Dietary and Lifestyle Predictors of Risk Of CVD: A Structural Equation Model Approach

Background Cardiovascular disease, driven by complex interactions between socioeconomic, behavioral, and dietary factors, remain critical global health challenges. This study employs structural equation modeling (SEM) to evaluate direct and indirect effects of these factors, mediated by dietary indices (Dietary Insulin Index [DII] and Dietary Glycemic Index [DGI]), on Cardiovascular disease in western Iran. Methods A cross-sectional analysis of 3,452 adults (35–70 years) from the Dehgolan Prospective Cohort Study (DehPCS) in western Iran was conducted. Data included anthropometric measures, socioeconomic status, lifestyle factors, chronic diseases, and dietary indices (DGI and DII). Structural equation modeling (SEM) evaluated pathways linking latent variables (socioeconomic status, personal habits, chronic diseases) and mediators (DII, DGI) to risk of CVD. Model fit was assessed using CFI, RMSEA, and χ² statistics. Results The model explained 11% of risk of CVD variance (R²=0.11). Socioeconomic status directly reduced risk of CVD (β=−0.28, p < 0.001), chronic diseases (β=−0.21, p = 0.002). Personal habits (e.g., physical activity, sleep) (β=−0.27, p < 0.001). Dietary Insulin Index (DII) elevated risk of CVD likelihood (β = 0.15, p < 0.001), whereas Dietary Glycemic Index (DGI) reduced it (β=−0.03, p < 0.001). Socioeconomic status(β = 0.086, p = 0.001), personal habits(β = 0.035, p = 0.001), and chronic diseases(β = 0.047, p = 0.001) indirectly elevate the risk of cardiovascular diseases by influencing dietary choices. Women, older adults, and those with lower education had significantly higher cardiovascular disease rates (p < 0.001). Conclusion Cardiovascular disease is mediated by dietary quality, with socioeconomic disparities and chronic conditions amplifying risk. Public health strategies must prioritize healthy diets and equitable access to nutritious foods to disrupt these pathways.