Synergy between adiposity, insulin resistance, metabolic risk factors, and inflammation in adolescents.
cross_sectional · Level IV
Where this comes from
- Record sourced from PubMed, PMID 19131468.
- Also identified by DOI 10.2337/dc08-1917 and PMC identifier 2660473.
- Licence recorded as CC BY-NC-ND.
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Abstract
The purpose of this study was to investigate relationships between inflammatory markers and components of a metabolic syndrome cluster in adolescents. This was a cross-sectional analysis of an Australian childhood cohort (n = 1,377) aged 14 years. Cluster analysis defined a "high-risk" group similar to adults with metabolic syndrome. Relevant measures were anthropometry, fasting insulin, glucose, lipids, inflammatory markers, liver function, and blood pressure. Of the children, 29% fell into a high-risk metabolic cluster group compared with 2% by a pediatric metabolic syndrome definition. Relative to the "low-risk" cluster, they had higher BMI (95% CI 19.5-19.8 vs. 24.5-25.4), waist circumference (centimeters) (95% CI 71.0-71.8 vs. 83.4-85.8), insulin (units per liter) (95% CI 1.7-1.8 vs. 3.5-3.9), homeostasis model assessment (95% CI 1.7-1.8 vs. 3.5-3.9), systolic blood pressure (millimeters of mercury) (95% CI 110.8-112.1 vs. 116.7-118.9), and triglycerides (millimoles per liter) (95% CI 0.78-0.80 vs. 1.25-1.35) and lower HDL cholesterol (millimoles per liter) (95% CI 1.44-1.48 vs. 1.20-1.26). Inflammatory and liver function markers were higher in the high-risk group: C-reactive protein (CRP) (P < 0.001), uric acid (P < 0.001), alanine aminotransferase (ALT) (P < 0.001), and gamma-glutamyl transferase (GGT) (P < 0.001). The highest CRP, GGT, and ALT levels were restricted to overweight children in the high-risk group. Cluster analysis revealed a strikingly high proportion of 14 year olds at risk of cardiovascular disease-related metabolic disorders. Adiposity and the metabolic syndrome cluster are synergistic in the pathogenesis of inflammation. Systemic and liver inflammation in the high-risk cluster is likely to predict diabetes, cardiovascular disease, and nonalcoholic fatty liver disease.
Medical subject headings
- Cardiovascular Diseases
- Inflammation
- Insulin Resistance
- Metabolic Diseases
- Overweight