Estimation of cardiovascular risk from self-reported knowledge of risk factors: Insights from the Minnesota Heart Survey

Background: Cost-effective primary prevention of cardiovascular disease (CVD) relies on accuracy of risk assessment. Current risk scores require clinical and laboratory measures, are expensive and are often difficult to apply in the population setting. Objective: This study sought to estimate CVD risk from individuals’ knowledge of their own CVD risk factors and compare it to the risk calculated from measured risk factors. Methods: Using the ACC/AHA Pooled Cohort Risk Equations (PCE), we calculated 10-year CVD risk for 9856 primary prevention individuals aged 40–79 in the Minnesota Heart Survey (MHS). Using log-linear regression models, we estimated PCE risk from the individual’s self-reported knowledge of four dichotomous risk factors: hypertension, hypercholesterolemia, diabetes, and smoking. Age was included in all models, and models were developed separately in women and men. Model performance was assessed internally using leave-one-out cross-validation. Results: The median measured PCE CVD risk in women was 2.1% (IQR: 0.8–5.6%), and in men was 6.3% (3.1–13.0%). Using the newly developed equations, the median estimated risk was 2.2% (0.9–5.8%) in women, and 6.9% (3.2–13.1%) in men. Using a threshold of 7.5% to categorize low and high risk, the novel risk calculation gave an accuracy of 95% for women and 87% for men compared to the measured PCE risk. The negative predictive value was 97% for women and 91% in men. Conclusion: Self-reported knowledge of risk may be useful in the identification of individuals at low risk for CV events, however, should always be followed up with measurement of risk factors if symptoms or history suggest CVD.