Gentrification, Mobility, and Exposure to Contextual Determinants of Health

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.