Lifestyle-Based Prediction Model for the Prevention of CVD: The Healthy Heart Score

Background-Clinical practice focuses on the primary prevention of cardiovascular (CV) disease (CVD) through the modification and pharmacological treatment of elevated risk factors. Prediction models based on established risk factors are available for use in the primary prevention setting. However, the prevention of risk factor development through healthy lifestyle behaviors, or primordial prevention, is of paramount importance to achieve optimal population-wide CV health and minimize long-term CVD risk. Methods and Results-We developed a lifestyle-based CVD prediction model among 61 025 women in the Nurses' Health Study and 34 478 men in the Health Professionals Follow-up Study, who were free of chronic disease in 1986 and followed for <= 24 years. Lifestyle factors were assessed by questionnaires in 1986. In the derivation step, we used the Bayes Information Criterion to create parsimonious 20-year risk prediction models among a random two thirds of participants in each cohort separately. The scores were validated in the remaining one third of participants in each cohort. Over 24 years, there were 3775 cases of CVD in women and 3506 cases in men. The Healthy Heart Score included age, smoking, body mass index, exercise, alcohol, and a composite diet score. In the validation cohort, the risk score demonstrated good discrimination (Harrell's C-index, 0.72; 95% confidence interval [CI], 0.71, 0.74 [women]; 0.77; 95% CI, 0.76, 0.79 [men]), fit, and calibration, particularly among individuals without baseline hypertension or hypercholesterolemia. Conclusions-The Healthy Heart Score accurately identifies individuals at elevated risk for CVD and may serve as an important clinical and public health screening tool for the primordial prevention of CVD.