Residential environments and cardiovascular risk

Improving Cardiovascular Health Through the Consideration of Social Factors in Genetics and Genomics Research: A Scientific Statement From the American Heart Association

Cardiovascular health (CVH) is affected by genetic, social, and genomic factors across the life course, yet little research has focused on the interrelationships among them. An extensive body of work has documented the impact of social determinants of health at both the structural and individual levels on CVH, highlighting pathways in which racism, housing, violence, and neighborhood environments adversely affect CVH and contribute to disparities in cardiovascular disease. Genetic factors have also been identified as contributors to risk for cardiovascular disease. Emerging evidence suggests that social factors can interact with genetic susceptibility to affect disease risk. Increasingly, social factors have been shown to affect epigenetic markers such as DNA methylation, which can regulate gene and protein expression. This is a potential biological mechanism through which exposure to poor social determinants of health becomes physically embodied at the molecular level, potentially contributing to the development of suboptimal CVH and chronic disease, thus reinforcing and propagating health disparities. The objective of this statement is to highlight and summarize key literature that has examined the joint associations between social, genetic, and genomic factors and CVH and cardiovascular disease.

Disparities in cardiac arrest mortality among patients with chronic kidney disease: A US-based epidemiological analysis

Background

Chronic kidney disease (CKD) increases cardiac arrest (CA) risk because of renal and cardiovascular interactions.

Methods

Using Centers for Disease Control and Prevention (CDC) data from 1999 to 2020, we analyzed CKD-related CA mortality and the impact of social vulnerability index (SVI).

Results

We identified 336 494 CKD-related CA deaths, with stable age-adjusted mortality rates over time. Disparities were observed across gender, racial/ethnic, and geographic subpopulations, with higher mortality among males, Hispanic and non-Hispanic Black populations, and those in urban and Western regions. Higher SVI correlated with increased mortality.

Conclusions

CKD-related CA mortality rates are stable, with disparities across demographics; higher SVI correlates with increased mortality, highlighting needed interventions.

Food Environments and Cardiovascular Disease: Evidence From the Health and Retirement Study

INTRODUCTION

Residential food environments are one of the important determinants of cardiovascular health. However, past literature has been limited by short-term follow-ups, time-invariant environmental measurements at baseline, and/or not investigating both healthy and unhealthy aspects of the food environment. This study examines the effects of time-varying healthy and unhealthy food environments on incident cardiovascular disease (CVD) over 10 years, extracting data from the Health and Retirement Study (2006-2016; N=10,413).

METHODS

Cox proportional hazards modeling was performed with inverse probability weighting to assess the association between time-varying food environmental measures (i.e., densities of grocery stores, supercenters/club stores, full-service restaurants, and fast-food restaurants) and incident CVD over 10 years. Education level and race/ethnicity were tested as potential moderators. Analyses were conducted in 2022-2023.

RESULTS

Race/ethnicity had a significant interaction effect with supercenters/club stores and indicated that a 1-standard-deviation increase in the density of supercenters/club stores was associated with a 6%-8% lower risk of incident CVD in non-Hispanic Black (HR=0.78, 95% CI=0.70-0.87) and Hispanic older adults (HR=0.69, 95% CI=0.50-0.96), but not non-Hispanic White older adults. Additionally, education had a significant interaction effect with full-service restaurants, indicating that a 1-standard-deviation increase in the density of full-service restaurants was associated with a 10% lower risk of incident CVD in individuals with 13+ years of schooling, but not those with 0-12 years of schooling.

CONCLUSIONS

Findings suggest that public policymakers should be aware of the benefits and nuances of varying food environment components as they can contribute to positive or negative cardiovascular health.

GIS-Based Assessments of Neighborhood Food Environments and Chronic Conditions: An Overview of Methodologies

The industrial revolution and urbanization fundamentally restructured populations' living circumstances, often with poor impacts on health. As an example, unhealthy food establishments may concentrate in some neighborhoods and, mediated by social and commercial drivers, increase local health risks. To understand the connections between neighborhood food environments and public health, researchers often use geographic information systems (GIS) and spatial statistics to analyze place-based evidence, but such tools require careful application and interpretation. In this article, we summarize the factors shaping neighborhood health in relation to local food environments and outline the use of GIS methodologies to assess associations between the two. We provide an overview of available data sources, analytical approaches, and their strengths and weaknesses. We postulate next steps in GIS integration with forecasting, prediction, and simulation measures to frame implications for local health policies.

Racial and Socioeconomic Determinants of Cardiovascular Health: A Comprehensive Review

Cardiovascular diseases (CVDs) are the leading cause of death globally. Their prevalence and mortality rates continue to rise. This narrative review explores well-known risk factors for CVDs such as dyslipidemia, hypertension, diabetes, obesity, and smoking, and their prevalence among different racial and ethnic groups. In addition, we expand the discussion to include the impact of socioeconomic status (SES) on cardiovascular outcomes. The data demonstrate that non-Hispanic Black and Hispanic populations not only exhibit higher rates of hypertension, obesity, diabetes, and smoking but also face systemic barriers linked to lower SES, which worsen their cardiovascular outcomes. These barriers include a lack of education, lower income, higher rates of unemployment, and poor living conditions. Beyond these commonly studied factors, these groups also suffer from higher levels of food and housing insecurity and a lack of adequate insurance coverage, all of which contribute to poorer health. Additionally, there is a higher prevalence of mental health disorders, such as depression and anxiety, among these populations. This further compounds the risks and adverse outcomes associated with CVDs. It is essential to conduct further research into how SES and race influence cardiovascular health and to refine risk assessment methods. Concentrating on these aspects would make it possible to create interventions designed to meet the needs of diverse communities and strategies that could potentially reduce morbidity and mortality from CVD across populations. Moreover, this review advocates for integrating comprehensive socioeconomic data into cardiovascular health strategies, which is crucial for developing effective public health initiatives.

Exploring residential relocation- differences between newcomers and settled residents in health, travel behaviour and neighbourhood perceptions

This study explores whether people who have recently moved to an area differ from longer-term residents in their health, travel behaviour, and perceptions of the environment. Using a large, representative sample from the UKHLS, Newcomers demonstrate significantly lower mental and physical health, reduced car commuting, and a higher likelihood of liking their neighbourhood. Area deprivation, urbanicity, household income, and age emerge as influential moderators with i.e. Newcomers in affluent areas experiencing lower physical health than Settled Residents, and rural Newcomers expressing less neighbourhood satisfaction. Our findings highlight that Newcomers' perceptions of their environment diverge and environmental influences vary among population segments, potentially impacting related health behaviours such as active travel. Furthermore, residential relocation introduces Newcomers with distinct characteristics into areas, affecting the context in which potential population health interventions aiming to influence health behaviours operate. This necessitates a deeper understanding of what influences reactions to the environment as well as ongoing adaptation of environmental interventions to respond to changing contexts within the same location over time.

Community Socioeconomic Status, Acute Cardiovascular Hospitalizations, and Mortality in Medicare, 2003 to 2019

BACKGROUND

Socioeconomically disadvantaged communities in the United States disproportionately experience poor cardiovascular outcomes. Little is known about how hospitalizations and mortality for acute cardiovascular conditions have changed among Medicare beneficiaries in socioeconomically disadvantaged and nondisadvantaged communities over the past 2 decades.

METHODS

Medicare files were linked with the Centers for Disease Control and Prevention's social vulnerability index to examine age-sex standardized hospitalizations for myocardial infarction, heart failure, ischemic stroke, and pulmonary embolism among Medicare fee-for-service beneficiaries ≥65 years of age residing in socioeconomically disadvantaged communities (highest social vulnerability index quintile nationally) and nondisadvantaged communities (all other quintiles) from 2003 to 2019, as well as risk-adjusted 30-day mortality among hospitalized beneficiaries.

RESULTS

A total of 10 942 483 Medicare beneficiaries ≥65 years of age were hospitalized for myocardial infarction, heart failure, stroke, or pulmonary embolism (mean age, 79.2 [SD, 8.7] years; 53.9% female). Although age-sex standardized myocardial infarction hospitalizations declined in socioeconomically disadvantaged (990-650 per 100 000) and nondisadvantaged communities (950-570 per 100 000) from 2003 to 2019, the gap in hospitalizations between these groups significantly widened (adjusted odds ratio 2003, 1.03 [95% CI, 1.02-1.04]; adjusted odds ratio 2019, 1.14 [95% CI, 1.13-1.16]). There was a similar decline in hospitalizations for heart failure in socioeconomically disadvantaged (2063-1559 per 100 000) and nondisadvantaged communities (1767-1385 per 100 000), as well as for ischemic stroke, but the relative gap did not change for both conditions. In contrast, pulmonary embolism hospitalizations increased in both disadvantaged (146-184 per 100 000) and nondisadvantaged communities (153-184 per 100 000). By 2019, risk-adjusted 30-day mortality was similar between hospitalized beneficiaries from socioeconomically disadvantaged and nondisadvantaged communities for myocardial infarction, heart failure, and ischemic stroke but was higher for pulmonary embolism (odds ratio, 1.10 [95% CI, 1.01-1.20]).

CONCLUSIONS

Over the past 2 decades, hospitalizations for most acute cardiovascular conditions decreased in both socioeconomically disadvantaged and nondisadvantaged communities, although significant disparities remain, while 30-day mortality is now similar across most conditions.

Influence of Socioeconomic Status on the Association Between Pregnancy Complications and Premature Coronary Artery Disease: Linking Three Cohorts

Background

We hypothesized that there is an influence of socioeconomic status (SES) on association between pregnancy complications and premature coronary artery disease (PCAD) risk.

Materials and Methods

This project involved a data linkage approach merging three databases of South Australian cohorts using retrospective, age-matched case-control study design. Cases (n = 721), that is, women aged <60 years from Coronary Angiogram Database of South Australia (CADOSA) were linked to South Australian Perinatal Statistics Collection (SAPSC) to ascertain prior pregnancy outcomes and SES. Controls (n = 194) were selected from North West Adelaide Health Study (NWAHS), comprising women who were healthy or had health conditions unrelated to CAD, age matched to CADOSA (±5 years), and linked to SAPSC to determine prior pregnancy outcomes and SES. This project performed comparative analysis of SES using socioeconomic indexes for areas-index of relative socioeconomic advantage and disadvantage (SEIFA-IRSAD) scores across three databases.

Results

Findings revealed that SEIFA-IRSAD scores at the time of pregnancy (p-value = 0.005) and increase in SEIFA-IRSAD scores over time (p-value = 0.040) were significantly associated with PCAD. In addition, when models were adjusted for SEIFA-IRSAD scores at the time of pregnancy and age, risk factors including placenta-mediated pregnancy complications such as preterm birth (odds ratio [OR] = 4.77, 95% confidence interval [CI]: 1.74-13.03) and history of a miscarriage (OR = 2.14, 95% CI: 1.02-4.49), and cardiovascular disease (CVD) risk factors including smoking (OR = 8.60, 95% CI: 3.25-22.75) were significantly associated with PCAD. When the model was adjusted for change in SEIFA-IRSAD scores (from CADOSA/NWAHS to SAPSC) and age, pregnancy-mediated pregnancy complications including preterm birth (OR = 4.40, 95% CI: 1.61-12.05) and history of a miscarriage (OR = 2.09, 95% CI: 1.00-4.35), and CVD risk factor smoking (OR = 8.75, 95% CI: 3.32-23.07) were significantly associated with PCAD.

Conclusion

SES at the time of pregnancy and change in SES were not associated with PCAD risk.

Neighborhoods and Cardiovascular Health: A Scientific Statement From the American Heart Association

The neighborhoods where individuals reside shape environmental exposures, access to resources, and opportunities. The inequitable distribution of resources and opportunities across neighborhoods perpetuates and exacerbates cardiovascular health inequities. Thus, interventions that address the neighborhood environment could reduce the inequitable burden of cardiovascular disease in disenfranchised populations. The objective of this scientific statement is to provide a roadmap illustrating how current knowledge regarding the effects of neighborhoods on cardiovascular disease can be used to develop and implement effective interventions to improve cardiovascular health at the population, health system, community, and individual levels. PubMed/Medline, CINAHL, Cochrane Library reviews, and ClinicalTrials.gov were used to identify observational studies and interventions examining or targeting neighborhood conditions in relation to cardiovascular health. The scientific statement summarizes how neighborhoods have been incorporated into the actions of health care systems, interventions in community settings, and policies and interventions that involve modifying the neighborhood environment. This scientific statement presents promising findings that can be expanded and implemented more broadly and identifies methodological challenges in designing studies to evaluate important neighborhood-related policies and interventions. Last, this scientific statement offers recommendations for areas that merit further research to promote a deeper understanding of the contributions of neighborhoods to cardiovascular health and health inequities and to stimulate the development of more effective interventions.

Construction and validation of the area level deprivation index for health research: A methodological study based on Nepal Demographic and Health Survey

Area-level factors may partly explain the heterogeneity in risk factors and disease distribution. Yet, there are a limited number of studies that focus on the development and validation of the area level construct and are primarily from high-income countries. The main objective of the study is to provide a methodological approach to construct and validate the area level construct, the Area Level Deprivation Index in low resource setting. A total of 14652 individuals from 11,203 households within 383 clusters (or areas) were selected from 2016-Nepal Demographic and Health survey. The index development involved sequential steps that included identification and screening of variables, variable reduction and extraction of the factors, and assessment of reliability and validity. Variables that could explain the underlying latent structure of area-level deprivation were selected from the dataset. These variables included: housing structure, household assets, and availability and accessibility of physical infrastructures such as roads, health care facilities, nearby towns, and geographic terrain. Initially, 26-variables were selected for the index development. A unifactorial model with 15-variables had the best fit to represent the underlying structure for area-level deprivation evidencing strong internal consistency (Cronbach's alpha = 0.93). Standardized scores for index ranged from 58.0 to 140.0, with higher scores signifying greater area-level deprivation. The newly constructed index showed relatively strong criterion validity with multi-dimensional poverty index (Pearson's correlation coefficient = 0.77) and relatively strong construct validity (Comparative Fit Index = 0.96; Tucker-Lewis Index = 0.94; standardized root mean square residual = 0.05; Root mean square error of approximation = 0.079). The factor structure was relatively consistent across different administrative regions. Area level deprivation index was constructed, and its validity and reliability was assessed. The index provides an opportunity to explore the area-level influence on disease outcome and health disparity.

Racial and Ethnic Residential Segregation and Monocyte DNA Methylation Age Acceleration

Importance

Neighborhood segregation and poverty may be important drivers of health inequities. Epigenomic factors, including DNA methylation clocks that may mark underlying biological aging, have been implicated in the link between social factors and health.

Objective

To examine the associations of neighborhood segregation and poverty with 4 DNA methylation clocks trained to capture either chronological age or physiological dysregulation.

Design, Setting, and Participants

This cohort study uses data from the Multi-Ethnic Study of Atherosclerosis (MESA), a longitudinal study that started in 2000 to 2002, with follow-up in 2002 to 2004, 2004 to 2005, 2005 to 2007, and 2010 to 2012. In 2000 to 2002, adults who identified as White or Black race or Hispanic or Chinese ethnicity in 6 US sites (Baltimore, Maryland; Chicago, Illinois; Forsyth County, North Carolina; Los Angeles County, California; Northern Manhattan, New York; and St. Paul, Minnesota) were sampled for recruitment. A random subsample of 4 sites (Maryland, North Carolina, New York, and Minnesota) were selected for inclusion in the MESA epigenomics ancillary study at examination 5 (2010-2012). Participants who identified as White or Black race or Hispanic ethnicity, were aged 45 to 84 years, and did not have clinical cardiovascular disease were included in this analysis. Data were analyzed from May 2021 to October 2023.

Exposure

Information on 2000 census tract poverty and Getis-Ord G statistic segregation of Hispanic residents, non-Hispanic Black residents, or non-Hispanic White residents were linked to participant addresses at examination 1 (2000-2002).

Main Outcomes and Measures

At examination 5, DNA methylation was measured in purified monocytes. DNA methylation age acceleration was calculated using 4 clocks trained on either chronological age or physiological dysregulation. Linear regressions were used to test associations.

Results

A total of 1102 participants (mean [SD] age, 69.7 [9.4] years; 562 [51%] women) were included, with 348 Hispanic participants, 222 non-Hispanic Black participants, and 533 non-Hispanic White participants. For non-Hispanic Black participants, living in tracts with greater segregation of Black residents was associated with GrimAge DNA methylation age acceleration, a clock designed to capture physiological dysregulation. A 1-SD increase in segregation was associated with 0.42 (95% CI, 0.20-0.64) years age acceleration (P < .001); this association was not observed with other clocks. This association was particularly pronounced for participants living in high poverty tracts (interaction term, 0.24; 95% CI, 0.07-0.42; P = .006). In the overall sample, census tract poverty level was associated with GrimAge DNA methylation age acceleration (β = 0.45; 95% CI, 0.20-0.71; adjusted P = .005).

Conclusions and Relevance

These findings suggest that epigenomic mechanisms may play a role in the associations of segregated and poor neighborhoods with chronic conditions.

Association of Income Level and Ischemic Heart Disease: Potential Role of Walkability

BACKGROUND

Association of Income Level and Ischemic Heart Disease: Potential Role of Walkability Association of ischemic heart disease (adjusted for traditional risk factors and socioeconomics variables) and income level (A), and walkability z-score (B), and association of walkability z-score and income level (C).

BACKGROUND

Socioeconomic status has been linked to ischemic heart disease (IHD). High-income neighborhoods may expose individuals to a walking-promoting built environment for daily activities (walkability). Data from the association between income and IHD is lacking in middle-income countries. It is also uncertain whether walkability mediates this association.

OBJECTIVES

To investigate whether income is associated with IHD in a middle-income country and whether neighborhood walkability mediates the income-IHD association.

METHODS

This cross-sectional study evaluated 44,589 patients referred for myocardial perfusion imaging (SPECT-MPI). Income and walkability were derived from participants' residential census tract. Walkability quantitative score combined 4 variables: street connectivity, residential density, commercial density, and mixed land use. IHD was defined by abnormal myocardial perfusion during a SPECT-MPI study. We used adjusted mixed effects models to evaluate the association between income level and IHD, and we performed a mediation analysis to measure the percentage of the income-IHD association mediated by walkability. We considered p values below 0.01 as statistically significant.

RESULTS

From 26,415 participants, those living in the lowest-income tertile census tract were more physically inactive (79.1% versus 75.8% versus 72.7%) when compared to higher-income tertile census tracts (p < 0.001). Income was associated with IHD (odds ratio: 0.91 [95% confidence interval: 0.87 to 0.96] for each 1,000.00 international dollars increase in income) for both men and women equally (p for interaction = 0.47). Census tracts with a higher income were associated with better walkability (p < 0.001); however, walkability did not mediate the income-IHD association (percent mediated = -0.3%).

CONCLUSIONS

Income was independently associated with higher prevalence of IHD in a middle-income country irrespective of gender. Although walkability was associated with census tract income, it did not mediate the income-IHD association.

Traveling Together: A Road Map for Researching Neighborhood Effects on Population Health and Health Inequities

As evidence of the relationship between place and health mounts, more epidemiologists and clinical science researchers are becoming interested in incorporating place-based measures and analyses into their examination of population health and health inequities. Given the extensive literature on place and health, it can be challenging for researchers new to this area to develop neighborhood-effects research questions and apply the appropriate measures and methods. This paper provides a road map for guiding health researchers through the conceptual and methodological stages of incorporating various dimensions of place into their quantitative health research. Synthesizing across reviews, commentaries, and empirical investigations, the road map consists of 4 broad stages for considering place and health: 1) why?: articulating the motivation for assessing place and health and grounding the motivation in theory; 2) what?: identifying the relevant place-based characteristics and specifying their link to health to build a conceptual framework; 3) how?: determining how to operationalize the conceptual framework by defining, measuring, and assessing place-based characteristics and quantifying their effect on health; and 4) now what?: discussing the implications of neighborhood research findings for future research, policy, and practice. This road map supports efforts to develop conceptually and analytically rigorous neighborhood research projects.

Major and minor ECG abnormalities depending on regional living conditions in Russia

The goal of our study was to explore the effect of living conditions on the odd of major and minor ECG abnormalities on a large region scale in Russia. For the analysis, cross-sectional data of the Russian study, ESSE-RF 2013-2014, were used. They were collected on a sample of 16,400 subjects from 10 regions of the Russia. ECG abnormalities were grouped into two categories: Major and Minor (sensu the 2009 version of the Minnesota Code Classification System). Regional living conditions were considered comprehensively via five indices combining 33 characteristics of the regions. The estimates were presented as odds ratios and their 95% confidence intervals. The prevalence values of major abnormalities in the sample were 8.4% among women and 9.4% among men (p = 0.021). The prevalence of minor abnormalities constituted 34.1% and 45.9%, respectively (p < 0.001). In men, the odd of major ECG abnormalities increased with the demographic depression growth (1.08: 1.04-1.12) and with industrial development growth in the region (1.12: 1.07-1.17). In women, an increase in the odd of major ECG abnormalities was directly associated with industrial development (1.12: 1.07-1.16) and inversely related to the economic development in the region (0.94: 0.89-0.99). The odd of minor ECG abnormalities in men and women declined with the growth of the regional economic development: OR of 0.95: 0.93-0.98, and OR of 0.92: 0.87-0.99, respectively. The study demonstrated an effect of regional living conditions of the Russian population on the odd of major and minor ECG abnormalities. The most stable and logically explainable relationships were obtained for industrial and economic characteristics of living conditions.

Effects of Socioeconomic Environment on Physical Activity Levels and Sleep Quality in Basque Schoolchildren

The socioeconomic and built environment of an area are interrelated with health data and have a direct influence on children’s development. There are facilitators and barriers for schools to promote physical activity depending on the socioeconomic status of the school. The aim of this study was to analyse the relationship between physical activity and sleep and the socioeconomic level of children in the Basque Country. The sample consisted of 1139 schoolchildren between the ages of six and seventeen (566 boys and 573 girls) from 75 schools (43 public and 32 private). Differences between groups were compared using the Mann–Whitney U test (two samples), Kruskal–Wallis one-factor ANOVA (k samples), and Spearman’s Rho correlation. There are sex differences in light (200.8 ± 62.5 vs. 215.9 ± 54.7) and moderate (69.0 ± 34.3 vs. 79.9 ± 32.1) physical activity in favour of the female group of higher socioeconomic status compared to male group of higher socioeconomic status. In the case of vigorous physical activity, the female group performed less than the male group across all socioeconomic statuses, which was statistically significant in the groups of high socioeconomic status (11.6 ± 9.3 vs. 6.9 ± 5.7) in group 2 and medium socioeconomic status (11.1 ± 9.3 vs. 7.7 ± 6.1) in group 3. There is an inverse relationship between sedentary behaviour and BMI, total bed time, total sleep time, and night-time awakenings. There is also an inverse relationship between all levels of physical activity performed with respect to BMI and total sleep efficiency. These data point towards notable inequalities in physical activity and daily sleep in Basque schoolchildren, which in turn may be marginalised in our current school system due to the effects of the socioeconomic environment.

Does the place of residence influence your risk of being hypertensive? A study-based on Nepal Demographic and Health Survey

Even though several studies have examined various risk factors for hypertension, residential influence is poorly explored especially in the low-income countries. We aim to investigate the association between residential characteristics and hypertension in resource limited and transitional settings like Nepal. A total of 14,652 individuals aged 15 and above were selected from 2016-Nepal Demographic and Health Survey. Individuals with blood pressure ≥140/90 mmHg or a history of hypertension (as identified by physicians/health professionals) or under antihypertensive medication were defined as hypertensive. Residential characteristics were represented by area level deprivation index, with a higher score representing higher level of deprivation. Association was explored using a two-level logistic regression. We also assessed if residential area modifies the association between individual socio-economic status and hypertension. Area deprivation had a significant inverse association with the risk of hypertension. Individuals from the least deprived areas had higher odds of hypertension compared to highly deprived areas 1.59 (95% CI 1.30, 1.89). Additionally, the association between literacy a proxy of socio-economic status and hypertension varied with a place of residence. Literate individuals from highly deprived areas were likely to have a higher odds of hypertension compared to those with no formal education. In contrast, literate from the least deprived areas had lower odds of hypertension. These results identify counterintuitive patterns of associations between residential characteristics and hypertension in Nepal, as compared with most of the epidemiological data from high-income countries. Differential stages of demographic and nutritional transitions between and within the countries might explain these associations.

Social Determinants, Cardiovascular Disease, and Health Care Cost: A Nationwide Study in the United States Using Machine Learning

Background Existing studies on cardiovascular diseases (CVDs) often focus on individual-level behavioral risk factors, but research examining social determinants is limited. This study applies a novel machine learning approach to identify the key predictors of county-level care costs and prevalence of CVDs (including atrial fibrillation, acute myocardial infarction, congestive heart failure, and ischemic heart disease). Methods and Results We applied the extreme gradient boosting machine learning approach to a total of 3137 counties. Data are from the Interactive Atlas of Heart Disease and Stroke and a variety of national data sets. We found that although demographic composition (eg, percentages of Black people and older adults) and risk factors (eg, smoking and physical inactivity) are among the most important predictors for inpatient care costs and CVD prevalence, contextual factors such as social vulnerability and racial and ethnic segregation are particularly important for the total and outpatient care costs. Poverty and income inequality are the major contributors to the total care costs for counties that are in nonmetro areas or have high segregation or social vulnerability levels. Racial and ethnic segregation is particularly important in shaping the total care costs for counties with low poverty rates or social vulnerability level. Demographic composition, education, and social vulnerability are consistently important across different scenarios. Conclusions The findings highlight the differences in predictors for different types of CVD cost outcomes and the importance of social determinants. Interventions directed toward areas that have been economically and socially marginalized may aid in reducing the impact of CVDs.

Virtual nature experiences and mindfulness practices while working from home during COVID-19: Effects on stress, focus, and creativity

In this study, we focus on the impact of daily virtual nature experiences combined with mindfulness practices on remote workers' creativity, stress, and focus over an extended period (9 weeks) during the COVID-19 pandemic. Our results show a positive effect of virtual reality (VR) nature experience on increasing focus and reducing stress. When VR nature and mindfulness practices were combined, we also found an increase in convergent thinking task performance. Our findings demonstrate that 10-minute daily exposure to VR nature and mindfulness practices could compensate for some of the adverse effects of working remotely by improving some aspects of workers' well-being and creativity.

Relationships between neighborhood disadvantage and cardiovascular findings at autopsy in subjects with sudden death

BACKGROUND

Neighborhood disadvantage is associated with a higher risk of sudden cardiac death. However, autopsy findings have never been investigated in this context. Here, we sought to explore associations between neighborhood disadvantage and cardiovascular findings at autopsy in cases of sudden death in the State of Maryland.

METHODS

State of Maryland investigation reports from 2,278 subjects within the CVPath Sudden Death Registry were screened for street addresses and 9-digit zip codes. Area deprivation index (ADI), used as metric for neighborhood disadvantage, was available for 1,464 subjects; 650 of whom self-identified as Black and 814 as White. The primary study outcome measurements were causes of death and gross and histopathologic findings of the heart.

RESULTS

Subjects from most disadvantaged neighborhoods (i.e., ADI ≥ 8; n = 607) died at younger age compared with subjects from less disadvantaged neighborhoods (i.e., ADI ≤ 7; n = 857; 46.07 ± 14.10 vs 47.78 ± 13.86 years; P = 0.02) and were more likely Black or women. They were less likely to die from cardiac causes of death (61.8% vs 67.7%; P = 0.02) and had less severe atherosclerotic plaque features, including plaque burden, calcification, intraplaque hemorrhage, and thin-cap fibroatheromas. In addition, subjects from most disadvantaged neighborhoods had lower frequencies of plaque rupture (18.8% vs 25.1%, P = 0.004). However, these associations were omitted after adjustment for traditional risk factors and race.

CONCLUSION

Neighborhood disadvantage did not associate with cause of death or coronary histopathology after adjustment for cardiovascular risk factors and race, implying that social determinants of health other than neighborhood disadvantage play a more prominent role in sudden cardiac death.

Regional Living Conditions and Individual Dietary Characteristics of the Russian Population

The goal of our study was to examine the effects of the regional characteristics of the living environment on individual a priori and a posteriori dietary patterns of the Russian population. For the analysis, we used cross-sectional data from the Epidemiology of Cardiovascular Diseases in the Regions of the Russian Federation study from 2013-2014. The sample included 18,054 men and women 25-64 years of age from 12 regions. Based on the frequency of consumption of basic foods, four a posteriori empirical dietary patterns (EDPs), along with an a priori cardioprotective dietary pattern (CPDP), were identified. To describe the regional living environment, five regional indices were used. Adherence to the meat-based EDP was directly associated with deterioration of social living conditions and a more northerly location for the region of residence. The probability of a CPDP increased with greater deterioration of social living conditions, aggravation of demographic crises, and higher industrial development in the region, as well as with declines in the economic development of the region, income, and economic inequality among the population. We detected several gender-dependent differences in the associations established. The patterns revealed reflect the national dietary preferences of Russians, and the regional indices characterize the effect of the living environment.

Role of Environment on Physical Activity Patterns of Older Adults Living With HIV in New York City

ABSTRACT

The purpose of this study was to survey the physical activity (PA) patterns of older adults with HIV and investigate the relationship between environmental factors and PA in this population. This study was a secondary data analysis from 100 adults, ages 50 years and older, living with HIV in New York City. Descriptive statistics assessed PA patterns. Linear regression assessed the association between environmental factors and time spent in PA. All participants had been living with HIV for 21 years on average, were on antiretroviral therapy, ranged in age from 50 to 71 years, and were 50% female. Participants performed at 75% of their functional capacity ( p < .0001), and females walked less than males ( p < .05). Traffic hazards were the sole environmental predictor of PA participation. Targeted interventions are needed to increase PA in this growing population. Interventions at the policy level should reduce traffic hazards to support PA.

Census-Tract-Level Median Household Income and Median Family Income Estimates: A Unidimensional Measure of Neighborhood Socioeconomic Status?

Previous studies suggested either census-tract-level median household income (MHI) or median family income (MFI) estimates may be used as a unidimensional measure of neighborhood socioeconomic status (SES) in the United States (US). To better understand its general use, the purpose of this study was to assess the usefulness of MHI and MFI in a wide range of geographic areas. Area-based socioeconomic data at the census tract level were obtained from the 2000 Census as well as the 2005-2009, 2010-2014, and 2015-2019 American Community Survey. MHI and MFI were used as two simple measures of neighborhood SES. Based on the five area-based indexes developed in the US, several census-tract-level socioeconomic indicators were used to derive five composite measures of neighborhood SES. Then, a series of correlation analyses was conducted to assess the relationships between these seven measures in the State of California and its seven Metropolitan Statistical Areas. Two simple measures were very strongly and positively correlated with one another, and were also strongly or very strongly correlated, either positively or negatively, with five composite measures. Hence, the results of this study support an analytical thinking that simple measures and composite measures may capture the same dimension of neighborhood SES in different geographic areas.

Does crime trigger genetic risk for type 2 diabetes in young adults? A G x E interaction study using national data

BACKGROUND

Living in neighborhoods perceived as disordered exacerbates genetic risk for type 2 diabetes (T2D) among older adults. It is unknown whether this gene-neighborhood interaction extends to younger adults. The present study aims to investigate whether crime, an objectively measured indicator of neighborhood disorder, triggers genetic risk for T2D among younger adults, and whether this hypothesized triggering occurs through exposure to obesity.

METHODS

Data were from the Wave I (2008) National Longitudinal Study of Adolescent to Adult Health. A standardized T2D polygenic score was created using 2014 GWAS meta-analysis results. Weighted mediation analyses using generalized structural equation models were conducted in a final sample of 7606 adults (age range: 25-34) to test the overall association of T2D polygenic scores with T2D, and the mediating path through obesity exposure in low, moderate, and high county crime-rate groups. Age, sex, ancestry, educational degree, household income, five genetic principal components, and county-level concentrated advantage and population density were adjusted.

RESULTS

The overall association between T2D polygenic score and T2D was not significant in low-crime areas (p = 0.453), marginally significant in moderate-crime areas (p = 0.064), and statistically significant in high-crime areas (p = 0.007). The mediating path through obesity was not significant in low or moderate crime areas (ps = 0.560 and 0.261, respectively), but was statistically significant in high-crime areas (p = 0.023). The indirect path through obesity accounted for 12% of the overall association in high-crime area.

CONCLUSION

A gene-crime interaction in T2D was observed among younger adults, and this association was partially explained by exposure to obesity.

The Associations Between Urban Form and Major Non-communicable Diseases: a Systematic Review

In the current century, non-communicable diseases (NCDs), particularly cardiovascular diseases, diabetes, cancer, and chronic respiratory diseases, are the most important cause of mortality all over the world. Given the effect of the built environment on people's health, the present study seeks to conduct a systematic review in order to investigate the relationship between urban form and these four major NCDs as well as their main risk factors. Two independent reviewers in November 2020 after an extensive search through PubMed and Scopus identified 77 studies. Studies published in English were included if they addressed one or more attributes of urban form in relation to any major NCDs and their main risk factors. Publication date, country, geographical scale, study design, methods of built environment measurement, and findings of the relationships among variables were extracted from eligible studies. The findings suggest that the elements of urban form (density, transportation and accessibility, characteristics of building and streetscape, land use, spatial layouts and configuration) could increase or inhibit these diseases through their effect on physical activity, diet, air pollution, blood pressure, and obesity. However, there are study shortages, contradictions, and ambiguities in these relationships which are mainly due to methodological and conceptual challenges. As a result, more in-depth research is needed to achieve solid and consistent results that could be made into clear guidelines for planning and designing healthier cities.

How do environmental characteristics jointly contribute to cardiometabolic health? A quantile g-computation mixture analysis

Accumulating evidence links cardiometabolic health with social and environmental neighborhood exposures, which may contribute to health inequities. We examined whether environmental characteristics were individually or jointly associated with insulin resistance, hypertension, obesity, type 2 diabetes, and metabolic syndrome in San Diego County, CA. As part of the Community of Mine Study, cardiometabolic outcomes of insulin resistance, hypertension, BMI, diabetes, and metabolic syndrome were collected in 570 participants. Seven census tract level characteristics of participants' residential environment were assessed and grouped as follows: economic, education, health care access, neighborhood conditions, social environment, transportation, and clean environment. Generalized estimating equation models were performed, to take into account the clustered nature of the data and to estimate β or relative risk (RR) and 95 % confidence intervals (CIs) between each of the seven environmental characteristics and cardiometabolic outcomes. Quantile g-computation was used to examine the association between the joint effect of a simultaneous increase in all environmental characteristics and cardiometabolic outcomes. Among 570 participants (mean age 58.8 ± 11 years), environmental economic, educational and health characteristics were individually associated with insulin resistance, diabetes, obesity, and metabolic syndrome. In the mixture analyses, a joint quartile increase in all environmental characteristics (i.e., improvement) was associated with decreasing insulin resistance (β, 95 %CI: -0.09, -0.18-0.01)), risk of diabetes (RR, 95 %CI: 0.59, 0.36-0.98) and obesity (RR, 95 %CI: 0.81, 0.64-1.02). Environmental characteristics synergistically contribute to cardiometabolic health and independent analysis of these determinants may not fully capture the potential health impact of social and environmental determinants of health.

County-Level Social Vulnerability is Associated With In-Hospital Death and Major Adverse Cardiovascular Events in Patients Hospitalized With COVID-19: An Analysis of the American Heart Association COVID-19 Cardiovascular Disease Registry

BACKGROUND

The COVID-19 pandemic has disproportionately affected low-income and racial/ethnic minority populations in the United States. However, it is unknown whether hospitalized patients with COVID-19 from socially vulnerable communities experience higher rates of death and/or major adverse cardiovascular events (MACEs). Thus, we evaluated the association between county-level social vulnerability and in-hospital mortality and MACE in a national cohort of hospitalized COVID-19 patients.

METHODS

Our study population included patients with COVID-19 in the American Heart Association COVID-19 Cardiovascular Disease Registry across 107 US hospitals between January 14, 2020 to November 30, 2020. The Social Vulnerability Index (SVI), a composite measure of community vulnerability developed by Centers for Disease Control and Prevention, was used to classify the county-level social vulnerability of patients' place of residence. We fit a hierarchical logistic regression model with hospital-level random intercepts to evaluate the association of SVI with in-hospital mortality and MACE.

RESULTS

Among 16 939 hospitalized COVID-19 patients in the registry, 5065 (29.9%) resided in the most vulnerable communities (highest national quartile of SVI). Compared with those in the lowest quartile of SVI, patients in the highest quartile were younger (age 60.2 versus 62.3 years) and more likely to be Black adults (36.7% versus 12.2%) and Medicaid-insured (31.1% versus 23.0%). After adjustment for demographics (age, sex, race/ethnicity) and insurance status, the highest quartile of SVI (compared with the lowest) was associated with higher likelihood of in-hospital mortality (OR, 1.25 [1.03-1.53]; P=0.03) and MACE (OR, 1.26 [95% CI, 1.05-1.50]; P=0.01). These findings were not attenuated after accounting for clinical comorbidities and acuity of illness on admission.

CONCLUSIONS

Patients hospitalized with COVID-19 residing in more socially vulnerable communities experienced higher rates of in-hospital mortality and MACE, independent of race, ethnicity, and several clinical factors. Clinical and health system strategies are needed to improve health outcomes for socially vulnerable patients.

Food insecurity and housing instability as determinants of cardiovascular health outcomes: A systematic review

AIMS

The primary objective of this study is to conduct a systematic review of existing literature on the association between food insecurity and housing instability with CVD and its subtypes-related outcomes. Summarizing the comprehensive evidence for independent/interchangeable relationship of food and housing instability with CVD outcomes may inform specific interventions strategies to reduce CVD-risk.

DATA SYNTHESIS

The search focused on English-language articles in PubMed/Medline, from January 1, 2010, to June 1, 2021, with restriction to the US adult population. We included studies estimating the association between food insecurity or/and housing instability(exposure) and CVD-subtypes-related health outcomes (outcome). The study methodological quality was assessed using the Study Quality Assessment Tools (SQAT). Nineteen studies met eligibility criteria, consisted of 15 cross-sectional and 4 cohort studies. Of total studies, 7 examined housing instability, 11 studies focused on food insecurity, and one examined both. Food insecurity/housing instability was associated with increased overall CVD-mortality rate and greater healthcare cost utilization, while evidence were mixed for hospital readmission rate. By subtype, stroke mortality was greater with food insecurity but not with housing instability. The likelihood of myocardial infarction, coronary heart disease, and congestive heart failure was greater with food insecurity. Although mortality with MI was higher with housing instability, readmission and surgical procedure rates were significantly lower than housing stable adults.

CONCLUSION

Findings from this review suggest an urgent need to test the impact of screening for food and housing insecurities, referral services, and community engagement for CV health, within clinical and public health settings.

PROTOCOL REGISTRATION

Prospero CRD4202123352.

Neighborhood deprivation and obesity: Sex-specific effects of cross-sectional, cumulative and residential trajectory indicators

Obesity is a long-term health issue that is becoming increasingly prevalent. Very few studies have considered the life course effects of neighborhood characteristics on obesity. In a sample of 35,856 adult participants (representative of the population of the Province of Quebec in Canada), we measured the association between neighborhood deprivation and obesity using logistic modelling on indicators of cross-sectional neighborhood deprivation, cumulative neighborhood deprivation and trajectories of neighborhood deprivation. For cross-sectional exposure, we found that females in our sample had higher odds of being affected by obesity when living in high-deprivation (OR 1.73, CI 1.41-2.13) or medium-deprivation neighborhoods (OR 1.27, CI 1.07-1.51) compared to females living in low-deprivation neighborhoods. Males also had higher odds of being affected by obesity when living in medium or high deprivation. For cumulative exposure to neighborhood deprivation, only females in the second highest category for longitudinal exposure to deprived neighborhoods had significantly higher odds of living with obesity (OR 1.89 CI 1.12-3.19) compared to females in the low cumulative exposure category. Using sequence analysis to determine neighborhood deprivation trajectories for up to 17 years, we found that females with a Deprived upward (OR 1.75 CI 1.10-2.78), an Average downward (OR 1.75 CI 1.08-2.84) or a Deprived trajectory (OR 1.81 CI 1.45-2.86) had higher odds of living with obesity compared to the Privileged trajectory. For males, there were no significant associations. Using trajectory indicators was beneficial to our analyses because this method shows that not only are individuals in low socioeconomic status neighborhoods at the end of their trajectory more susceptible to living with obesity, but so are those exposed to neighborhood deprivation at the beginning of their trajectory. These results could help to more precisely identify individuals at higher risk of developing obesity-related health issues.

Selected Research Issues of Urban Public Health

Health is created within the urban settings of people’s everyday lives. In this paper we define Urban Public Health and compile existing evidence regarding the spatial component of health and disease in urban environments. Although there is already a substantial body of single evidence on the links between urban environments and human health, focus is mostly on individual health behaviors. We look at Urban Public Health through a structural lens that addresses health conditions beyond individual health behaviors and identify not only health risks but also health resources associated with urban structures. Based on existing conceptual frameworks, we structured evidence in the following categories: (i) build and natural environment, (ii) social environment, (iii) governance and urban development. We focused our search to review articles and reviews of reviews for each of the keywords via database PubMed, Cochrane, and Google Scholar in order to cover the range of issues in urban environments. Our results show that linking findings from different disciplines and developing spatial thinking can overcome existing single evidence and make other correlations visible. Further research should use interdisciplinary approaches and focus on health resources and the transformation of urban structures rather than merely on health risks and behavior.

Obesogenic environments and cardiovascular disease: a path analysis using US nationally representative data

INTRODUCTION

People living in obesogenic environments, with limited access to healthful food outlets and exercise facilities, generally have poor health. Previous research suggests that behavioral risk factors and indicators of physiological functioning may mediate this link; however, no studies to date have had the requisite data to investigate multi-level behavioral and physiological risk factors simultaneously. The present study conducted serial and parallel mediation analyses to examine behavioral and physiological pathways explaining the association between environmental obesogenicity and cardiovascular disease (CVD).

METHODS

This cross-sectional observational study used data from the 2012-2016 Health and Retirement Study, a representative survey of US older adults (n = 12,482, mean age 65.9). Environmental obesogenicity was operationalized as a combined score consisting of nine environmental measures of food and physical activity. CVD and health-compromising behaviors (diet, alcohol consumption, smoking, and exercise) were self-reported. Physiological dysregulation was assessed with measured blood pressure, heart rate, HbA1c, cholesterol levels, BMI, and C-reactive protein. The Hayes Process Macro was used to examine serial and parallel paths through health-compromising behaviors and physiological dysregulation in the environmental obesogenicity-CVD link.

RESULTS

People living in more obesogenic environments had greater odds of self-reported CVD (odds ratio = 1.074, 95% confidence interval (CI): 1.028, 1.122), engaged in more health-compromising behaviors (β = 0.026, 95% CI: 0.008, 0.044), and had greater physiological dysregulation (β = 0.035, 95% CI: 0.017, 0.054). Combined, health-compromising behaviors and physiological dysregulation accounted for 7% of the total effects of environmental obesogenicity on CVD.

CONCLUSION

Behavioral and physiological pathways partially explain the environmental obesogenicity-CVD association. Obesogenic environments may stymie the success of cardiovascular health-promotion programs by reducing access to resources supporting healthy lifestyles.

Health Inequity in Georgia During the COVID-19 Pandemic: An Ecological Analysis Assessing the Relationship Between County-Level Racial/Ethnic and Economic Polarization Using the ICE and SARS-CoV-2 Cases, Hospitalizations, and Deaths in Georgia as of October 2020

Introduction

The coronavirus disease 2019 (COVID-19) pandemic disproportionately burdens communities of color in the United States. The prevalence of preexisting conditions in these populations has not accounted for the observed health inequities. A growing body of research indicates a significant role of racialized residential segregation and income inequality on health outcomes. The Index of Concentration at the Extremes (ICE) is a metric which captures socio-spatial and economic polarization that has proven to be a valuable predictor of a large variety of health outcomes.

Objectives

The primary objective of this ecologic study was to determine the impact of socio-spatial and economic segregation on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) morbidity and mortality in Georgia.

Methods

The ICE scores for racial/ethnic, economic, and racialized economic segregation for each county in Georgia (n=159) were calculated and investigated as predictors of increased SARS-CoV-2 positivity rate, case-hospitalization rate, and case-mortality rate after controlling for the prevalence of preexisting conditions (diabetes, obesity, and smoking) and potential barriers to care (uninsured rate).

Results

Counties with the largest income disparity had 1.57 times the case rate (p<0.0001) and 1.7 times (p<0.01) the case-mortality rate compared to the most privileged counties. Cases in counties with the largest racialized economic segregation were 1.8 times more likely to be hospitalized (p<0.0001).

Conclusion

Racialized economic segregation is a strong correlate of pandemic health inequities in Georgia and highlights the need for structural interventions to address barriers to minority and vulnerable population health. Increased focus and efforts to address the structural and systematic barriers faced by communities of color is necessary to address health inequities.

Neighborhood characteristics and ideal cardiovascular health among Black adults: results from the Morehouse-Emory Cardiovascular (MECA) Center for Health Equity

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.

Wakȟáŋyeža (Little Holy One) - an intergenerational intervention for Native American parents and children: a protocol for a randomized controlled trial with embedded single-case experimental design

Background

Trauma within Native American communities compromises parents’ parenting capacity; thus, increasing childrens’ risk for substance use and suicide over the lifespan. The objective of this manuscript is to describe the Wakȟáŋyeža (Little Holy One) intervention and evaluation protocol, that is designed to break cycles of intergenerational trauma, suicide, and substance use among Fort Peck Assiniboine and Sioux parents and their children.

Methods

A randomized controlled trial with an embedded single-case experimental design will be used to determine effectiveness of the modular prevention intervention on parent-child outcomes and the added impact of unique cultural lesson-components. Participants include 1) Fort Peck Assiniboine and Sioux parents who have had adverse childhood experiences, and 2) their children (3–5 years). Parent-child dyads are randomized (1:1) to Little Holy One or a control group that consists of 12 lessons taught by Indigenous community health workers. Lessons were developed from elements of 1) the Common Elements Treatment Approach and Family Spirit, both evidence-based interventions, and 2) newly created cultural (intervention) and nutrition (control group only) lessons. Primary outcomes are parent (primary caregiver) trauma symptoms and stress. Secondary outcomes include: Parent depression symptoms, parenting practices, parental control, family routines, substance use, historical loss, communal mastery, tribal identity, historical trauma. Child outcomes include, externalizing and internalizing behavior and school attendance. Primary analysis will follow an intent-to-treat approach, and secondary analysis will include examination of change trajectories to determine impact of cultural lessons and exploration of overall effect moderation by age and gender of child and type of caregiver (e.g., parent, grandparent).

Discussion

Many Native American parents have endured adverse childhood experiences and traumas that can negatively impact capacity for positive parenting. Study results will provide insights about the potential of a culturally-based intervention to reduce parental distress – an upstream approach to reducing risk for childrens’ later substance misuse and suicidality. Intervention design features, including use of community health workers, cultural grounding, and administration in Head Start settings lend potential for feasibility, acceptability, sustainability, and scalability.

Trial registration

ClinicalTrials.gov: NCT04201184. Registered 11 December 2019.

Interpreting a standardized and normalized measure of neighborhood socioeconomic status for a better understanding of health differences

BACKGROUND

Standardization and normalization of continuous covariates are used to ease the interpretation of regression coefficients. Although these scaling techniques serve different purposes, they are sometimes used interchangeably or confused for one another. Therefore, the objective of this study is to demonstrate how these scaling techniques lead to different interpretations of the regression coefficient in multilevel logistic regression analyses.

METHODS

Area-based socioeconomic data at the census tract level were obtained from the 2015-2019 American Community Survey for creating two measures of neighborhood socioeconomic status (SES), and a hypothetical data on health condition (favorable versus unfavorable) was constructed to represent 3000 individuals living across 300 census tracts (i.e., neighborhoods). Two measures of neighborhood SES were standardized by subtracting its mean and dividing by its standard deviation (SD) or by dividing by its interquartile range (IQR), and were normalized into a range between 0 and 1. Then, four separate multilevel logistic regression analyses were conducted to assess the association between neighborhood SES and health condition.

RESULTS

Based on standardized measures, the odds of having unfavorable health condition was roughly 1.34 times higher for a one-SD change or a one-IQR change in neighborhood SES; these reflect a health difference of individuals living in relatively high SES (relatively affluent) neighborhoods and those living in relatively low SES (relatively deprived) neighborhoods. On the other hand, when these standardized measures were replaced by its respective normalized measures, the odds of having unfavorable health condition was roughly 3.48 times higher for a full unit change in neighborhood SES; these reflect a health difference of individuals living in highest SES (most affluent) neighborhoods and those living in lowest SES (most deprived) neighborhoods.

CONCLUSION

Multilevel logistic regression analyses using standardized and normalized measures of neighborhood SES lead to different interpretations of the effect of neighborhood SES on health. Since both measures are valuable in their own right, interpreting a standardized and normalized measure of neighborhood SES will allow us to gain a more rounded view of the health differences of individuals along the gradient of neighborhood SES in a certain geographic location as well as across different geographic locations.

Exploring the spatial scale effects of built environments on transport walking: Multi-Ethnic Study of Atherosclerosis

We employed a longitudinal distributed lag modeling approach to systematically estimate how associations between built environment features and transport walking decayed with the increase of distance from home to built environment destinations. Data came from a cohort recruited from six U.S. cities (follow-up 2000-2010, N = 3913, baseline mean age 60). Built environment features included all walkable destinations, consisting of common and popular destinations for daily life. We also included two subsets frequent social destinations and food stores to examine if the spatial scale effects differed by varying density for different types of built environment destinations. Adjusted results found that increases in transport walking diminished when built environment destinations were farther, although distance thresholds varied across different types of built environment destinations. Higher availability of walking destinations within 2-km and frequent social destinations within 1.6-km were associated with transport walking. Food stores were not associated with transport walking. This new information will help policymakers and urban designers understand at what distances each type of built environment destinations influences transport walking, in turn informing the development of interventions and/or the placement of amenities within neighborhoods to promote transport walking. The findings that spatial scales depend on specific built environment features also highlight the need for methods that can more flexibly estimate associations between outcomes and different built environment features across varying contexts, in order to improve our understanding of the spatial mechanisms involved in said associations.

CARDEA study protocol: investigating early markers of cardiovascular disease and their association with lifestyle habits, inflammation and oxidative stress in adolescence using a cross-sectional comparison of adolescents with type 1 diabetes and healthy controls

INTRODUCTION

Little is known regarding associations between potentially modifiable lifestyle habits and early markers of cardiovascular disease (CVD) in pediatric type 1 diabetes (T1D), hindering early prevention efforts. Specific objectives are: (1) compare established risk factors (dyslipidemia, hypertension) with novel early markers for CVD (cardiac phenotype, aortic distensibility, endothelial function) in adolescents with T1D and healthy age-matched and sex-matched controls; (2) examine associations between these novel early markers with: (i) lifestyle habits; (ii) adipokines and measures of inflammation; and (iii) markers of oxidative stress among adolescents with T1D and controls, and determine group differences in these associations; (3) explore, across both groups, associations between CVD markers and residential neighbourhood features.

METHODS AND ANALYSES

Using a cross-sectional design, we will compare 100 participants aged 14-18 years with T1D to 100 healthy controls. Measures include: anthropometrics; stage of sexual maturity (Tanner stages); physical activity (7-day accelerometry); sleep and sedentary behaviour (self-report and accelerometry); fitness (peak oxygen consumption); and dietary intake (three non-consecutive 24- hour dietary recalls). Repeated measures of blood pressure will be obtained. Lipid profiles will be determined after a 12- hour fast. Cardiac structure/function: non-contrast cardiac magnetic resonance imaging (CMR) images will evaluate volume, mass, systolic and diastolic function and myocardial fibrosis. Aortic distensibility will be determined by pulse wave velocity with elasticity and resistance studies at the central aorta. Endothelial function will be determined by flow-mediated dilation. Inflammatory markers include plasma leptin, adiponectin, tumour necrosis factor alpha (TNF-α), type I and type II TNF-α soluble receptors and interleukin-6 concentrations. Measures of endogenous antioxidants include manganese superoxide dismutase, glutathione peroxidase and glutathione in blood. Neighbourhood features include built and social environment indicators and air quality.

ETHICS AND DISSEMINATION

This study was approved by the Sainte-Justine Hospital Research Ethics Board. Written informed assent and consent will be obtained from participants and their parents.

TRIAL REGISTRATION NUMBER

NCT04304729.

Educational inequalities, urbanicity and levels of non-communicable diseases risk factors: evaluating trends in Argentina (2005-2013)

BACKGROUND

We investigated a) whether urbanicity is associated with individual-level non-communicable diseases (NCD) risk factors and whether urbanicity modifies trends over time in risk factors; and (b) whether educational inequalities in NCD risk factors change over time or are modified by province urbanicity.

METHODS

We used data from three large national surveys on NCD risk factors (Encuesta Nacional de Factores de Riesgo; ENFR2005-2009-2013) conducted in urban areas of Argentina (n = 108,489). We used gender-stratified logistic random-intercept models (individuals nested within provinces) to determine adjusted associations of self-reported individual NCD risk factors (hypertension, diabetes, obesity, and current smoking) with education and urbanicity.

RESULTS

In both men and women, the prevalence of obesity and diabetes increased over time but smoking decreased. Hypertension prevalence increased over time in men. Higher urbanicity was associated with higher odds of smoking and lower odds of hypertension in women but was not associated with NCD risk factors in men. Obesity increased more over time in more compared to less urbanized provinces (in men) while smoking decreased more over time in less urbanized provinces. All risk factors had a higher prevalence in persons with lower education (stronger in women than in men), except for diabetes in men and smoking in women. Educational inequalities in obesity (in men) and hypertension (in men and women) became stronger over time, while an initial inverse social gradient in smoking for women reverted and became similar to other risk factors over time. In general, the inverse associations of education with the risk factors became stronger with increasing levels of province urbanicity.

CONCLUSION

Increasing prevalence of diabetes and obesity over time and growing inequities by education highlight the need for policies aimed at reducing NCD risk factors among lower socioeconomic populations in urban environments in Argentina.

Does a physical activity supportive environment ameliorate or exacerbate socioeconomic inequities in incident coronary heart disease?

BACKGROUND

Efforts to reduce socioeconomic inequities in cardiovascular disease include interventions to change the built environment. We aimed to explore whether socioeconomic inequities in coronary heart disease (CHD) incidence are ameliorated or exacerbated in environments supportive of physical activity (PA).

METHODS

We used data from the Reasons for Geographic and Racial Differences in Stroke study, which recruited US residents aged 45 or older between 2003 and 2007. Our analyses included participants at risk for incident CHD (n=20 808), followed until 31 December 2014. We categorised household income and treated it as ordinal: (1) US$75 000+, (2) US$35 000-US$74 000, (3) US$20 000-US$34 000 and (4)

RESULTS

We found a 25% (95% CI 1.17% to 1.34%) increased hazard of CHD per 1-category decrease in household income category. Adjusting for PA-supportive environments slightly reduced this association (HR=1.24). The income-CHD association was strongest in areas without walking destinations (HR=1.57), an interaction which reached statistical significance in analyses among men. In contrast, the income-CHD association showed a trend towards being strongest in areas with the highest percentage of green land cover.

CONCLUSIONS

Indicators of a PA supportive environment show divergent trends to modify socioeconomic inequities in CHD . Built environment interventions should measure the effect on socioeconomic inequities.

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Key Words

• cardiovascular disease
• neighborhood/place
• socio-economic

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MESH Headings Collapse

Grants

• DP5 OD026429 NIH HHS
• R01 AG049970 NIA NIH HHS
• U01 NS041588 NINDS NIH HHS

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Affiliation(s)

Pedro Gullon Public Health and Epidemiology Research Group, Universidad de Alcala de Henares Facultad de Medicina y Ciencias de la Salud, Alcala de Henares, Spain Urban Health Collaborative, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA
Usama Bilal Urban Health Collaborative, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA Epidemiology and Statistics, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA
Jana A Hirsch Urban Health Collaborative, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA Epidemiology and Statistics, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA
Andrew G Rundle Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA
Suzanne Judd Department of Biostatistics, University of Alabama at Birmingham College of Arts and Sciences, Birmingham, Alabama, USA
Monika M Safford Department of Medicine, Joan and Sanford I Weill Medical College of Cornell University, New York, New York, USA
Gina S Lovasi Urban Health Collaborative, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA Epidemiology and Statistics, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA

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[Impact of socioeconomic factors on blood pressure control: Observational study about 2887 hypertensive patients]

INTRODUCTION

Despite therapeutic progress, less than half of hypertensive patients are controlled. The objective of this study was to examine the links between blood pressure control and socioeconomic factors.

METHODS

We used data collected in the cardiology department of Sfax University Hospital as part of the Tunisian national hypertension registry. We studied the associations between the socio-economic variables (educational level, profession, medical insurance) and optimal blood pressure control (SBP<140mmHg and DBP<90mmHg) using logistic regression models.

RESULTS

The average age of our population was 65 and the sex ratio was 0.95. We found, as expected, the clinical and behavioral factors associated with a good blood pressure control, namely: female sex, low-sodium diet, therapeutic compliance, and regular physical activity. However, obesity and an increased number of antihypertensive drugs have been associated with poor blood pressure control. The study of the effect of socio-economic variables on BP control finds a significant gradient against the most disadvantaged social categories for our three social variables in the univariate analysis. The inclusion of clinical and behavioral factors in the multivariate analysis attenuated these associations but did not fully explain them.

CONCLUSION

Our study shows that there are social inequalities in the control of blood pressure. Social justice and improving living conditions are probably the real solutions to the problem of these social inequalities in health.

Geographical Variability in Mortality in Urban Areas: A Joint Analysis of 16 Causes of Death

The geographical distribution of mortality has frequently been studied. Nevertheless, those studies often consider isolated causes of death. In this work, we aim to study the geographical distribution of mortality in urban areas, in particular, in 26 Spanish cities. We perform an overall study of 16 causes of death, considering that their geographical patterns could be dependent and estimating the dependence between the causes of death. We study the deaths in these 26 cities during the period 1996-2015 at the census tract level. A multivariate disease mapping model is used in order to solve the potential small area estimation problems that these data could show. We find that most of the geographical patterns found show positive correlations. This suggests the existence of a transversal geographical pattern, common to most causes of deaths, which determines those patterns to a higher/lower extent depending on each disease. The causes of death that exhibit that underlying pattern in a more prominent manner are chronic obstructive pulmonary disease (COPD), lung cancer, and cirrhosis for men and cardiovascular diseases and dementias for women. Such findings are quite consistent for most of the cities in the study. The high positive correlation found between geographical patterns reflects the existence of both high and low-risk areas in urban settings, in general terms for nearly all the causes of death. Moreover, the high-risk areas found often coincide with neighborhoods known for their high deprivation. Our results suggest that dependence among causes of death is a key aspect to be taken into account when mapping mortality, at least in urban contexts.

Neighborhood Socioeconomic Resources and Crime-Related Psychosocial Hazards, Stroke Risk, and Cognition in Older Adults

Living in neighborhoods with lower incomes, lower education/occupational levels, and/or higher crime increases one’s risk of developing chronic health problems including cardiovascular disease risk factors and stroke. These cardiovascular health problems are known to contribute to cognitive decline and dementia. The purpose of this study was to determine the association of neighborhood socioeconomic resources and crime-related psychosocial hazards on stroke risk and cognition, hypothesizing that cardiovascular health would mediate any relationship between the neighborhood-level environment and cognition. The study evaluated 121 non-demented Chicago-area adults (~67 years; 40% non-Latino White) for cardiovascular health problems using the Framingham Stroke Risk Profile 10-year risk of stroke (FSRP-10). The cognitive domains that were tested included memory, executive functioning, and attention/information processing. Neighborhood socioeconomic resources were quantified at the census tract level (income, education, and occupation); crime-related psychosocial hazards were quantified at the point level. Structural equation modeling (SEM) did not show that the FSRP-10 mediated the relationship between neighborhood characteristics and domain-specific cognition. The SEM results did suggest that higher crime rates were associated with a higher FSRP-10 (β(105) = 2.38, p = 0.03) and that higher FSRP-10 is associated with reduced attention/information processing performance (β(105) = −0.04, p = 0.02) after accounting for neighborhood socioeconomic resources. Clinicians may wish to query not only individual but also neighborhood-level health when considering cognition.

Associations between neighborhood violence during pregnancy and birth outcomes: evidence from São Paulo's Western Region Birth Cohort

BACKGROUND

Low birth weight and prematurity remain leading causes of infant mortality and morbidity globally. Although extensive literature has highlighted the importance of socioenvironmental characteristics for birth outcomes, the role of indirect violence on health remains fairly understudied.

METHODS

Using geocoded birth records from the ongoing Western Region Birth Cohort (Região Oeste Coorte - ROC-Cohort) of infants born between 2012 and 2014 and geocoded crime reports, we assessed the associations between exposure to violent crimes during pregnancy within a 1-km radius of the mother's residence and low birth weight, preterm delivery, and being born small-for-gestational-age. Violent crime exposure was categorized into quintiles. Multivariate logistic regressions were used to examine the associations between violence exposure and birth outcomes. Models were adjusted for sex, maternal age and education, socioeconomic status, and risk factors such as hypertension, diabetes, smoking, and drinking during pregnancy.

RESULTS

Among the 5268 children included, the average crime exposure during the first two trimesters of pregnancy ranged from 0.44 violent crimes in the least exposed quintile to 12.74 crimes in the most exposed. Compared to children with the lowest violence exposure, children in the highest exposure quintile had higher odds of being born small-for-gestational-age (1.41[1.06-1.89]), preterm (1.35[1.01-1.80]), and low birth weight (1.42[1.03-1.98]). While socioeconomic status and maternal education were positively associated with lower violence exposure, no associations were found between these characteristics and birth outcomes.

CONCLUSIONS

Higher exposure to violent crimes in the close vicinity of pregnant women's residence is associated with substantial increases in the odds of adverse birth outcomes. Policies to improve neighborhood safety can potentially contribute not only to the short-term wellbeing of populations but may also have large social, economic, and health benefits in the long term.

Associations of neighborhood physical and crime environments with obesity-related outcomes in Jamaica

OBJECTIVE

To examine whether proximity and density of public open spaces, public parks, street connectivity, and serious and violent crimes were associated with Body Mass Index (BMI) and Waist Circumference (WC) within and across levels of urbanicity, sex and socioeconomic status (SES) in Jamaica, a small island developing state (SIDS).

METHODS

Secondary analysis was conducted using data from the Jamaica Health and Lifestyle Survey 2008 (JHLS II). All respondents were geocoded to area of residence in Enumeration Districts (EDs). Intraclass correlation coefficients (ICCs) were derived and multilevel mixed effects regression models applied to 2529 participants nested within 101 EDs from all 14 parishes in Jamaica.

RESULTS

There was significant clustering across neighborhoods for mean BMI (ICC = 4.16%) and mean WC (ICC = 4.42%). In fully adjusted models statistically significant associations included: increased mean BMI among men, with increased intersection density/ km2 (β = 0.02; 95% CI = 1.96 x10-3, 0.04, p = 0.032); increased mean WC among urban residents with increased crimes/km2/yr (β = 0.09; 95% CI = 0.03, 0.16, p<0.01) and among persons in the middle class, with further distance away from public parks (β = 0.30; 95% CI = 0.08, 0.53, p<0.01).

CONCLUSIONS

Neighborhood physical and crime environments were associated with obesity-related outcomes in Jamaica. Policymakers in SIDS such as Jamaica should also note the important differences by urbanicity, sex and SES in prevention efforts designed to stem the growing obesity epidemic.

Geographical variation and clustering are found in atrial fibrillation beyond socioeconomic differences: a Danish cohort study, 1987-2015

BACKGROUND

The prevalence and incidence rate of atrial fibrillation (AF) increase worldwide and AF is a risk factor for more adverse cardiovascular diseases including stroke. Approximately 44% of AF cases cannot be explained by common individual risk factors and risk might therefore also be related to the environment. By studying geographical variation and clustering in risk of incident AF adjusted for socioeconomic position at an individual level, potential neighbourhood risk factors could be revealed.

METHODS

Initially, yearly AF incidence rates 1987-2015 were estimated overall and stratified by income in a register-based cohort study. To examine geographical variation and clustering in AF, we used both spatial scan statistics and a hierarchical Bayesian Poisson regression analysis of AF incidence rates with random effect of municipalities (n = 98) in Denmark in 2011-2015.

RESULTS

The 1987-2015 cohort included 5,453,639 individuals whereof 369,800 were diagnosed with an incident AF. AF incidence rate increased from 174 to 576 per 100,000 person-years from 1987 to 2015. Inequality in AF incidence rate ratio between highest and lowest income groups increased from 23% in 1987 to 38% in 2015. We found clustering and geographical variation in AF incidence rates, with incidence rates at municipality level being up to 34% higher than the country mean after adjusting for socioeconomic position.

CONCLUSIONS

Geographical variations and clustering in AF incidence rates exist. Compared to previous studies from Alberta, Canada and the United States, we show that geographical variations exist in a country with free access to healthcare and even when accounting for socioeconomic differences at an individual level. An increasing social inequality in AF was seen from 1987 to 2015. Therefore, when planning prevention strategies, attention to individuals with low income should be given. Further studies focusing on identification of neighbourhood risk factors for AF are needed.

A Multilevel Perspective on the Health Effect of Social Capital: Evidence for the Relative Importance of Individual Social Capital over Neighborhood Social Capital

Employing a multilevel perspective on the health effects of social capital, this study analyzes how individual and neighborhood differences in self-rated health in Ghent (Belgium), relate to individual and collective social mechanisms, when taking demographic and socioeconomic characteristics of individuals into account. This study estimates the health effects of social trust, informal social control and disorder at the neighborhood level and social support and network size at the individual level, using indicators indebted to both the normative and resource-based approaches to social capital. Instead of the mere aggregation of individual indicators of social capital, this study uses the key informant technique as a methodologically superior measurement of neighborhood social capital, which combined with a multilevel analysis strategy, allows to disentangle the health effects of individual and neighborhood social capital. The analysis highlights the health benefits of individual social capital, i.e., individual social support and network size. The study indicates that controlling for individual demographic and socioeconomic characteristics reduces the effect of the neighborhood-level counterparts and the neighborhood characteristics social trust and neighborhood disorder have significant, but small health effects. In its effects on self-rated health, social capital operates on the individual level, rather than the neighborhood level.

Neighborhood Characteristics and Cardiovascular Biomarkers in Middle-Aged and Older Adults: the Baltimore Memory Study

Neighborhood greenness has been linked to better cardiovascular health, but little is known about its association with biomarkers related to cardiovascular risk. Adverse neighborhood conditions, such as disorder and socioeconomic disadvantage, are associated with higher cardiovascular biomarker levels, but these relationships may differ in neighborhoods with more greenness. This study evaluated cross-sectional associations of validated measures of neighborhood greenness, disorder, and socioeconomic disadvantage with cardiovascular biomarkers in middle-aged and older adults living in Baltimore City. The sample included 500 adults, aged 57-79 years, enrolled in the Baltimore Memory Study and living in Baltimore City during 2009-2010. Multi-level log-gamma regressions examined associations between the three neighborhood characteristics and seven cardiovascular biomarkers. Models additionally evaluated the effect modification by neighborhood greenness on associations of neighborhood disorder and socioeconomic disadvantage with the biomarkers. Adjusting for covariates and neighborhood greenness, greater neighborhood disorder was associated with higher C-reactive protein (exp β = 1.21, SE = 0.11, p = 0.035) and serum amyloid A (exp β = 1.28, SE = 0.12, p = 0.008), while greater neighborhood socioeconomic disadvantage was associated with higher tumor necrosis factor alpha (exp β = 1.24, SE = 0.12, p = 0.019). Higher neighborhood greenness was associated with lower soluble vascular cell adhesion molecule-1, accounting for disorder (exp β = 0.70, SE = 0.10, p = 0.010) and socioeconomic disadvantage (exp β = 0.73, SE = 0.10, p = 0.025). There was no evidence of effect modification among neighborhood characteristics. The findings suggest that neighborhood effects on cardiovascular health may be mediated through cardiovascular biomarker levels, and that socioeconomic disadvantage, disorder, and greenness may each be important features of neighborhoods.

Neighborhood social environment and changes in leukocyte telomere length: The Multi-Ethnic Study of Atherosclerosis (MESA)

Given limited research on the impact of neighborhood environments on accelerated biological aging, we examined whether changes in neighborhood socioeconomic and social conditions were associated with change in leukocyte telomere length using 10 years of longitudinal data from the Multi-Ethnic Study of Atherosclerosis (years 2000-2011; N = 1031; mean age = 61, SD = 9.4). Leukocyte telomere length change was corrected for regression to the mean and neighborhood was defined as census tract. Neighborhood socioeconomic indicators (factor-based score of income, education, occupation, and wealth of neighborhood) and neighborhood social environment indicators (aesthetic quality, social cohesion, safety) were obtained from the U.S Census/American Community Survey and via study questionnaire, respectively. Results of linear mixed-effects models showed that independent of individual sociodemographic characteristics, each unit of improvement in neighborhood socioeconomic status was associated with slower telomere length attrition over 10-years (β = 0.002; 95% Confidence Interval (CI): 0.0001, 0.004); whereas each unit of increase in safety (β = -0.043; 95% CI: -0.069, -0.016) and overall neighborhood social environment score (β = -0.005; 95% CI: -0.009, -0.0004) were associated with more pronounced telomere attrition, after additionally adjusting for neighborhood socioeconomic status. This study provides support for considerations of the broader social and socioeconomic contexts in relation to biological aging. Future research should explore potential psychosocial mechanisms underlying these associations using longitudinal study designs with repeated observations.

Multiple impacts and pathways of urban form and environmental factors on cardiovascular mortality

Air pollution and heat are significant threats to public health, especially in urban areas with intensive human activities under the trend of climate change. However, the mediation effects of urban form on health via air pollution and heat have been overlooked in previous investigations. This study explored the potential impacts and pathways of urban form on cardiovascular mortality through air pollutants and heat by using partial least squares model with data from Taiwan. The measurable characteristics of urban form include city size, urban sprawl, and mixed land use. Other factors that influence cardiovascular mortality, such as urban industrial level, economic status, aging population, and medical resource, were also considered in the model. Results revealed that maximizing mixed land use and minimizing city size and urban sprawl can help reduce cardiovascular mortality, and the minimizing city size was the most important one. Urban industrial level, economic status, aging population, and medical resource were also influential factors. This is the first study to consider the pathways and impacts of urban form on cardiovascular mortality, and our results indicate that proper urban planning and policy could reduce cardiovascular mortality.

Importance of Housing and Cardiovascular Health and Well-Being: A Scientific Statement From the American Heart Association

Cardiovascular disease disparities are shaped by differences in risk factors across racial and ethnic groups. Housing remains an important social determinant of health. The objective of this statement is to review and summarize research that has examined the associations of housing status with cardiovascular health and overall health. PubMed/Medline, Centers for Disease Control and Prevention data, US Census data, Cochrane Library reviews, and the annual Heart Disease and Stroke Statistics report from the American Heart Association were used to identify empirical research studies that examined associations of housing with cardiovascular health and overall well-being. Health is affected by 4 prominent dimensions of housing: stability, quality and safety, affordability and accessibility, and neighborhood environment. Vulnerable and underserved populations are adversely affected by housing insecurity and homelessness, are at risk for lower-quality and unsafe housing conditions, confront structural barriers that limit access to affordable housing, and are at risk for living in areas with substandard built environment features that are linked to cardiovascular disease. Research linking select pathways to cardiovascular health is relatively strong, but research gaps in other housing pathways and cardiovascular health remain. Efforts to eliminate cardiovascular disease disparities have recently emphasized the importance of social determinants of health. Housing is a prominent social determinant of cardiovascular health and well-being and should be considered in the evaluation of prevention efforts to reduce and eliminate racial/ethnic and socioeconomic disparities.