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

项目概要/摘要 结构性种族主义，社会通过相互强化的不平等 系统，已成为一个重要的社会风险因素，并导致少数民族的健康状况不佳 少数民族（Egede 2020，Bailey 2017，Paradies 2015）。结构性种族主义的一个重要组成部分 没有被充分研究是历史性的红线。历史性的红线是指以前的法律的做法 （1934年由联邦住房管理局发起）系统地拒绝信贷和保险 对于那些经济上处于不利地位的社区的借款人来说， 种族少数群体（理查森2020，罗斯坦2017）。虽然现在禁止在 1968年的公平住房法，住宅红线的残余影响，确保同一地区， 迄今为止，遭受历史性结构性种族主义的居民不成比例地居住在不适当的 面临更严重的社会风险因素（定义为：住房不稳定;粮食不安全;交通需求; 经济需求;和安全），人力资本（定义为个人知识的总和， 技能）和较低的卫生保健资源（定义为能够使 他们处理广泛和复杂的医疗事件/病例）（Brillioux 2017，Bailey 2021，Hidalgo 2021）;以及 划红线可能是历史上结构性种族主义与当今健康差距之间的重要联系 结果（定义为：死亡率、医疗保健成本、医疗保健利用率）（Egede 2020）。 这个项目的目标是告知我们的结构性种族主义之间的途径的理解 （定义为历史性红线）、社会风险因素、人力资本、卫生保健资源和卫生成果; 并评估有助于减少结构性种族主义对健康差距影响的政策。本 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，结构方程模型，反事实分析，沿着利益相关者的参与， （1）审查各区域遭受结构性种族主义（定义为： 历史红线）和当今的社会风险因素，人力资本和医疗保健资源。2)审查 区域性结构性种族主义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 这可以用来减少历史上结构性种族主义的地区脆弱性， 健康结果的差异。4)让不同的关键利益攸关方参与，以确定战略并确定优先次序， 降低社会风险，建设人力资本，改善各地区的卫生保健资源和成果 通过历史性的歧视暴露于结构性种族主义。本研究的创新之处在于：（一）研究了 结构性种族主义与卫生成果之间的联系，（二）在衡量卫生保健资源方面， (iii)它强调确定减少结构性种族主义长期影响的政策渠道。

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.