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.

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.

Impressive Words: Linguistic Predictors of Public Approval of the U.S. Congress

What type of language makes the most positive impression within a professional setting? Is competent/agentic language or warm/communal language more effective at eliciting social approval? We examined this basic social cognitive question in a real world context using a “big data” approach—the recent record-low levels of public approval of the U.S. Congress. Using Linguistic Inquiry and Word Count (LIWC), we text analyzed all 123+ million words spoken by members of the U.S. House of Representatives during floor debates between 1996 and 2014 and compared their usage of various classes of words to their public approval ratings over the same time period. We found that neither agentic nor communal language positively predicted public approval. However, this may be because communion combines two disparate social motives (belonging and helping). A follow-up analysis found that the helping form of communion positively predicted public approval, and did so more strongly than did agentic language. Next, we conducted an exploratory analysis, examining which of the 63 standard LIWC categories predict public approval. We found that the public approval of Congress was highest when politicians used tentative language, expressed both positive emotion and anxiety, and used human words, numbers, prepositions, numbers, and avoided conjunctions and the use of second-person pronouns. These results highlight the widespread primacy of warmth over competence as the primary dimensions of social cognition.