Racial Inequalities in Adolescents' Exposure to Racial and Socioeconomic Segregation, Collective Efficacy, and Violence.

In the United States, Black youth tend to grow up in remarkably less resourced neighborhoods than White youth. This study investigates whether and to what extent Black youth are moreover exposed to less resourced activity spaces beyond the home. We draw on GPS data from a large sample of urban youth in the Columbus, Ohio-based Adolescent Health and Development in Context study (2014-2016) to examine to what extent Black youth experience nontrivial, disproportionate levels of exposure to more disadvantaged and segregated contexts in their daily routines compared with similarly residentially situated White youth. Specifically, we estimate Black-White differences in nonhome exposure to concentrated disadvantage, racial segregation, collective efficacy, and violent crime. We find that Black youths' activity spaces have substantially higher rates of racial segregation and violent crime than those of White youth, and substantially lower levels of collective efficacy-even after accounting for a host of individual- and home neighborhood-level characteristics. We find more modest evidence of differences in exposure to socioeconomic disadvantage. These findings have important implications for neighborhood-centered interventions focused on youth well-being and the contextual effects and segregation literatures more generally.

Neighborhoods, Activity Spaces, and the Span of Adolescent Exposures.

Since the inception of urban sociology, the "neighborhood" has served as the dominant context thought to capture developmentally significant youth experiences beyond the home. Yet no large-scale study has examined patterns of exposure to the most commonly used operationalization of neighborhood - the census tract - among urban youth. Using smartphone GPS data from the Adolescent Health and Development in Context study (N=1405), we estimate the amount of time youth spend in residential neighborhoods and consider explanations for variation in neighborhood exposure. On average, youth (ages 11 to 17) spend 5.7% of their waking time in their neighborhood but not at home, 60% at home, and 34.3% outside their neighborhood. Multilevel negative binomial regression models indicate that residence in economically disadvantaged neighborhoods is associated with less time in neighborhood. Higher levels of local violence and the absence of a neighborhood school the youth is eligible to attend are negatively associated with time in neighborhood and mediate the concentrated disadvantage effect. Fractional multinomial logit models indicate that higher violence is linked with increased time at home while school absence is associated with increased outside-neighborhood time. Theoretical development and empirical research on neighborhood effects should incorporate findings on the extent and nature of neighborhood and broader activity space exposures among urban youth.

The timing of geographic power.

In many studies on the spatial risk of disease, investigators use geographic locations at the time of disease diagnosis in spatial models to search for individual areas of elevated risk. However, these studies often fail to find a significant spatial signal. This may be due to the misspecification of the timing and location of pertinent exposures. Environmental exposures related to cancer risk vary over space and time, and many cancers have long latencies. When these factors are considered in conjunction with a mobile population, it is likely that the spatial signal related to relevant historic environmental exposures is obscured. To investigate this hypothesis, we conducted simulation studies to characterize the effect of residential mobility on the ability of generalized additive models to detect areas of significantly elevated historic environmental exposure. We generated data based on the residential histories of participants in the National Cancer Institute Surveillance, Epidemiology, and End Results non-Hodgkin lymphoma study, and varied the duration and intensity of the environmental exposure. Results showed that the probability of detection, mean spatial sensitivity, and mean spatial specificity of models decreased steadily as the time since relevant exposure increased. This suggests that for diseases with long latencies, spatial areas of high risk due to high-intensity exposure of relatively short duration will be difficult to detect over time when using residential locations at the time of diagnosis in mobile study populations.

The Geometry of Continuous Latent Space Models for Network Data.

We review the class of continuous latent space (statistical) models for network data, paying particular attention to the role of the geometry of the latent space. In these models, the presence/absence of network dyadic ties are assumed to be conditionally independent given the dyads' unobserved positions in a latent space. In this way, these models provide a probabilistic framework for embedding network nodes in a continuous space equipped with a geometry that facilitates the description of dependence between random dyadic ties. Specifically, these models naturally capture homophilous tendencies and triadic clustering, among other common properties of observed networks. In addition to reviewing the literature on continuous latent space models from a geometric perspective, we highlight the important role the geometry of the latent space plays on properties of networks arising from these models via intuition and simulation. Finally, we discuss results from spectral graph theory that allow us to explore the role of the geometry of the latent space, independent of network size. We conclude with conjectures about how these results might be used to infer the appropriate latent space geometry from observed networks.

Feasibility and Validity of Geographically Explicit Ecological Momentary Assessment With Recall-Aided Space-Time Budgets.

We employ data from the Adolescent Health and Development in Context Study-a representative sample of urban youth ages 11-17 in and around the Columbus, OH area-to investigate the feasibility and validity of smartphone-based geographically explicit ecological momentary assessment (GEMA). Age, race, household income, familiarity with smartphones, and self-control were associated with missing global positioning systems (GPS) coverage, whereas school day was associated with discordance between percent of time at home based on GPS-only versus recall-aided space-time budget data. Fatigue from protocol compliance increases missing GPS across the week, which results in more discordance. Although some systematic differences were observed, these findings offer evidence that smartphone-based GEMA is a viable method for the collection of activity space data on urban youth.

Ecological Networks and Urban Crime: The Structure of Shared Routine Activity Locations and Neighborhood-Level Informal Control Capacity.

Drawing on Jacobs (1961), we hypothesize that public contact among neighborhood residents while engaged in day-to-day routines, captured by the aggregate network structure of shared local exposure, is consequential for crime. Neighborhoods in which residents come into contact more extensively in the course of conventional routines will exhibit higher levels of public familiarity, trust, and collective efficacy with implications for the informal social control of crime. We employ the concept of ecological ("eco-") networks - networks linking households within neighborhoods through shared activity locations - to formalize the notion of overlapping routines. Using micro-simulations of household travel patterns to construct census tract-level eco-networks for Columbus, OH, we examine the hypothesis that eco-network intensity (the probability that households tied through one location in a neighborhood eco-network will also be tied through another visited location) is negatively associated with tract-level crime rates (N=192). Fitted spatial autoregressive models offer evidence that neighborhoods with higher intensity eco-networks exhibit lower levels of violent and property crime. In contrast, a higher prevalence of non-resident visitors to a given tract is positively associated with property crime. These analyses hold the potential to enrich insight into the ecological processes that shape variation in neighborhood crime.

Understanding Racial Differences in Exposure to Violent Areas: Integrating Survey, Smartphone, and Administrative Data Resources.

Emerging evidence indicates that exposure to violent areas may influence youth wellbeing. We employ smartphone GPS data on youth activity spaces to examine the extent of, and potential explanations for, racial disparities in these exposures. Multilevel models of data from the Adolescent Health and Development in Context study indicate that exposures to violent areas vary significantly across days of the week and between youth who reside in the same neighborhood. African American youth are exposed to areas with substantially higher levels of violence. Residing in a disadvantaged neighborhood is significantly associated with exposure to violent areas and explains a non-trivial proportion of the racial difference in this outcome. However, neighborhood factors are incomplete explanations of the racial disparity. Characteristics of the activity locations at which youth spend time explain the residual racial disparity in exposure to violent areas. These findings highlight the importance of youth activity spaces, above and beyond their neighborhood environments.

Empirical Reference Distributions for Networks of Different Size.

Network analysis has become an increasingly prevalent research tool across a vast range of scientific fields. Here, we focus on the particular issue of comparing network statistics, i.e. graph-level measures of network structural features, across multiple networks that differ in size. Although "normalized" versions of some network statistics exist, we demonstrate via simulation why direct comparison is often inappropriate. We consider normalizing network statistics relative to a simple fully parameterized reference distribution and demonstrate via simulation how this is an improvement over direct comparison, but still sometimes problematic. We propose a new adjustment method based on a reference distribution constructed as a mixture model of random graphs which reflect the dependence structure exhibited in the observed networks. We show that using simple Bernoulli models as mixture components in this reference distribution can provide adjusted network statistics that are relatively comparable across different network sizes but still describe interesting features of networks, and that this can be accomplished at relatively low computational expense. Finally, we apply this methodology to a collection of ecological networks derived from the Los Angeles Family and Neighborhood Survey activity location data.

Patterns of local segregation: Do they matter for neighborhood crime?

In this paper, we extend recent research on the spatial measurement of segregation and the spatial dynamics of urban crime by conceptualizing, measuring, and describing local segregation by race-ethnicity and economic status, and examining the linkages of these conditions with levels of neighborhood violent and property crime. The analyses are based on all 8895 census tracts within a sample of 86 large U.S. cities. We fit multilevel models of crime that incorporate measures of local segregation. The results reveal that, net of city-level and neighborhood characteristics, White-Black local segregation is associated with lower violent and property crime. In contrast, local segregation of low income from high income households is connected with higher crime, particularly neighborhood violence.

Statistical inference for complete and incomplete mobility trajectories under the flight-pause model.

We formulate a statistical flight-pause model (FPM) for human mobility, represented by a collection of random objects, called motions, appropriate for mobile phone tracking (MPT) data. We develop the statistical machinery for parameter inference and trajectory imputation under various forms of missing data. We show that common assumptions about the missing data mechanism for MPT are not valid for the mechanism governing the random motions underlying the FPM, representing an understudied missing data phenomenon. We demonstrate the consequences of missing data and our proposed adjustments in both simulations and real data, outlining implications for MPT data collection and design.

Leveraging Experience Sampling/Ecological Momentary Assessment for Sociological Investigations of Everyday Life.

Experience sampling (ES) - also referred to as ecological momentary assessment (EMA) - is a data collection method that involves asking study participants to report on their thoughts, feelings, behaviors, activities, and environments in (or near) real time. ES/EMA is typically administered using an intensive longitudinal design (repeated assessments within and across days). Although use of ES/EMA is widespread in psychology and health sciences, uptake of the method among sociologists has been limited. We argue that ES/EMA offers key advantages for the investigation of sociologically relevant phenomena, particularly in light of recent disciplinary emphasis on investigating the everyday mechanisms through which social structures and micro (individual and relational) processes are mutually constitutive. We describe extant and potential research applications illustrating advantages of ES/EMA regarding enhanced validity, disentangling short-term dynamics, and the potential for linkage with spatially and temporally referenced data sources. We also consider methodological challenges facing sociological research using ES/EMA.

Racial Differences in Activity Space Exposures and Everyday Perceptions of Safety Among Urban Youth.

PURPOSE: The everyday experience of safety promotes health and successful development during adolescence. To date, few studies have examined racial variation in the spatial determinants of in-the-moment perceived safety. METHODS: Drawing on data from the Columbus, Ohio-based Adolescent Health and Development in Context study (N = 1,405), we consider the influence of intraindividual variability in Global Positioning System-based exposure to both high-proportion White urban neighborhoods and neighborhood violence for the everyday location-based safety perceptions of Black and White youth (ages 11-17) as captured by ecological momentary assessment. RESULTS: Exposure to higher area-level violence reduces youths' safety perceptions. Momentary exposure to residentially White-dominated neighborhoods also reduces perceived safety, but only for Black youth who spend more time, on average, in White areas. In contrast, we observe some limited evidence that White youth perceive greater safety when in White neighborhoods if they spend more time in white neighborhoods on average. DISCUSSION: These findings point to the need for greater attention to in situ experiences in understanding the origins of racial disparities in health and wellbeing. For Black youth, a restricted focus on the consequences of residing in Black segregated neighborhoods may obscure potentially health consequential exposures beyond these areas.

LAND-USE FILTERING FOR NONSTATIONARY SPATIAL PREDICTION OF COLLECTIVE EFFICACY IN AN URBAN ENVIRONMENT.

Collective efficacy-the capacity of communities to exert social control toward the realization of their shared goals-is a foundational concept in the urban sociology and neighborhood effects literature. Traditionally, empirical studies of collective efficacy use large sample surveys to estimate collective efficacy of different neighborhoods within an urban setting. Such studies have demonstrated an association between collective efficacy and local variation in community violence, educational achievement, and health. Unlike traditional collective efficacy measurement strategies, the Adolescent Health and Development in Context (AHDC) Study implemented a new approach, obtaining spatially-referenced, place-based ratings of collective efficacy from a representative sample of individuals residing in Columbus, OH. In this paper we introduce a novel nonstationary spatial model for interpolation of the AHDC collective efficacy ratings across the study area, which leverages administrative data on land use. Our constructive model specification strategy involves dimension expansion of a latent spatial process and the use of a filter defined by the land-use partition of the study region to connect the latent multivariate spatial process to the observed ordinal ratings of collective efficacy. Careful consideration is given to the issues of parameter identifiability, computational efficiency of an MCMC algorithm for model fitting, and fine-scale spatial prediction of collective efficacy.

Paws on the Street: Neighborhood-Level Concentration of Households with Dogs and Urban Crime.

The formative work of Jane Jacobs underscores the combination of "eyes on the street" and trust between residents in deterring crime. Nevertheless, little research has assessed the effects of residential street monitoring on crime due partly to a lack of data measuring this process. We argue that neighborhood-level rates of households with dogs captures part of the residential street monitoring process core to Jacobs' hypotheses and test whether this measure is inversely associated with property and violent crime rates. Data from a large-scale marketing survey of Columbus, OH, USA residents (2013; n = 43,078) are used to measure census block group-level (n = 595) rates of households with dogs. Data from the Adolescent Health and Development in Context study are used to measure neighborhood-level rates of trust. Consistent with Jacobs' hypotheses, results indicate that neighborhood concentration of households with dogs is inversely associated with robbery, homicide, and, to a less consistent degree, aggravated assault rates within neighborhoods high in trust. In contrast, results for property crime suggest that the inverse association of dog concentration is independent of levels of neighborhood trust. These associations are observed net of controls for neighborhood sociodemographic characteristics, temporally lagged crime, and spatial lags of trust and dog concentration. This study offers suggestive evidence of crime deterrent benefits of local street monitoring and dog presence and calls attention to the contribution of pets to other facets of neighborhood social organization.

Everyday perceptions of safety and racial disparities in hair cortisol concentration.

OBJECTIVE: Black-White disparities in physiological stress during adolescence are increasingly evident but remain incompletely understood. We examine the role of real-time perceptions of safety in the context of everyday routines to gain insight into the sources of observed adolescent racial differences in chronic stress as measured by hair cortisol concentration (HCC). METHOD: We combined social survey, ecological momentary assessment (EMA), and hair cortisol data on 690 Black and White youth ages 11-17 from wave 1 of the Adolescent Health and Development in Context (AHDC) study to investigate racial differences in physiological stress. Individual-level, reliability-adjusted measures of perceived unsafety outside the home were drawn from a week-long smartphone-based EMA and tested for association with hair cortisol concentration. RESULTS: We observed a statistically significant interaction (p < .05) between race and perceptions of unsafety. For Black youth, perceived unsafety was associated with higher HCC (p < .05). We observed no evidence of an association between perceptions of safety and expected HCC for White youth. For youth who perceive their out-of-home activity locations to be consistently safe, the racial difference in expected HCC was not statistically significant. At the high end of perceived unsafety, however, Black-White differences in HCC were pronounced (0.75 standard deviations at the 95th percentile on perceived unsafety; p < .001). DISCUSSION: These findings call attention to the role of everyday perceptions of safety across non-home routine activity contexts in explaining race differences in chronic stress as assessed by hair cortisol concentrations. Future research may benefit from data on in situ experiences to capture disparities in psychological and physiological stress.

RESTRICTED SPATIAL REGRESSION METHODS: IMPLICATIONS FOR INFERENCE.

The issue of spatial confounding between the spatial random effect and the fixed effects in regression analyses has been identified as a concern in the statistical literature. Multiple authors have offered perspectives and potential solutions. In this paper, for the areal spatial data setting, we show that many of the methods designed to alleviate spatial confounding can be viewed as special cases of a general class of models. We refer to this class as Restricted Spatial Regression (RSR) models, extending terminology currently in use. We offer a mathematically based exploration of the impact that RSR methods have on inference for regression coefficients for the linear model. We then explore whether these results hold in the generalized linear model setting for count data using simulations. We show that the use of these methods have counterintuitive consequences which defy the general expectations in the literature. In particular, our results and the accompanying simulations suggest that RSR methods will typically perform worse than non-spatial methods. These results have important implications for dimension reduction strategies in spatial regression modeling. Specifically, we demonstrate that the problems with RSR models cannot be fixed with a selection of "better" spatial basis vectors or dimension reduction techniques.

Geographic Isolation, Compelled Mobility, and Everyday Exposure to Neighborhood Racial Composition Among Urban Youth.

Foundational urban social theories view heterogeneity of exposure to spatial and social contexts as essential aspects of the urban experience. In contrast, contemporary neighborhood research emphasizes the isolation of city dwellers - particularly residents of racially segregated neighborhoods. Using geospatial data on a sample of youth from the 2014-16 Columbus, OH-based Adolescent Health and Development in Context study, we explore the extent to which the neighborhood locations of everyday activities vary with respect to residential racial composition. In the context of segregated US metro areas, the geographic isolation approach expects home census tract racial composition to powerfully shape the racial composition of activity location neighborhoods. In this view, Black youth residing in high proportion Black neighborhoods are expected to spend the vast majority of their time exposed to similarly Black-concentrated neighborhoods. Consistent with an alternative compelled mobility approach, we find that Black youth residing in high proportion Black neighborhoods exhibit among the highest levels of heterogeneity in the racial composition of neighborhoods encountered. Moreover, Black youth residing in high proportion Black neighborhoods are expected to spend 39% of their non-home time (roughly 2.5 hours a day) in low proportion Black neighborhoods compared to 23% (1.5 hours) in high proportion Black neighborhoods. Exposures to low proportion Black neighborhoods among these youth are largely driven by organizationally-based resource seeking. These findings call into question the assumption that residence in Black segregated neighborhoods leads to homogeneously Black segregated neighborhood exposures and encourage theoretical development and data collection strategies that acknowledge the potential for significant heterogeneity in the everyday neighborhood experiences of urban youth.

West Nile virus impacts in American crow populations are associated with human land use and climate.

West Nile virus (WNV) was first detected in the western hemisphere during the summer of 1999, reawakening US public awareness of the potential severity of vector-borne pathogens. Since its New World introduction, WNV has caused disease in human, avian, and mammalian communities across the continent. American crows (Corvus brachyrhynchos) are a highly susceptible WNV host and when modeled appropriately, changes in crow abundances can serve as a proxy for the spatio-temporal presence of WNV. We use the dramatic declines in abundance of this avian host to examine spatio-temporal heterogeneity in WNV intensity across the northeastern US, where WNV was first detected. Using data from the Breeding Bird Survey, we identify significant declines in crow abundance after WNV emergence that are associated with lower forest cover, more urban land use, and warmer winter temperatures. Importantly, we document continued declines as WNV was present in an area over consecutive years. Our findings support the urban-pathogen link that human WNV incidence studies have shown. For each 1% increase in urban land cover we expect an additional 5% decline in the log crow abundance beyond the decline attributed to WNV in undeveloped areas. We also demonstrate a significant relationship between above-average winter temperatures and WNV-related declines in crow abundance. The mechanisms behind these patterns remain uncertain and hypotheses requiring further research are suggested. In particular, a strong positive relationship between urban land cover and winter temperatures may confound mechanistic understanding, especially when a temperature-sensitive vector is involved.

Activity Locations, Residential Segregation, and the Significance of Residential Neighborhood Boundary Perceptions.

The inadequacies of residential census geography in capturing urban residents' routine exposures have motivated efforts to more directly measure residents' activity spaces. In turn, insights regarding urban activity patterns have been used to motivate alternative residential neighborhood measurement strategies incorporating dimensions of activity space in the form of egocentric neighborhoods-measurement approaches that place individuals at the center of their own residential neighborhood units. Unexamined, however, is the extent to which the boundaries of residents' own self-defined residential neighborhoods compare with census-based and egocentric neighborhood measurement approaches in aligning with residents' routine activity locations. We first assess this question, examining whether the boundaries of residents' self-defined residential neighborhoods are in closer proximity to the coordinates of a range of activity location types than are the boundaries of their census and egocentric residential neighborhood measurement approaches. We find little evidence that egocentric or, crucially, self-defined residential neighborhoods better align with activity locations, suggesting a division in residents' activity locations and conceptions of their residential neighborhoods. We then examine opposing hypotheses about how self-defined residential neighborhoods and census tracts compare in socioeconomic and racial composition. Overall, our findings suggest that residents bound less segregated neighborhoods than those produced by census geography, but self-defined residential neighborhoods still reflect a preference toward homophily when considering areas beyond the immediate environment of their residence. These findings underscore the significance of individuals' conceptions of residential neighborhoods to understanding and measuring urban social processes such as residential segregation and social disorganization.

Human Mobility and Crime: Theoretical Approaches and Novel Data Collection Strategies.

This review outlines approaches to explanations of crime that incorporate the concept of human mobility-or the patterns of movement throughout space of individuals or populations in the context of everyday routines-with a focus on novel strategies for the collection of geographically referenced data on mobility patterns. We identify three approaches to understanding mobility-crime linkages: (a) Place and neighborhood approaches characterize local spatial units of analysis of varying size with respect to the intersection in space and time of potential offenders, victims, and guardians; (b) person-centered approaches emphasize the spatial trajectories of individuals and person-place interactions that influence crime risk; and (c) ecological network approaches consider links between persons or collectivities based on shared activity locations, capturing influences of broader systems of interconnection on spatial- and individual-level variation in crime. We review data collection strategies for the measurement of mobility across these approaches, considering both the challenges and promise of mobility-based research for criminology.