Contextual Effects on Cardiometabolic Health: Evidence from a Natural Experiment

项目摘要 越来越多的人认为，地方会影响健康。一系列社区层面的背景因素 包括贫困、步行能力、食品环境、社会凝聚力、社交网络和犯罪等， 已被概念化为广泛的个人健康结果的驱动因素。然而，程度 这些物理和社会背景的影响是因果关系，并有助于地理差异， 健康仍然是一个悬而未决的问题。这是因为个人可以根据自己的选择进入社区， 观察到的（如社会经济背景）和未观察到的（如口味，偏好）特征，可以 也会影响健康，因此很难使用观察数据从相关性中分离出因果效应。的 因果路径与自我选择在多大程度上有助于县环境之间的联系 环境和个人健康是制定有效公共卫生政策的一个关键问题。 本研究旨在探讨情境因素影响认知行为的因果机制和途径 影响成人的心脏代谢（CM）结局，包括BMI/肥胖、糖尿病和高血压。到 从自我选择中解开因果路径，我们将利用一个独特的自然实验， 定期将军人重新安置到不同的县，从而使他们面临地理上的危险。 由于个人无法控制的原因和持续时间，CM风险负担不同的领域。这提供了一个 提供关于三个主要研究问题的因果关系的证据的独特机会。第一、 是否暴露于CM风险较高的县（以较高的肥胖率为代表）会增加个人的风险 这些健康状况。第二，哪些具体的县和街道一级的物质和社会 背景因素介导个人的CM结果和县的肥胖率之间的关系。 第三，背景对个体CM结果的影响是否受到性别和种族的调节。到 为了实现这些目标，我们将把千年队列研究的个人水平纵向数据与 县和邻里一级的背景数据的物理和社会环境和估计多， 水平纵向模型我们将使用结构方程模型来评估一组丰富的县的作用， 邻里水平的背景因素作为中介。此外，人口统计学上多样化的样本将使我们能够 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， CM条件的巨大差异。考虑到大规模和多样性，对普遍性的担忧是有限的。 样本，他们大量接触平民社区，以及他们的健康行为和 结果和平民之间的关系。 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对因果通路理解的方法学进步 环境通过它影响健康行为和结果。因此，该研究将允许 政策制定者应针对最具影响力的背景因素，使其政策适合特定群体。

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.