Gentrification Yields Racial And Ethnic Disparities In Exposure To Contextual Determinants Of Health.

This article examines racial and ethnic disparities in the relationship between gentrification and exposure to contextual determinants of health. In our study, we focused on changes in selected contextual determinants of health (health care access, social deprivation, air pollution, and walkability) and life expectancy during the period 2006-21 among residents of gentrifying census tracts in six large US cities that have experienced different gentrification patterns and have different levels of segregation: Chicago, Illinois; Los Angeles, California; New York, New York; Philadelphia, Pennsylvania; San Francisco, California; and Seattle, Washington. We found that gentrification was associated with overall improvements in the likelihood of living in Medically Underserved Areas across racial and ethnic groups, but it was also associated with increased social deprivation and reduced life expectancy among Black people, Hispanic people, and people of another or undetermined race or ethnicity. In contrast, we found that gentrification was related to better (or unchanged) contextual determinants of health for Asian people and White people. Our findings can inform policies that target communities identified to be particularly at risk for worsening contextual determinants of health as a result of gentrification.

Association between property investments and crime on commercial and residential streets: Implications for maximizing public safety benefits.

Physical property investments enhance public safety in communities while alleviating the need for criminal justice system responses. Policy makers and local government officials must allocate scare resources for community and economic development activities. Understanding where physical property investments have the greatest crime reducing benefits can inform decision making to maximize economic, safety, and health outcomes. This study uses Spatial Durbin models with street segment and census tract by year fixed effects to examine the impact of physical property investments on changes in property and violent crime over an 11-year period (2008-2018) in six large U.S. cities. The units of analysis are commercial and residential street segments. Street segments are classified into low, medium, and high crime terciles defined by initial crime levels (2008-2010). Difference of coefficients tests identify significant differences in building permit effects across crime terciles. The findings reveal there is a significant negative relationship between physical property investments and changes in property and violent crime on commercial and residential street segments in all cities. Investments have the greatest public safety benefit where initial crime levels are the highest. The decrease in violent crime is larger on commercial street segments, while the decrease in property crime is larger on residential street segments. Targeting the highest crime street segments (i.e., 90th percentile) for property improvements will maximize public safety benefits.

Gentrification, Mobility, and Exposure to Contextual Social Determinants of Health.

This study uses individual level consumer trace data for 2006 residents of low- and moderate-income neighborhoods for the principal cities of the 100 largest metropolitan regions in the US using their location in 2006 and 2019 to examine exposure to the following four cSDOH: healthcare access (Medically Underserved Areas), socioeconomic condition (Area Deprivation Index), air pollution (NO2, PM 2.5 and PM10), and walkability (National Walkability Index). The results control for individual characteristics and initial neighborhood conditions. Residents of neighborhoods classified as gentrifying were exposed to more favorable cSDOH as of 2006 relative to residents of low- and moderate-income neighborhoods that were not gentrifying in terms of likelihood to be in a MUA, and level of local deprivation and walkability while experiencing similar level of air pollution. As a result of changes in neighborhood characteristics and differential mobility pattern, between 2006 and 2019, individuals who originally lived in gentrifying neighborhoods experienced worse changes in MUAs, ADI, and Walkability Index but a greater improvement in exposure to air pollutants. The negative changes are driven by movers, while stayers actually experience a relative improvement in MUAs and ADI and larger improvements in exposure to air pollutants. The findings indicate that gentrification may contribute to health disparities through changes in exposure to cSDOH through mobility to communities with worse cSDOH among residents of gentrifying neighborhoods although results in terms of exposure to health pollutants are mixed.

Housing cost burden and life satisfaction.

The share of income spent on housing varies across individuals and countries but it has been increasing over time in a wide range of countries, particularly among lower income households, rising housing affordability as a prominent challenge in higher income economies. Variations in share of income spent on housing can reflect variations in household preferences but when more than a certain level of income is spent on housing, households face tradeoffs between housing and non-housing consumption that are expected to negatively affect their overall life satisfaction. Using data from the 2018 European Union Statistics on Income and Living Conditions (EU-SILC) for 14 countries we find that, controlling for household sociodemographic characteristics, households spending more than 30 percent of their income and those spending more than 50 percent of their income on housing report lower levels of life satisfaction, with the latter group reporting the lowest level. The negative relationship between housing cost burden and reported life satisfaction is found across countries but varies in magnitude, which points to the need to further investigate the mechanisms behind the association between housing cost burden and life satisfaction and the role of country-specific effects, including differences in welfare systems, in moderating this association.