• Longitudinal, multivariate risk-factor epidemiology reveals a core set of CHD predictors (blood pressure, serum cholesterol, smoking, lipoproteins) across diverse cohorts, supporting predictive models and preventive emphasis [3], [7], [20], [5], [12].

• Cross-population and international CHD studies test generalizability of risk patterns, showing similar risk-factor associations in Framingham, Seven Countries, Japan/Hawaii/California cohorts, and Minnesota samples [9], [18], [19], [15].

• Methodological foundations and critiques shape epidemiologic practice—survey methods, long-term study design, and interpretation of cohort data—through discussions of Framingham, cardiovascular survey methods, and early community studies [2], [13], [16].

• Prediction and prevention-oriented research leverage biomarker and risk-factor data to forecast CHD events and guide preventive strategies, integrating predictive studies, pooling results, and risk-factor management [4], [5], [20].

• Lipid biology as a central CHD risk marker: serum cholesterol and lipoprotein profiles track incident CHD and illustrate population-specific dyslipidemia patterns (e.g., Hawaii Japanese men) [7], [11].