Background—Prediction of coronary heart disease (CHD) and cerebrovascular disease (CeVD) can aid healthcare providers and prevention programs. Previous reports have focused on traditional cardiovascular risk factors; less information has been available on the role of overweight and obesity.

Methods and Results—Baseline data from 4780 Framingham Offspring Study adults with up to 24 years of follow-up were used to assess risk for a first CHD event (angina pectoris, myocardial infarction, or cardiac death) alone, first CeVD event (acute brain infarction, transient ischemic attack, and stroke-related death) alone, and CHD and CeVD events combined. Accelerated failure time models were developed for the time of first event to age, sex, cholesterol, high-density lipoprotein cholesterol, diabetes mellitus (DM), systolic blood pressure, smoking status, and body mass index (BMI). Likelihood-ratio tests of statistical significance were used to identify the best-fitting predictive functions. Age, sex, smoking status, systolic blood pressure, ratio of cholesterol to high-density lipoprotein cholesterol, and presence of DM were highly related (P<0.01 for all) to the development of first CHD events, and all of the above except sex and DM were highly related to the first CeVD event. BMI also significantly predicted the occurrence of CHD (P=0.05) and CeVD (P=0.03) in multivariable models adjusting for traditional risk factors. The magnitude of the BMI effect was reduced but remained statistically significant when traditional variables were included in the prediction models.

Conclusions—Greater BMI, higher systolic blood pressure, higher ratio of cholesterol to high-density lipoprotein cholesterol, and presence of DM were all predictive of first CHD events, and all but the presence of DM were predictive of first CeVD events. These results suggest that common pathophysiological mechanisms underlie the roles of BMI, DM, and systolic blood pressure as predictors for first CHD and CeVD events.