Bayesian Network Modeling of Environmental, Social, and Behavioral Determinants of Cardiovascular Disease Risk

作者：Nyavor H, Obeng-Gyasi E · 发表于：International journal of environmental research and public health · 年份：2025 · DOI：10.3390/ijerph22101551 · 被引用次数：58 · 研究领域：Cardiovascular Diseases、Humans、Bayes Theorem、Male、Female、Middle Aged、Adult、Cross-Sectional Studies、Risk Factors、Nutrition Surveys、United States、Aged

BACKGROUND: Cardiovascular disease (CVD) is the leading global cause of death and is shaped by interacting biological, environmental, lifestyle, and social factors. Traditional models often treat risk factors in isolation and may miss dependencies among exposures and biomarkers. OBJECTIVE: To map interdependencies among environmental, social, behavioral, and biological predictors of CVD risk using Bayesian network models. METHODS: A cross-sectional analysis was conducted using NHANES 2017-2018 data. After complete-case procedures, the analytic sample included 601 adults and 22 variables: outcomes (systolic/diastolic blood pressure, total/LDL/HDL cholesterol, triglycerides) and predictors (BMI, C-reactive protein (CRP), allostatic load, Dietary Inflammatory Index, income, education, age, gender, race, smoking, alcohol, and serum lead, cadmium, mercury, and PFOA). Spearman's correlations summarized pairwise associations. Bayesian networks were learned with two approaches: Grow-Shrink (constraint-based) and Hill-Climbing (score-based, Bayesian Gaussian equivalent score). Network size metrics included number of nodes, directed edges, average neighborhood size, and Markov blanket size. RESULTS: Correlation screening reproduced expected patterns, including very high systolic-diastolic concordance (p ≈ 1.00), strong LDL-total cholesterol correlation (p = 0.90), inverse HDL-triglycerides association, and positive BMI-CRP association. The final Hill-Climbing network contained 22 no...