Dietary Behavior Clustering and Cardiovascular Risk Markers in a Large Population Cohort.

Abstract

Eating habits influence cardiometabolic health alongside traditional dietary measures. However, the links between dietary patterns, body composition, and heart-healthy food preferences remain under-explored in large cohorts. In this cross-sectional study, 2461 adults (aged 18 to 75 years) completed an online survey on eating behaviors, food preferences, and lifestyle. Principal component analysis (PCA) of seven behaviors identified dietary profiles. A heart-healthy diet score (range -2 to 10; higher = greater preference for fruit, vegetables, legumes, fish, and less meat/processed meat) was derived from these food preferences. ANOVA and adjusted regressions linked the profiles to BMI, fat mass, waist circumference, and diet score. Four profiles emerged: structured, social, irregular, and disordered eaters. Structured eaters had the lowest BMI (26.8 ± 5.1 kg/m 2 ), lowest fat mass (28.9 ± 9.4%), and highest dietary score (4.73 ± 2.0). Disorganized eaters had the highest BMI (29.0 ± 5.5 kg/m 2 ), the highest fat mass (31.2 ± 8.8%) and the lowest score (3.93 ± 2.0); all p < 0.05. Dose-response analyses confirmed that greater disordered eating (PCA1) was associated with worse outcomes. Dietary profiles are associated with body composition and cardioprotective preferences. Behavioral assessment could refine the identification of cardiometabolic risk and personalize nutrition.