Racial disparities in cardiovascular disease (CVD) risk and mortality is an important challenge for health care in the United States and worldwide [1‐4]. The Eight Americas Study indicated that CVD represents the main driver of disparities in life expectancy across various racial/ethnic groups in the United States [5]. We have previously reported that Black race is associated with CVD risk independent of several novel and traditional CVD risk factors [6]. While studies of biological determinants of such disparities are important, current evidence suggests that racial differences in CVD incidence are mainly related to social and environmental factors, such as socioeconomic deprivation (e.g., low family income, low education level). Myriad, complex and interacting downstream social and psychological constructs such as access to healthcare, medical compliance, eating habits, depression and stress are thought to play role in this relationship [7‐11].

Socially disadvantaged individuals often have multiple types of social risk factors. However, few studies to date have investigated the cumulative effect of multiple social risk factors on CVD risk [7, 8]. Identification of the cumulative effect of various social risk factors on CVD risk can provide insight into the real-world effects of social disadvantage on CVD and may inform approaches to addressing CVD disparities that extend beyond strategies focusing on a single risk factor. For example, a recent study of NHANES III data reported the cumulative effect of four social risk factors (i.e., belonging to an ethnic minority group, low income, low education, single living status) on risk of CVD mortality and all-cause mortality [7]. Each additional social risk score was found to be associated with a 17% higher risk of CVD mortality and 43% higher risk of under 65-year old mortality [7]. However, the NHANES report did not include non-fatal CVD events in the outcome. In order to further understand the role of socio-environmental factors in CVD disparities, we used data from the Heart Strategies Concentrating on Risk Evaluation (HeartSCORE) study to create an index of cumulative social risk (CSR) and quantify its association with incident CVD events and all-cause mortality. We also assessed the cross-sectional association between CSR and carotid intima-media thickness (CIMT), which is a non-invasive intermediate marker of atherosclerosis.

Using prospective data from a cohort composed of comparable proportions of Black and White participants followed for an average of 8.3 years, we demonstrated that accumulation of four social risk factors (belonging to racial minority group, low social income, low education, and single living status) is associated in a gradient manner with increased risk of combined all-cause mortality and CVD events, as well as with presence of significant CIMT, which is a marker of subclinical atherosclerosis. Cumulative social risk was associated with several traditional CVD risk factors including smoking, blood pressure, diabetes, BMI, and family history of coronary artery disease, as well as with high levels of inflammatory marker (hsCRP, IL6) and adverse psychosocial factors (depression, stress, perceived discrimination). Adjustment for traditional CVD risk factors, as well as for inflammatory and psychosocial factors, several of which may be in the causal pathway of the association, did not materially attenuate the relative risks for the primary outcome of mortality or non-fatal CVD events. These findings suggest a strong independent effect of CSR on risk of mortality and CVD.

Previous studies have shown that the presence of single measures of socioeconomic disadvantage, such as ethnic minority status, low education or low income, is associated with adverse cardiovascular outcomes [3, 6, 7, 22‐24]. It has also been demonstrated that these different measures are not necessarily interchangeable [25]. Furthermore, studies have also shown that the duration of time that individuals spent living in a disadvantaged socioeconomic position increases the risk of adverse CVD outcomes [8, 26]. However, few studies have evaluated the cumulative effect of the simultaneous presence of multiple social risk factors on the risk of non-fatal CVD outcomes and mortality and the construct of cumulative social risk has been defined differently in studies [7, 27]. Our findings complement and supplement findings from previous studies by using a 4-variable construct of CSR, assessing its association with several traditional and novel CVD risk factors, as well as its associations with risk of non-fatal CVD events and all-cause mortality. For instance, while extant studies have only investigated mortality [7], we also investigated incident CVD events and subclinical disease, thus providing a more robust and comprehensive assessment of the relation of CSR to CVD.

The associations between CSR and several traditional CVD risk factors, inflammatory factors, depression, perceived discrimination, and stress suggest that these factors may potentially mediate or confound the primary association between CSR and CVD and mortality outcomes. In particular, there is a growing evidence supporting the role of psychosocial factors such as perceived discrimination, stress and depression in mediating and modifying the relationship between disadvantageous social exposures (such as ethnic minority status and low income) and clinical outcomes [9‐11]. That the association was minimally attenuated after adjustment for the factors discussed above, may suggest a strong independent effect of CSR. Important related considerations, however, include measurement error in mediators and confounders, as well as unidentified effect modifications and interactions.

We also investigated the effect of adjustment for ideal fruit and vegetable consumption in attempt to partially account for more proximal potential effect-mediating social constructs, which did not materially attenuate the association. These proximal social constructs which include, but are not limited to, factors such as health behavior (e.g., medical compliance, healthy eating index, physical activity) and access to health care (e.g., having medical insurance and primary care follow-up) are not likely to be fully captured by the limited adjustment that was possible in the current analyses. Behavioral risk factors are of importance, as it has been hypothesized that social stressors adversely affect health behaviors, such as diet, physical activity, smoking habit, and alcohol use, partly accounting for the high rates of obesity and CVD seen among minorities and lower social status populations who may experience a greater number of stressors than non-minority populations.

Epigenetic modifications, i.e., heritable and potentially modifiable markers that regulate gene expression without changing the underlying DNA sequence, provide potential mechanistic explanation for social determinants of CVD. Epigenetic markers are responsive to non-biological and environmental exposures, particularly those encountered in early life [28]. Indeed, existing evidence suggests an association between socioeconomic circumstances and global and genome-wide DNA methylation [29‐32]. Hence, further studies should investigate the interrelation of social and biological risk factors and CVD outcomes.

The contribution of access to health care to racial disparities observed among the US general population was demonstrated by a recent study of a large cohort of US veterans, which showed that African-American veterans, in contrast to non-veteran African-Americans, do not have an increased risk of CVD and mortality outcomes [33]. On the other hand, a nationwide study of the association between income and life expectancy in the US using deidentified tax data and Social Security Administration death records found that differences in life expectancy between geographic locations for individuals in the lowest income quartile were correlated to health behavior factors such smoking rate and exercise rate, and local area characteristics such as fraction of college graduates, fraction of immigrants, and government expenditures. This important study, which found a life expectancy difference of 14.8 years for men and 10.1 years for women between the richest 1% and the poorest 1% individuals, highlighted the intricate nature of wealth-health relationship [34].

Our findings indicate the need to take into account a construct for defining social disadvantage in CVD prevention and control strategies. The social environment should be considered as important target for reducing the risk and burden of CVD. Socially disadvantaged individuals may require more attention in addressing the risk of CVD and adverse clinical outcomes. The inclusion of a CSR index in CVD risk assessment tools may help improve the identification of at-risk individuals for targeting with interventions. For instance, in the UK, social deprivation has been included in CVD risk assessment tools, resulting in improvement in risk prediction [35]. Also, in analyses combining data from the Atherosclerosis Risk in Communities (ARIC) Study and NHANES, improvements in calibration of CVD risk prediction models were noted after including data on social risk factors [36]. Evidence indicates that not accounting for social factors may lead to inaccurate CVD risk estimation. For example, the Framingham risk score overestimates the risk of coronary heart disease in high-socioeconomic status individuals and underestimates the risk in low–socioeconomic status individuals. Thus, recent studies have begun to evaluate the potential benefit of including socioeconomic status in risk prediction models [37]. Accounting for the totality of social disadvantage may therefore improve the prediction of CVD risk.

Our findings also have policy implications. Given the multidimensional and intricate nature of social risk factors, multi-lateral collaboration among various sectors to address root causes of social disadvantage such as lack of education, unsafe neighborhood, and unhealthy behavior is needed. For instance, a multi-pronged approach involving governmental and nongovernmental organizations and communities to target early childhood education and foster supportive community environments can help to shift life-course trajectories, equipping children with tools to break the cycle of illiteracy and poverty. Such interventions promote health and would be cost saving in the long-term.

Our study has a number of limitations. First, because of modest statistical power, we merged categories of CSR in order to avoid low prevalence groups and provide for more precise estimates of effect. Second, we were unable to investigate clinical outcomes (e.g., mortality, coronary disease, stroke) separately. Third, we did not assess potential up-stream effect mediators that may be associated with CSR, such as health-access, health-care seeking behavior and medical compliance. Fourth, the definition of CSR can vary between studies and the current CSR construct may not be applicable in other settings. In addition, it is not clear if the various components of CSR carry equal weight. Therefore, further studies are needed to assess the generalizability of these findings. Nevertheless, the strengths of our study include an examination of a range of social risk factors, and their cumulative deleterious effects in a cohort composed of Black and White participants, accounting for various aspects of social disadvantage, as well as their combined effect on subclinical cardiovascular disease, which has not been extensively examined previously.

In summary, we found that an accumulation of social risk factors increased the likelihood of CVD events and deaths in a cohort composed of comparable proportions of Whites and Blacks; we also found a graded association between CSR and presence of significant CIMT in cross-sectional analyses. The sizable toll that simultaneous exposure to a multitude of social risks factors take on CVD risk points toward the need for appropriate clinical and preventive strategies that allocate sufficient and specific resources to address the needs of socially disadvantaged groups.