Clustering of Social Determinants of Health and their Association with Adverse Cardiovascular Outcomes in Atrial Fibrillation in UK Biobank

BackgroundDespite improvements in diagnostic and therapeutic options, individuals with atrial fibrillation (AF) remain at high risk for major adverse cardiovascular events (MACE). Social determinants of health (SDOH) are strongly associated with cardiovascular outcomes, yet the complex patterns through which these factors cluster to create distinct vulnerability profiles remain poorly understood. MethodsWe conducted a latent class analysis utilizing data from the UK Biobank cohort, examining 15 SDOH indicators across economic, psychological, and neighborhood domains among 3,842 participants with AF (35.1% female). Multi-group latent class analysis (LCA) evaluated differences in vulnerability pattern distribution, and explored whether SDOH clusters of vulnerability varies by sex. Cox proportional hazards models assessed the association between identified SDOH clusters and composite cardiovascular outcomes comprising major adverse cardiovascular events (MACE) and all-cause mortality. ResultsWe identified five distinct SDOH vulnerability clusters based on multi-group LCA: 1) low vulnerability across all domains; 2) primarily economic vulnerability; 3) primarily neighborhood-related vulnerability; 4) economic and neighborhood vulnerability with favorable psychological conditions; and 5) high vulnerability across all domains. Male participants demonstrated a higher representation in more advantaged profiles than their female counterpart (Cluster 1: 37.0% vs. 26.6%; Cluster 4: 25.3% vs. 14.1%). Female participants exhibited the greater representation in the overall highest vulnerability cluster(Cluster 5: 35.1% vs. 25.2%) as compared with male participants. Compared to Cluster 1, individuals with AF from classes with adverse economic conditions (Cluster 2, 4 and 5) had a higher risk of MACE events with individuals in Cluster 5 having twice the risk. No sex interactions were observed with SDOH clusters in their association with MACE. ConclusionsWe identified five distinct SDOH vulnerability patterns among individuals with AF, revealing economic determinants as pivotal drivers of cardiovascular risk. These findings provide an evidence-based framework for implementing precision medicine approaches that incorporate comprehensive SDOH assessment into AF clinical management.