International Urology and Nephrology

, Volume 50, Issue 6, pp 1113–1121 | Cite as

Effect of socio-demographic factors on endogenous biomarkers (cystatin C and creatinine) among elderly chronic kidney disease patients: a cross-sectional study

  • Irfanullah Khan
  • Amer Hayat Khan
  • Azreen Syazril Adnan
  • Syed Azhar Syed Sulaiman
  • Azhar Bin Amir Hamzah
  • Nafees Ahmed
  • Amjad Khan
Nephrology - Original Paper



Creatinine is normally used to evaluate kidney function among elderly patients in clinical practice, which has been reported to be affected by socio-demographic factors like BMI and age. Cystatin C a newly introduced biomarker may be more efficient in identifying kidney function in obese and aged CKD patients. The aim of the current study was to assess the effect of BMI on endogenous biomarkers (cystatin C and creatinine) among elderly CKD patients in Malaysia, a first such study in the country.


The current study was conducted at the Hospital University Sains Malaysia, Kelantan. A total of 300 elderly Malay participants ≥ 65 years, with CKD, were taken in study. Demographic data, blood pressure, weight, and height were documented. Serum creatinine was assayed by Chemistry Analyzer Model Architect-C8000 (Jaffe Method), while serum cystatin C was examined by Human cystatin C ELISA kit (Sigma-Aldrich) using Thermo Scientific Varioskan Flash ELISA reader.


The study participants were divided into three groups on the basis of age. There was a statistically significant difference at the p value < 0.05 in serum creatinine level for the three age groups [F (2, 297) = 1.98, p value 0.045]. Patients were divided into four groups on the basis of BMI. The results of one-way ANOVA revealed a statistically significant difference at the p value < 0.05 in the mean serum creatinine level for the four groups [F (3, 396) = 2.99, p value 0.032]. However, no statistically significant differences between mean serum cystatin C levels were observed on the basis of patient’s age and BMI.


Cystatin C is not related to BMI and age among elderly chronic kidney disease patients. The study clearly evaluates the role of serum cystatin C as a good competitor of creatinine among the elderly CKD patients.


Cystatin C Creatinine Estimated GFR 


Author contribution

All authors contributed in a professional way. IK collected the data and wrote the manuscript. AHK and ASA reviewed the manuscript. SASS and ABAH helped in English editing, while NA and AK shared their clinical expertise in the preparation of manuscript.


The research study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interests.

Human and animal rights statement

The study was approved by Human Resource Ethics Committee Jawatankuasa Etika Penyelidikan-Manusia (JEPeM) of HUSM (USM/JEPeM/1311553).


  1. 1.
    Levey AS, Eckardt K-U, Tsukamoto Y, Levin A, Coresh J, Rossert J et al (2005) Definition and classification of chronic kidney disease: a position statement from Kidney Disease: improving Global Outcomes (KDIGO). Kidney Int 67(6):2089–2100CrossRefPubMedGoogle Scholar
  2. 2.
    Zimmet P, Alberti K, Shaw J (2001) Global and societal implications of the diabetes epidemic. Nature 414(6865):782–787CrossRefPubMedGoogle Scholar
  3. 3.
    Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS et al (2016) Global prevalence of chronic kidney disease—a systematic review and meta-analysis. PLoS ONE 11(7):e0158765CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    El Nahas AM, Bello AK (2005) Chronic kidney disease: the global challenge. Lancet 365(9456):331–340CrossRefGoogle Scholar
  5. 5.
    Sterner G, Frennby B, Mansson S, Nyman U, Van Westen D, Almén T (2008) Determining ‘true’ glomerular filtration rate in healthy adults using infusion of inulin and comparing it with values obtained using other clearance techniques or prediction equations. Scand J Urol Nephrol 42(3):278–285CrossRefPubMedGoogle Scholar
  6. 6.
    Price CP, Finney H (2000) Developments in the assessment of glomerular filtration rate. Clin Chim Acta 297(1):55–66CrossRefPubMedGoogle Scholar
  7. 7.
    Hojs R, Bevc S, Ekart R, Gorenjak M, Puklavec L (2006) Serum cystatin C as an endogenous marker of renal function in patients with mild to moderate impairment of kidney function. Nephrol Dial Transpl 21(7):1855–1862CrossRefGoogle Scholar
  8. 8.
    Grubb AO (2001) Cystatin C-properties and use as diagnostic marker. Adv Clin Chem 35:63–99CrossRefGoogle Scholar
  9. 9.
    Grubb A (1991) Diagnostic value of analysis of cystatin C and protein HC in biological fluids. Clin Nephrol 38:S20–S27Google Scholar
  10. 10.
    Rose B (2012) UpToDate—introduction to renal function. Accessed 17 Oct 2017
  11. 11.
    Perrone RD, Madias NE, Levey AS (1992) Serum creatinine as an index of renal function: new insights into old concepts. Clin Chem 38(10):1933–1953PubMedGoogle Scholar
  12. 12.
    Köttgen A, Glazer NL, Dehghan A, Hwang S-J, Katz R, Li M et al (2009) Multiple loci associated with indices of renal function and chronic kidney disease. Nat Genet 41(6):712–717CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Foundation NK (2002) Clinical practice guidelines for chronic kidney disease: evaluation, classification and stratification: National Kidney FoundationGoogle Scholar
  14. 14.
    Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW et al (2003) National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med 139(2):137–147CrossRefPubMedGoogle Scholar
  15. 15.
    Woitas RP, Stoffel-Wagner B, Flommersfeld S, Poege U, Schiedermaier P, Klehr H-U et al (2000) Correlation of serum concentrations of cystatin C and creatinine to inulin clearance in liver cirrhosis. Clin Chem 46(5):712–715PubMedGoogle Scholar
  16. 16.
    Grubb A, Simonsen O, Sturfelt G, Truedsson L, Thysell H (1985) Serum concentration of Cystatin C, Factor D and β2-microglobulin as a measure of glomerular filtration rate. Acta Med Scand 218(5):499–503CrossRefPubMedGoogle Scholar
  17. 17.
    Tangri N, Stevens LA, Schmid CH, Zhang YL, Beck GJ, Greene T et al (2011) Changes in dietary protein intake has no effect on serum cystatin C levels independent of the glomerular filtration rate. Kidney Int 79(4):471–477CrossRefPubMedGoogle Scholar
  18. 18.
    Simonsen O, Grubb A, Thysell H (1985) The blood serum concentration of cystatin C (γ-trace) as a measure of the glomerular filtration rate. Scand J Clin Lab Invest 45(2):97–101CrossRefPubMedGoogle Scholar
  19. 19.
    Zhang P, Zhan J, Xie H, Li L, Liu Z (2010) Evaluation of glomerular filtration rate using cystatin C in diabetic patients analysed by multiple factors including tubular function. J Int Med Res 38(2):473–483CrossRefPubMedGoogle Scholar
  20. 20.
    Aksun SA, Özmen D, Özmen B, Parildar Z, Mutaf I, Turgan N et al (2004) β2-Microglobulin and cystatin C in type 2 diabetes: assessment of diabetic nephropathy. Exp Clin Endocrinol Diabetes 112(04):195–200CrossRefPubMedGoogle Scholar
  21. 21.
    WHO EC (2004) Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet (Lond, Engl) 363(9403):157CrossRefGoogle Scholar
  22. 22.
    Bardi E, Dobos É, Kappelmayer J, Kiss C (2010) Differential effect of corticosteroids on serum cystatin C in thrombocytopenic purpura and leukemia. Pathol Oncol Res 16(3):453–456CrossRefPubMedGoogle Scholar
  23. 23.
    Stevens LA, Coresh J, Feldman HI, Greene T, Lash JP, Nelson RG et al (2007) Evaluation of the modification of diet in renal disease study equation in a large diverse population. J Am Soc Nephrol 18(10):2749–2757CrossRefPubMedGoogle Scholar
  24. 24.
    Taal M, Brenner B (2006) Predicting initiation and progression of chronic kidney disease: developing renal risk scores. Kidney Int 70(10):1694–1705CrossRefPubMedGoogle Scholar
  25. 25.
    Cockcroft DW, Gault MH (1976) Prediction of creatinine clearance from serum creatinine. Nephron 16(1):31–41CrossRefPubMedGoogle Scholar
  26. 26.
    Shemesh O, Golbetz H, KRIss JP, Myers BD (1985) Limitations of creatinine as a filtration marker in glomerulopathic patients. Kidney Int 28(5):830–838CrossRefPubMedGoogle Scholar
  27. 27.
    Swedish Council on Health Technology Assessment (2013) Methods to estimate and measure renal function (Glomerular filtration rate)—a systematic review. ISBN: 978-91-85413-53-9, 2013. Report no. 214Google Scholar
  28. 28.
    Stevens LA, Coresh J, Greene T, Levey AS (2006) Assessing kidney function—measured and estimated glomerular filtration rate. N Engl J Med 354(23):2473–2483CrossRefPubMedGoogle Scholar
  29. 29.
    Rule AD, Bailey KR, Schwartz GL, Khosla S, Lieske JC, Melton LJ (2009) For estimating creatinine clearance measuring muscle mass gives better results than those based on demographics. Kidney Int 75(10):1071–1078CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Geigy scientific tables, 7th edn. Basle, Ciba-Geigy Ltd. 1971: 572,665. 1971Google Scholar
  31. 31.
    Lee J, Auyeung T, Leung J, Kwok T, Leung P, Woo J (2010) The effect of diabetes mellitus on age-associated lean mass loss in 3153 older adults. Diabet Med 27(12):1366–1371CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Pupim LB, Heimburger O, Qureshi AR, Ikizler T, Stenvinkel P (2005) Accelerated lean body mass loss in incident chronic dialysis patients with diabetes mellitus. Kidney Int 68(5):2368–2374CrossRefPubMedGoogle Scholar
  33. 33.
    Chew-Harris JS, Florkowski CM, George PM, Elmslie JL, Endre ZH (2013) The relative effects of fat versus muscle mass on cystatin C and estimates of renal function in healthy young men. Ann Clin Biochem 50(1):39–46CrossRefPubMedGoogle Scholar
  34. 34.
    Camara A, Arn K, Reimer A, Newburgh L (1951) The twenty-four hourly endogenous creatinine clearance as a clinical measure of the functional state of the kidneys. J Lab Clin Med 37(5):743–763PubMedGoogle Scholar
  35. 35.
    Chang A, Greene TH, Wang X, Kendrick C, Kramer H, Wright J et al (2015) The effects of weight change on glomerular filtration rate. Nephrol Dial Transpl 30(11):1870–1877CrossRefGoogle Scholar
  36. 36.
    Ryu S, Chang Y, Woo H-Y, Kim S-G, Kim D-I, Kim WS et al (2008) Changes in body weight predict CKD in healthy men. J Am Soc Nephrol 19(9):1798–1805CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Shankar A, Leng C, Chia KS, Koh D, Tai ES, Saw SM et al (2008) Association between body mass index and chronic kidney disease in men and women: population-based study of Malay adults in Singapore. Nephrol Dial Transpl 23(6):1910–1918CrossRefGoogle Scholar
  38. 38.
    Śledziński T, Proczko-Markuszewska M, Kaska Ł, Stefaniak T, Świerczyński J (2012) Serum cystatin C in relation to fat mass loss after bariatric surgery. Polish J Surg 84(4):202–207Google Scholar
  39. 39.
    al HVe (2012) Validity of serum cystatin C for predicting obesity nephropathy. Interdiscip Bio Central 4(4):1–4Google Scholar
  40. 40.
    Sinkeler SJ, Visser FW, Krikken JA, Stegeman CA, van der Heide JJH, Navis G (2011) Higher body mass index is associated with higher fractional creatinine excretion in healthy subjects. Nephrol Dial Transpl 26(10):3181–3188CrossRefGoogle Scholar
  41. 41.
    Marwyne M, Loo C, Halim A, Norella K, Sulaiman T, Zaleha M (2011) Estimation of glomerular filtration rate using serum cystatin C in overweight and obese subjects. Med J Malaysia 66(4):313–317PubMedGoogle Scholar
  42. 42.
    Baxmann AC, Ahmed MS, Marques NC, Menon VB, Pereira AB, Kirsztajn GM et al (2008) Influence of muscle mass and physical activity on serum and urinary creatinine and serum cystatin C. Clin J Am Soc Nephrol 3(2):348–354CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Hari P, Bagga A, Mahajan P, Lakshmy R (2007) Effect of malnutrition on serum creatinine and cystatin C levels. Pediatr Nephrol 22(10):1757–1761CrossRefPubMedGoogle Scholar
  44. 44.
    Segarra A, de la Torre J, Ramos N, Quiroz A, Garjau M, Torres I et al (2011) Assessing glomerular filtration rate in hospitalized patients: a comparison between CKD-EPI and four cystatin C-based equations. Clin J Am Soc Nephrol 6(10):2411–2420CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    United States Renal data Systems. Accessed 17 Oct 2017
  46. 46.
    Dharnidharka VR, Kwon C, Stevens G (2002) Serum cystatin C is superior to serum creatinine as a marker of kidney function: a meta-analysis. Am J Kidney Dis 40(2):221–226CrossRefPubMedGoogle Scholar
  47. 47.
    Almualm Y, Huri HZ (2015) Chronic kidney disease screening methods and its implication for Malaysia: an in depth review. Glob J Health Sci 7(4):96CrossRefPubMedGoogle Scholar
  48. 48.
    Hooi LS, Ong LM, Ahmad G, Bavanandan S, Ahmad NA, Naidu BM et al (2013) A population-based study measuring the prevalence of chronic kidney disease among adults in West Malaysia. Kidney Int 84(5):1034–1040CrossRefPubMedGoogle Scholar
  49. 49.
    Huri HZ, Lim LP, Lim SK (2015) Glycemic control and antidiabetic drugs in type 2 diabetes mellitus patients with renal complications. Drug Des Dev Ther 9:4355CrossRefGoogle Scholar
  50. 50.
    Begum R, Khan TM, Ming LC (2016) Burden of chronic kidney disease and its risk factors in Malaysia. J Epidemiol Glob Health.
  51. 51.
    National strategic plan for non-communicable disease (2010) Malaysia: Ministry of HealthGoogle Scholar
  52. 52.
    Heymsfield SB, Arteaga C, McManus C, Smith J, Moffitt S (1983) Measurement of muscle mass in humans: validity of the 24-hour urinary creatinine method. Am J Clin Nutr 37(3):478–494CrossRefPubMedGoogle Scholar
  53. 53.
    Preiss DJ, Godber IM, Lamb EJ, Dalton RN, Gunn IR (2007) The influence of a cooked-meat meal on estimated glomerular filtration rate. Ann Clin Biochem 44(1):35–42CrossRefPubMedGoogle Scholar
  54. 54.
    Bellomo R, Kellum J, Ronco C (2004) Defining acute renal failure: physiological principles. Intensive Care Med 30(1):33–37CrossRefPubMedGoogle Scholar
  55. 55.
    Levey AS, de Jong PE, Coresh J, El Nahas M, Astor BC, Matsushita K et al (2011) The definition, classification, and prognosis of chronic kidney disease: a KDIGO Controversies Conference report. Kidney Int 80(1):17–28CrossRefPubMedGoogle Scholar
  56. 56.
    Rule AD, Teo BW (2009) GFR estimation in Japan and China: what accounts for the difference? Am J Kidney Dis 53(6):932CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Irfanullah Khan
    • 1
    • 2
  • Amer Hayat Khan
    • 1
    • 2
  • Azreen Syazril Adnan
    • 2
  • Syed Azhar Syed Sulaiman
    • 1
  • Azhar Bin Amir Hamzah
    • 4
  • Nafees Ahmed
    • 3
  • Amjad Khan
    • 1
    • 5
  1. 1.Discipline of Clinical Pharmacy, School of Pharmaceutical SciencesUniversity Sains MalaysiaPenangMalaysia
  2. 2.Chronic Kidney Disease Resource Centre, School of Medical Sciences, Health CampusUniversity Sains MalaysiaKubang KerianMalaysia
  3. 3.Department of PharmacyUniversity of BalochistanQuettaPakistan
  4. 4.Urology Unit, School of Medical Sciences, Health CampusUniversity Sains MalaysiaKubang KerianMalaysia
  5. 5.Department of PharmacyQuaid-i-Azam UniversityIslamabadPakistan

Personalised recommendations