Access to care: There is evidence that lower-income patients are likely to receive poorer medical care. A US study of over 10,000 patients with acute coronary syndromes reported low-income patients as presenting with more severe disease compared to high-income patients (Rao et al. 2003). Furthermore, lower-income patients were less likely to receive evidence-based treatment including cardiac ­catheterization, percutaneous coronary intervention, and prescription of ­aspirin or beta-blockers, although these differences were attenuated on multivariable adjustment. These trends may go some way to explaining the significantly higher 6-month mortality rate in the low-income group. Additional studies found discrepancies between treatments received by MI patients according to SES. A large-scale cohort study involving over 50,000 Canadian MI patients reported increased use of coronary angiography and reduced waiting times in the highest SES compared to lowest SES neighborhoods, based on census data (Alter et al. 1999). Furthermore, there was a strong inverse relationship between income and mortality 1 year post-MI, despite the universal healthcare provided in Canada. Similar results have been reported in numerous studies, presenting reduced use of invasive cardiac procedures in lower-income MI patients (Philbin et al. 2000; Rathore et al. 2000). Besides provision of treatment, access to medical facilities may differ according to SES. In the FINMONICA study, low-income males with MI were more likely to present with more than 4h delay compared to wealthier patients (Salomaa et al. 2001). Whether this delay is due to poorer access to appropriate care or to reduced help-seeking behavior remains open to debate.

Risk factors: An alternative or parallel explanation for the poorer survival odds of low SES MI patients is a difference in baseline risk factors (Ebrahim et al. 2004), which contribute to both the development and progression of CHD. While CHD mortality has declined over the years as has the prevalence of some primary CV risk factors such as smoking and physical inactivity, socioeconomic inequalities persist (Hotchkiss et al. 2011). Secondary risk factors such as diabetes and hypertension are on the increase. Less educated MI patients were more likely to have a history of diabetes mellitus and congestive heart failure in the Multicenter Investigation of the Limitation of Infarct Size (Tofler et al. 1993). Risk factors differed not only prior to MI but also during follow-up, with less educated patients less likely to stop smoking (never graduated 38 % vs. high school graduates 49 %). Patients who continued to smoke had increased mortality risk. This finding was replicated in an Israeli cohort study, with SES contributing to the likelihood of quitting smoking post-MI (Gerber et al. 2011a). Additionally, low neighborhood SES was associated with lower physical activity after MI (Gerber et al. 2011b), a factor strongly related to prognosis.

The Black report identified four types of explanations for social inequalities in health. These are artifacts, or measurement errors in attributing social class, including the fact that lower or working classes are diminishing; social selection which proposes that health status determines socioeconomic status; behavioral, whereby unhealthy behaviors are more prevalent in lower social classes; and materialist, involving “hazards inherent in society,” such as working in hazardous jobs or residing in heavily polluted areas (Smith et al. 1990). All these factors contribute to the socioeconomic gradient in cardiovascular health.

Risk factors: Much has been written about risk factors as the link between SES and cardiovascular outcomes. Evidence from the Framingham Heart Study – a long-term investigation which pioneered the concept of cardiac risk factors – has demonstrated that the primary risk factors for CVD are smoking, hypertension, high cholesterol (dyslipidemia), sedentary lifestyle, and diabetes, largely lifestyle-influenced factors alongside genetic predisposition (Mendis 2010). The Kuopio Ischemic Heart Disease Risk Factor Study investigated whether 23 biological, behavioral, psychological, and social risk factors could account for the association between income and CV mortality in men (Lynch et al. 1996). Adjustment for risk factors not only reduced but completely eliminated the association. Multivariable adjustment also attenuated the relation between SES and acute MI. Biological factors had the greatest effect in risk reduction. The question remains, why do low SES populations have a higher prevalence of CV risk factors, such as blood glucose, hypertension, and high cholesterol? There is direct evidence that SES affects behavior styles, coping styles, the endocrine system, the homeostasis system, and access to medical care (Kaplan and Keil 1993). While some evidence exists for psychological, physiological, and biochemical mediators of the relation between SES and disease, much remains open to speculation.

Hypertension, a risk factor for MI, stroke, and heart failure, has been frequently associated with SES (Cirera et al. 1998). This could be due to greater awareness of hypertension, the effects of diet and the importance of regular checkups, and better access to health services among more highly educated people or could be a by-product of a generally more stressful life associated with deprivation. Cumulative stress has an effect on the heart, increasing allostatic load, illustrated by delayed recovery of the cardiovascular system, specifically blood pressure and heart rate variability, after mental stress in low SES groups, in a sub-cohort of the Whitehall II study (Steptoe et al. 2002). This implies that certain characteristics of low SES – prolonged stress, dietary factors – may put a strain on the heart, making it more vulnerable to injury. Evidence has shown that acute stress can have adverse CV effects, for example, impairment of endothelial function or an increase in cytokine levels lasting for several hours (Steptoe et al. 2001). Cumulative stress is therefore likely to have an enduring effect on the CV system. Fibrinogen has also been demonstrated to be higher in lower socioeconomic groups, showing a significant association with four separate socioeconomic measures in the Kuopio Ischemic Heart Disease Risk Factor Study (Wilson et al. 1993).

Psychological factors: Certain psychological factors are associated with poorer outcomes in patients with established CHD and post-MI patients. Patients with depressive symptoms in the aftermath of MI are at significantly increased risk of mortality and re-infarction. Two meta-analyses of post-MI depression reported that patients diagnosed with depression within 3 months of MI had more than double the risk of all-cause and cardiac mortality than those without depression (van Melle et al. 2004; Meijer et al. 2011). Elevated rates of recurrent cardiac events were also detected. Depression is generally more prevalent among low SES backgrounds (Lorant et al. 2003), and low income has been associated with depression in CHD patients. A cohort study of post-MI patients found that those with depressive symptoms were less educated, had lower income, and were more likely to be unemployed than those without depressive symptoms (Myers et al. 2012). Furthermore, depression was associated with increased cardiac-related hospital admissions during 13 years of follow-up. In a British study of 300 patients with acute coronary syndromes, depression was also found to be more prevalent in lower SES individuals (Steptoe et al. 2011).

Health literacy: Various hypotheses have been suggested to determine why education is so strongly associated with health outcomes. The concept of health literacy posits that individuals with lower ability to read and comprehend medical information are likely to have poorer outcomes. This may be due to lack of awareness of the impact of lifestyle behaviors, nonadherence or incorrect adherence to medication, delayed presentation of symptoms, and poorer management of chronic disease due to poorer understanding of the condition. Scales have been devised to test health literacy, involving both reading and numeracy for health information, and studies have reported increased mortality in individuals with inadequate health literacy (Baker et al. 2007; Bostock and Steptoe 2012). A study of community-dwelling adults with heart failure found that patients with low health literacy were older, were less educated, and had more comorbidities than those who scored high (Morrow et al. 2006).

Lifestyle and environment: Behaviors associated with cardiovascular risk seem to be more prevalent in low SES individuals, whether defined by lower educational attainment or lower income, as evidenced in numerous studies. A study of socioeconomic differentials in CV and cancer mortality in Greece found not only a socioeconomic gradient in CV mortality but also that obesity, poor diet, and physical inactivity were more prevalent in the less educated participants (Naska et al. 2012). In fact, while smoking trends are decreasing in industrialized countries, this reduction is more evident in higher SES populations, while less educated sectors continue to smoke at high levels (Filion et al. 2012). Obesity is also strongly related to socioeconomic status (Wang and Beydoun 2007). Many cross-sectional analyses have found a connection between physical activity and both individual (Barnett et al. 2008) and neighborhood deprivation (Yen and Kaplan 1998; Lee et al. 2007). In order to establish a robust association, longitudinal cohort studies are required. Gerber et al., in a study of post-MI patients followed up for 10–13 years, reported neighborhood deprivation to be strongly associated with uptake of physical activity after MI (Gerber et al. 2011b). Some research has attempted to uncover which neighborhood features may influence exercise patterns and explain the discrepancy between high and low SES areas. Explanatory factors include both physical elements (such as lighting, street layout, and access to facilities) and social characteristics, particularly perceptions of others’ behavior and perceived safety of the environment. An American study demonstrated that not only did deprived neighborhoods have fewer sports facilities including parks and gyms compared to high-SES neighborhoods, but they were also less likely to provide free sports facilities (Estabrooks et al. 2003). Further environmental factors, such as air pollution or poor living conditions, may also be involved in overall poorer health outcomes.

SES has also been associated with attendance at cardiac rehabilitation, a crucial component of post-MI recovery, but one for which uptake is low. A study of Danish MI survivors reported nonattendance to be associated with low income (Nielsen et al. 2008). A systematic review found nonattenders to be older and to have lower income or greater deprivation among other factors (Cooper et al. 2002).

Growing evidence suggests that our health may be influenced not only by our own SES but additionally by the socioeconomic characteristics of the neighborhood in which we live. Neighborhood SES may influence health through availability of health services and other resources, infrastructure, prevailing health attitudes and behaviors, social norms, environmental pollution, and stress (Pickett and Pearl 2001).

Epidemiological evidence has shown an increased risk of developing cardiovascular disease in more deprived areas (Diez-Roux et al. 1997, 2001; Sundquist et al. 2004). For example, in Sundquist et al., a random population sample followed up for incident CHD showed an increased risk associated with decreasing neighborhood income and education (Sundquist et al. 2004). By assessing the proportion of residents in each neighborhood with less than 10 years’ education and the ­proportion in the lowest national income quartile, a neighborhood SES score was assigned to each participant, enabling detection of this inverse association, which withstood multivariable adjustment. In addition to increased incidence of CHD, neighborhood deprivation has also been shown to be associated with increased case fatality. In a prospective study of almost four million Swedish men and women, CHD incidence was 1.9 times higher for women and 1.5 times higher for men in the most compared to the least deprived neighborhoods (Winkleby et al. 2007). Case fatality was similarly increased by around 1.6 times. This increased risk occurred regardless of individual SES.

Little data exists on the role of neighborhood SES after heart attack. The Israel Study of First Acute Myocardial Infarction assessed neighborhood SES by geocoding patients’ residential addresses based on census data. The authors found neighborhood SES to be strongly related to survival in MI patients, with individuals from the most disadvantaged areas 47 % more likely to die than those in the best neighborhoods, even after controlling for clinical factors and individual SES characteristics (Gerber et al. 2010). There was a clear dose-response pattern between neighborhood SES and post-MI mortality (Fig. 9.2). The relationship with cardiac death was even stronger. Similar results were published from a US study of MI survivors, with a 30 % higher mortality rate in the most deprived neighborhoods compared to the wealthiest and a 47 % higher death rate for areas with the highest proportion of residents with less than high school education (Tonne et al. 2005).

Based on these findings, the Israeli study group went on to investigate the association between neighborhood SES and health behaviors which could potentially mediate the relationship with post-MI outcomes. Indeed, they reported that post-MI patients living in the most deprived areas were less likely to be physically active than their counterparts living in better-off areas (Gerber et al. 2011b) (Fig. 9.3).

Neighborhood SES is also likely to influence access to health services. A study of 50,000 post-MI patients found that not only were those in less deprived areas more likely to undergo angiography within 6 months than their less well-off counterparts, but they also experienced shorter waiting times as well as improved survival (Alter et al. 1999).

Since SES is so strongly associated with cardiovascular development and ­progression, it stands to reason that by changing SES – not a trivial matter – ­cardiovascular risk may be altered. Several studies investigated the impact of social mobility on subsequent risk. The GAZEL French cohort study plotted socioeconomic trajectory by comparing father’s occupational grade, own occupation in early adulthood, and midlife occupation. Premature mortality was associated both with persistently low SES/occupational grade (termed “lifelong socioeconomic disadvantage”) and with downward mobility (moving from high to low-grade occupation). The strongest associations were for cancer and cardiovascular disease deaths (Melchior et al. 2006). The relationship was partially explained by tobacco and alcohol consumption, BMI, and diet. The authors concluded that while sustained socioeconomic disadvantage predicted premature mortality, occupational trajectory in adulthood played a greater part than socioeconomic circumstances in childhood. A study of Swedish women, also based on occupational class in childhood and adulthood, similarly found adult occupational status to be more strongly associated with CVD mortality than childhood status (Tiikkaja et al. 2009). Women whose occupational class went down (from nonmanual to manual) were twice as likely to die from CV cause compared to those who remained in nonmanual occupations, with a large percentage explained by educational level.

Barker theory lends support to the importance of childhood SES, proposing that early childhood factors influence the development of the heart, going as far back as pregnancy, with reports of low birth weight and small placental size being associated with development of CHD in adulthood (Barker et al. 2010). Childhood BMI measures were also related to the development of heart failure in adulthood. While research in this field is limited, these findings present the possibility of early intervention in childhood and even before birth to reduce levels of CHD in later life.