Neighborhoods and Coronary Disease: Exploring Mechanisms and Improving Methods

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DESCRIPTION (provided by applicant): Background: Previous studies have provided justification for more detailed investigations of causal mechanisms behind the neighborhood effect on coronary heart disease (CHD). Objectives: To further our understanding of specific neighborhood effects on CHD-related outcomes in a life-course perspective, improve knowledge of causal mechanisms, and provide a more robust basis for policy interventions and health promotion via an integrated genetics and environmental cross-disciplinary approach. Specific aims: To examine the accumulated impact of neighborhood social environments (e.g., neighborhood affluence/deprivation, neighborhood safety/criminality, social capital) and neighborhood physical environments (using objective measures of neighborhood goods, services, and resources) over time on incident CHD as well as metabolic and behavioral CHD risk factors. To examine mediators and effect modifiers in population subgroups. To examine gene-environment interactions between genetic variants (SNPs) in relation to incident CHD and CHD risk factors and neighborhood-level social and physical environments. Design/methods: We will use two new databases, the Geographic Information System (GIS)-Environment Database and the Coronary Risk Database, that are based on comprehensive datasets from multiple nationwide sources in Sweden. This will allow us to assess cumulative neighborhood exposures beginning in 1970 for: 1) the entire Swedish population, and 2) population-based cohorts (including biobanks and genetic data); and conduct follow-up analyses of CHD-related outcomes until 2016. Our new Coronary Risk Database contains nationwide data on 11.8 million men and women whose neighborhoods of residence are geocoded; the new GIS- Environment Database contains historical and current information on more than 250,000 geocoded goods, services and resources in all of Sweden. All persons in Sweden have a personal identification number that has been replaced by a serial number and used to construct the databases by linking census data, neighborhood- level social and physical environmental records, cause of death records, inpatient and outpatient hospital records, and all prescription medicine records. CHD diagnoses are available beginning in 1985 (inpatient) and 2001 (outpatient), and individual- and neighborhood-level factors beginning in 1970. We will account for individual mobility and neighborhood change over time by using latent class growth modeling and marginal structural models. We will use propensity score matching and family-based designs to control for selective migration and thereby improve the ability to determine causality compared to previous research. Furthermore, we will produce refined assessments of neighborhood exposures from advanced GIS analytic techniques and study interactions between common genetic variants (SNPs) and neighborhood social and physical environments that may influence CHD, the latter by using an exploratory Environment-Wide Association Study.