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

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.