Socioeconomic status (SES) has a measurable and significant effect on cardiovascular health. Biological, behavioral, and psychosocial risk factors prevalent in disadvantaged individuals accentuate the link between SES and cardiovascular disease (CVD). Four measures have been consistently associated with CVD in high-income countries: income level, educational attainment, employment status, and neighborhood socioeconomic factors. In addition, disparities based on sex have been shown in several studies. Interventions targeting patients with low SES have predominantly focused on modification of traditional CVD risk factors. Promising approaches are emerging that can be implemented on an individual, community, or population basis to reduce disparities in outcomes. Structured physical activity has demonstrated effectiveness in low-SES populations, and geomapping may be used to identify targets for large-scale programs. Task shifting, the redistribution of healthcare management from physician to nonphysician providers in an effort to improve access to health care, may have a role in select areas. Integration of SES into the traditional CVD risk prediction models may allow improved management of individuals with high risk, but cultural and regional differences in SES make generalized implementation challenging. Future research is required to better understand the underlying mechanisms of CVD risk that affect individuals of low SES and to determine effective interventions for patients with high risk. We review the current state of knowledge on the impact of SES on the incidence, treatment, and outcomes of CVD in high-income societies and suggest future research directions aimed at the elimination of these adverse factors, and the integration of measures of SES into the customization of cardiovascular treatment.

Cardiovascular disease is a leading cause of morbidity and mortality worldwide, and a key barrier to improved outcomes is medication non-adherence. The aim of this study is to review the role of mobile health (mHealth) tools for improving medication adherence in patients with cardiovascular disease. We performed a systematic search for randomized controlled trials that primarily investigated mHealth tools for improving adherence to cardiovascular disease medications in patients with hypertension, coronary artery disease, heart failure, peripheral arterial disease, and stroke. We extracted and reviewed data on the types of mHealth tools used, preferences of patients and healthcare providers, the effect of the mHealth interventions on medication adherence, and the limitations of trials. We identified 10 completed trials matching our selection criteria, mostly with <100 participants, and ranging in duration from 1 to 18 months. mHealth tools included text messages, Bluetooth-enabled electronic pill boxes, online messaging platforms, and interactive voice calls. Patients and healthcare providers generally preferred mHealth to other interventions. All 10 studies reported that mHealth interventions improved medication adherence, though the magnitude of benefit was not consistently large and in one study was not greater than a telehealth comparator. Limitations of trials included small sample sizes, short duration of follow-up, self-reported outcomes, and insufficient assessment of unintended harms and financial implications. Current evidence suggests that mHealth tools can improve medication adherence in patients with cardiovascular diseases. However, high-quality clinical trials of sufficient size and duration are needed to move the field forward and justify use in routine care.

Aims Mental stress-induced myocardial ischemia (MSIMI) in patients with coronary artery disease (CAD) is associated with adverse cardiovascular outcomes. We aim to assess hemodynamic, neuro-hormonal, endothelial, vasomotor and vascular predictors of MSIMI. Methods and Results We subjected 660 patients with stable CAD to 99mTc sestamibi myocardial perfusion imaging at rest, with mental (speech task) and with conventional (exercise/pharmacological) stress. Endothelium-dependent flow-mediated dilation (FMD), microvascular reactivity [reactive hyperemia index (RHI)] and arterial stiffness [pulse wave velocity (PWV)] were measured at rest and 30-min after mental stress. The digital microvascular vasomotor response during mental stress was assessed using peripheral arterial tonometry (PAT). A total of 106(16.1%) patients had MSIMI. Mental stress was accompanied by significant increases in rate-pressure-product (heart rate x systolic blood pressure; RPP), epinephrine levels and PWV, and significant decreases in FMD and PAT ratio denoting microvascular constriction. In comparison to those with no MSIMI, patients with MSIMI had higher hemodynamic and digital vasoconstrictive responses (p<0.05 for both), but did not differ in epinephrine, endothelial or macrovascular responses. Only presence of ischemia during conventional stress (OR of 7.1, 95%CI of 4.2, 11.9), high hemodynamic response (OR for RPP response ≥ vs < ROC cutoff of 1.8, 95%CI of 1.1, 2.8), and high digital vasoconstriction (OR for PAT ratio < vs ≥ ROC cutoff of 2.1, 95%CI of 1.3, 3.3) were independent predictors of MSIMI. Conclusion Ischemia during conventional stress testing and hemodynamic and vasoconstrictive responses to mental stress can help predict subjects with CAD at greater risk of developing MSIMI.