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<p>Historical redlining, a housing policy applied across numerous cities in the United States in the 1930s, resulted in disinvestment in predominantly non-White, immigrant, or impoverished neighborhoods and has been associated with various adverse health outcomes. However, little is known about the effects of gentrification and residential mobility on health in historically redlined neighborhoods. Using linear regression, we evaluated the association between redlining, gentrification, and life expectancy at birth before and after adjustment for socio-spatial residential mobility in the Philadelphia metropolitan area. Tract-level data on life expectancy were obtained from the Centers for Disease Control and Prevention. Census data were used to define tract gentrification status in 2000–2010 (earlier-gentrification) and 2011–2018 (recent-gentrification). Tract socio-spatial mobility characteristics were defined using DataAxle’s household-level data. Life expectancy at birth was generally higher in historically privileged than disadvantaged tracts. After stratification by gentrification status, however, life expectancy in historically disadvantaged (redlined) areas was higher in earlier-gentrified than non-gentrified tracts. This difference was largely explained by socio-spatial mobility, namely a greater influx of moderate- and higher-income households to gentrified and lower-income households to non-gentrified tracts. In redlined tracts, for example, life expectancy in the unadjusted model was 4.7&#xa0;years lower in non-gentrified than earlier-gentrified tracts (confidence interval: − 6.4, − 2.9); this difference decreased to 1.7&#xa0;years (− 3.2, − 0.1) after adjustment for socio-spatial mobility. These findings have substantial implications for future public health research, highlighting the importance of including gentrification and/or socio-spatial mobility data when evaluating the association between historical policies, like redlining, and health outcomes in a given geographic area.</p>

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Effect of Gentrification and Residential Mobility on Associations Between Historical Redlining and Life Expectancy at Birth

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月3日

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  • Daniel Wiese,
  • Jordan Baeker Bispo,
  • Ann C. Klassen,
  • Charnita Zeigler-Johnson,
  • Ahmedin Jemal,
  • Kevin A. Henry,
  • Farhad Islami

摘要

Historical redlining, a housing policy applied across numerous cities in the United States in the 1930s, resulted in disinvestment in predominantly non-White, immigrant, or impoverished neighborhoods and has been associated with various adverse health outcomes. However, little is known about the effects of gentrification and residential mobility on health in historically redlined neighborhoods. Using linear regression, we evaluated the association between redlining, gentrification, and life expectancy at birth before and after adjustment for socio-spatial residential mobility in the Philadelphia metropolitan area. Tract-level data on life expectancy were obtained from the Centers for Disease Control and Prevention. Census data were used to define tract gentrification status in 2000–2010 (earlier-gentrification) and 2011–2018 (recent-gentrification). Tract socio-spatial mobility characteristics were defined using DataAxle’s household-level data. Life expectancy at birth was generally higher in historically privileged than disadvantaged tracts. After stratification by gentrification status, however, life expectancy in historically disadvantaged (redlined) areas was higher in earlier-gentrified than non-gentrified tracts. This difference was largely explained by socio-spatial mobility, namely a greater influx of moderate- and higher-income households to gentrified and lower-income households to non-gentrified tracts. In redlined tracts, for example, life expectancy in the unadjusted model was 4.7 years lower in non-gentrified than earlier-gentrified tracts (confidence interval: − 6.4, − 2.9); this difference decreased to 1.7 years (− 3.2, − 0.1) after adjustment for socio-spatial mobility. These findings have substantial implications for future public health research, highlighting the importance of including gentrification and/or socio-spatial mobility data when evaluating the association between historical policies, like redlining, and health outcomes in a given geographic area.