Gentrification, Mobility, and Exposure to Contextual Determinants of Health

中产阶级化、流动性和健康的背景决定因素

• 批准号: 10592167
• 负责人: Arthur Acolin
• 金额: $ 24.6万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-02 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10592167
• 关键词: Address; Affect; Air Pollution; Area; Asthma; Buffers; Censuses; Characteristics; Chronic; Communities; Data; Data Set; Data Sources; Databases; Demography; Destinations; Diabetes Mellitus; Disadvantaged; Disparity; Economics; Environment; Ethnic Origin; Event; Exposure to; Gender; Geography; Green space; Health; Health Promotion; Household; Housing; Income; Individual; Infrastructure; Investigation; Investments; Length; Life Expectancy; Literature; Location; Low income; Malignant Neoplasms; Marketing; Measures; Medically Underserved Area; Methods; Migrant; Neighborhoods; Obesity; Outcome; Pathway interactions; Pattern; Policies; Population; Process; Public Health; Race; Research; Residential Mobility; Socioeconomic Status; Sociology; Source; Specificity; Surveys; Testing; Work; built environment; deprivation; design; ethnic disparity; ethnic health disparity; ethnic minority; experience; health determinants; health disparity; health equity; health inequalities; innovation; longitudinal dataset; metropolitan; migration; multidisciplinary; novel; open source; population health; racial disparity; racial health disparity; racial minority; residence; segregation; social; sociodemographics; socioeconomic disparity; socioeconomics; theories

Project Summary: This project investigates the relationship between gentrification, displacement, and contextual determinants of health (CDOH) using consumer trace data as a unique new source to examine long term mobility for a large number of individuals. The impacts of neighborhoods on health are well established; differences in residential environments contribute to inequalities in health outcomes that systematically disadvantage racial/ethnic minorities. Gentrification is the process through which lower income neighborhoods experience a rapid rise in their relative socioeconomic position within the metropolitan region (Core-Based Statistical Area or CBSA). It is an increasingly prevalent phenomenon in recent decades with the potential to cause negative health outcomes through residential displacement. Yet, we currently have limited evidence on whether residents of gentrifying neighborhoods are more likely to move compared to residents of non-gentrifying neighborhoods; where they move to, particularly if the destination neighborhoods are more disadvantaged in terms of contextual CDOH, defined as place-based CDOH that operate at the neighborhood level; and who is more likely to move, specifically if racial and ethnic minorities are disproportionately impacted. Data limitations have constrained empirical investigation of the public health impacts of gentrification. The proposed research leverages consumer trace data from Data Axle that have broad population coverage and high temporal and spatial specificity to further our understanding of gentrification, mobility, and health disparities. Our multidisciplinary team's expertise in demography, applied economics, sociology, and public health is ideally suited to conduct this research. Specific aims: (1) document the impact of gentrification on mobility patterns; (2) demonstrate how these mobility patterns affect exposure to key CDOH shown to contribute to the perpetuation of socioeconomic and race/ethnic inequities in health; and (3) examine the differential effects of gentrification across race/ethnicity, gender, residents socioeconomic status, local housing market dynamics, as well as metropolitan-area segregation levels. To achieve these aims, our approach leverages a novel longitudinal dataset for the 100 largest US metros based on consumer trace data at the address level with broad population coverage, including for lower income residents. We will use regression at the individual level controlling for individual and neighborhood characteristics to establish the relationship between gentrification (defined at the tract level) and likelihood to move, distance and characteristics of the moves as well as to analyze changes in CDOH (at different scales depending on conceptual considerations and data availability) among stayers and movers between 2006 and 2020. The proposed research is the first to our knowledge to address these questions with such comprehensive data and represents a significant contribution to public health. It will also develop open-source infrastructure to produce neighborhood level migration measures that can support future research.

项目概述：这个项目调查了士绅化、流离失所和 使用消费者跟踪数据作为检查Long的唯一新来源的健康背景决定因素(CDOH) 大量个人的术语流动性。社区对健康的影响是公认的； 居住环境的差异导致健康结果的不平等，这是系统性的 对少数族裔不利。士绅化是低收入社区通过的过程 经历他们在大都市区域内的相对社会经济地位的快速上升(以核心为基础 统计区或CBSA)。这是近几十年来日益普遍的现象，有可能 通过居住流离失所造成负面的健康后果。然而，我们目前掌握的证据有限 中产阶级化社区的居民是否比非中产阶级化社区的居民更有可能搬家 社区；他们搬到哪里，特别是如果目的地社区在 上下文CDOH的术语，定义为在邻里层面运作的基于地点的CDOH；以及谁是 更有可能搬家，特别是如果种族和少数民族受到不成比例的影响。 数据限制限制了对士绅化对公共健康影响的实证调查。这个 拟议的研究利用来自Data Axle的消费者跟踪数据，这些数据具有广泛的人口覆盖率和 高度的时间和空间特异性，以加深我们对士绅化、流动性和健康差异的理解。 我们的多学科团队在人口学、应用经济学、社会学和公共卫生方面的专业知识是理想的 适合进行这项研究。 具体目标：(1)记录士绅化对流动模式的影响；(2)展示这些流动如何 模式影响对关键的CDOH的暴露，被证明有助于社会经济和种族/民族的永久化 以及(3)审查不同种族/族裔、性别和性别的士绅化的不同影响。 居民的社会经济地位、当地住房市场动态以及大都市地区的隔离程度。 为了实现这些目标，我们的方法利用了美国100个最大的地铁的新的纵向数据集 关于具有广泛人口覆盖面的地址级别的消费者跟踪数据，包括较低收入的数据 居民。我们将在个人层面上使用回归来控制个人和邻里特征 要确定绅士化(在区域层面上定义)与移动的可能性、距离之间的关系 以及移动的特征以及分析CDOH的变化(在不同的尺度上取决于 概念上的考虑和数据的可获得性)在2006至2020年间在留守人员和搬运者之间。 据我们所知，拟议的研究是第一次用如此全面的数据来解决这些问题 对公共卫生做出了重大贡献。它还将开发开源基础设施，以 制定社区层面的移民措施，以支持未来的研究。