Causal Models of Segregation and Health

描述（由申请人提供）：居住隔离被许多人认为是健康方面种族差异的根本原因（Acevedo-Garcia 2003; Schulz et al. 2002; Williams & Collins 2001）。种族隔离通过集中贫困、降低邻里社会和自然环境的质量、削弱个人社会经济成就和向上流动而不成比例地影响少数群体（Collins and Williams 1999）。然而，我们仍然不能完全理解社区隔离在多大程度上导致了健康差异——不仅仅是因为明确解决这个问题的研究相对较少，还因为过去许多试图衡量种族隔离对健康影响的研究使用了不恰当的方法和站不了脚的假设（Duncan et al. 1997），并且很大程度上依赖于总体水平的数据（Williams & Collins 2001）。我们可以用下列方法弥补传统分析中的许多缺点。首先，虽然先前的研究几乎完全依赖于受生态谬误影响的汇总数据，但我们能够利用个人层面的数据来检查隔离与健康（自我评估的健康和死亡率）之间的关系，以及社区层面（人口普查区）的数据来检查隔离影响健康的可能途径。其次，利用面板数据，我们可以估计隔离在生命过程中不同时间点的影响；先前的研究几乎都依赖于一个单一的（当代的）时间点对社区对健康影响的估计。第三，除了传统上使用的差异指数之外，我们还能够计算出一套广泛的隔离措施，这些措施与集中贫困和社会空间的其他方面有更强的理论和分析相关性，而这些方面可能与健康有更强的联系。最后，也是最重要的是，通过使用面板数据，我们至少能够部分控制未观察到的异质性，并通过应用各种固定效应分析，通过控制未观察到的个人水平特征，恢复隔离对健康结果影响的因果估计。本项目使用复杂的面板数据集，结合人口普查区和县一级的人口普查数据，调查居住隔离在整个生命过程中对黑人和白人成年人健康和死亡率的影响。该项目将对种族隔离和社区贫困的无偏影响进行估计，以确定任何可能观察到的影响在多大程度上导致了已知的健康和死亡率方面的种族差异。

DESCRIPTION (provided by applicant): Residential segregation has been argued by many as a fundamental cause of racial disparities in health (Acevedo-Garcia 2003; Schulz et al. 2002; Williams & Collins 2001). Segregation disproportionately affects minority groups by concentrating poverty, diminishing the quality of neighborhood social and physical environments, and attenuating individual socio-economic attainment and upward mobility (Collins and Williams 1999). However, we still do not fully understand the extent to which neighborhood segregation contributes to health disparities-not simply because relatively few studies have explicitly addressed this question, but because many of the past research attempts to measure the effects of racial segregation on health have used inappropriate methods and untenable assumptions (Duncan et al. 1997) and have relied largely on aggregate level data (Williams & Collins 2001). We are able to remedy many of the shortcomings in conventional analysis in the following ways. One, while prior studies have relied almost exclusively on aggregate data that is subject to ecological fallacy, we are able to utilize individual-level data to examine relationships between segregation and health (self-rated health and mortality) as well as neighborhood-level (census-tract) data to examine the possible pathways through which segregation affects health. Second, utilizing panel data, we can estimate the effects of segregation at various points in time during the life course; prior studies have almost all relied on a single (contemporary) point-in-time estimate of neighborhood effects on health. Third, we are able to calculate a broad set of segregation measures in addition to the traditionally used dissimilarity index-measures that have a much stronger theoretical and analytical correlation with concentrated poverty and other aspects of social space that may have a much stronger connection to health. Finally, and most importantly, by using panel data we are able to at least partially control for unobserved heterogeneity and recover causal estimates of the effects of segregation on health outcomes by controlling for unobserved individual-level characteristics through the application of various fixed-effect analyses. This project investigates the effect of residential segregation over the life-course on the health and mortality of Black and White adults using a sophisticated panel data set, merged with census data at the census-tract and county levels. This project will estimate unbiased effects of segregation and neighborhood poverty to determine how much any potential observed effects contribute to known racial disparities in health and mortality.