Evaluation and comparison of models of metabolic syndrome using confirmatory factor analysis

The aim of this study was to evaluate and compare three competing models of the underlying factor structure of metabolic syndrome using confirmatory factor analysis (CFA). Data from the Insulin Resistance Atherosclerosis Study (IRAS) was used, which has previously been evaluated using principal components analysis (PCA). The three models that were evaluated consisted of oblique and orthogonal two-factor models with hypothesized underlying "metabolic" and "blood pressure" factors, and a four-factor model theorizing "insulin resistance," "obesity," "lipids," and "blood pressure" as the underlying constructs. Several CFAs were performed using EQS Multivariate Software Version 5.7b with maximum likelihood estimation. The results showed that the four-factor model yielded significantly better data-model fit than two-factor models, with a comparative fit index of 0.963, and standardized root mean square residual of 0.036. Factors exhibited good construct reliability and variance extracted estimates except for the lipids factor. We concluded that the four-factor model of metabolic syndrome was the most plausible model among the three competing models.