1. Hayman, Laura L. PhD, RN, FAAN, FAHA
  2. Worel, Jane Nelson MSN, APRN-BC, APNP, FAHA

Article Content

Mortality from cardiovascular disease (CVD) has decreased substantially in the United States over the past 5 decades.1 Advances in both prevention and treatment have been credited for this positive trend. Important to note, however, is that the burden of CVD remains high, particularly in marginalized subgroups of the population, and the prevalence is projected to increase approximately 10% between 2010 and 2030.2 Several reasons have been offered for these projections, including the aging of the US population and the substantial increases in chronic conditions, particularly obesity.1 Epidemiological and clinical studies have documented an excess burden of obesity, its comorbidities, and adverse behavioral-lifestyle patterns in subgroups of the US population, including racial/ethnic minorities and those from lower socioeconomic strata.1 Viewed from a socioecological perspective, considerable research attention has focused on factors that operate beyond the individual level to alter life course trajectories that result in excess risk and burden of CVD. On the basis of accumulated evidence, the American Heart Association (AHA) recently issued a scientific statement that highlights the importance of the social correlates and determinants of both risk and outcomes for CVD.3


The World Health Organization has defined the social determinants of health broadly as "the circumstances in which people are born, grow, live, work and age and the systems put in place to deal with illness."4 Consistent with life course socioecological perspectives, this World health Organization definition was operationalized in the AHA statement with evidence indicating social economic position, race/ethnicity, social support, culture and language, access to care, and residential environment as social determinants of health.3 Recent research and systematic reviews strongly suggest that socioeconomic conditions early in life contribute to risk for CVD in adulthood, particularly when early-life factors influence the developmental trajectories of conventional risk factors such as blood pressure, lipid levels, body mass index, and health behaviors.5 Harper and colleagues5 suggest that the interactions among early-life socioeconomic environments and risk factor trajectories influence both the development and maintenance of health behaviors and their "cumulative biological sequelae" as part of a major life-course process linking social economic position in early life to CVD in adulthood.


Racial/ethnic differences in the prevalence, treatment, and outcomes of CVD have been investigated extensively and well documented. As summarized by Havranek and colleagues in the AHA statement,3 numerous factors interact to influence the excess burden of CVD in racial/ethnic minority populations. Points of emphasis that are particularly relevant to healthcare providers include the concepts of implicit bias and stereotype threat that may be root causes of disparate care.3 Although research has demonstrated that clinicians exhibit minimal explicit or intentional bias in clinical decision making that influences care provided, implicit (unconscious, attitudinal) bias has been well documented.6-8 Several studies have demonstrated that implicit bias may result in lower-quality clinical interactions and communication between clinicians and minority patients.6-8 For example, in a study of primary care providers, Blair and colleagues6 observed that implicit race bias predicted differences between black and white patients' reports of their clinicians' patient centeredness. Black patients in this study reported less interpersonal treatment and poorer communication, reducing comfort and trust in clinicians who were previously categorized as having higher levels of implicit racial bias.6 Substantial research has focused on patients' perceptions of discrimination and bias during healthcare encounters. One comprehensive review indicated that 52% of blacks, 13% of Latinos, and 6% of non-Hispanic whites reported biased treatment based on their respective race or ethnicity.9 Although the results are not consistent across studies, perception of biased treatment has been associated with self-reports of poorer health status, self care, adherence to treatment regimens, and underutilization of available health services.3,9 Although less data are available on stereotype threat, the often unconscious fear of being judged negatively according to racial stereotypes, evidence suggests adverse effects on patient-provider communication and patient adherence.10,11


Social support and its links with health and illness across the life course of individuals from diverse populations have been investigated extensively. Although evidence indicates significant associations between low levels of social support and risk for and outcomes of CVD, lacking are effective interventions designed to increase social support.3,12 In relation, social networks have emerged as an important area of emphasis thought to influence health through social influence on behavior and through the material resources (social capital) available to respective members.13 Of note, as documented in a national survey by Marsden,14 whites have social networks of greater size and diversity compared with their Latino and black counterparts. Lacking, however, are data on the mechanisms by which social networks influence health and healthcare for individuals from diverse racial/ethnic populations.


Accumulated data and anecdotal clinical observations point to the importance of language differences and cultural beliefs and practices as important social determinants of health-seeking behaviors and access to and utilization of healthcare services. Results of several studies point to the promise and potential of community health workers as part of healthcare teams in reducing these barriers and improving both prevention and control of CVD.15-18 Often, members of the target population with similar cultural and linguistic practices, community health workers, assume numerous roles in facilitating access to healthcare services, monitoring patient health status, improving patient-provider communication, and adherence to treatment regimens.15-18


Taken together and as summarized by Havranek and colleagues,3 additional research is needed to explicate the specific mechanisms through which these social determinants influence both risk and outcomes for CVD and to guide and inform effective and efficient multilevel interventions designed to attenuate adverse social influences and optimize cardiovascular health for all. Cognizant of the importance of social factors in both prevention and management of CVD, cardiovascular nurses are well prepared and positioned to add to the existing knowledge base and to advocate for multilevel policies designed to mitigate adverse social influences.



Laura L. Hayman acknowledges grant support from the National Institute of Minority Health and Health Disparities (1 P60 MD006912-03).




1. Mozaffarian D, Benjamin EJ, Go AS, et al. Executive summary: heart disease and stroke statistics-2016 update: a report from the American Heart Association. Circulation. 2016;133:447-454. doi:10.1161/CIR.0000000000000366. [Context Link]


2. Heidenrich PA, Albert NM, Allen LA, et al. Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association. Circ Heart Fail. 2013;6:606-619. doi:10.1161/HHF.Ob013e318291329a. [Context Link]


3. Havranek EP, Mujahid MS, Barr DA, et al. Social determinants of risk and outcomes for cardiovascular disease: a scientific statement from the American Heart Association. Circulation. 2015;132:873-898. doi:10.1161/CIR.0000000000000228. [Context Link]


4. Marmot M, Fried S, Bell R, Houweling TA, Taylor S; Commission on social determinants of health. Closing the gap in a generation: health equity through action on the social determinants of health. Lancet. 2008;372:1661-1669. doi:10.1146/annurev.publhealth.18.1.341. [Context Link]


5. Harper S, Lynch L, Smith GD. Social determinants and the decline of cardiovascular disease: understanding the links. Annu Rev Public Health. 2011;32:39-69. doi:10.1146/annurev-publhealth-031210-101234. [Context Link]


6. Blair IV, Havranek EP, Price DW, et al. Assessment of biases against Latinos and African Americans among primary care providers and community members. Am J Public Health. 2013;103:92-98. doi:10.205/AJPH.2012.300812. [Context Link]


7. Green AR, Carney DR, Palin DJ, et al. Implicit bias among physicians and its prediction of thrombolysis decisions for black and white patients. J Gen Intern Med. 2007;22:1231-1238. doi:10.1007/s11606-007-0258-5. [Context Link]


8. Sabin J, Nosek BA, Greenwald A, Rivara FP. Physicians' implicit and explicit attitudes about race by MD race, ethnicity, and gender. J Health Care Poor Underserved. 2009;20:896-913. doi:10.1353/hpu.0.0185. [Context Link]


9. Shavers VL, Fagan P, Jones D, et al. The state of research on racial/ethnic discrimination in the receipt of health care. Am J Publ Health. 2012;102:953-966. doi:10.2105/AJPH.2012.300773. [Context Link]


10. Burgess DJ, Warren J, Phelan S, Dovidio J, van Ryn M. Stereotype threat and health disparities: what medical educators and future physicians need to know. J Gen Intern Med. 2010;25(suppl 2):S169-S177. doi:10:1007/s11606-009-1221-4. [Context Link]


11. Havranek EO, Hanratty R, Tate C, et al. The effect of values affirmation on race-discordant patient-provider communication. Arch Intern Med. 2012;172:1662-1667. doi:10.1001/2013.jamaintermed.258. [Context Link]


12. Stansfeld SA. Social support and social cohesion. In: Marmot M, Wilkinson R, eds. Social Determinants of Health. Oxford, UK: Oxford University Press; 2006:155-174. [Context Link]


13. Lin N. Inequality in social capital. Contemp Sociol. 200;29:785-795. [Context Link]


14. Marsden PV. Homogeneity in confiding relations. Soc Networks. 1988;10:57-76. [Context Link]


15. Brownstein JN, Bone LR, Dennison CR, Hill MN, Kim MT, Levine DM. Community health workers as interventionists in the prevention and control of heart disease and stroke. Am J Prev Med. 2005;29(suppl1):128-133. doi:10.1016/j.amepre.2005.07.024. [Context Link]


16. Allen JK, Dennison-Himmelfarb CR, Szanton SL, et al. Community outreach and cardiovascular health (COACH) trial: a randomized, controlled trial of nurse practitioner/community health worker cardiovascular disease risk reduction in urban community health centers. Circ Cardiovasc Qual Outcomes. 2011;4:595-602. doi:10.1161/CIRCOUTCOMES.111.961573. [Context Link]


17. Choi SE, Rush EB. Effect of a short-duration, culturally tailored, community-based diabetes self-management intervention for Korean immigrants: a pilot study. Diabetes Educ. 2012;38:377-385. doi:10.1177/014572171244392. [Context Link]


18. Levesque JF, Harris MF, Russell G. Patient-centred access to health care: conceptualising access at the interface of health systems and populations. Int J Equity Health. 2013;12:18. doi:10.1186/1475-9276-12-18. [Context Link]