Pediatric metabolic syndrome and cell blood counts: bivariate Bayesian modeling.

Cell blood counts are components of hematological parameters and indicators of pro-inflammatory states. They are proposed to be associated with metabolic syndrome (MetS). This study aimed to assess the relationship of the white blood cell (WBC) and the red blood cell (RBC) counts with components of MetS in the pediatric age group. The sample consisted of 300 children (152 boys) aged 6-12 years. Hierarchical Bayesian analysis of the bivariate Poisson regression model was used to estimate the effect of various components of MetS according to the cell blood counts. We found that RBC and WBC counts were correlated with the fasting blood glucose, the waist-to-height ratio, serum triglycerides and the blood pressure levels adjusted for age, the body mass index, gender, total cholesterol, low-density lipoprotein cholesterol and the hip circumference. The high-density lipoprotein cholesterol was correlated with the RBC counts based on 95% high posterior density regions for parameters in the Bayesian model. Our findings may serve as confirmatory evidence for the beginning of inflammatory process related to the cardio-metabolic factors from early life.