Cardiovascular diseases (CVD) are responsible for more deaths than any other disease, continue to threaten the quality of life for many, and is a major burden to the health care system. The Framingham Heart Study (FHS) identified the major CVD risk factors that became essential to effective CVD screening strategies and the Framingham Risk Score (FRS), is used to assess CVD risk. Based on the concepts of the health behavior model and CVD as a cardiometabolic disorder, multivariate logistic regression analysis was used to evaluate the association between fasting blood glucose (FBG) levels and a CHD event, and to determine the value of FBG replacing a diagnosis of diabetes (DM2) in the FRS. The data set consisted of the 2,677 subjects of the FHS III cohort. In the univariate analysis, both DM2 and FBG were statistically significant (both p =.000), but the association was stronger for DM2, b = 2.138, OR = 8.483 (95% CI: 4.229, 17.105) than for FBG, b = .015, p = .000, OR=1.015 (95% CI: 1.009, 1.022). When adjusted for age, blood pressure, cholesterol, and smoking status, only DM2 remained statistically significant, OR = 2.295, p = .041, (95% CI: 1.035, 5.087) in the model. The FBG version of the FRS did not provide any improvement in performance, as it was marginally inferior to the DM2 version. Furthermore, the interactions between FBG and the metabolic risk factors were not statistically significant for this given data set. The results imply that a diagnosis of diabetes remains the factor of choice for inclusion in the FRS model for predicting the 10-year risk of CHD and replacing it with FBG provides little to no practical benefit. These findings support the use of CVD risk factor reduction and the use of effective screening tools in CVD prevention and promotion heart health.