Cardiac Rehabilitation

Extensive research consistently demonstrates a strong association between lower socioeconomic status (SES), uncontrolled cardiovascular disease (CVD) risk factors, and suboptimal health outcomes in patients with CVD.1 Four markers of SES including income level, educational attainment, employment status, and environmental factors have been shown to have a profound impact on the prevalence, progression, and outcomes of CVD.1 Several interrelated factors contribute to this relationship, including limited access to health care services, reduced educational opportunities, and income disparities.2–6 Individuals with lower SES often face barriers to adopting healthier lifestyles, such as engaging in regular physical activity and maintaining a balanced diet, which are essential for CVD prevention.7 Additionally, psychosocial stressors associated with socioeconomic disadvantage, such as job insecurity and financial strain, can contribute to the development of CVD through mechanisms involving chronic inflammation and sympathetic nervous system dysregulation.8 These disparities in risk, prevention, and treatment outcomes underscore the importance of addressing socioeconomic inequalities as a fundamental component of strategies aimed at reducing the global burden of CVD. As the cornerstone of secondary CVD prevention, cardiac rehabilitation (CR) incorporates supervised exercise training, cardiovascular health education, health behavior modification, and CVD risk factor control to improve outcomes following a CVD diagnosis or event.9 Despite its clear evidence base for reducing CVD and all-cause mortality, it is highly underutilized by populations experiencing socioeconomic disadvantage.10 In this issue of the Journal of Cardiopulmonary Rehabilitation and Prevention, Khadanga and colleagues provide a prospective cohort analysis examining differences in risk factor profiles among >3000 patients enrolling in outpatient phase 2 CR based on SES.11 Utilizing enrollment in Medicaid as a marker of low SES, the authors found striking differences in risk factor profiles between patients enrolled in Medicaid and those enrolled in Medicare or private insurance. Despite being on average 10 yr younger than those of higher SES, patients with lower SES demonstrated lower cardiorespiratory fitness as measured by peak oxygen uptake during exercise in addition to lower self-reported physical function. Patients with low SES were also drastically more likely to be current smokers, have higher depressive symptoms, and have abnormal clinical factors (eg, body mass index, waist circumference, hemoglobin A1c, and lipid profiles) compared with patients with high SES. Women with low SES demonstrated significant physical limitations and increased depressive symptoms compared with men with low SES. The authors also found that the presence of any CVD risk factor was more common in patients with low SES, with over a third having four or more risk factors. Smoking and depressive symptoms were the most discordant CVD risk factors measured based on SES. Given the large disparity in modifiable CVD risk factors between patients with lower versus higher SES, the authors concluded that a greater emphasis should be placed on implementing behavioral interventions within standard CR programs to address CVD risk factors in this vulnerable population. Notably, part of the enrollment period occurred during the COVID-19 pandemic, which further exacerbated CVD risk factor disparities among patients with low SES.12 TAILORING CARDIAC REHABILITATION PROGRAMS TO ADDRESS UNIQUE PATIENT RISKS While the impact of SES on CVD is well established, this is among the first studies to evaluate the differences in CVD risk factor profiles based on SES among patients enrolling in CR. The frequent interactions between patients and health care professionals over the course of CR (typically 36 interactions over 12-16 wk) create an ideal environment for introducing novel interventions designed to empower patients with high CVD risk to make healthy lifestyle changes.9 Additionally, patients enrolling in CR have recently experienced a major cardiovascular event, which potentially increases their motivation to adopt such changes.13 Gaining insights into the specific CVD risk factor profiles of patients enrolling in CR enables CR programs to tailor their offerings, which may better meet the needs of patients facing overwhelming barriers to behavioral change/risk factor modification.14 We commend Khadanga and investigators for recognizing a critical opportunity to promote individualized patient care and better support patients with lower SES. The authors acknowledge several study limitations that may limit generalizability of their findings. Specifically, the authors note that their study was conducted at a single site and only utilized one measure of SES to compare patients, a metric that often varies with time and notably omits patients without health insurance. Patients enrolled in Medicaid often have income fluctuations and frequent burdensome eligibility evaluations, which result in patients cycling on and off the program.15 Additionally, there was no stratification by race/ethnicity, potentially reflecting lack of diversity or homogeneity of the patient sample. Additional multisite studies evaluating CVD risk factor profiles based on more comprehensive assessments of SES could deepen the socioenvironmental understanding of patient needs to maximize the effectiveness of such tailored interventions. Moreover, the authors cite several studies that demonstrate dismal CR referral/enrollment in patients with low SES, a prerequisite to even gain access to the beneficial CVD risk factor modification interventions afforded by CR.10,16–19 Thus, rigorous evaluation of novel interventions that both expand CR access to patients with low SES and tailor CR content to address CVD risk factor disparities is imperative. FUTURE RESEARCH DIRECTIONS Based on their findings, Khadanga and colleagues propose the incorporation of more patient-centric interventions within standard CR programs aimed to specifically address the disparate CVD risk factor profiles noted in their study.11 For example, they suggest implementing referrals to interventions for psychological symptom treatment and incorporating behavioral weight loss programs with comprehensive diet and exercise education. Unfortunately, standard interventions aimed at CVD risk factor modification in the general population have not consistently shown similar benefit in patients with low SES.1 For example, a study by Jiang and colleagues showed that patients with lower household income had a less robust weight loss response to standard interventions addressing weight loss, dietary modification, and physical activity than those with higher household incomes.20 To bolster the above proposed interventions, researchers and clinicians must understand the complex social determinants of health that influence risk factors among patients with low SES to develop effective CVD risk factor modification strategies. A growing body of literature demonstrates immense value in engaging community members within target populations in the design and implementation of innovative lifestyle interventions.21 Community-engaged research has emerged as a powerful tool in addressing CVD risk factors among historically marginalized groups, including populations with low SES.22–25 This approach prioritizes collaboration among researchers, health care professionals, and community partners from diverse populations who have first-hand experience of social, environmental, and cultural factors that either promote or hinder optimal cardiovascular health.21 Community engagement fosters trusting relationships between health care team members and patients leading to more culturally sensitive and effective interventions.21 Given the complex interplay between various psychosocial factors that influence the disparate SES-based CVD risk factor profiles identified by Khadanga et al, community-engaged research is imperative to successfully employ novel strategies to modify such risks among those most affected by CVD. CONCLUSIONS In summary, Khadanga and colleagues astutely identified CR as an optimal opportunity to tailor interventions to better address the complex psychosocial needs of patients with low SES to attenuate their disproportionate burden of suboptimal CVD outcomes. Understanding disparities in CVD risk factor profiles in patients with low SES entering CR has the potential to inform equity-focused interventions customized to meet and address the specific needs of this population. Additional population-level research is needed to provide a more nuanced understanding of the barriers faced by patients of lower SES including those related to CR access as well as to their meaningful participation in and completion of this highly valuable secondary CVD prevention modality. Authentic community engagement may provide an avenue to accomplish this worthy goal.