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

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.