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A large body of research has been dedicated to understanding the neighborhood conditions that impact health, which outcomes are affected, and how these associations vary by demographic and socioeconomic neighborhood and individual characteristics. This literature has focused mostly on the neighborhoods in which individuals reside, thus failing to recognize that residents across race/ethnicity and class spend a non-trivial amount of their time in neighborhoods far from their residential settings. To address this gap, we use mobile phone data from the company SafeGraph to compare racial inequality in neighborhood socioeconomic advantage exposure across three scales: the neighborhoods that residents live in, their adjacent neighborhoods, and the neighborhoods that they regularly visit. We found that the socioeconomic advantage levels in neighborhood networks differ from the levels at the residential and adjacent scales across all ethnoracial neighborhoods. Furthermore, socioeconomic advantage at the network level is associated with diabetes and hypertension prevalence above and beyond its impact at the residential and adjacent levels. We also find ethnoracial differences in these associations, with greater beneficial consequences of network socioeconomic advantage exposure on hypertension and diabetes for white neighborhoods. Future social determinants of health research needs to reconceptualize exposure to include the larger neighborhood network that a community is embedded in based on where their residents travel to and from.

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Research has made clear that neighborhoods impact the health and well-being of their residents. A related strand of research shows that neighborhood disadvantage is geographically clustered. Because the neighborhoods of low-income and minority populations tend to be more disadvantaged, neighborhood conditions help explain racial and socioeconomic inequalities. These strands of research restrict processes of neighborhood influence to operate only within and between geographically contiguous neighbors. However, we are underestimating the role of neighborhood conditions in explaining inequality if disadvantage extends beyond the residential and extralocal environments into a network of neighborhoods spanning the urban landscape based on where residents move within a city. I use anonymized mobile phone data to measure exposure to air pollution among residents of poor and minority neighborhoods in 88 of the most populous US cities. I find that residents from minority and poor neighborhoods travel to neighborhoods that have greater air pollution levels than the neighborhoods that residents from White and nonpoor neighborhoods visit. Hispanic neighborhoods exhibit the greatest overall pollution burden, Black/White and Asian/White disparities are greatest at the network than residential scale, and the socioeconomic advantage of lower risk exposure is highest for residents from White neighborhoods. These inequalities are notable given recent declines in segregation and air pollution levels in American cities.

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Ride-hailing businesses, including Uber and Lyft, have reshaped road traffic since they first began operating in the United States approximately a decade ago. It follows that ride-hailing may also alter the incidence and distribution of road traffic crash injuries and deaths. The available evidence relating ride-hailing to crashes is critically reviewed in this article. We present a theoretical model that synthesizes the hypothesized mechanisms, and we identify common methodological challenges and suggest priorities for future research. Mixed results have been reported for the overall incidence of road traffic crash injuries and deaths, likely due to heterogeneous impacts on vehicular traffic flow (e.g., increasing the volume of vehicles); on vehicle-, person-, and event-level characteristics (e.g., reducing alcohol-impaired driver crashes); on road-user types (e.g., increasing pedestrian crashes); and on environmental conditions (e.g., reducing crashes most substantially where public transit access is poorest). The lack of a well-developed theory of human mobility and methodological challenges that are common to many ecological studies impede exploration of these sources of moderation. Innovative solutions are required to explicate ride-hailing's heterogeneous impacts, to guide policy that can take advantage of the public health benefits of ride-hailing, and to ensure that research keeps pace with technological advances that continue to reshape road traffic use.

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Public school closures are increasing in number and size in U.S. cities. When public schools close, heated debates typically ensue. A central argument within this debate asserts that schools being closed are more likely to be located in minority, socioeconomically disadvantaged neighborhoods, and thus their abandonment has the potential for widening racial and socioeconomic gaps and exacerbating spatial inequality. Using school attendance boundary data in over 260 U.S. metropolitan areas, we examine the relationship between the locations of traditional elementary public school closures between 2010 and 2016 and neighborhood ethnoracial and socioeconomic composition in 2010 and their change over time. Our overall results indicate that closures are associated with lower neighborhood percent White and percent Hispanic and higher percent Black and socioeconomic disadvantage. While increasing percent White is positively associated with closure, we found little other evidence of a relationship between closure and other changes in ethnoracial and socioeconomic composition. However, the relationship between neighborhood context and closure varies across region and urbanicity, with closures associated with patterns of gentrification in urban areas, and exhibiting differential relationships with neighborhood SES, race and ethnicity across region.

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A diverse set of research has examined the ways in which population-level health and its ecological risk factors are embedded within self-reinforcing structures. Syndemic theory, for example, focuses on the co-occurrence of multiple diseases, whereas the spatial diffusion literature highlights the concentration of poor health among communities sharing geographic boundaries. This study combines these related but disciplinarily-isolated perspectives to examine the clustering of population-level health and its determinants across four dimensions: co-occurrence, spatial, temporal, and social network. Using data on U.S. county-level health outcomes and health factors from the Robert Wood Johnson Foundation's County Health Rankings, this study estimates associations between health outcomes within communities and the co-occurrence of community-level factors theorized to influence ecological health. Not only do health outcomes and their ecological risk factors cluster within counties, but also between geographically adjacent counties and counties connected via migration network pathways. Moreover, the self-reinforcing structures uncovered across the co-occurrence, spatial and network dimensions persist over time, and this clustering has consequences on county health and well-being. Rather than adopting the perspective that either health and its community-level factors should be broadly targeted and detached from local context or communities are different, have unique needs and thus should be treated in isolation, the approach advanced in this study identifies shared vulnerabilities in a way that allows for the development of knowledge networks between communities dealing with similar issues.

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Exposure to heat is a growing public health concern as climate change accelerates worldwide. Different socioeconomic and racial groups often face unequal exposure to heat as well as increased heat-related sickness, mortality, and energy costs. We provide new insight into thermal inequities by analyzing 20 Southwestern U.S. metropolitan regions at the census block group scale for three temperature scenarios (average summer heat, extreme summer heat, and average summer nighttime heat). We first compared average temperatures for top and bottom decile block groups according to demographic variables. Then we used spatial regression models to investigate the extent to which exposure to heat (measured by land surface temperature) varies according to income and race. Large thermal inequities exist within all the regions studied. On average, the poorest 10% of neighborhoods in an urban region were 2.2 °C (4 °F) hotter than the wealthiest 10% on both extreme heat days and average summer days. The difference was as high as 3.3-3.7 °C (6-7 °F) in California metro areas such as Palm Springs and the Inland Empire. A similar pattern held for Latinx neighborhoods. Temperature disparities at night were much smaller (usually ~1 °F). Disparities for Black neighborhoods were also lower, perhaps because Black populations are small in most of these cities. California urban regions show stronger thermal disparities than those in other Southwestern states, perhaps because inexpensive water has led to more extensive vegetation in affluent neighborhoods. Our findings provide new details about urban thermal inequities and reinforce the need for programs to reduce the disproportionate heat experienced by disadvantaged communities.

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Ridehailing services such as Uber have been promoted as viable interventions for curbing alcohol-involved driving fatalities. However, evidence of ridehailing's impact has been mixed, with some studies finding no association but others finding either an increase or a decrease in fatalities. We contribute to this literature by examining more recent years of data, which capture a period during which Uber ridership has grown substantially and alcohol-involved fatalities have increased. Furthermore, we test whether the relationship between Uber availability and traffic fatalities depends on local characteristics. We employ multivariate regression models to test the association between Uber availability and total, alcohol-involved, and weekend and holiday-specific traffic fatalities in the 100 most populated metropolitan areas in the United States between 2009 and 2017. We find that Uber availability is not associated with changes in total, alcohol-involved, and weekend and holiday-specific traffic fatalities in aggregate, yet it is associated with increased traffic fatalities in urban, densely populated counties.

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The nature of transportation has fundamentally transformed in recent years with the rise of ridehailing providers such as Uber. Yet, few studies have examined whether there is an association between ridehailing and rates of road accident injuries, and virtually all of the existing studies focus on the exceptional case of the United States. In this study, we exploit differences in the timing of the deployment of Uber across Britain to test the association between the advent of Uber's ridehailing services and rates of fatal and non-fatal road accidents. We find that the deployment of Uber in Great Britain is associated with a marginally significant reduction in the number of serious road accident injuries (e.g., fractures and internal injuries), although not the number of serious accidents. Slight injuries (e.g., sprains and bruises) declined outside of London after the rollout of Uber, but increased within London. We do not observe a statistically significant association between Uber and traffic fatalities. One interpretation for the decline in serious road injuries is that Uber may be a substitute form of transportation for risky drivers, including drink-drivers. However, ridehailing is also a substitute for public transit, particularly buses. The increase in the number of cars on the road may explain why slight injuries increased in London following Uber's rollout.

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Using data from the National Longitudinal Study of Adolescent to Adult Health, this study examines the relationship between significant changes in neighbourhood poverty during the transition to adulthood and shifts in depressive symptoms. We found that associations between changes in neighbourhood poverty and mental health disappeared after controlling for contemporaneous life course events, specifically transitions associated with intimate relationship building and human capital formation. The exception is a decrease in depressive symptoms for females moving into lower poverty neighbourhoods across the entire transition to adulthood period. We conclude that the impact of moving into significantly higher or lower poverty neighbourhoods during the transition to adulthood is conditioned on age, period and gender and complicated by the occurrence of other significant life course transitions.

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Uber and similar rideshare services are rapidly dispersing in cities across the United States and beyond. Given the convenience and low cost, Uber has been characterized as a potential countermeasure for reducing the estimated 121 million episodes of drunk driving and the 10,000 resulting traffic fatalities that occur annually in the United States. We exploited differences in the timing of the deployment of Uber in US metropolitan counties from 2005 to 2014 to test the association between the availability of Uber's rideshare services and total, drunk driving-related, and weekend- and holiday-specific traffic fatalities in the 100 most populated metropolitan areas in the United States using negative binomial and Poisson regression models. We found that the deployment of Uber services in a given metropolitan county had no association with the number of subsequent traffic fatalities, whether measured in aggregate or specific to drunk-driving fatalities or fatalities during weekends and holidays.

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Estimating the effects of international migration on left-behind children's educational attainment is complicated by the potential offsetting effects of fathers' absences and household remittances. Most research has not separated these aspects of international migration on children's human capital outcomes. We address this deficiency by using instrumental variables to isolate the effects of fathers' international migration absences from international household remittances on student enrollment and grade progression in Guatemala. Results indicate that fathers' absences and household international remittances are negatively related to enrollment, providing evidence for a culture of migration effect. For students who remain in school, household international remittances neutralize the harmful influence of fathers' absences on grade progression.

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Historically, Guatemalans have suffered high rates of poverty and malnutrition while nearly ten percent of their population resides abroad. Many Guatemalan parents use economic migration, mainly international migration to the United States, as a means to improve the human capital prospects of their children. However, as this investigation shows, the timing of migration events in relation to left-behind children's ages has important, often negative and likely permanent, repercussions on the physical development of their children. To illustrate these dynamics, this investigation uses an instrumental variables framework to disentangle the countervailing effects of Guatemalan fathers' absences due to migration from concomitant remittances on left-behind children's growth outcomes. Based on national-level data collected in 2000, the investigation reveals that the international migration of a father in the previous year is correlated with a 22.1% lower length/height-for-age z-score for the average left-behind child aged ≤ 3. In contrast, the receipt of remittance income has no influence on the physical stature of a child, which may indicate that migrant fathers with young children are not able to achieve economic success soon enough during their ventures abroad to fully ameliorate the harmful effects caused by their absences.

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Despite a well-established literature investigating race-related predictors of riot incidence, the racial aftermath of riots remains unexamined. In this study, I use the 1960s U.S. race riots to investigate trends in black residential segregation levels following large-scale riot activity in seven major U.S. cities. I use a novel approach--namely, synthetic control matching--to select a group of cities against which segregation trends can be compared. I find that levels of black segregation rose in 1970 for four of the seven cities, but these increases disappeared in 1980 and 1990 except in Detroit. These results mask differential trends at lower geographic levels: suburban neighborhoods in affected areas experienced larger and longer-term increases in segregation, particularly in traditionally hypersegregated cities in the Midwest and Northeast.

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BACKGROUND: Empirical research describes retirement migration to Mexico as a viable option for some older Americans. However, far less research examines this phenomenon among Mexican immigrants in the United States. The literature that does address this topic treats international migration as a singular occurrence and does not examine the possibility of return and subsequent reentry between countries. This omission creates an important gap in our knowledge of international retirement migration considering the strong transnational ties that Mexican immigrants maintain to the home and destination countries. OBJECTIVE: Using a multistate life table approach, this study examines the rate of return to Mexico and reentry back into the United States among Mexican males aged 50 and older with U.S. migration experience, as well as the number of years spent in both countries. RESULTS: Results show that the rate of reentry from Mexico into the United States declined from 3.33% at age 50-54 to less than 1% at age 70 and older (p-value<0.05). In contrast, the rate of return to Mexico from the United States increased from 3.19% at age 50 to 54 to 4.44%at age 65 to 69 and dropped to less than 2% at age 70 and older (p-value<0.05). CONCLUSIONS: While rates of return and reentry among this population are relatively low, they provide insight on the potential life course factors driving the migration patterns of a population of increasing size and relevance in the United States.