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September 16, 2022

Study underscores the relationship between social conditions and heart disease

The results could help health professionals and policymakers plan interventions for the most vulnerable diabetic CVD patients.

By GlobalData Healthcare

Social determinants of health have inspired a growing body of work on the influence of race, gender and socioeconomic status (SES) on health outcomes. A recent publication by Corwin and colleagues in JAMA Network Open contributes to the literature by exploring the impact of specific indicators of social hardship (such as economic security, healthcare access and social support) on cardiovascular disease (CVD) risk among elderly diabetic patients. Using nationally representative data, the authors identified a positive correlation between biomarkers for higher CVD risk and several of these indicators.

Accordingly, the publication offers a more granular view into the epidemiology of CVD by shedding light on who falls into its risk profiles and noting what facets of their lives contribute to its incidence. Given that GlobalData epidemiologists expect a rise in diabetics with CVD in the US within the next decade, these results could help health professionals and policymakers plan interventions for the most vulnerable demographic groups among diabetic CVD patients.

The authors considered data for older diabetic Americans participating in the longitudinal, nationally representative Health and Retirement Study (HRS) between 2006 and 2016, yielding a cohort of nearly 5,000 participants. The HRS consists of case interviews and biomarker collection, allowing for insights into the social, economic and environmental conditions of participants, as well as key medical indicators. To quantify CVD risk, the authors measured glycaemic, cholesterol and blood pressure control, which were aggregated into a composite score. CVD risk was analysed regarding various indicators of social risk, including healthcare access, education, economic security, built environment, and the physical and perceived social attributes of participants’ neighbourhoods for signs of correlation.

This analysis highlighted significant relationships between inadequate cholesterol control and lacking access to education and healthcare, adverse social support and poor glycaemic control, and access to healthcare and affordable medication with poor blood pressure control. Furthermore, participants who identified as racial or ethnic minorities experienced a 97% higher likelihood of poor glycaemic control than non-Hispanic white participants.

While recent literature has built a strong case for the association between SES, race and heightened CVD risk, Corwin and colleagues shed light on the interplay between particular social conditions and health indicators underlying this pattern. In a clinical setting, practitioners can consider these findings when formulating risk profiles and plans of care for diabetic patients from marginalised communities. However, many of the conclusions drawn from the data suggest that broader, structural factors such as environmental conditions and equitable access to care play a larger role than the clinical experience. For that reason, the study’s chief utility is to policymakers and community health specialists, whose interventions may need to adopt a more targeted approach depending on their community of interest.

GlobalData epidemiologists forecast that in the US, the diagnosed prevalent cases of type 2 diabetes with CVD as a comorbidity will rise from under 7.35 million cases to nearly eight million cases between now and 2028. Although current models do not yet segment these cases by race or SES, the observed study lends a more granular view into the profile of diabetic patients who are most at risk for developing CVD.

Given the structural influences identified by analysts such as Corwin and colleagues, it is also important to consider the impact of health policy. National legislation aimed at expanding infrastructure and lowering drug prices, as well as California’s recent passage of a bill supporting state-run generic prescription drug production, suggest that the policy landscape is shifting toward addressing some of the adverse social conditions identified by the authors. These patterns indicate tangible–if modest–changes to the state of chronic disease health disparities in the US.

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