Neighborhoods and Coronary Disease: Exploring Mechanisms and Improving Methods

背景：以前的研究已经为更详细地调查邻里效应对冠心病（CHD）的因果机制提供了理由。目的：通过综合遗传学和环境跨学科方法，进一步了解社区对冠心病相关结果的具体影响，提高对因果机制的认识，并为政策干预和健康促进提供更坚实的基础。具体目的：研究社区社会环境（例如，社区富裕/贫困、社区安全/犯罪、社会资本）和社区物理环境（使用社区商品、服务和资源的客观测量）随时间推移对突发冠心病以及代谢和行为冠心病风险因素的累积影响。研究人群亚组中的调节因子和效果调节因子。研究基因变异（snp）与冠心病发病、冠心病危险因素、社区社会和物理环境之间的基因-环境相互作用。设计/方法：我们将使用两个新的数据库，地理信息系统（GIS）环境数据库和冠状动脉风险数据库，这两个数据库基于瑞典多个全国性来源的综合数据集。这将使我们能够评估1970年开始的累积邻里暴露：1)整个瑞典人口，2)基于人口的队列（包括生物库和遗传数据）；并在2016年之前对冠心病相关结果进行随访分析。我们新的冠状动脉风险数据库包含全国1180万男性和女性的数据，他们的居住地是地理编码的；新的地理信息系统环境数据库包含了整个瑞典超过25万个地理编码商品、服务和资源的历史和当前信息。在瑞典，所有人都有一个个人识别号码，该号码已被序列号所取代，用于通过连接人口普查数据、社区一级的社会和自然环境记录、死亡原因记录、住院和门诊医院记录以及所有处方药物记录来构建数据库。冠心病的诊断开始于1985年（住院）和2001年（门诊），个人和社区水平的因素开始于1970年。我们将使用潜在阶级增长模型和边际结构模型来解释个人流动性和社区随时间的变化。我们将使用倾向评分匹配和基于家庭的设计来控制选择性迁移，从而提高与先前研究相比确定因果关系的能力。此外，我们将利用先进的GIS分析技术对社区暴露进行精细评估，并研究可能影响冠心病的常见遗传变异（snp）与社区社会和物理环境之间的相互作用，后者将通过探索性环境关联研究。

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.