Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the US, accounting for an estimated one-third of all deaths and contributing to disability, poor quality of life, and increased health care spending. One strategy to reduce CVD incidence is to target prevalent and well-established clinical risk factors for CVD, such as hypertension. While the majority of work on CVD risk factors examines the role of individual predictors, scholars are increasingly recognizing the importance of social determinants of health risks, such as neighborhood environments. However, existing studies of neighborhood effects on CVD and its risk factors are dominated by analyses that use a single composite measure of neighborhood socioeconomic status. Furthermore, prior work has not fully tested the pathways by which neighborhood features may influence risk factors for CVD. The purpose of this study is to examine the associations between modifiable neighborhood characteristics (i.e., indicators of physical infrastructure, social environment, and disorder) and the CVD risk factor hypertension, with a focus on the potential mediating role of healthcare access, health behaviors, social support, and psychological distress.
We conducted a secondary analysis of quantitative data from two sources. First, wave 1 (2004-2009) of Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS), an investigation by the National Institute on Aging’s Intramural Research Program of a socioeconomically diverse sample of African Americans and whites (ages 30-64 at baseline) in Baltimore, MD. Second, neighborhood indicators from various local, state, and federal agencies compiled by the Baltimore Neighborhood Indicators Alliance. We used structural equation modeling to examine the associations between neighborhood features and hypertension, which we defined as self-reported hypertension, self-reported pharmacologic treatment for hypertension, or average sitting systolic blood pressure (SBP) >140 mmHg, average sitting diastolic blood pressure (DBP) >90 mmHg.
Preliminary analyses for hypertension produced adequate model fit (x2=6310, p<.001; CFI=.91; RMSEA=.02) with the full model. Findings indicate that direct associations of neighborhood characteristics, such as property crime rates (β=-.062) and businesses nearby (β=-0.085), are entirely mediated by psychological distress (β=0.11) and healthcare access (β=0.276).
Conclusions and Implications:
Documenting the combination of biopsychosocial and neighborhood factors that contribute to cardiovascular health is critical for evidence-based practices and policies. These preliminary results reveal pathways for potentially modifying urban neighborhoods to promote health. We will discuss implications particularly in terms of Baltimore City and other cities in the US that have experienced economic upheaval, deteriorating infrastructure, disrupted social cohesion, racial segregation, and unequal distribution of resources.