Cardiometabolic Risk Patterns Among Adults: A Latent Class Analysis from the Hoveyzeh Cohort Study

Cardiometabolic risk factors may cluster into heterogeneous patterns that are not fully captured by conventional approaches. This study aimed to identify latent cardiometabolic profiles and examine their association with incident dyslipidemia among adults participating in the Hoveyzeh Cohort Study. This prospective cohort study included 1,660 adults free of dyslipidemia at baseline who were reassessed approximately five years later. Latent class analysis was conducted using five binary indicators: hypertension, diabetes, low physical activity, high saturated-fat intake, and metabolic waist. Two-, three-, and four-class models were evaluated based on fit, convergence, interpretability, and classification quality. Incident dyslipidemia was defined as newly developed dyslipidemia at reassessment. Risk ratios (RRs) and 95% confidence intervals (CIs) were estimated using robust Poisson regression. A two-class model was selected. Class 1 included 1,197 participants (72.1%) and had lower probabilities of the indicators, whereas Class 2 included 463 (27.9%) and showed higher probabilities of hypertension, diabetes, and metabolic waist. During follow-up, 876 participants (52.8%) developed dyslipidemia. No association was observed between Class 2 and incident dyslipidemia in crude (RR = 0.97, 95% CI: 0.88–1.08) or adjusted analyses (RR = 1.03, 95% CI: 0.92–1.14). Two distinct cardiometabolic profiles were identified, but latent class membership was not associated with incident dyslipidemia.