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

结构性种族主义和社会风险、人力资本、医疗保健资源和健康结果的差异：变革路径和政策杠杆的多层次分析

• 批准号: 10654440
• 负责人: Leonard E. Egede
• 金额: $ 63.95万
• 依托单位: MEDICAL COLLEGE OF WISCONSIN
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-13 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10654440
• 关键词: Address; Area; Charge; Code; Color; Communities; Complex; Data; Data Sources; Discrimination; Disparity; Ensure; Equation; Event; Exposure to; Federal Government; Fostering; Goals; Government; Health; Health Care Costs; Healthcare; Hispanic; Home; Hospital Closures; Housing; Individual; Inequity; Insurance; Investments; Knowledge; Legal; Link; Local Government; Maps; Measurement; Medicaid; Medical; Methods; Modeling; Neighborhoods; Outcome; Pathway Analysis; Pathway interactions; Police; Policies; Residual state; Resources; Risk; Risk Factors; Safety; Schools; Security; Societies; State Government; Statutes and Laws; Structural Racism; System; Time; Wages; cost; disparity gap; disparity reduction; economic disparity; economic need; ethnic disparity; ethnic minority; evidence base; food insecurity; health care service utilization; health disparity; health outcome disparity; housing instability; human capital; implementation strategy; improved; innovation; machine learning method; mortality; multilevel analysis; novel; poor health outcome; programs; racial disparity; racial minority population; skills; social; social health determinants; voucher

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.

项目摘要/摘要 结构性种族主义，社会通过相互加强不平等的方式促进歧视 系统已成为重要的社会风险因素，并为种族造成健康状况不佳的贡献 少数民族（Egge 2020，Bailey，2017年，2015年Paradies）。结构性种族主义的重要组成部分 他的研究不足是历史性的红线。历史性的红线是指先前的法律实践 （由联邦住房管理局于1934年发起）系统地否认信用访问和保险 对于在经济上处于不利地位并且由小学致命的社区中的借款人 种族少数群体（Richardson 2020，Rothstein，2017年）。虽然现在禁止明确的红线 1968年的《公平住房法》，居民红线的残余影响可确保与 到目前为止，暴露于历史结构性种族主义一直受到居民的不成比例的邀请 受到较差的社会风险因素（跨越：住房不稳定；粮食不安全；运输需求； 经济需求；和安全），较低的人力资本（被定义为个人的知识和 技能）和降低医疗保健资源（定义为启用领域的医疗资源能力 他们处理广泛而复杂的医疗活动/案件）（Brillioux 2017，Bailey 2021，Hidalgo 2021）；那 红线可能呈现历史性的结构种族主义与当今健康分布之间的重要联系 结果（跨跨：死亡率，医疗保健成本，医疗保健利用率）（Egge 2020）。 该项目的目的是告知我们对结构种族主义之间的途径的理解 （定义为历史性的红线），社会风险因素，人力资本，卫生保健资源和健康成果； 并评估可以帮助减少结构性种族主义对健康差异的影响的政策。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相关者的参与， 地址四个目的：1）检查区域暴露于结构种族主义之间的关系（定义为： 历史性的红线）和当今的社会风险因素，人力资本和医疗资源。 2）检查 区域暴露于结构性种族主义对通过社会风险的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 可以用来减少对历史结构种族主义的地区脆弱性，这可以减少当今 健康成果分布。 4）参与各种关键利益相关者，以确定并确定策略的优先级 减轻社会风险，建立人力资本并改善地区的医疗保健资源和成果 通过历史红线暴露于结构性种族主义。该研究具有创新性：（i）检查 结构性种族主义与健康成果之间的联系，（ii）在衡量医疗保健资源和 （iii）强调确定减少结构种族主义的永久影响的政策渠道。