Components of insulin resistance syndrome in a community-based population assessed by log-linear models

To investigate the clustering of insulin resistance syndrome with hyperinsulinemia, hypertriglyceridemia, low high-density lipoprotein (HDL) cholesterol, hypertension, and obesity, we conducted this cross-sectional study and analyzed the patterns of conditional independence among these five elements.

Fasting insulin, lipid profiles, blood pressure, and anthropometric data from 2165 Taiwanese older than 35 years in the Chin-Shan community were examined. The cut-off points of these five factors (all binary variables) were defined. The hierarchical log-linear regression with nested effects model was applied to fit this higher-order contingency table of five variables, and likelihood ratio (chi2) statistics were used to test the goodness of fit.

Hyperinsulinemia was independently correlated with obesity (odds ratio [OR] 5.7, 95% confidence interval [CI] 4.5-7.3), low HDL (OR 2.3, 95% CI 1.8-2.9), and hypertriglyceridemia (OR 1.6, 95% CI 1.2-2.2). Hypertriglyceridemia was significantly associated with low HDL (OR 3.6, 95% CI 2.7-4.8), and non-significantly associated with hypertension (OR 1.3, 95% CI 0.9-1.7) and obesity (OR 1.1, 95% CI 0.8-1.6). In persons with normal triglyceride levels, hypertension was positively associated with obesity (OR 2.8, 95% CI 2.1-3.7) and low HDL (OR 2.0, 95% CI 1.5-2.8). Analyses from forward and backward selection methods gave similar results. Graphical models with conditional independence relationships among these five variables were demonstrated.

The components of insulin resistance syndrome have intricate relationships. Hyperinsulinemia was most related to obesity, and hypertriglyceridemia was most related to low HDL.