Contextual Effects on Cardiometabolic Health: Evidence from a Natural Experiment

项目摘要 越来越多的人一致认为，地点会影响健康。广泛的社区层面的背景因素 包括贫困、步行、食物环境、社会凝聚力、社会网络和犯罪等， 已被概念化为广泛的个人健康结果的驱动因素。然而，到目前为止， 这些物理和社会背景的影响是因果的，并导致了 健康仍然是一个悬而未决的问题。这是因为个人可以根据以下条件自行选择进入社区 可以观察到的(例如社会经济背景)和未观察到的(例如品味、偏好)特征 还会影响健康，因此很难利用观测数据将因果关系与相关性区分开来。这个 因果路径与自我选择在多大程度上促进了县与县之间的联系 环境和个人健康是制定有效公共卫生政策的关键问题。 这项研究建议调查背景因素通过的原因机制和途径 影响成人心脏代谢(CM)结果，包括BMI/肥胖、糖尿病和高血压。至 从自我选择中分离出因果路径，我们将利用由 定期将服役人员迁往不同的县，从而使他们暴露在地理位置上 由于个人无法控制的原因和持续时间，具有不同CM风险负担的地区。这提供了一种 提供关于三个主要研究问题因果关系的证据的独特机会。第一, 暴露在心脏病风险较高的县(以肥胖率较高为代表)是否会增加个人风险 在这些健康状况下。第二，哪些具体的县和街道一级的物质和社会 背景因素在个人CM结果与国家肥胖率之间的关系中起中介作用。 第三，背景对个体CM结果的影响是否受到性别和种族的影响。至 为了实现这些目标，我们将把千禧年队列研究中的个人层面的纵向数据与 县和社区层面的物理和社会环境背景数据，并估计多个 水平纵向模型。我们将使用结构方程模型来评估丰富的县和地区 邻里层面的语境因素作为调解人。此外，人口统计学上的多样性样本将使我们能够 研究这些关系如何在性别和种族/民族之间变化-这是一个关键的贡献，因为 CM条件方面存在很大差异。考虑到大规模和多样性，对通用性的担忧是有限的 样本，他们与平民社区的大量接触，以及他们的健康行为和 结果和在平民中的结果。 这项研究可能会产生很大的影响，因为自然实验设计与 纵向数据方法代表了我们在理解因果路径方面的方法论进步 环境通过这种方式影响健康行为和结果。因此，这项研究将允许 政策制定者以最有影响力的背景因素为目标，并针对特定群体制定政策。

Project Summary There is growing consensus that place affects health. A wide range of community-level contextual factors including poverty, walkability, food environment, social cohesion, social networks, and crime, among others, have been conceptualized as drivers of a broad range of individual health outcomes. However, the extent to which these physical and social contextual influences are causal and contribute to geographic disparities in health remains an open question. That is because individuals can self-select into communities based on observed (e.g. socioeconomic background) and unobserved (e.g. tastes, preferences) characteristics that can also influence health, making it difficult to isolate causal effects from correlations using observational data. The extent to which causal pathways versus self-selection contribute to the link between county contextual environment and individuals' health is a critical question in the development of effective public health policies. This study proposes to investigate the causal mechanisms and pathways through which contextual factors influence cardiometabolic (CM) outcomes in adults, including BMI/obesity, diabetes, and hypertension. To disentangle causal pathways from self-selection, we will leverage a unique natural experiment created by the periodic relocation of military service-members to different counties, thereby exposing them to geographic areas with varying burdens of CM risk for reasons and durations outside the individuals' control. This offers a unique opportunity to provide evidence on causality with respect to three main research questions. First, whether exposure to counties with higher CM risk (proxied by a higher obesity rate) increases individuals' risk for these health conditions. Second, which specific county- and neighborhood-level physical and social contextual factors mediate the relationship between individuals' CM outcomes and the county's obesity rate. And third, whether contextual effects on individuals' CM outcomes are moderated by sex and race-ethnicity. To address these aims, we will link individual-level longitudinal data from the Millennium Cohort Study to county- and neighborhood-level contextual data on the physical and social environment and estimate multi- level longitudinal models. We will use structural equation modeling to assess the role of a rich set of county and neighborhood level contextual factors as mediators. Also, the demographically diverse sample will allow us to examine how these relationships vary across sex and race/ethnicity – a critical contribution given the substantial disparities in CM conditions. Concerns about generalizability are limited given the large and diverse sample, their substantial exposure to civilian communities, and similarities between their health behaviors and outcomes and those among civilians. The study is likely to have a high impact given that the combination of a natural experiment design with longitudinal data methods represents a methodological advance in our understanding of the causal pathways through which the environment influences health behaviors and outcomes. Hence, the study will allow policymakers to target the most influential contextual factors and tailor their policies to particular groups.