Endocrinol Metab.  2013 Sep;28(3):207-213. 10.3803/EnM.2013.28.3.207.

Variation in Serum Creatinine Level Is Correlated to Risk of Type 2 Diabetes

Affiliations
  • 1Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea. jsyoon9@ynu.ac.kr
  • 2Department of Internal Medicine, CHA Gumi Medical Center, CHA University, Gumi, Korea. chieun@naver.com

Abstract

BACKGROUND
Skeletal muscle is well established as a major target organ of insulin action, and is associated with the pathogenesis of type 2 diabetes. Therefore, we attempted to determine whether a variation in serum creatinine is related to the development of type 2 diabetes and other risk factors for diabetes.
METHODS
A total of 2,676 nondiabetic subjects with stable and normal renal function (estimated glomerular filtration rate >60 mL/min/1.73 m2) were followed up for approximately 4.5 years. New onset diabetes was defined as fasting plasma glucose (FPG) > or =7.0 mmol/L, glycated hemoglobin (HbA1c) > or =6.5%, or subjects taking antidiabetic agents. Variation of serum creatinine (DeltaCre) was defined as a difference between follow-up and baseline creatinine. In subgroup analysis, body composition was examined by bioelectric impedance analysis method.
RESULTS
A total of 106 subjects were diagnosed with new-onset diabetes during the follow-up period. Baseline serum creatinine was not different between the new-onset diabetes and no diabetes groups. Negative DeltaCre (DeltaCre <0) showed an association with increased risk of type 2 diabetes after adjusting for age, sex, body mass index, systolic blood pressure, FPG, HbA1c, triglyceride, high density lipoprotein cholesterol, and gamma-glutamyl transpeptidase (odds ratio, 1.885; 95% confidence interval, 1.127 to 3.153). Serum creatinine level demonstrated positive correlation with muscle mass and negative correlation with percentage of body fat in body composition analysis.
CONCLUSION
Serum creatinine reflected body muscle mass and the decrease of serum creatinine might be regarded as a risk factor for type 2 diabetes.

Keyword

Diabetes mellitus; Risk factors; Creatinine; Muscle mass

MeSH Terms

Adipose Tissue
Blood Pressure
Body Composition
Body Mass Index
Cholesterol
Cholesterol, HDL
Creatinine
Diabetes Mellitus
Electric Impedance
Fasting
Follow-Up Studies
gamma-Glutamyltransferase
Glomerular Filtration Rate
Glucose
Hemoglobins
Hypoglycemic Agents
Insulin
Lipoproteins
Muscle, Skeletal
Muscles
Plasma
Risk Factors
Cholesterol
Cholesterol, HDL
Creatinine
Glucose
Hemoglobins
Hypoglycemic Agents
Insulin
Lipoproteins
gamma-Glutamyltransferase

Figure

  • Fig. 1 Correlation between serum creatinine level, (A) muscle mass, (B) lean body mass, and (C) percentage of body fat tissue by linear regression analysis with 95% mean prediction interval.


Cited by  1 articles

Brief Review of Articles in 'Endocrinology and Metabolism' in 2013
Won-Young Lee
Endocrinol Metab. 2014;29(3):251-256.    doi: 10.3803/EnM.2014.29.3.251.


Reference

1. DeFronzo RA, Jacot E, Jequier E, Maeder E, Wahren J, Felber JP. The effect of insulin on the disposal of intravenous glucose: results from indirect calorimetry and hepatic and femoral venous catheterization. Diabetes. 1981; 30:1000–1007.
2. DeFronzo RA, Gunnarsson R, Bjorkman O, Olsson M, Wahren J. Effects of insulin on peripheral and splanchnic glucose metabolism in noninsulin-dependent (type II) diabetes mellitus. J Clin Invest. 1985; 76:149–155.
3. DeFronzo RA. Lilly lecture 1987. The triumvirate: beta-cell, muscle, liver: a collusion responsible for NIDDM. Diabetes. 1988; 37:667–687.
4. Harita N, Hayashi T, Sato KK, Nakamura Y, Yoneda T, Endo G, Kambe H. Lower serum creatinine is a new risk factor of type 2 diabetes: the Kansai healthcare study. Diabetes Care. 2009; 32:424–426.
5. Solerte SB, Fioravanti M, Locatelli E, Bonacasa R, Zamboni M, Basso C, Mazzoleni A, Mansi V, Geroutis N, Gazzaruso C. Improvement of blood glucose control and insulin sensitivity during a long-term (60 weeks) randomized study with amino acid dietary supplements in elderly subjects with type 2 diabetes mellitus. Am J Cardiol. 2008; 101(11A):82E–88E.
6. Kaplan LA, Pesce AJ, Kazmierczak SC. Clinical chemistry: theory, analysis, correlation. 4th ed. St. Louis: Mosby;2003.
7. American Diabetes Association. Standards of medical care in diabetes: 2010. Diabetes Care. 2010; 33 Suppl 1:S11–S61.
8. Levey AS, Bosch JP, Lewis JB, 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; 130:461–470.
9. Srikanthan P, Hevener AL, Karlamangla AS. Sarcopenia exacerbates obesity-associated insulin resistance and dysglycemia: findings from the National Health and Nutrition Examination Survey III. PLoS One. 2010; 5:e10805.
10. Dominguez LJ, Barbagallo M. The cardiometabolic syndrome and sarcopenic obesity in older persons. J Cardiometab Syndr. 2007; 2:183–189.
11. Atlantis E, Martin SA, Haren MT, Taylor AW, Wittert GA. Members of the Florey Adelaide Male Ageing Study. Inverse associations between muscle mass, strength, and the metabolic syndrome. Metabolism. 2009; 58:1013–1022.
12. Kim TN, Park MS, Lim KI, Yang SJ, Yoo HJ, Kang HJ, Song W, Seo JA, Kim SG, Kim NH, Baik SH, Choi DS, Choi KM. Skeletal muscle mass to visceral fat area ratio is associated with metabolic syndrome and arterial stiffness: the Korean Sarcopenic Obesity Study (KSOS). Diabetes Res Clin Pract. 2011; 93:285–291.
13. Srikanthan P, Karlamangla AS. Relative muscle mass is inversely associated with insulin resistance and prediabetes: findings from the third National Health and Nutrition Examination Survey. J Clin Endocrinol Metab. 2011; 96:2898–2903.
14. Kim TN, Yang SJ, Yoo HJ, Lim KI, Kang HJ, Song W, Seo JA, Kim SG, Kim NH, Baik SH, Choi DS, Choi KM. Prevalence of sarcopenia and sarcopenic obesity in Korean adults: the Korean sarcopenic obesity study. Int J Obes (Lond). 2009; 33:885–892.
15. Lim S, Kim JH, Yoon JW, Kang SM, Choi SH, Park YJ, Kim KW, Lim JY, Park KS, Jang HC. Sarcopenic obesity: prevalence and association with metabolic syndrome in the Korean Longitudinal Study on Health and Aging (KLoSHA). Diabetes Care. 2010; 33:1652–1654.
16. Haderslev KV, Haderslev PH, Staun M. Accuracy of body composition measurements by dual energy x-ray absorptiometry in underweight patients with chronic intestinal disease and in lean subjects. Dyn Med. 2005; 4:1.
17. Choi KM. Sarcopenia and sarcopenic obesity. Endocrinol Metab. 2013; 28:86–89.
18. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, Martin FC, Michel JP, Rolland Y, Schneider SM, Topinkova E, Vandewoude M, Zamboni M. European Working Group on Sarcopenia in Older People. Sarcopenia: European consensus on definition and diagnosis: report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010; 39:412–423.
19. Patel SS, Molnar MZ, Tayek JA, Ix JH, Noori N, Benner D, Heymsfield S, Kopple JD, Kovesdy CP, Kalantar-Zadeh K. Serum creatinine as a marker of muscle mass in chronic kidney disease: results of a cross-sectional study and review of literature. J Cachexia Sarcopenia Muscle. 2013; 4:19–29.
20. Schutte JE, Longhurst JC, Gaffney FA, Bastian BC, Blomqvist CG. Total plasma creatinine: an accurate measure of total striated muscle mass. J Appl Physiol. 1981; 51:762–766.
21. Donadio C, Halim AB, Caprio F, Grassi G, Khedr B, Mazzantini M. Single- and multi-frequency bioelectrical impedance analyses to analyse body composition in maintenance haemodialysis patients: comparison with dual-energy X-ray absorptiometry. Physiol Meas. 2008; 29:S517–S524.
22. Keshaviah PR, Nolph KD, Moore HL, Prowant B, Emerson PF, Meyer M, Twardowski ZJ, Khanna R, Ponferrada L, Collins A. Lean body mass estimation by creatinine kinetics. J Am Soc Nephrol. 1994; 4:1475–1485.
23. Kalantar-Zadeh K, Streja E, Kovesdy CP, Oreopoulos A, Noori N, Jing J, Nissenson AR, Krishnan M, Kopple JD, Mehrotra R, Anker SD. The obesity paradox and mortality associated with surrogates of body size and muscle mass in patients receiving hemodialysis. Mayo Clin Proc. 2010; 85:991–1001.
24. Oterdoom LH, Gansevoort RT, Schouten JP, de Jong PE, Gans RO, Bakker SJ. Urinary creatinine excretion, an indirect measure of muscle mass, is an independent predictor of cardiovascular disease and mortality in the general population. Atherosclerosis. 2009; 207:534–540.
Full Text Links
  • ENM
Actions
Cited
CITED
export Copy
Close
Share
  • Twitter
  • Facebook
Similar articles
Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr