON study). Med J Aust. 2006;185:140–4.

    Article  Google Scholar 

  36. O’Keefe J, Bybee K, Lavie C. Alcohol and cardiovascular health: the razor-sharp double-edged sword. J Am Coll Cardiol. 2007;50(11):1009–14.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ka Yee Mok.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mok, K.Y., Chan, P.F., Lai, L.K.P. et al. Prevalence of diabetic nephropathy among Chinese patients with type 2 diabetes mellitus and different categories of their estimated glomerular filtration rate based on the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation in primary care in Hong Kong: a cross-sectional study. J Diabetes Metab Disord 18, 281–288 (2019). https://doi.org/10.1007/s40200-018-00382-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40200-018-00382-y

Keywords

Navigation