Social Determinants of Cardiovascular Health: A Longitudinal Analysis of Cardiovascular Disease Mortality in US Counties From 2009 to 2018

Rationale, design, and participant characteristics of the FAITH! Heart Health+ study: An exploration of the influence of the social determinants of health, stress, and structural racism on African American cardiovascular health

BACKGROUND

African Americans (AAs) face cardiovascular health (CVH) disparities linked to systemic racism. The 2020 police killing of Mr. George Floyd in Minneapolis, Minnesota, alongside the COVID-19 pandemic, exacerbated adverse psychosocial factors affecting CVH outcomes among AAs. This manuscript describes the study protocol and participant characteristics in an ancillary study exploring the relationship between biopsychosocial factors and CVH among AAs.

METHODS

Using a community-based participatory approach, a mixed-methods ancillary study of 58 AA participants from an overarching randomized control trial (RCT) was conducted. Baseline RCT health assessments (November 2020) provided sociodemographic, medical, and clinical data. Subsequent health assessments (February-December 2022) measured sleep quality, psychosocial factors (e.g., high-effort coping), biomarkers (e.g., cortisol), and cardiovascular diagnostics (e.g., cardio-ankle vascular index). CVH was assessed using the American Heart Association Life's Simple 7 (LS7) (range 0 to 14, poor to ideal) and Life's Essential 8 (LE8) scores (range 0 to 100, low to high). Correlations between these scores will be examined. Focus group discussions via videoconferencing (March to April 2022) assessed psychosocial and structural barriers, along with the impact of COVID-19 and George Floyd's killing on daily life.

RESULTS

Participants were predominantly female (67%), with a mean age of 54.6 [11.9] years, high cardiometabolic risk (93% had overweight/obesity and 70% hypertension), and moderate LE8 scores (mean 57.4, SD 11.5).

CONCLUSION

This study will enhance understanding of the associations between biopsychosocial factors and CVH among AAs in Minnesota. Findings may inform risk estimation, patient care, and healthcare policies to address CVD disparities in marginalized populations.

Health Literacy, Individual and Community Engagement, and Cardiovascular Risks and Disparities: JACC: CardioOncology State-of-the-Art Review

Cardiovascular and cancer outcomes intersect within the realm of cardio-oncology survivorship care, marked by disparities across ethnic, racial, social, and geographical landscapes. Although the clinical community is increasingly aware of this complex issue, effective solutions are trailing. To attain substantial public health impact, examinations of cancer types and cardiovascular risk mitigation require complementary approaches that elicit the patient's perspective, scale it to a population level, and focus on actionable population health interventions. Adopting such a multidisciplinary approach will deepen our understanding of patient awareness, motivation, health literacy, and community resources for addressing the unique challenges of cardio-oncology. Geospatial analysis aids in identifying key communities in need within both granular and broader contexts. In this review, we delineate a pathway that navigates barriers from individual to community levels. Data gleaned from these perspectives are critical in informing interventions that empower individuals within diverse communities and improve cardio-oncology survivorship.

Examining the relationship between social determinants of health, measures of structural racism and county-level overdose deaths from 2017-2020

INTRODUCTION

Despite being an important determinant of health outcomes, measures of structural racism are lacking in studies examining the relationship between the social determinants of health (SDOH) and overdose deaths. The aim of this study is to examine the association between per capita revenue generated from fines and forfeitures, a novel measure of structural racism, and other SDOH with county-level overdose deaths from 2017-2020.

METHODS

This longitudinal analysis of 2,846 counties from 2017-2020 used bivariate and multivariate Generalized Estimating Equations models to estimate associations between county overdose mortality rates and SDOH characteristics, including the fines and forfeitures measure.

RESULTS

In our multivariate model, higher per capita fine and forfeiture revenue (5.76; CI: 4.76, 6.78), households receiving food stamps (1.15; CI: 0.77, 1.53), residents that are veterans (1.07; CI: 0.52, 1.63), substance use treatment availability (4.69; CI: 3.03, 6.33) and lower population density (-0.002; CI: -0.004, -0.001) and percent of Black residents (-0.7`; CI: -1.01, -0.42) were significantly associated with higher overdose death rates. There was a significant additive interaction between the fines and forfeitures measure (0.10; CI: 0.03, 0.17) and the percent of Black residents.

CONCLUSIONS

Our findings suggest that structural racism, along with other SDOH, is associated with overdose deaths. Future research should focus on connecting individual-level data on fines and forfeitures to overdose deaths and other health outcomes, include measures of justice-related fines, such as court fees, and assess whether interventions aimed at increasing economic vitality in disadvantaged communities impact overdose deaths in a meaningful way.

Comprehensively evaluating the relationships between marital status and other family factors with cardiovascular disease and long-term overall mortality in the elderly: a study of 48 510 Chinese individuals

BACKGROUND

Marital status is associated with cardiovascular disease (CVD) incidence and overall mortality, yet limited research on this topic in elderly individuals is available. Our aim was to comprehensively assess the impact of marital status and other family factors on CVD incidence and long-term mortality among elderly people.

METHODS

Data from the Chinese Longitudinal Healthy Longevity Survey (2002/2005/2008-2018) for participants aged ≥60 years were analysed. A cross-sectional study initially examined the correlation between spouses, offspring, living arrangements, and CVD using logistic regression. Subsequently, a retrospective cohort study investigated the long-term associations of these factors with overall mortality via Kaplan-Meier and Cox regression analyses.

RESULTS

The study involved 48 510 subjects (average age: 87 years). The cross-sectional analysis revealed a correlation between living with a spouse and an increased incidence of heart disease (adjusted OR 1.27, 95% CI 1.04-1.55) and cerebrovascular disease/stroke (adjusted OR 1.26, 95% CI 1.11-1.42). According to the retrospective cohort analysis, living with a spouse significantly reduced overall mortality (adjusted HR 0.84, 95% CI 0.80-0.87), irrespective of marital relationship quality. Conversely, living with offspring (adjusted HR 1.12, 95% CI 1.08-1.16), having more children (adjusted Pnonlinearity = 0.427) or cohabitants (adjusted Pnonlinearity < 0.0001) were associated with increased overall mortality.

CONCLUSION

In the elderly population, being married and living with a spouse were not significantly associated with a decrease in CVD incidence but were associated with a reduction in long-term overall mortality. Living with offspring, having more children, or having a larger family size did not replicate the protective effect but indicated greater overall mortality.

Discrimination and Cardiovascular Health in Black Americans: Exploring Inflammation as a Mechanism and Perceived Control as a Protective Factor

OBJECTIVE

Inflammation may be an integral physiological mechanism through which discrimination impacts cardiovascular health and contributes to racial health disparities. Limited research has examined psychosocial factors that protect against the negative effects of discrimination on inflammation. Perceived control is a promising possible protective factor, given that it has been shown to moderate the relationship between other psychosocial stressors and physiological outcomes. This study thus tested whether systemic inflammation mediated the link between discrimination and cardiovascular health and whether perceived control moderated this relationship.

METHODS

Data for this project included 347 non-Hispanic/Latinx Black adults (mean [standard deviation] age = 51.64 [11.24] years; 33% female) taken from the Midlife in the United States study. Perceived control and daily discrimination were assessed via self-report, and inflammation was measured via circulating levels of C-reactive protein (CRP), interleukin-6 (IL-6), fibrinogen, and tumor necrosis factor α. Cardiovascular health was measured by morbidity of cardiovascular conditions: heart disease, hypertension, and/or stroke.

RESULTS

CRP (indirect effect: b = 0.004, 95% confidence interval [CI] = 0.001-0.007) and fibrinogen (indirect effect: b = 0.002, 95% CI = 0.0003-0.005) mediated the link between discrimination and cardiovascular conditions. Perceived control moderated the relationship between discrimination and CRP ( F (1, 293) = 4.58, Δ R2 = 0.013, b = -0.02, SE = 0.01, p = .033). CRP mediated the link between discrimination and cardiovascular conditions only for those who reported low levels of perceived control (Index = -0.003, 95% CI = -0.007 to -0.0001).

CONCLUSION

Findings provide empirical evidence of inflammation as a mechanism linking discrimination to cardiovascular conditions among Black Americans. Additionally, perceived control may be protective. Findings could suggest beliefs about control as a potential intervention target to help reduce the negative effects of discrimination on cardiovascular health among Black Americans.

Rurality, Cardiovascular Risk Factors, and Early Cardiovascular Disease among Childhood, Adolescent, and Young Adult Cancer Survivors

Background and Aims

Cardiovascular risk factors (CVRFs) later in life potentiate risk for late cardiovascular disease (CVD) from cardiotoxic treatment among survivors. This study evaluated the association of baseline CVRFs and CVD in the early survivorship period.

Methods

This analysis included patients ages 0-29 at initial diagnosis and reported in the institutional cancer registry between 2010 and 2017 (n = 1228). Patients who died within five years (n = 168), those not seen in the oncology clinic (n = 312), and those with CVD within one year of diagnosis (n = 17) were excluded. CVRFs (hypertension, diabetes, dyslipidemia, and obesity) within one year of initial diagnosis, were constructed and extracted from the electronic health record based on discrete observations, ICD9/10 codes, and RxNorm codes for antihypertensives.

Results

Among survivors (n = 731), 10 incident cases (1.4%) of CVD were observed between one year and five years after the initial diagnosis. Public health insurance (p = 0.04) and late effects risk strata (p = 0.01) were positively associated with CVD. Among survivors with public insurance(n = 495), two additional cases of CVD were identified from claims data with an incidence of 2.4%. Survivors from rural areas had a 4.1 times greater risk of CVD compared with survivors from urban areas (95% CI: 1.1-15.3), despite adjustment for late effects risk strata.

Conclusions

Clinically computable phenotypes for CVRFs among survivors through informatics methods were feasible. Although CVRFs were not associated with CVD in the early survivorship period, survivors from rural areas were more likely to develop CVD.

Implications for Survivors

Survivors from non-urban areas and those with public insurance may be particularly vulnerable to CVD.

Lack of leisure time physical activity and variations in cardiovascular mortality across US communities: a comprehensive county-level analysis (2011-2019)

OBJECTIVES

To investigate the associations between county-level proportions of adults not engaging in leisure-time physical activity (no LTPA) and age-adjusted cardiovascular mortality (AACVM) rates in the overall US population and across demographics.

METHODS

Analysing 2900 US counties from 2011 to 2019, we used the Centers for Disease Control and Prevention (CDC) databases to obtain annual AACVM rates. No LTPA data were sourced from the CDC's Behavioural Risk Factor Surveillance System survey and county-specific rates were calculated using a validated multilevel regression and poststratification modelling approach. Multiple regression models assessed associations with county characteristics such as socioeconomic, environmental, clinical and healthcare access factors. Poisson generalised linear mixed models were employed to calculate incidence rate ratios (IRR) and additional yearly deaths (AYD) per 100 000 persons.

RESULTS

Of 309.9 million residents in 2900 counties in 2011, 7.38 million (2.4%) cardiovascular deaths occurred by 2019. County attributes such as socioeconomic, environmental and clinical factors accounted for up to 65% (adjusted R2=0.65) of variance in no LTPA rates. No LTPA rates associated with higher AACVM across demographics, notably among middle-aged adults (standardised IRR: 1.06; 95% CI (1.04 to 1.07)), particularly women (1.09; 95% CI (1.07 to 1.12)). The highest AYDs were among elderly non-Hispanic black individuals (AYD=68/100 000).

CONCLUSIONS

Our study reveals a robust association between the high prevalence of no LTPA and elevated AACVM rates beyond other social determinants. The most at-risk groups were middle-aged women and elderly non-Hispanic black individuals. Further, county-level characteristics accounted for substantial variance in community LTPA rates. These results emphasise the need for targeted public health measures to boost physical activity, especially in high-risk communities, to reduce AACVM.

Closing the Last Mile Gap in Access to Multimodality Imaging in Rural Settings: Design of the Imaging Core of the Risk Underlying Rural Areas Longitudinal Study

Achieving optimal cardiovascular health in rural populations can be challenging for several reasons including decreased access to care with limited availability of imaging modalities, specialist physicians, and other important health care team members. Therefore, innovative solutions are needed to optimize health care and address cardiovascular health disparities in rural areas. Mobile examination units can bring imaging technology to underserved or remote communities with limited access to health care services. Mobile examination units can be equipped with a wide array of assessment tools and multiple imaging modalities such as computed tomography scanning and echocardiography. The detailed structural assessment of cardiovascular and lung pathology, as well as the detection of extracardiac pathology afforded by computed tomography imaging combined with the functional and hemodynamic assessments acquired by echocardiography, yield deep phenotyping of heart and lung disease for populations historically underrepresented in epidemiological studies. Moreover, by bringing the mobile examination unit to local communities, innovative approaches are now possible including engagement with local professionals to perform these imaging assessments, thereby augmenting local expertise and experience. However, several challenges exist before mobile examination unit-based examinations can be effectively integrated into the rural health care setting including standardizing acquisition protocols, maintaining consistent image quality, and addressing ethical and privacy considerations. Herein, we discuss the potential importance of cardiac multimodality imaging to improve cardiovascular health in rural regions, outline the emerging experience in this field, highlight important current challenges, and offer solutions based on our experience in the RURAL (Risk Underlying Rural Areas Longitudinal) cohort study.

Geographically Weighted Modeling to Explore Social and Environmental Factors Affecting County-Level Cardiovascular Mortality in People With Diabetes in the United States: A Cross-Sectional Analysis

Disparities exist in the cardiovascular mortality rates among people with type 2 diabetes (T2D). Research has established that these disparities are often related to the environmental and social determinations of health. This study explores the spatial variation between air pollution, social determinants of health and T2D related age-adjusted cardiovascular mortality (aa-CVM) in the United States. We obtained county-level T2D related to aa-CVM (per 100,000 residents) from Centers for Disease Control and Prevention WONDER (Wide-ranging Online Data for Epidemiologic Research) (2010 to 2019). We fit a geographically weighted linear regression with aa-CVM as the outcome and the following covariates (ambient air pollution [particulate matter of 2.5 µm size], median annual household income, racial/ethnic minorities, higher education, rurality, food insecurity, and primary health care access) were included. Overall, the median aa-CVM rate was 92.9 and highest in the South (102.2). In the West, aa-CVM was significantly associated with particulate matter of 2.5 µm size, annual median household income, racial minority status and primary health care access. Food insecurity was the most significant exposure in the Midwest and Northeast, while in the South, annual median household income and food insecurity were significant. In conclusion, this study demonstrated a substantial regional variation of exposure to determinants of T2D related aa-CVM in the United States. These findings should be considered in policy frameworks and interventions as part of community-level approaches to addressing T2D related aa-CVM, and within broader state and national discussions of the importance of population health.

Regional Variation in Pulmonary Arterial Hypertension in the United States: The Pulmonary Hypertension Association Registry

Rationale: Pulmonary arterial hypertension (PAH) is a heterogeneous disease within a complex diagnostic and treatment environment. Other complex heart and lung diseases have substantial regional variation in characteristics and outcomes; however, this has not been previously described in PAH. Objectives: To identify baseline differences between U.S. census regions in the characteristics and outcomes for participants in the Pulmonary Hypertension Association Registry (PHAR). Methods: Adults with PAH were divided into regional groups (Northeast, South, Midwest, and West), and baseline differences between census regions were presented. Kaplan-Meier survival analyses and Cox proportional hazards were used to estimate the association between region and mortality in unadjusted and adjusted models. Results: Substantial differences by census regions were seen in age, race, ethnicity, marital status, employment, insurance payor breakdown, active smoking, and current alcohol use. Differences were also seen in PAH etiology and baseline 6-minute walk distance test results. Treatment characteristics varied by census region, and mortality appeared to be lower in PHAR participants in the West (hazard ratio, 0.60; 95% confidence interval, 0.43-0.83, P = 0.005). This difference was not readily explained by differences in demographic characteristics, PAH etiology, baseline severity, baseline medication regimen, or disease prevalence. Conclusions: The present study suggests significant regional variation among participants at accredited pulmonary vascular disease centers in multiple baseline characteristics and mortality. This variation may have implications for clinical research planning and represent an important focus for further study to better understand whether there are remediable care aspects that can be addressed in the pursuit of providing equitable care in the United States.

Trends in Cardiovascular Disease Mortality by County-Level Social Vulnerability Index in the United States

Background Although cardiovascular mortality (CVM) rates in the United States have been declining overall, our study evaluated whether this holds true for areas with increased social deprivation. Methods and Results We used county-level cross-sectional age-adjusted CVM rates (aa-CVM) (2000-2019) linked to the Centers for Disease Control and Prevention Social Vulnerability Index (SVI-2010). We grouped counties as per SVI (Groups I 0-0.2, II 0.21-0.4, III 0.41-0.6, IV 0.61-0.8, and V 0.81-1) and calculated the relative change in the aa-CVM between 2000 to 2003 and 2016 to 2019. We used adjusted linear regression analyses to explore the association between a higher SVI and temporal aa-CVM improvement; we studied this temporal change in aa-CVM across subgroups of race, sex, and location. The median aa-CVM rate (per 100 000) was 272.6 (interquartile range [IQR]: 237.5-311.7). The aa-CVM was higher in men (315.6 [IQR: 273.4-363.9]) than women (221.3 [IQR: 189.6-256.7]), and in Black residents (347.2 [IQR: 301.1-391.1]; P<0.001) than White residents (258.9 [IQR: 226-299.1]; P<0.001). The aa-CVM for SVI I (233.6 [IQR: 214.8-257.0]) was significantly lower than that of group V (323.6 [IQR: 277.2-359.2]; P<0.001). The relative reduction in CVM was significantly higher for SVI group I (32.2% [IQR: 24.2-38.4]) than group V (27.2% [IQR: 19-34.1]) counties. After multivariable adjustment, a higher SVI index was associated with lower relative improvement in the age-adjusted CVM (model coefficient -3.11 [95% CI, -5.66 to -1.22]; P<0.001). Conclusions Socially deprived counties in the United States had higher aa-CVM rates, and the improvement in aa-CVM over the past 20 years was lower in these counties.

Rural-urban disparities in health outcomes, clinical care, health behaviors, and social determinants of health and an action-oriented, dynamic tool for visualizing them

While rural-urban disparities in health and health outcomes have been demonstrated, because of their impact on (and intervenability to improve) health and health outcomes, we sought to examine cross-sectional and longitudinal inequities in health, clinical care, health behaviors, and social determinants of health (SDOH) between rural and non-rural counties in the pre-pandemic era (2015 to 2019), and to present a Health Equity Dashboard that can be used by policymakers and researchers to facilitate examining such disparities. Therefore, using data obtained from 2015-2022 County Health Rankings datasets, we used analysis of variance to examine differences in 33 county level attributes between rural and non-rural counties, calculated the change in values for each measure between 2015 and 2019, determined whether rural-urban disparities had widened, and used those data to create a Health Equity Dashboard that displays county-level individual measures or compilations of them. We followed STROBE guidelines in writing the manuscript. We found that rural counties overwhelmingly had worse measures of SDOH at the county level. With few exceptions, the measures we examined were getting worse between 2015 and 2019 in all counties, relatively more so in rural counties, resulting in the widening of rural-urban disparities in these measures. When rural-urban gaps narrowed, it tended to be in measures wherein rural counties were outperforming urban ones in the earlier period. In conclusion, our findings highlight the need for policymakers to prioritize rural settings for interventions designed to improve health outcomes, likely through improving health behaviors, clinical care, social and environmental factors, and physical environment attributes. Visualization tools can help guide policymakers and researchers with grounded information, communicate necessary data to engage relevant stakeholders, and track SDOH changes and health outcomes over time.

Epigenetics of Early Cardiometabolic Disease: Mechanisms and Precision Medicine

Epigenetics has transformed our understanding of the molecular basis of complex diseases, including cardiovascular and metabolic disorders. This review offers a comprehensive overview of the current state of knowledge on epigenetic processes implicated in cardiovascular and metabolic diseases, highlighting the potential of DNA methylation as a precision medicine biomarker and examining the impact of social determinants of health, gut bacterial epigenomics, noncoding RNA, and epitranscriptomics on disease development and progression. We discuss challenges and barriers to advancing cardiometabolic epigenetics research, along with the opportunities for novel preventive strategies, targeted therapies, and personalized medicine approaches that may arise from a better understanding of epigenetic processes. Emerging technologies, such as single-cell sequencing and epigenetic editing, hold the potential to further enhance our ability to dissect the complex interplay between genetic, environmental, and lifestyle factors. To translate research findings into clinical practice, interdisciplinary collaborations, technical and ethical considerations, and accessibility of resources and knowledge are crucial. Ultimately, the field of epigenetics has the potential to revolutionize the way we approach cardiovascular and metabolic diseases, paving the way for precision medicine and personalized health care, and improving the lives of millions of individuals worldwide affected by these conditions.

Longitudinal trends (2011-2020) of premature mortality and years of potential life loss (YPLL) and associated covariates of the 62 New York State counties

BACKGROUND

New York State (NYS) is the 27^th largest state and the 4^th most populous state in the U.S., with close to 20 million people in 62 counties. Territories with diverse populations present the best opportunity to study health outcomes and associated covariates, and how these differ across different populations and groups. The County Health Ranking and Roadmaps (CHR&R) ranks counties by linking the population's characteristics and health outcomes and contextual factors in a synchronic approach.

METHODS

The goal of this study is to analyze the longitudinal trends in NYS counties of age-adjusted premature mortality rate and years of potential life loss rate (YPLL) from 2011-2020 using (CHR&R) data to identify similarities and trends among the counties of the state. This study used a weighted mixed regression model to analyze the longitudinal trend in health outcomes as a function of the time-varying covariates and clustered the 62 counties according to the trend over time in the covariates.

RESULTS

Four clusters of counties were identified. Cluster 1, which represents 33 of the 62 counties in NYS, contains the most rural counties and the least racially and ethnically diverse counties. Clusters 2 and 3 mirror each other in most covariates and Cluster 4 is comprised of 3 counties (Bronx, Kings/Brooklyn, Queens) representing the most urban and racial and ethnic diverse counties in the state.

CONCLUSION

The analysis clustered counties according to the longitudinal trends of the covariates, and by doing so identified clusters of counties that shared similar trends among the covariates, to later examine trends in the health outcomes through a regression model. The strength of this approach lies in the predictive feature of what is to come for the counties by understanding the covariates and setting prevention goals.