Social determinants of health (SDH) have substantial and broad impact on overall health, including cardiovascular health.1 SDH and socioeconomic status (SES) are multi-dimensional, interrelated, and may be challenging to quantify simply. Useful and commonly used metrics include yearly family income, insurance status, educational attainment, and neighborhood characteristics, including education, income, and built environment.2 The high cost of medical care may also place significant burden on patients, families, and communities.3 The extent to which these factors correlate with and cause worse cardiovascular outcomes is of tremendous importance.

In this issue of the Journal of Nuclear Cardiology, Kitkungvan et al. explore the association between financial distress, abnormal stress myocardial perfusion imaging, and downstream major adverse cardiac events (MACE) in a prospective cohort study design. The authors applied having medical insurance as a metric for financial hardship, a novel approach in the nuclear cardiology literature. Prior studies in this arena have focused on the adverse impact of lower socioeconomic status on cardiovascular health more generally and not specifically on access to cardiac PET studies.

Prior work has related lower SES with increased likelihood of premature coronary artery disease.4 In addition, lower SES has been correlated with increased incidence of ASCVD, as well as both increased cardiovascular and all-cause mortality.5 Other recent studies have reviewed how markers of SES impact management decisions in cardiovascular care. For example, one cohort of patients was reviewed following abnormal SPECT myocardial perfusion to identify factors associated with referral for invasive coronary angiography.6 This study found that referral for ICA was less likely in both uninsured patients as well as those of non-white race/ethnicity, even after controlling for other clinical variables.6 Another large retrospective study of patients presenting with NSTEMI found that those of non-white race were statistically less likely to undergo angiography and PCI, although this effect was largely eliminated when controlling for household income.7 Finally, increasing burden of adverse social determinants of health has been shown to be associated with higher financial toxicity from medical care in patients with cardiovascular disease.3 Despite this, prior literature on metrics of SES and abnormal cardiac imaging studies is very limited.

In the present study, a prospective cohort was enrolled consisting of all patients at a single center for whom stress PET myocardial perfusion imaging was ordered to evaluate for known or suspected coronary artery disease. Patients were monitored for development of adverse cardiac events, such as heart attack, stroke, and revascularization. Unique to this institution, all patients are served regardless of ability to pay. As a result, this population is quite unique and enables the authors to investigate how ability to afford diagnostic testing might be associated with differential clinical outcomes. The authors defined financial distress as the inability to afford payment for PET MPI. The authors found that patients with inability to afford PET MPI were likely to have more significant perfusion abnormalities. They also had more comorbidities ranging from hypertension to type II diabetes. Over time, those who were unable to afford PET MPI experienced a statistically significant increased rate of MACE (hazard ratio [HR] 2.168, 95% CI 1.658–2.834, P < .001), even after adjustment for comorbidities and PET findings. Causal mediation analysis demonstrated that this increased risk of MACE was not mediated by abnormal cardiac PET findings or known CAD at baseline—suggesting that a broader approach addressing comorbidities and complex SDOH may be necessary to improve cardiovascular outcomes among populations such as this.

Interestingly, percentage of insured patients in this study is higher than many studies on SES and cardiovascular disease. In one study assessing family income and its impact on cardiovascular disease risk, in the group with incomes at or below the poverty line, 37.4% of patients were uninsured, and the next higher-income group contained 28% uninsured patients, a group somewhat similar to the present study by Kitkungvan et al.8 This may be a consequence of the requirement for an initial visit with a medical provider to order the PET MPI scan. The uniqueness of this population may somewhat constrain generalizability of the findings.

The choice of inability to pay for stress PET MPI as surrogate for financial distress is also worthy of discussion. Inability to pay for this type of high-end study may be more transient than other metrics of socioeconomic status due to varying insurance coverage and policies. Given that patients with a higher burden of comorbidities had difficulty with affording the PET scan, it is possible that there is a component of reverse causation in which high cost of prior medical care caused subsequent difficulty with affording care or imaging. Previous work has shown that subjective measures of financial difficulties from medical care like inability to pay medical bills has been associated with delays in medical care or declining recommended treatment.9 This phenomenon has been described previously as a key component of the “financial toxicity” of medical care.3 The present study also used the zip code-based Distress Community Index, which combines seven SES and community characteristics.10 While geographic location of residence is suggestive of a patient’s socioeconomic status or background social determinants of health, it may also be subject to some degree of misclassification. Finally, given that many patients were likely referred to the study center specifically due to their widely known policy of accepting all patients regardless of ability to pay, there may be some degree of referral bias.

More generally, SDH are complex and multi-dimensional and may be difficult to quantify with a singular metric. Other aspects of SDH not characterized in this study likely also play a significant role in determining health outcomes, such as education, employment status, gender, race, ethnicity, language, cultural background, marital status, and built environment issues, such as access to green spaces and food establishments. Even financial factors may have many other manifestations, such as challenges with paying bills, housing insecurity, and lack of access to affordable and nutritious food.11,12,13 Future studies should employ multi-dimensional approaches to consider these issues broadly.

Nonetheless, studies such as this are vital first steps in exploring the impact of SES and SDOH on nuclear cardiology services and the role they play in overall cardiovascular care and CVD outcomes. The finding that patients with hardships are more likely to have abnormal studies but that the abnormal PET MPI studies do not directly mediate the worse outcomes, this population experiences is a critical insight which will no doubt help design future studies and financial support programs.