Assessing CVD Risk: Traditional Approaches
Cardiovascular disease (CVD) is a leading cause of disability and death. Primary and secondary prevention measures help reduce cardiovascular events and improve the overall health of patients. In an attempt to understand the factors contributing to the development of CVD, several epidemiological and prospective studies have been conducted over the last 60 years. These studies have followed thousands of individuals over a number of years to pinpoint a first or recurrent cardiovascular event. One of the first studies was the Framingham Heart Study. This landmark U.S. study followed men and women who were initially free of CVD in order to gain initial insight on the major cause(s) of heart disease. It has enabled researchers to identify major CVD risk factors such as hypertension, smoking, elevated cholesterol or LDL cholesterol (bad cholesterol) concentrations, reduced levels of HDL cholesterol (good cholesterol), and type 2 diabetes. Many international prospective studies have confirmed that these risk factors have a significant impact on the development of heart disease. Because they were identified early on, these variables are referred to as “traditional” risk factors. Further analyses from the Framingham Heart Study have led to the development of a CVD risk prediction model based on these traditional risk factors: the Framingham risk score. Another well-recognized epidemiological prospective study—the PROCAM study—has also developed a risk prediction model that uses some of the risk factors included in the Framingham risk score along with other variables. The risk of subsequent CVD is categorized as low, intermediate, or high depending on the result obtained. Other organizations and groups have also developed CVD risk prediction algorithms. With the obesity and type 2 diabetes epidemics sweeping the world, it remains unresolved whether these global risk assessment tools fully capture the risk of abdominal obesity and the related abnormalities of the metabolic syndrome.