Ortega-Cortes R, Trujillo X, Hurtado López EF, López Beltrán AL, Colunga Rodríguez C, Barrera-de Leon JC, Tlacuilo-Parra A. Models Predictive of Metabolic Syndrome Components in Obese Pediatric Patients.
Arch Med Res 2016;
47:40-8. [PMID:
26820798 DOI:
10.1016/j.arcmed.2016.01.003]
[Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2015] [Accepted: 01/14/2016] [Indexed: 12/22/2022]
Abstract
BACKGROUND AND AIMS
Components of metabolic syndrome (MetS) are complications caused by abdominal obesity and insulin resistance (IR). Diagnosis of MetS by clinical indicators could help to identify patients at risk of cardiovascular disease and type 2 diabetes. We undertook this study to propose predictive indicators of MetS in obese children and adolescents.
METHODS
A cross-sectional study was carried out. After obtaining informed consent and the registration of the study with an institutional research committee, 172 obese patients from an Obesity Clinic, aged 6-15 years, were included. Variables included were waist circumference (WC), glucose, high-density lipoprotein (HDL), triglycerides (TGL), blood pressure, insulin resistance (by homeostatic model assessment HOMA-index), acanthosis nigricans (AN), uric acid, serum glutamic oxaloacetic transaminase (GOT) and alanine transaminase, and hepatic sonogram. International standards for age and sex variables were used. Multivariate analysis was applied.
RESULTS
Variables predicted components of MetS in children: HOMA-IR (insulin resistance by HOMA index) was increased by 2.4 in hepatic steatosis, by 0.6 for each unit of SUA (serum uric acid), and by 0.009 for every mg/dL of triglycerides. In adolescents, every cm of waist circumference increased systolic blood pressure by 0.6 mmHg, and each unit of SUA increased it by 2.9 mmHg.
CONCLUSIONS
Serum uric acid and waist circumference are useful and accessible variables that can predict an increased risk of cardiovascular disease in obese pediatric patients.
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