Abstract 12549: Population Patterns of Clustering in Cardiovascular Health Metrics and Associations With Cardiovacular Disease: A Latent Classpopulation Patterns of Clustering in Cardiovascular Health Metrics and Associations With Cardiovacular Disease: A Latent Class Analysis

Abstract

Background: Cardiovascular health (CVH) is defined by 7 health behaviors (smoking, diet, physical activity) and factors (body mass index, blood pressure, total cholesterol, glucose). we sought to explore how CVH components cluster in individuals and examine associations of clusters with cardiovascular disease (CVD). Methods: Participants aged 20-79 years were included from four longitudinal cohorts. Levels of each CVH metric were classified as ideal, intermediate, or poor using AHA definitions. Among sex and race subgroup, we applied latent class analysis (LCA) models on CVH metrics and individuals were assigned to a class based on the highest posterior probability of membership. Cox regression model was conducted to estimate the association of cluster and the CVD events. Results: Among 9270 White and 3913 Black women, and 7773 White and 2875 Black men, 6004 CVD events occurred during 19.5 years’ follow-up. Three common classes were observed (Figure 1): Suboptimal (unfavorable behaviors and factors), Mixed (diverse levels of behaviors and factors), and Favorable factors. One additional class of Unfavorable Behaviors (with relatively favorable factors) was identified in Whites. Compared with Favorable factors, other classes had significantly higher risk for CVD (Figure 2), except in Black women. Conclusions: We observed three common clusters of CVH component, with an additional class of Unfavorable Behaviors (only) in White participants, that were significantly associated with incident CVD across subgroups. Given that 27-47% of participants were in the Suboptimal group, multifaceted primordial prevention strategies will be needed to bend the CVD epidemic curve.