Longitudinal associations of dynamic transitions of multidimensional health vulnerability with cardiovascular disease risk: evidence from UK Biobank

Background: Health vulnerability (HV), an intrinsic multidimensional construct integrating physiological, psychological, and social domains, may be associated with cardiovascular disease (CVD) risk. However, existing HV assessments lack integration and temporal dynamics change. This study identifies the dynamic association between the HV and risk of CVD. Methods: This longitudinal cohort study included 16,072 participants from the UK Biobank with HV assessments at baseline (2006-2010) and repeat assessment (2014). Latent class analysis and latent transition analysis were used to identify HV transition patterns. Cox proportional hazards models were applied to evaluate associations between HV transitions and incident CVD, with follow-up initiated from baseline assessment. Sensitivity analyses included alternative HV transitions classification, exclusion of hypertensive diseases from the composite outcome, and competing risk analyses considering non-CVD death. Results: During a median follow-up of 8.9 years, 3,033 incident CVD events were identified. Compared with persistently low vulnerability, increasing vulnerability and persistently elevated vulnerability were associated with higher CVD risk after multivariable adjustment (HR = 2.14, 95% CI: 1.74-2.63 and HR = 1.18, 95% CI: 1.08-1.29, respectively). Subgroup analyses identified significant effect modification by age and smoking status, indicating that the associations between HV transitions and CVD risk differed across these populations. The main findings remained consistent in sensitivity analyses. Conclusion: Dynamic changes in HV were associated with subsequent CVD risk, with increasing and persistently elevated vulnerability showing higher risks. These findings highlight the potential importance of monitoring multidimensional vulnerability changes for cardiovascular risk assessment.