Diabetes, Depression, and the Contextual Environment: A Multilevel Analysis

描述（由申请人提供）：流行病学和临床研究已经确定，重度抑郁症（MD）经常与晚年的医疗状况共同发生，包括2型糖尿病（T2DM）。糖尿病和2型糖尿病之间的关系可能是双向的。事实上，基于人群的队列研究有一致的证据表明，MD与T2DM的风险和死亡率增加有关，并且T2DM与MD的发病和复发有关。然而，前瞻性研究不能明确区分MD是否是T2DM的独特危险因素，或者这种现象是否是由于MD和T2DM共有的共同因素，如遗传倾向或环境背景。本研究的目的是利用一个大的、以人群为基础的样本，前瞻性地调查背景环境、家族遗传风险及其对合并T2DM和MD发展的相互作用的动态作用。数据来自瑞典国家多代住院、门诊和药房登记，这些数据与瑞典初级保健中心的全国代表性样本相关联，该样本自2001年以来收集，代表超过100万人。这些数据已被地理编码为社区级别的物理和社会上下文环境数据。本研究利用多层次纵向和结构方程模型来探讨具体目的：1)研究情境环境特征（如社区社会经济剥夺、犯罪、靠近公园或快餐店、社会混乱）与T2DM和MD共病之间的关系；2)研究家族遗传对T2DM和MD合并症的影响；3)研究遗传风险和环境环境对T2DM和MD发展的相互作用。遗传信息设计为探索环境环境和遗传风险之间共病T2DM-MD的相互竞争的病因学模型提供了独特的机会。使用家族设计，我们可以估计个体对2型糖尿病和MD的遗传倾向，从而对导致这种合并症的背景环境因素进行更直接和公正的检查。本应用旨在明确地将环境因素纳入我们对遗传倾向如何被环境表达和调节的理解中，研究结果将为环境环境如何影响2型糖尿病和糖尿病风险的广泛病因机制提供见解。该研究计划涉及两种常见且使人衰弱的健康状况，即2型糖尿病和糖尿病，这两种疾病是美国和全球医疗成本和公共卫生负担的主要来源。了解遗传风险、环境背景及其相互作用在合并T2DM和MD发展中的动态作用，将为反映这种复杂性的创新方案提供信息，从而更有效地促进公众健康和指导临床护理。

DESCRIPTION (provided by applicant): Epidemiologic and clinical studies have established that Major Depression (MD) often co-occurs with medical conditions in later life, including Type 2 Diabetes Mellitus (T2DM). The relationship between MD and T2DM is likely bi-directional. Indeed, there is consistent evidence from population-based cohort studies that MD is associated with increased risk of and mortality from T2DM, and that T2DM is associated with onset and recurrence of MD. However, prospective studies cannot definitively distinguish whether MD is a unique risk factor for T2DM, or if this phenomenon is due to a common factor shared by both MD and T2DM such as genetic liability or environmental context. The goal of this study is to utilize a large, population-based sample to prospectively investigate the dynamic roles of the contextual environment, familial genetic risk, and their interplay on the development of comorbid T2DM and MD. Data come from Swedish national multi-generational inpatient, outpatient, and pharmacy registries, which have been linked to a nationally-representative sample of primary care centers in Sweden representing over 1 million individuals, collected since 2001. These data have been geocoded to neighborhood-level physical and social contextual environment data. This research utilizes multi-level longitudinal and structural equation modeling to investigate the specific aims, which are to: 1) investigate the association between contextual environmental characteristics (e.g., neighborhood socioeconomic deprivation, crime, proximity to parks or fast food restaurants, social disorganization) and comorbid T2DM and MD; 2) examine the familial genetic contributions to the comorbidity between T2DM and MD; and 3) examine the interplay between genetic risk and the contextual environment on development of T2DM and MD. Genetically-informative designs provide a unique opportunity for exploring competing etiologic models of the relationships between the contextual environment and genetic risk for comorbid T2DM-MD. Using family designs we can estimate an individual's genetic liability for T2DM and MD, and thus conduct a more direct and unbiased examination of the contextual environmental factors that contribute to this comorbidity. This application aims to explicitly incorporate contextual environmental factors into our understanding of how genetic liability is expressed and moderated by the environment, and the findings will provide insight into the broad etiologic mechanisms of how environmental context influences risk of T2DM and MD. Public health significance: The research plan addresses the intersection of two common and debilitating health conditions, T2DM and MD, that are leading sources of healthcare costs and public health burden in the US and globally. Understanding the dynamic roles that genetic risk, environmental context, and their interaction play in development of comorbid T2DM and MD will inform innovative programs that reflect this complexity in order to more effectively promote public health and guide clinical care.