Neighborhood Racial Composition and Unequal Exposure to Violent Crime in Everyday Contexts.

Exposure to violence is a critical aspect of contemporary racial inequality in the United States. While extensive research has examined variations in violent crime rates across neighborhoods, less attention has been given to understanding individuals' everyday exposure to violent crimes. This study investigates patterns of exposure to violent crimes among neighborhood residents using cell phone mobility data and violent crime reports from Chicago. The analysis reveals a positive association between the proportion of Black residents in a neighborhood and the level of exposure to violent crimes experienced by residents. Controlling for a neighborhood's level of residential disadvantage and other neighborhood characteristics did not substantially diminish the relationship between racial composition and exposure to violent crimes in everyday life. Even after controlling for violence within residents' neighborhoods, individuals residing in Black neighborhoods continue to experience significantly higher levels of violence in their day-to-day contexts compared to those living in White neighborhoods. This suggests that racial segregation in everyday exposures, rather than residential segregation, plays a central role in racial inequality in exposure to violence. Additionally, the analysis suggests that neighborhoods with more Hispanic and Asian residents are exposed to less and more violent crime, respectively, compared to neighborhoods with more White residents. However, this is only observed when not adjusting for the volume of visits points of interest receive; otherwise, the finding is reversed. This study offers valuable insights into potentially novel sources of racial disparities in exposure to violent crimes in everyday contexts, highlighting the need for further investigation.

Assessing interstate racial and socioeconomic disparities in newborn screening policies in the United States.

Introduction: This paper explores racial and socioeconomic disparities in newborn screening (NBS) policies across the United States. While inter-state inequality in healthcare policies is often considered a meaningful source of systemic inequity in healthcare outcomes, to the best of our knowledge, no research has explored racial and socioeconomic disparities in newborn screening policies based on state of residence. Methods: We investigate these disparities by calculating weighted average exposure to specific NBS tests by racial and socioeconomic group. We additionally estimate count models of the number (and type) of NBS conditions screened for by state racial and socioeconomic composition. Results: Adding to the knowledge base that social determinants of health and health disparities are linked, our analysis surprisingly reveals little evidence of substantial inter-state inequity in newborn screenings along racial and socioeconomic lines. Discussion: While there is substantial nationwide racial and socioeconomic inequity in terms of infant health, the distribution of state-level policies does not appear to be structured in a manner to be a driver of these disparities. Our findings suggest that efforts to reduce inequities in outcomes related to NBS should shift focus toward the delivery of screening results and follow-up care as discussion builds on expanding NBS to include more conditions and genomic testing.

Cold weather isolation is worse in poor and non-white neighborhoods in the United States.

Social isolation can cause a variety of adverse physical and mental health effects and is central to understanding broader social disparities among marginalized groups in the United States. This study aims to assess whether temperature variation is associated with daily social isolation at the neighborhood level. I test a series of two-way fixed effects models to see if mean daily temperature is associated with individuals spending the entire day at home, as measured using smartphone data, across a sample of 45 million devices in 2019 in the United States. Using interaction terms, I specifically examine heterogeneity in temperature effects by neighborhood racial composition and socioeconomic status. The two-way fixed effects models reveal highly statistically significant negative coefficients for the interaction between temperature and neighborhood proportion Black, temperature and neighborhood proportion Hispanic, and temperature and neighborhood residential disadvantage, in predicting the probability of spending the entire day at home. In marginal terms, the findings indicate the gap in the probability of spending the entire day at home between an all-Black neighborhood and an all-White neighborhood grows by nearly 10 percentage points from the warmest day of the year to the coldest day of the year in some parts of the United States. My models highlight how residents of poor and majority Black and Hispanic neighborhoods experience disproportionate social isolation in the form of a greater propensity to spend the entire day at home.

Inter-City Emotional Synchrony Is Conditional on Mobility Patterns.

Recent research has attempted to document large-scale emotional contagion on online social networks. Despite emotional contagion being primarily driven by in-person mechanisms, less research has attempted to measure large-scale emotional contagion in in-person contexts. In this paper, I operationalize the temporal emotions associated with a particular city at particular points in time using sentiment analysis on Twitter data. Subsequently, I study how emotions converge between seven proximal cities in the state of Virginia, using two-way fixed effect models. I find that positive emotions tend to be synchronous between cities, but that effect is conditional on the level of contact between city residents at that period of time, as indicated by cell phone mobility data. I do not find any synchrony based on other types of emotions or general sentiment. I discourage drawing causal conclusions based on the presumed existence of several unmeasured sources of bias.

Neighborhood socioeconomic inequality based on everyday mobility predicts COVID-19 infection in San Francisco, Seattle, and Wisconsin.

Race and class disparities in COVID-19 cases are well documented, but pathways of possible transmission by neighborhood inequality are not. This study uses administrative data on COVID-19 cases for roughly 2000 census tracts in Wisconsin, Seattle/King County, and San Francisco to analyze how neighborhood socioeconomic (dis)advantage predicts cumulative caseloads through February 2021. Unlike past research, we measure a neighborhood's disadvantage level using both its residents' demographics and the demographics of neighborhoods its residents visit and are visited by, leveraging daily mobility data from 45 million mobile devices. In all three jurisdictions, we find sizable disparities in COVID-19 caseloads. Disadvantage in a neighborhood's mobility network has greater impact than its residents' socioeconomic characteristics. We also find disparities by neighborhood racial/ethnic composition, which can be explained, in part, by residential and mobility-based disadvantage. Neighborhood conditions measured before a pandemic offer substantial predictive power for subsequent incidence, with mobility-based disadvantage playing an important role.

Property Tax Foreclosure, Spatial Effects, and Neighborhood Racial Demographic Change: Examining Data From Detroit.

In recent decades, the city of Detroit has experienced the greatest population loss of any major American city. Applying Event History Analysis methodology to a large dataset containing information on all properties in Detroit between 2002 and 2013, I examine how Property Tax Foreclosure spatially perpetuated itself in Detroit, finding evidence that the number of past but recent Property Tax Foreclosures in a localized area significantly predicts the likelihood of a future foreclosure. I extrapolate these findings to mathematical simulations and find evidence that suggests that initial Property Tax Foreclosures played a significant role in cascading many later on. Finally, building off past research that suggests neighborhood blight disproportionally affects white residential preferences and patterns, I perform an empirical analysis that examines how the initial distribution of Property Tax Foreclosures in Detroit neighborhoods played some role in determining how those neighborhoods have experienced racial demographic change.