Impact of Traditional and Novel Risk Factors on the Relationship Between Socioeconomic Status and Incident Cardiovascular Events

Background— Persons of lower socioeconomic status have greater cardiovascular risk than those of higher socioeconomic status. However, the mechanism through which socioeconomic status affects cardiovascular disease (CVD) is uncertain. Virtually no data are available that examine the prospective association between novel inflammatory and hemostatic CVD risk indicators, socioeconomic status, and incident CVD events. Methods and Results— We assessed the relationship between 2 indicators of socioeconomic status (education and income), traditional and novel CVD risk factors (high sensitivity C-reactive protein, soluble intercellular adhesion molecule-1, fibrinogen, and homocysteine), and incident CVD events among 22 688 apparently healthy female health professionals participating in the Women’s Health Study. These women were followed up for 10 years for the development of myocardial infarction, ischemic stroke, coronary revascularization, and cardiovascular death. More educated women were less likely to be smokers; had a lower prevalence of hypertension, diabetes, and obesity; and were more likely to participate in vigorous physical activity than less educated women. At baseline, median total cholesterol, low-density lipoprotein, triglyceride, C-reactive protein, intercellular adhesion molecule-1, fibrinogen, and homocysteine levels for women in 5 categories of education (<2 years of nursing education, 2 to <4 years of nursing education, a bachelor’s degree, a master’s degree, and a doctoral degree) and 6 categories of income [≤19 999, 20 000 to 29 999, 30 000 to 39 999, 40 000 to 49 999, 50 000 to 99 999, and ≥100 000) decreased progressively with increasing education or income levels (all P <0. 001), whereas an opposite pattern was observed for high-density lipoprotein (P <0. 001). Overall, in age-adjusted Cox proportional hazards models, the relative risk of incident CVD events decreased with increasing education (1. 0, 0. 7, 0. 5, 0. 4, and 0. 5; P for trend <0. 001) and income (1. 0, 1. 0, 0. 9, 0. 7, 0. 6, and 0. 4; P for trend <0. 001) categories. In multivariate models that assessed the impact of traditional and novel CVD risk factors on the relationship between education/income and CVD events, the relative hazard of incident CVD associated with a 1-category-higher level of education changed from 0. 79 in age- and race-adjusted analysis to 0. 89 in fully adjusted analysis. The 11% lower risk per 1 category of education remained significant (P for trend=0. 006), suggesting that controlling for both novel and traditional risk factors could not explain the protective effect of education. A similar analysis for income revealed that its relationship with CVD events was explained largely by these noted risk factors. Conclusions— In this prospective analysis, we observed a decrease in incident CVD events with increasing levels of education and income. In contrast to the relationship between income and CVD events, the relationship of CVD events with education was explained only partially by traditional and novel risk factors for CVD.