Network analysis of adverse childhood experiences and cardiovascular diseases.

Significance: The findings to date indicate that adverse childhood experiences (ACEs) increase the risk of cardiovascular disease (CVD) in later life. We demonstrate how network analysis, a statistical method that estimates complex patterns of associations between variables, can be used to model ACEs and CVD. The main goal is to explore the differential impacts of ACE components on CVD outcomes, conditioned on other ACEs and important covariates using network analysis. We also sought to determine which ACEs are most synergistically correlated and subsequently cluster together to affect CVD risk. Methods: Our analysis was based on cross-sectional data from the 2020 Behavioral Risk Factor Surveillance System, which included 31,242 adults aged 55 or older (54.6% women, 79.8% whites, mean age of 68.7 ± 7.85 years). CVD outcomes included angina/coronary heart disease (CHD) and stroke prevalence. Mixed graphical models were estimated using the R-package Results: In the network for men, the variable "household incarceration" was most strongly associated with stroke. For women, the strongest connection was between "physical abuse" and stroke, followed by "sexual abuse" and angina/CHD. For men, angina/CHD and stroke were clustered with several CVD risk factors, including depressive disorder, diabetes, obesity, physical activity, and smoking, and further clustered with components of household dysfunction (household substance abuse, household incarceration, and parental separation/divorce). No clusters emerged for women. Conclusions: Specific ACEs associated with CVDs across gender may be focal points for targeted interventions. Additionally, findings from the clustering method (especially for men) may provide researchers with valuable information on potential mechanisms linking ACEs with cardiovascular health, in which household dysfunction plays a critical role.