Metabolic syndrome and risk factors in children: a risk score proposal.

INTRODUCTION/OBJECTIVE: The lack of international consensus on the definition of Metabolic Syndrome (MS) in the pediatric population makes it difficult to estimate its prevalence. In this study, we intend to identify MS prevalence and a cutoff point based on a continuous score in children aged four to seven years. METHODS: A cross-sectional study of 402 children (4-7 years) monitored by the Lactation Support Program (PROLAC). A continuous MS risk score was assessed using Principal Component Analysis (PCA). In order to calculate the score, the following MS risk factors were considered: Waist circumference (WC), High Density Lipoprotein (HDL), Triglycerides (TG), Blood Pressure (BP) and Blood sugar. Using a Receiver Operating Characteristics (ROC) curve, the cutoff point for predicting MS risk based on continuous score was evaluated. RESULTS: A progressive increase in MS scores was observed according to increase in the number of risk factors. This increase was also observed when comparing boys and girls (p < 0.001). In the absence of MS, the median score among the children was -0.0486 (-0.2929-0.2151). For children with MS, the median score was 0.5237 (0.2286-0.7104) (p < 0.001). The best cutoff score for predicting MS in children aged four to five years was >0.09 (100% sensitivity and specificity 72.67%). For children aged six to seven years, this value was >0.14 (100% sensitivity and 64.65% specificity). CONCLUSION: The calculated continuous risk score can predict MS with good accuracy and high sensitivity and reasonable specificity.

"Traditional" and "Healthy" Dietary Patterns Are Associated with Low Cardiometabolic Risk in Brazilian Subjects.

This study aimed at determining the dietary patterns and investigating their association with cardiometabolic risk markers in a brazilian population at risk. This transversal study was carried out with data of 265 patients (n = 123 M/172 W, age 42 ± 16 years) of the Cardiovascular Health Care Program-PROCARDIO-UFV, Brazil-who had their first appointment between 2012 and 2017. A 24-hour recall was applied. The dietary patterns were determined by Principal Component Analysis. Anthropometric, clinical-metabolic, sociodemographic, and lifestyle data were collected through medical record analysis. Five patterns were identified: "Traditional", "Caloric", "Unhealthy", "Healthy," and "Healthy Snacks". In bivariate analysis, the "Healthy" pattern was negatively associated with WC (waist circunference), BMI (body mass index), WHR (waist-to-hip ratio), SBP (systolic blood pressure), fasting glucose, TG/HDL, LDL/HDL, and TG/HDL values and positively to HDL. The "Traditional" pattern was positively associated with adiposity indicators (WC, BMI, and WHR) and negatively associated with body fat, TyG (triglyceride-glucose index), HDL, and LDL (P < 0.05). However, in adjusted models of Poisson regression, individuals with positive factor score (higher adherence) in the "Traditional" and "Healthy" patterns had less occurrence of abdominal obesity (PR 0.85; 95% CI 0.74-0.99/PR 0.88; 95% CI 0.02-0.76), as well as dyslipidemia (PR 0.06; 95% CI 0.02-0.51/PR 0.03; 95% CI 0.01-0.27), diabetes (PR 0.05; 95% CI 0.01-0.45/PR 0.02; 95% CI 0.01-021), and hypertension (PR 0.06; 95% CI 0.02-0.50/PR 0.02; 95% CI 0.01-0.21). A greater adherence to the "Healthy" pattern was associated with lower values to cardiometabolic risk markers and less occurrence of chronic diseases, while the "Traditional" pattern presented contradictory results.