The metabolic syndrome and coronary artery disease: a structural equation modeling approach suggestive of a common underlying pathophysiology

Abstract

Objective: The purpose of this research was to utilize a structural equation modeling (SEM) approach to simultaneously examine the relationship among the Metabolic Syndrome (MetSyn) and coronary artery calcification (CAC), a surrogate marker for sub-clinical atherosclerosis and coronary artery disease (CAD).

Materials/methods: Data were derived from the Spokane Heart Study (SHS), a prospective study designed to examine the role of traditional and non-traditional biological, psychological, and behavioral risk factors predictive of CAC. Study participants included 434 non-clinical healthy volunteers (54% female, 46% male; mean age of 56 years) who were asymptomatic for CAD at enrollment and had complete data for the primary variables of interest (MetSyn components and CAC) during the data collection period (i.e., 2002-2006). A confirmatory factor analysis (CFA) was conducted on the MetSyn factor with the following indicator variables: body mass index, fasting glucose, high-density lipoprotein cholesterol, fasting triglyceride levels, and systolic blood pressure. SEM was used to test the theoretical model that the MetSyn is associated with CAC.

Results: This study demonstrated that body mass index, fasting glucose, fasting triglyceride levels, HDL cholesterol, and blood pressure do cluster together under a single latent factor, and that this latent factor is associated with CAC.

Conclusions: Our results highlight the possibility that there is a common pathophysiological pathway that could explain the relationship between the MetSyn and CAD. Future studies should examine these relationships in a prospective fashion for early detection and prevention of CAD and to identify ideal time points for clinical intervention.