Gentrification and Displacement in the San Francisco Bay Area: A Comparison of Measurement Approaches

Mahasin S. Mujahid, Elizabeth Kelley Sohn, Jacob Izenberg, Xing Gao, Melody E. Tulier, Matthew M. Lee and Irene H. Yen
Additional contact information
Mahasin S. Mujahid: Division of Epidemiology, Berkeley School of Public Health, University of California, 2121 Berkeley Way West, Berkeley, CA 94720-7360, USA
Elizabeth Kelley Sohn: Kaiser Permanente, Oakland, CA 94611, USA
Jacob Izenberg: Department of Psychiatry, San Francisco School of Medicine, University of California, 982 Mission St., San Francisco, CA 94103, USA
Xing Gao: Division of Epidemiology, Berkeley School of Public Health, University of California, 2121 Berkeley Way West, Berkeley, CA 94720-7360, USA
Melody E. Tulier: Center for Interdisciplinary Research on AIDS, Yale University, New Haven, CT 06510, USA
Matthew M. Lee: Division of Epidemiology, Berkeley School of Public Health, University of California, 2121 Berkeley Way West, Berkeley, CA 94720-7360, USA
Irene H. Yen: University of California, Merced, Public Health, 5200 N. Lake Road Merced, CA 95343, USA

IJERPH, 2019, vol. 16, issue 12, 1-13

Abstract: Gentrification may play an important role in influencing health outcomes, but few studies have examined these associations. One major barrier to producing empirical evidence to establish this link is that there is little consensus on how to measure gentrification. To address this barrier, we compared three gentrification classification methodologies in relation to their ability to identify neighborhood gentrification in nine San Francisco Bay Area counties: the Freeman method, the Landis method, and the Urban Displacement Project (UDP) Regional Early Warning System. In the 1580 census tracts, 43% of the population had a bachelor’s degree or higher. The average median household income was $79,671 in 2013. A comparison of gentrification methodologies revealed that the Landis and Freeman methodologies characterized the vast majority of census tracts as stable, and only 5.2% and 6.1% of tracts as gentrifying. UDP characterized 46.7% of tracts at risk, undergoing, or experiencing advanced stages of gentrification and displacement. There was substantial variation in the geographic location of tracts identified as gentrifying across methods. Given the variation in characterizations of gentrification across measures, studies evaluating associations between gentrification and health should consider using multiple measures of gentrification to examine the robustness of the study findings across measures.

Keywords: gentrification; neighborhoods; health and health disparities (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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