Component A: A multi-level study of community context and type 2 diabetes and coronary heart disease using electronic health record and new primary data across nested geographies in Pennsylvania

项目摘要 2型糖尿病是美国第六大死亡原因，主要是由于心脏代谢 并发症，如冠心病（CHD）。2型糖尿病的患病率从4%以下到近18%不等 在全国各县。地理上的差异可以部分解释为几个地方层面的差异。 背景因素，但县级指标解释的差异比例因区域而异。为 例如，虽然主要是社会经济，种族/民族和建筑的九个县级措施的组合， 环境特征解释了中西部T2 D患病率高达94%的变化， 这些因素解释了大西洋中部各县（包括宾夕法尼亚州）的变化。我们的研究 重点关注我们假设影响PA中T2 D和CHD结局的四个背景领域：慢性 环境污染、社会环境、食品环境和身体活动环境（两者都是） 实用性[步行性]和娱乐性体育活动）。我们将评估多种机制， 这些因素可能影响T2 D和CHD。潜在的途径包括身体和社会的影响 环境背景因素对压力，睡眠质量，心理健康，医疗保健系统的有效性， 肥胖相关的行为有必要在多个尺度上使用嵌套地理的多水平研究， 解开与T2 D及其后果相关的背景和个人因素的作用。因此我们 将对T2 D和CHD发作和T2 D控制进行两项嵌套多水平研究。每一个的设置都是 由盖辛格卫生系统服务的PA的大，多样化的区域，使我们能够将上下文因素与 电子健康记录（EHR）中包含的丰富的个人数据。每个人都将评估上下文 主要影响，然后调解和缓和这些影响。这两项相关研究代表了 高效的大数据研究方法，同时提供T2 D的深入背景检查 还有CHD第一项（38个县的EHR研究[38 co-EHR]）将使用30，000名T2 D患者的现有数据， 200，000例无T2 D患者。这项纵向研究将在38个县进行， 在县和较小的嵌套地区（多尺度）与T2 D发作和控制以及CHD发作的关系。 第二项研究（4个县的行为和生物标志物研究[4co-BBS]）将研究其中4个县的T2 D控制情况。 T2 D负担高和低的县，评估较小地区的横截面关联。4co- BBS将使用唾液收集原始数据，以补充EHR措施和次要上下文数据 皮质醇，直接观察社区，和病人问卷。4co-BBS研究将扩大 检查途径的范围，收集有关健康行为、卫生系统不信任和社区的数据 感知确定对T2 D和T2 D患病率影响最大的环境因素 PA中的心脏代谢并发症对于了解区域差异至关重要，并将告知 制定有针对性的一级和二级预防战略。

Project Summary Type 2 diabetes is the sixth leading cause of death in the U.S., largely as a result of cardiometabolic complications such as coronary heart disease (CHD). T2D ranges in prevalence from under 4% to almost 18% in counties across the country. The geographic variation can be explained in part by several place-level contextual factors, but the proportion of variance explained by county-level indicators differs regionally. For example, while a combination of nine county-level measures of mainly socioeconomic, race/ethnicity, and built environmental features explain up to 94% of the variation in T2D prevalence in the Midwest, these same factors explain very little variation in Mid-Atlantic counties, including those in Pennsylvania (PA). Our study focuses on four contextual domains that we hypothesize impact T2D and CHD outcomes in PA: chronic environmental contamination, social environment, food environment, and physical activity environment (both utilitarian [walkability] and recreational physical activity). We will evaluate multiple mechanisms through which these factors could impact T2D and CHD. Potential pathways include the influence of physical and social environmental contextual factors on stress, sleep quality, mental health, health care system effectiveness, and obesity-related behaviors. Multilevel studies using nested geographies at several scales are necessary to disentangle the role of contextual and individual factors associated with T2D and its consequences. Thus, we will conduct two nested multilevel studies of T2D and CHD onset and control of T2D. The setting for each is the large, diverse region of PA served by the Geisinger Health System, allowing us to link contextual factors to the wealth of individual-level data contained in electronic health records (EHR). Each will evaluate contextual main effects and then mediation and moderation of these effects. The two connected studies represent an efficient, big data approach to research while simultaneously offering a deep contextual examination of T2D and CHD. The first (38-county EHR study [38co-EHR]) will use existing data on 30,000 patients with T2D and 200,000 patients without T2D. This longitudinal study will be conducted in 38 counties comparing associations in counties and smaller, nested geographies (multi-scale) in relation to T2D onset and control and CHD onset. The second (4-county Behavior and Biomarker Study [4co-BBS]) will study T2D control in four of these counties with high and low T2D burden, evaluating cross-sectional associations in smaller geographies. 4co- BBS will supplement EHR measures and secondary contextual data with primary data collection using saliva cortisol, direct observation of communities, and patient questionnaires. The 4co-BBS study will broaden the scope of pathways examined, collecting data on health behaviors, health system distrust, and community perceptions. Identifying the contextual factors with the greatest influence on the prevalence of T2D and T2D cardiometabolic complications in PA is critical to understanding regional differences and will inform the development of targeted primary and secondary prevention strategies.