Socio-Spatial Determinants of Health (SSDH)

National Institute On Minority Health And Health Disparities

Investigators

Linked publications & trials

Abstract

In FY22 we set up the Socio-Spatial Determinants of Health (SSDH) laboratory focusing on neighborhood social environment and cardiovascular disease (CVD) risk factors and outcomes from a geospatial perspective. We recruited two postdoctoral fellows and two postbac fellows. We continued to collaborate with intramural and extramural researchers to publish manuscripts on geospatial determinants of health disparities in minority populations. These efforts and accomplishments are described in detail below. Objective 1. In FY22, regarding Objective 1, we set up a new laboratory ready to perform high-quality research. We installed the computer software necessary to conduct geospatial analyses, such as geographic information systems technology, i.e., ESRI ArcGIS and global positioning systems. We also installed ActiLife which allows us to analyze objectively measured physical activity via ActiGraph accelerometers. In addition to setting up a laboratory, it is important to seek and hire postdoctoral (postdoc) and postbaccalaureate (postbac) fellows who conduct neighborhood research with a special emphasis on CVD risk factors and outcomes. During fall 2021, we posted an advertisement at the Office of Intramural Training & Education (OITE), the American Public Health Association, Emory Rollins School of Public Health, and the Society for Epidemiologic Research. Additionally, we reached out to numerous public health schools and sent our flyer for the postdoc fellowship at the SSDH Lab. Subsequently, we hired two postdoc fellows and two postbac fellows. Research interests of these postdoc fellows include physical activity, mental health, and neighborhood contexts from a life-course perspective. Postbac fellows research interests include neighborhoods and physical among minorities and women and mental health among understudied populations. Objective 2. The goal of Objective 2 is to better elucidate the mechanisms by which adverse neighborhood social environmental factors, as measured by using geospatial technologies, impact biomarkers of stressors. Pursuant to this goal in collaboration with the Social Determinants of Obesity and Cardiovascular Health Laboratory, we published a research protocol, focusing on neighborhood environments and cardiovascular health among women in JMIR Research Protocols. The main aim of this study is to test the hypothesis that women residing with exposure to adverse residential neighborhood contexts are associated with higher stress biomarkers (amygdala activity, vascular function, immune system activation), and to test the hypothesis that the association is moderated by objectively measured PA using an accelerometer. This study has started recruiting healthy women living in low (n=30) and high (n=30) socio-economic status areas in Washington, D.C. among a total of 60 Black and White adult women. In collaboration with the Social Determinants of Obesity and Cardiovascular Health Lab, we further plan to address the current limitations in neighborhood research. Neighborhood social contexts and their links to CVD risk factors are expected to be interconnected, and parts of a multifaceted system. However, traditional statistical techniques do not incorporate feedback loops into the linkages among biomarkers, individuals, and the environment. In addition, such methods have rarely provided new insights into the effectiveness of environmental intervention in a community before allocating scarce resources. To address these shortcomings, building upon established collaborations first, we are developing a protocol that performs a detailed match to compare immune cell biomarkers among individuals residing in different socioeconomic status neighborhoods in Washington DC. Second, we will develop an agent-based model (ABM) to determine the dynamic linkages between neighborhood crime, perceived safety, immune system activation, and CVD risk. Third, we will use the ABM to assess the cost-effectiveness of potential multifaceted environmental interventions targeting crime or safety as environmental barriers to behavior change. Combining temporally dense, complex "big data" in a systems model could accelerate the development and implementation of multilevel interventions to manage crime and perceived safety as stressors, increase physical activity, reduce obesity, and subsequently, reduce CVD risk. Objective 3. The goal of Objective 3 is to investigate how neighborhood physical and social environments are associated with CVD risk factors and outcomes. To achieve this goal, we sought out potential collaborative research projects with intramural and extramural researchers who utilize large cohort studies, such as the Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis. First, we examined the associations between perceived neighborhood social environments and sleep health among the Jackson Heart Study (JHS) participants and examined whether these associations were mediated by self-reported physical activity. As expected, those who perceived greater violence and problems in their neighborhoods had lower physical activity levels. In turn, higher physical activity levels are associated with shorter sleep duration and low sleep quality. Second, we investigated the mediating role of physical activity on the associations between neighborhood social environments and the severity of metabolic syndromes stratified by gender. We found women perceiving greater neighborhood violence and problems had a higher severity of the metabolic syndrome, mediated by low levels of physical activity. Similarly, men perceiving greater neighborhood violence and problems had a higher severity of the metabolic syndrome, mediated by low levels of physical activity. Both studies highlighted the importance of interventions to promote physical activity in conjunction with community efforts to reduce neighborhood violence and problems. Objective 4. The goal of Objective 4 is to understand how COVID-19-related outcomes (vaccine rates and therapeutics) are geographically clustered and how these clusters are varied based on sociodemographic and societal factors, such as the social vulnerability index across U.S counties. We found that some significant socio-demographic characteristics such as neighborhood-level racial composition, poverty level, etc. are less likely to be fully vaccinated. The results might be beneficial for public health practitioners and policymakers in reducing disparities in vaccine rates by racial and economic barriers across the U.S. As a next step, we plan to perform additional analyses to address geographic disparities in COVID-19 therapeutics, which could inform allocating limited resources effectively across the U.S.