Introduction Despite the growing interest in place as a determinant of health, areas that promote rather than reduce cardiovascular disease (CVD) in blacks are understudied. We performed an ecologic analysis to identify areas with high levels of CVD resilience and risk among blacks from a large southern, US metropolitan area. Methods We obtained census tract-level rates of cardiovascular deaths, emergency department (ED) visits, and hospitalizations for black adults aged 35 to 64 from 2010 through 2014 for the Atlanta, Georgia, metropolitan area. Census tracts with substantially lower rates of cardiovascular events on the basis of neighborhood socioeconomic status were identified as resilient and those with higher rates were identified as at risk. Logistic regression was used to estimate the odds ratios (OR) and 95% confidence intervals (CIs) of being classified as an at-risk versus resilient tract for differences in census-derived measures. Results We identified 106 resilient and 121 at-risk census tracts, which differed in the rates per 5,000 person years of cardiovascular outcomes (mortality, 8.13 vs 13.81; ED visits, 32.25 vs 146.3; hospitalizations, 26.69 vs 130.0), despite similarities in their median black income ($46,123 vs $ 45,306). Tracts with a higher percentage of residents aged 65 or older (odds ratio [OR], 2.29; 95% CI, 1.41-3.85 per 5% increment) and those with incomes less than 200% of the federal poverty level (OR, 1.19; 95% CI, 1.02-1.39 per 5% increment) and greater Gini index (OR, 1.56; 95% CI, 1.19- 2.07 per 0.05 increment) were more likely to be classified as at risk than resilient neighborhoods. Discussion Despite matching on median income level, at-risk neighborhoods for CVD among black populations were associated with a higher prevalence of socioeconomic indicators of inequality than resilient neighborhoods.

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.

Background-Food deserts (FD), neighborhoods defined as low-income areas with low access to healthy food, are a public health concern. We evaluated the impact of living in FD on cardiovascular risk factors and subclinical cardiovascular disease (CVD) with the hypothesis that people living in FD will have an unfavorable CVD risk profile. We further assessed whether the impact of FD on these measures is driven by area income, individual household income, or area access to healthy food. Methods and Results-We studied 1421 subjects residing in the Atlanta metropolitan area who participated in the METAHealth study (Morehouse and Emory Team up to Eliminate Health Disparities; n=712) and the Predictive Health study (n=709). Participants' zip codes were entered into the United States Food Access Research Atlas for FD status. Demographic data, metabolic profiles, hs-CRP (high-sensitivity C-reactive protein) levels, oxidative stress markers (glutathione and cystine), and arterial stiffness were evaluated. Mean age was 49.4 years, 38.5% male and 36.6% black. Compared with those not living in FD, subjects living in FD (n=187, 13.2%) had a higher prevalence of hypertension and smoking, higher body mass index, fasting glucose, and 10-year risk for CVD. They also had higher hs-CRP (P=0.014), higher central augmentation index (P=0.015), and lower glutathione level (P=0.003), indicative of increased oxidative stress. Area income and individual income, rather than food access, were associated with CVD risk measures. In a multivariate analysis that included food access, area income and individual income, both low-income area and low individual household income, were independent predictors of a higher 10-year risk for CVD. Only low individual income was an independent predictor of higher hs-CRP and augmentation index. Conclusions-Although living in FD is associated with a higher burden of cardiovascular risk factors and preclinical indices of CVD, these associations are mainly driven by area income and individual income rather than access to healthy food.

Background-Using data from 4 community-based cohorts of African Americans, we tested the association between genomewide markers (single-nucleotide polymorphisms) and cardiac phenotypes in the Candidate-gene Association Resource study. Methods and Results-Among 6765 African Americans, we related age, sex, height, and weight-adjusted residuals for 9 cardiac phenotypes (assessed by echocardiogram or magnetic resonance imaging) to 2.5 million single-nucleotide polymorphisms genotyped using Genome-wide Affymetrix Human SNP Array 6.0 (Affy6.0) and the remainder imputed. Within the cohort, genomewide association analysis was conducted, followed by meta-analysis across cohorts using inverse variance weights (genome-wide significance threshold=4.0 ×10-7). Supplementary pathway analysis was performed. We attempted replication in 3 smaller cohorts of African ancestry and tested lookups in 1 consortium of European ancestry (EchoGEN). Across the 9 phenotypes, variants in 4 genetic loci reached genome-wide significance: rs4552931 in UBE2V2 (P=1.43×10-7) for left ventricular mass, rs7213314 in WIPI1 (P=1.68×10-7) for left ventricular internal diastolic diameter, rs1571099 in PPAPDC1A (P=2.57×10-8) for interventricular septal wall thickness, and rs9530176 in KLF5 (P=4.02×10-7) for ejection fraction. Associated variants were enriched in 3 signaling pathways involved in cardiac remodeling. None of the 4 loci replicated in cohorts of African ancestry was confirmed in lookups in EchoGEN. Conclusions-In the largest genome-wide association study of cardiac structure and function to date in African Americans, we identified 4 genetic loci related to left ventricular mass, interventricular septal wall thickness, left ventricular internal diastolic diameter, and ejection fraction, which reached genome-wide significance. Replication results suggest that these loci may be unique to individuals of African ancestry. Additional large-scale studies are warranted for these complex phenotypes.

Background: Factors promoting cardiovascular health in the face of high risk, ie, resilience, are unknown and may identify novel areas of intervention for reducing racial health disparities. We examined neighborhood perceptions and psychological attributes of blacks living in high and low cardiovascular–risk neighborhoods, as potential characteristics of resilience promoting cardiovascular health. Methods and Results: We identified 1433 blacks residing in census tracts of Atlanta, GA, with higher-than-expected (“high” risk) or lower-than-expected (“low” risk) rates of cardiovascular mortality, hospitalizations, and emergency department visits during 2010–2014. Domains of psychosocial well-being and neighborhood quality were assessed via telephone survey between August 2016 and October 2016. Using multilevel logistic regression, odds of reporting better resilient characteristics were compared between individuals living in low- versus high-risk neighborhoods. Those from low-risk (versus high-risk) neighborhoods reported better neighborhood aesthetic quality (odds ratio [OR], 1.84), healthy food access (OR, 1.69), and absence of violence (OR, 0.67). Individuals from low-risk neighborhoods reported greater optimism (OR, 1.38), purpose in life (OR, 1.42), and fewer depressive symptoms (OR, 0.69). After full adjustment, these associations remained significant for neighborhood factors (aesthetic quality, healthy food access, violence) and psychosocial well-being (purpose in life). We found no evidence of differences in self-reported cardiovascular risk factors or disease history between low- versus high-risk neighborhoods. Conclusions: Positive neighborhood environments and psychological characteristics are associated with low cardiovascular–risk neighborhoods, despite similar prevalence of cardiovascular risk factors, in the census tracts studied. These factors may confer cardiovascular resilience among blacks.

Historical events and the illumination of unequal treatment of cardiovascular and other diseases among African Americans and their white counterparts have suppressed African Americans’ participation in research. Approaches that bring scientific professionals into actual partnership with affected communities show promise for overcoming this reluctance. Two examples are the Jackson Heart Study (JHS) and the emerging Moyo Health Network (MOYO). JHS uses layers of community engagement, including a pioneering effort to develop future health scientists and practitioners, the JHS Undergraduate Training and Education Center (UTEC). JHS-UTEC focuses on preparing young adults and teenagers (mostly African Americans) for rigorous higher-level learning and careers in health research and practice. MOYO is a mobile platform for health research to examine factors contributing to the development of disparities in the young while creating channels to disseminate interventions. Community trust in MOYO is substantially enhanced through its education and training program, which offers engaging ideation events along with app development and coding training opportunities to young people. Participants impart their cultural insights while using newly acquired technology skills to help with the community-focused design and launch of the network. The JHS and MOYO provide models for addressing cardiovascular health disparities by fostering community partnerships.

A holistic view of racial and gender disparities that simultaneously compares multiple groups can suggest associated underlying contextual factors. Therefore, to more comprehensively understand temporal changes in combined racial and gender disparities, we examine variations in the orders of county-level race-gender specific heart disease death rates by age group from 1973–2015. We estimated county-level heart disease death rates by race, gender, and age group (35–44, 45–54, 55–64, 65–74, 75–84, ≥ 85, and ≥ 35) from the National Vital Statistics System of the National Center for Health Statistics from 1973–2015. We then ordered these rates from lowest to highest for each county and year. The predominant national rate order (i.e., white women (WW) < black women (BW) < white men (WM) < black men (BM)) was most common in younger age groups. Inverted rates for black women and white men (WW<WM<BW<BM) was observed nationally only for ages 35–44, but was observed in at least some counties for all age groups < 75. From 1973 through 1979, national rates for black men aged ≥ 35 were lower than those for white men. This national observation was found in a minority of counties, primarily among ages 55–64 and 65–74. The observed rates orders and their differences over time and place suggest that social and economic forces may be driving trends in heart disease mortality. Learning more about the places and times that deviate from the predominant rate order can further inform our understanding of these macro-level drivers of heart disease mortality trends.

Background: It has been hypothesized that low access to healthy and nutritious food increases health disparities. Low-accessibility areas, called food deserts, are particularly commonplace in lower-income neighborhoods. The metrics for measuring the food environment’s health, called food desert indices, are primarily based on decadal census data, limiting their frequency and geographical resolution to that of the census. We aimed to create a food desert index with finer geographic resolution than census data and better responsiveness to environmental changes. Materials and methods: We augmented decadal census data with real-time data from platforms such as Yelp and Google Maps and crowd-sourced answers to questionnaires by the Amazon Mechanical Turks to create a real-time, context-aware, and geographically refined food desert index. Finally, we used this refined index in a concept application that suggests alternative routes with similar ETAs between a source and destination in the Atlanta metropolitan area as an intervention to expose a traveler to better food environments. Results: We made 139,000 pull requests to Yelp, analyzing 15,000 unique food retailers in the metro Atlanta area. In addition, we performed 248,000 walking and driving route analyses on these retailers using Google Maps’ API. As a result, we discovered that the metro Atlanta food environment creates a strong bias towards eating out rather than preparing a meal at home when access to vehicles is limited. Contrary to the food desert index that we started with, which changed values only at neighborhood boundaries, the food desert index that we built on top of it captured the changing exposure of a subject as they walked or drove through the city. This model was also sensitive to the changes in the environment that occurred after the census data was collected. Conclusions: Research on the environmental components of health disparities is flourishing. New machine learning models have the potential to augment various information sources and create fine-tuned models of the environment. This opens the way to better understanding the environment and its effects on health and suggesting better interventions.

Purpose: Neighborhood environment is increasingly recognized as an important determinant of cardiovascular health (CVH) among Black adults. Most research to date has focused on negative aspects of the neighborhood environment, with little attention being paid to the specific positive features, in particular the social environment, that promote cardiovascular resilience among Black adults.We examined whether better neighborhood physical and social characteristics are associated with ideal CVH among Black adults, as measured by Life's Simple 7 (LS7) scores. Methods: We recruited 392 Black adults (age 53 ± 10 years, 39% men) without known CV disease living in Atlanta, GA. Seven neighborhood domains were assessed via questionnaire: asthetic quality, walking environment, safety, food access, social cohesion, activity with neighbors, and violence. CVH was determined by LS7 scores calculated from measured blood pressure; glucose; cholesterol; body mass index (BMI); and self-reported exercise, diet, and smoking, and categorized into poor (0–8), intermediate (9–10), and ideal (11–14). Multinomial logistic regression was used to examine the association between neighborhood characteristics and the odds of intermediate/ideal CVH categories compared with poor CVH after adjustment for age, gender, household income, education, marital status, and employment status. Results: Better scores in the neighborhood domains of social cohesion and activity with neighbors were significantly associated with higher adjusted odds of ideal LS7 scores (OR 2.02, 95% CI [1.36–3.01] and 1.71 [1.20–2.45] per 1 standard deviation [SD] increase in respective scores). These associations were stronger for both social cohesion (OR 2.61, 95% CI [1.48–4.61] vs. 1.40 [0.82–2.40]) and activity with neighbors (OR 1.82, 95% CI [1.15–2.86] vs. 1.53 [0.84–2.78]) in Black women than men. Specifically, better scores in social cohesion were associated with higher odds of ideal CVH in exercise (OR 1.73 [1.16–2.59]), diet (OR 1.90 [1.11–3.26]), and BMI (OR 1.52 [1.09–2.09]); better scores in activity with neighbors were also similarly associated with higher odds of ideal CVH in exercise (OR 1.48 [1.00–2.19]), diet (OR 2.15 [1.23–3.77]), and BMI (OR 1.45 [1.07–1.98]; per 1 SD in respective scores). Conclusions: More desirable neighborhood characteristics, particularly social cohesion and activity with neighbors, were associated with better CVH among Black adults.