Structural Racism and Disparities in Social Risk, Human Capital, Health Care Resources, and Health Outcomes: A Multi-level Analysis of Pathways and Policy Levers for Change

项目摘要/摘要 结构性种族主义，社会通过相辅相成的不平等促进歧视的方式 系统，已成为一个重要的社会风险因素和造成不良健康结果的民族 少数民族(Egede 2020、Bailey 2017、Parades 2015)。结构性种族主义的一个重要组成部分 没有得到充分研究的是历史性的红线。历史红线是指以前的法律实践 (由联邦住房管理局于1934年发起)有系统地拒绝获得信贷和保险 对于居住在经济条件较差且主要由 少数族裔群体(理查森2020，罗斯坦2017)。虽然现在禁止使用显式红线标记 1968年《公平住房法》规定，住宅红线的残余影响确保了与 直到今天，暴露在历史性结构性种族主义中的居民仍然不成比例地居住在不适当的 受更严重的社会风险因素影响(定义为：住房不稳定；粮食不安全；交通需求； 经济需求；和安全)，较低的人力资本(定义为个人知识和 技能)和较低的卫生保健资源(定义为实现以下目标的地区的医疗资源能力 他们处理广泛和复杂的医疗事件/病例)(Brillioux 2017、Bailey 2021、Hidalgo 2021) 红线标记可能在历史上的结构性种族主义和当今的健康差距之间呈现出重要的联系 结果(定义为：死亡率、保健费用、保健利用率)(Egede 2020)。 这个项目的目标是让我们了解结构性种族主义之间的路径 (定义为历史性红线)、社会风险因素、人力资本、保健资源和健康结果； 并评估有助于减少结构性种族主义对健康差距的影响的政策。现在 研究将通过使用最近开发的因果和可解释的机器学习来实现这一目标 方法、结构方程建模、反事实分析以及利益攸关方参与，以 发言四个目标：1)审查区域暴露于结构性种族主义之间的关系(定义为： 历史红线)和当今的社会风险因素、人力资本和卫生保健资源。2)审查 暴露于结构性种族主义的区域通过社会风险对健康结果的直接和间接影响， 人力资本和医疗保健资源。3)评估联邦、州和地区政府的政策杠杆 这可以用来减少该地区对历史性结构性种族主义的脆弱性，这可以减少当今 健康结果差异。4)让一系列不同的关键利益攸关方参与确定战略并确定其优先顺序 降低社会风险，建设人力资本，改善地区卫生保健资源和成果 通过历史上的红线暴露在结构性种族主义之下。这项研究的创新之处在于：(I)它对 结构性种族主义与健康结果之间的联系，(2)卫生保健资源的计量，以及 (3)强调确定减少结构性种族主义永久影响的政策渠道。

Project Summary/Abstract Structural racism, the ways in which societies foster discrimination through mutually reinforcing inequitable systems, has emerged as an important social risk factor and contributor to poor health outcomes for ethnic minorities (Egede 2020, Bailey 2017, Paradies 2015). An important component of structural racism that has been inadequately studied is historic redlining. Historic redlining refers to the previously legal practice (initiated in 1934 by the Federal Housing Administration) of systematically denying credit access and insurance for borrowers in neighborhoods that were economically disadvantaged and that were inhabited by primarily racial minority groups (Richardson 2020, Rothstein 2017). While explicit redlining is now prohibited under the Fair Housing Act of 1968, the residual effects of residential redlining ensures that the same areas with exposure to historic structural racism are to this day disproportionately inhabited by residents that are unduly subject to worse social risk factors (defined across: Housing Instability; Food Insecurity; Transport Needs; Economic Needs; and Safety), lower human capital (defined as the totality of individuals’ knowledge and skills), and lower health care resources (defined as the medical resource capabilities of areas which enable them to handle broad and complex medical events/cases) (Brillioux 2017, Bailey 2021, Hidalgo 2021); and that redlining may present an important link between historic structural racism and present day disparities in health outcomes (defined across: mortality, health care cost, health care utilization) (Egede 2020). The goal of this project is to inform our understanding of the pathways between structural racism (defined as historic redlining), social risk factors, human capital, health care resources and health outcomes; and to evaluate policies that can help reduce the impact of structural racism on health disparities. The present study will accomplish this objective by using recently developed causal and interpretable machine learning methods, structural equation modelling, counterfactual analysis, along with stakeholder engagement, to address four aims: 1) Examine the relationship between regional exposure to structural racism (defined as: historic redlining) and present-day social risk factors, human capital, and health care resources. 2) Examine the direct and indirect effects of regional exposure to structural racism on health outcomes via social risk, human capital, and healthcare resources. 3) Assess policy levers of federal, state, and regional governments that can be used to reduce area vulnerabilities to historic structural racism, and that can reduce present-day health outcomes disparities. 4) Engage a diverse set of key stakeholders to identify and prioritize strategies for mitigating social risk, building human capital, and improving health care resources and outcomes for regions exposed to structural racism through historical redlining. The study is innovative in: (i) its examination of the linkages between structural racism and health outcomes, (ii) in its measurement of health care resources, and (iii) in its emphasis on identifying policy channels for reducing the perpetual impact of structural racism.