Skip to main content
Log in

Metabolic syndrome risk factors and estimated glomerular filtration rate among children and adolescents

  • Original Article
  • Published:
Pediatric Nephrology Aims and scope Submit manuscript

Abstract

The aim of this study was to seek the possible relationship between estimated glomerular filtration rate (e-GFR) and anthropometric indexes, lipids, insulin sensitivity, and metabolic syndrome risk factors among healthy children and adolescents. Sufficient evidence suggest that obesity is related with a novel form of glomerulopathy named obesity-related glomerulopathy (ORG) among adults, children, and adolescents. Glomerular filtration rate was estimated from serum creatinine in 166 healthy children and adolescents [79 males, 87 females; age 10.6 ± 3.3 (3–18) years]. Anthropometric indexes and systolic and diastolic blood pressure were measured. Fasting insulin, glucose, creatinine, uric acid, total cholesterol, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, and triglycerides were estimated. Insulin sensitivity was estimated from known formulas. The presence of certain metabolic syndrome risk factors was checked among the studied population. Boys showed higher e-GFR rates than girls (f = 8.49, p = 0.004). We found a strong positive correlation between e-GFR and body weight (r = 0.415), body mass index (BMI) (r = 0.28), waist circumference (r = 0.419), hip circumference (r = 0.364), birth weight (r = 0.164), systolic blood pressure (SBP) (r = 0.305), and mean arterial pressure (MAP) (r = 0.207). A negative correlation was found between e-GFR and fasting glucose (r = -0.19), total cholesterol (r = -0.27) and LDL-cholesterol (r = -0.26). Clustering of metabolic syndrome risk factors among certain individuals was correlated with higher e-GFR rates (f = 3.606, p = 0.007). The results of this study suggest that gender, anthropometric indexes, and SBP are strong positive determinants of e-GFR among children and adolescents. Waist circumference is the most powerful determinant of e-GFR. Fasting glucose and lipid abnormalities are negative determinants of e-GFR among the studied population. Clustering of metabolic syndrome risk factors is coupled with higher e-GFR rates.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Steinberg J, Daniels SR (2003) Obesity, insulin resistance, diabetes, and cardiovascular risk in children: an American Heart Association Scientific Statement from the Atherosclerosis, Hypertension, and Obesity in the Young Committee (Council on Cardiovascular Disease in the Young) and the Diabetes Committee (Council on Nutrition, Physical Activity, and Metabolism). Circulation 107:1448–1453

    Article  Google Scholar 

  2. Crutz ML, Weigensberg MJ, Huang T, Ball G, Shaibi GQ, Goram MI (2004) The metabolic syndrome in overweight Hispanic youth and the role of insulin sensitivity. J Clin Endocrinol Metab 89:108–113

    Article  Google Scholar 

  3. Kambham N, Markowitz GS, Valeri AM, D’Agati VD (2001) Obesity-related glomerulopathy; an emerging epidemic. Kidney Int 59:1498–1509

    Article  CAS  PubMed  Google Scholar 

  4. Kurella M, Lo JC, Chertow GM (2005) Metabolic syndrome and the risk for chronic kidney disease among nondiabetic adults. J Am Soc Nephrol 16:2134–2140

    Article  PubMed  Google Scholar 

  5. Tuttle KR (2005) Renal manifestations of the metabolic syndrome. Nephrol Dial Transplant 20:861–864

    Article  PubMed  Google Scholar 

  6. Chagnac A, Weinstein T, Korzets A, Ramadan E, Hirsh J, Gafter U (2000) Glomerular hemodynamics in severe obesity. Am J Physiol Renal Physiol 278:F817–F822

    CAS  PubMed  Google Scholar 

  7. Tomaszewski M, Charchar FJ, Maric C, McClure J, Crawford L, Grzeszcak W, Sattar N, Zukowska-Szczechowska E, Dominiczak AF (2007) Glomerular hyperfiltration: A new marker of metabolic risk. Kidney Int 71:816–821

    Article  CAS  PubMed  Google Scholar 

  8. Schwartz GJ, Haycock GB, Edelman CM Jr, Spitzer A (1976) A simple estimate of glomerular filtration rate in children derived from body length and plasma creatinine. Pediatrics 58:259–263

    CAS  PubMed  Google Scholar 

  9. Zappitelli M, Joseph L, Gupta IR, Bell L, Paradis G (2007) Validation of child serum creatinine-based prediction equations for glomerular filtration rate. Pediatr Nephrol 23:272–281

    Article  Google Scholar 

  10. Matthews DR, Hosker JP, Rudensky AS, Naylor BA, Treacher DF, Turner RC (1988) Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma and insulin concentrations in man. Diabetologia 28:412–419

    Article  Google Scholar 

  11. Katz A, Nambi SS, Mather K, Baron AD, Follman DA, Sullivan G, Quon MJ (2000) Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 85:2402–2410

    Article  CAS  PubMed  Google Scholar 

  12. National High Blood Pressure Education Program Working Group on High Blood Pressure in Children and Adolescents (2004) The fourth report on the diagnosis, evaluation and treatment of high blood pressure in children and adolescents. Pediatrics 114:555–576

    Article  Google Scholar 

  13. Ford ES, Chaoyang L (2008) Defining the metabolic syndrome in children and adolescents: will the real definition please stand up? J Pediatr 152:160–164

    Article  PubMed  Google Scholar 

  14. Hannon TS, Janosky J, Arslanian SA (2006) Longitudinal study of physiologic insulin resistance and metabolic changes of puberty. Pediatr Res 60:759–763

    Article  CAS  PubMed  Google Scholar 

  15. Daniels SR, Greer FR, Committee on Nutrition (2008) Lipid screening and cardiovascular health in childhood. Pediatrics 122:198–208

    Article  PubMed  Google Scholar 

  16. Forman JP, Brenner BM (2006) Hypertension and microalbuminuria: the bell tolls for thee. Kidney Int 69:22–28

    Article  CAS  PubMed  Google Scholar 

  17. Wilkin TJ, Murpy MJ (2006) The gender insulin hypothesis: why girls are born lighter than boys, and the implications for insulin resistance. Int J Obes (Lond) 30:1056–1061

    Article  CAS  Google Scholar 

  18. Pinto-Sietsma SJ, Navis G, Janssen WM, de Zeeuw D, Gans RO, de Jong PE (2003) A central body fat distribution is related to renal function impairment, even in lean subjects. Am J Kidney Dis 41:733–741

    Article  PubMed  Google Scholar 

  19. Brenner BM, Lawler EV, Mackenzie HS (1996) The hyperfiltration theory: a paradigm shift in nephrology. Kidney Int 49:1774–1777

    Article  CAS  PubMed  Google Scholar 

  20. Li S, Chen S-C, Shlipak M, Bakris G, McCollough PA, Sowers J, Stevens L, Jurkovitz C, McFarlane S, Norris K, Vassalotti J, Klag MJ, Brown WW, Narva A, Calthoun D, Johnson B, Obialo C, Whaley-Connell A, Becker B, Collins AJ (2008) Low birth weight is associated with chronic kidney disease only in men. Kidney Int 73:637–642

    Article  CAS  PubMed  Google Scholar 

  21. Gielen M, Pinto-Sietsma S-J, Zeegers MP, Loos RJ, Fagard R, de Leeuw PW, Beunen G, Derom C, Vlietinck R (2005) Birth weight and creatinine clearance in young adult twins: influence of genetic, prenatal and maternal factors. J Am Soc Nephrol 16:2471–2476

    Article  PubMed  Google Scholar 

  22. Keijzer-Veen MG, Schrevel M, Finken MJJ, Dekker FW, Nauta J, Hille ETM, Frolich M, van der Heijden BJ (2005) Microalbuminuria and lower glomerular filtration rate at young adult age in subjects born very premature and after intrauterine growth retardation. J Am Soc Nephrol 16:2762–2768

    Article  CAS  PubMed  Google Scholar 

  23. Franco MC, Nishida SK, Sesso R (2008) GFR estimated from cistatin C versus creatinine born small for gestational age. Am J Kidney Dis 51:925–932

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Efstathios Koulouridis.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Koulouridis, E., Georgalidis, K., Kostimpa, I. et al. Metabolic syndrome risk factors and estimated glomerular filtration rate among children and adolescents. Pediatr Nephrol 25, 491–498 (2010). https://doi.org/10.1007/s00467-009-1364-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00467-009-1364-x

Keywords

Navigation