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BackgroundThe coronavirus disease pandemic has disproportionately affected poor and racial/ethnic minority individuals and communities, especially Indigenous Peoples. The object of this study is to understand the spatially varying associations between socioeconomic disadvantages and the number of confirmed COVID-19 cases in New Mexico at the ZIP code level.MethodsWe constructed ZIP code-level data (n=372) using the 2014–2018 American Community Survey and COVID-19 data from the New Mexico Department of Health (as of 24 May 2020). The log-linear Poisson and geographically weighted Poisson regression are applied to model the number of confirmed COVID-19 cases (total population as the offset) in a ZIP code.ResultsThe number of confirmed COVID-19 cases in a ZIP code is positively associated with socioeconomic disadvantages—specifically, the high levels of concentrated disadvantage and income inequality. It is also positively associated with the percentage of American Indian and Alaskan Native populations, net of other potential confounders at the ZIP code level. Importantly, these associations are spatially varying in that some ZIP codes suffer more from concentrated disadvantage than others.ConclusionsAdditional attention for COVID-19 mitigation effort should focus on areas with higher levels of concentrated disadvantage, income inequality, and higher percentage of American Indian and Alaska Native populations as these areas have higher incidence of COVID-19. The findings also highlight the importance of plumbing in all households for access to clean and safe water, and the dissemination of educational materials aimed at COVID-19 prevention in non-English language including Indigenous languages.

Native Americans are disproportionately affected by COVID-19. The present study explores whether areas with high percentages of Native American residents are experiencing the equal risks of contracting COVID-19 by examining how the relationships between structural inequalities and confirmed COVID-19 cases spatially vary across Arizona using a geographically weighted regression (GWR). GWR helps with the identification of areas with high confirmed COVID-19 cases in Arizona and with understanding of which predictors of social inequalities are associated with confirmed COVID-19 cases at specific locations. We find that structural inequality indicators and presence of Native Americans are significantly associated with higher confirmed COVID-19 cases; and the relationships between structural inequalities and confirmed COVID-19 cases are significantly stronger in areas with high concentration of Native Americans, particular on Tribal lands. The findings highlight the negative effects that lack of infrastructure (i.e., housing with plumbing, transportation, and accessible health communication) may have on individual and population health, and, in this case, associated with the increase of confirmed COVID-19 cases.

Children in communities with concentrated socioeconomic and structural disadvantage tend to have elevated rates of nonurgent visits to emergency departments (EDs). Using a spatial regression model of 264 census block groups in Pittsburgh, Pennsylvania, we investigated sociodemographic and structural factors associated with lower-than-expected ("low utilization") versus higher-than-expected ("high utilization") nonurgent ED visit rates among children in block groups with concentrated disadvantage. Compared with high-utilization block groups, low-utilization block groups had higher percentages of households with two adults, high school graduates, access to vehicles, sound housing quality, and owner-occupied housing. Notably, low-utilization block groups did not differ significantly from high-utilization block groups either in the percentage of households located within very close proximity to public transit or primary care or in children's health insurance coverage rates. Stakeholders wishing to reduce pediatric nonurgent ED visits among families in communities of concentrated disadvantage should consider strategies to mitigate financial, time, transportation, and health literacy constraints that may affect families' access to primary care.

Objective: Mexican American (MA) children are more likely to grow up in poverty than their non-Hispanic/Latinx white peers and are at an elevated risk for early onset obesity. The current study evaluated the effects of prenatal family- and neighborhood-level disadvantage on children's weight and weight gain from 12 months through 4.5 years of age. Maternal breastfeeding duration was evaluated as a potential mechanism underlying the relation between multilevel disadvantage and weight. Methods: Data was collected from 322 low-income, MA mother-child dyads. Women reported the degree of family socioeconomic disadvantage and breastfeeding status. Neighborhood disadvantage was evaluated with census-level metrics. Children's weight and height were measured at laboratory visits. Results: Greater prenatal neighborhood disadvantage predicted higher child Body Mass Index (BMI) at 12 months, over and above family-level disadvantage; this effect remained stable through 4.5 years. Breastfeeding duration partially mediated the effect of neighborhood disadvantage on child BMI. Breastfeeding duration predicted child BMI at all timepoints. Conclusions: Maternal prenatal residence in a neighborhood with high concentrated disadvantage may place low-income, MA children at increased risk of elevated weight status during the first few years of life. Breastfeeding duration emerged as potentially modifiable pathway through which the prenatal neighborhood impacts children's early life weight. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Intimate partner violence (IPV) remains a public health issue plaguing families and communities in the USA. Despite considerable research devoted to individual-level factors affecting IPV and a smaller body of ecological IPV research, few studies explore the interaction between individual-level protective factors and neighborhood- or community-level factors in predicting the incidents of IPV among women. Moreover, most IPV studies utilize a unidimensional approach for social capital, despite strong empirical and theoretical support for a multi-dimensional conceptualization. In a sample of heterosexual women in the USA (N = 1884), we found that concentrated disadvantage, social and physical disorder, and community violence together significantly predicted increased rates of IPV victimization. Concentrated disadvantage and higher scores on the social capital index independently predicted a lower probability of victimization. Moderating effects were found for social capital: the protective effects of social capital on the probability of IPV were attenuated for those reporting community violence compared with women who did not report it. These findings enhance the field’s understanding of the synergistic relationship between individual- and neighborhood-level factors, providing important implications for community-based IPV interventions.

This study examines the place-based differences in opportunity experienced by men from lowincome backgrounds across U.S. and Pennsylvania counties. Our quantitative findings suggest that U.S. and Pennsylvania counties are very unequal in terms of how men raised in low-income families fare in adulthood on measures of upward mobility, household income, college graduation, incarceration, and marriage. A variety of county-level measures of concentrated disadvantage were associated with these outcomes, including county household income, poverty rate, degree of racial segregation, college graduation rate, single parenthood rate, social capital rate, and job growth rate. Additionally, anonymous qualitative data from phone interviews with county commissioners from some of the Pennsylvania counties that struggled the most in our analysis helped to confirm our findings with valuable on-the-ground perspectives. We discuss these findings and their implications for equality of opportunity in the U.S. and the state of Pennsylvania.

Despite significant progress in research on the treatment and prevention of psychological, behavioral, and health problems, the translation of this knowledge into population-wide benefit remains limited. This paper reviews the state of America's children and families, highlighting the influence of stressful contextual and social conditions on child and family well-being and the concentration of disadvantage in numerous neighborhoods and communities throughout the nation. It then briefly reviews the progress that has been made in pinpointing policies that can reduce stressful contextual conditions such as poverty, discrimination, and the marketing of unhealthful foods and substances. It also describes numerous family and school interventions that have proven benefit in preventing psychological and behavioral problems as diverse as tobacco, alcohol, and other drug use; depression; antisocial behavior; academic failure; obesity prevention; and early childbearing. We argue that progress in translating existing knowledge into widespread benefit will require a nationwide effort to intervene comprehensively in neighborhoods and communities of concentrated disadvantage. We present a strategic plan for how such an effort could be organized. The first step in this organizing would be the creation of a broad and diverse coalition of organizations concerned with advancing public health and well-being. Such a coalition could increase public support both for the policies needed to focus on these disadvantaged areas and the research needed to incrementally improve our ability to help these areas.

Background Firearm homicides disproportionately affect Black communities. Redlining – discriminatory lending practices of the early 20th century - are associated with current increased rates of firearm violence. Poverty and concentrated disadvantage are also associated with firearm violence. The interaction of these factors with racist redlining housing practices remains unclear. Methods We used generalized structural equation modeling to characterize the mediators through which redlining practices of the 1930s led to present rates of firearm violence in Boston using a negative binomial model. Principle component analysis was used to create four distinct mediating variables representing census block socioeconomic and built environment information, while reducing dimensionality. We calculated the direct effect between harmful (Red and Yellow) vs beneficial (Green) designations and firearm incident rate, indirect effect between redlining designation and firearm incident rate through each mediating variable, and the total effect. The percentage mediation of each mediator was subsequently calculated. Findings Red and Yellow areas of Boston were associated with an 11•1 (95% CI 5•5,22•4) and 11•4 (5•7,22•8) increased incident rate of shooting when compared to Green. In the pathway between Red designation and firearm incident rate, poverty and poor educational attainment mediated 20% of the interaction, share of rented housing mediated 8%, and Black share of the population 3%. In the pathway between Yellow designation and firearm incident rate, poverty and poor educational attainment mediated 16% of the association, and Black share of the population mediated 13%. Interpretation Redlining practices of the 1930s potentially contribute to increased rates of firearm violence through changes to neighborhood environments, namely through preclusion from homeownership, poverty, poor educational attainment, and concentration (i.e. segregation) of Black communities. These downstream mediating factors serve as points for policy interventions to address urban firearm violence. Funding Michael Poulson and Miriam Neufeld were supported by T32 Training Grants (HP10028, GM86308).

This paper assesses the relevance of social disorganization and collective efficacy in accounting for neighbourhood inequalities in the exposure to crime. Specifically, it questions the potential of community and voluntary organizations to enhance informal social control and reduce exposure to crime. It utilizes calls-for-service (incident) data for Greater Manchester (UK) and a Bayesian spatio-temporal modelling approach. Contrary to expectations, the research finds that measures of social disorganization (concentrated disadvantage aside) and collective efficacy hold a limited effect on neighbourhood exposure to crime. We discuss the implications of these findings for criminological inquiry and theoretical development, highlighting the necessity of such endeavour to account for the national political-economy and welfare regime of research settings

Static indicators may fail to capture spatiotemporal differences in the spatial influence of urban features on different crime types. In this study, with a base station analogy, we introduced crime risk stations that conceptualize the spatial influence of urban features as crime risk signals broadcasted throughout a coverage area. We operationalized these risk signals with two novel risk scores, risk strength and risk intensity, obtained from novel distance-aware risk signal functions. With a crime-specific spatiotemporal approach, through a spatiotemporal influence analysis we examined and compared these risk scores for different crime types across various spatiotemporal models. Using a correlation analysis, we examined their relationships with concentrated disadvantage. The results showed that bus stops had relatively lower risk intensity, but higher risk strength, while fast-food restaurants had a higher risk intensity, but a lower risk strength. The correlation analysis identified elevated risk intensity and strength around gas stations in disadvantaged areas during late-night hours and weekends. The results provided empirical evidence for a dynamic spatial influence that changes across space, time, and crime type. The proposed risk functions and risk scores could help in the creation of spatiotemporal crime hotspot maps across cities by accurately quantifying crime risk around urban features.

Summary Introduction Significant health disparities exist in asthma and obesity for African American youths. Successful interventions present an opportunity to address these disparities but require detailed study in order to ensure generalizability. This study investigated the intersection of obesity, neighbourhood disadvantage, and asthma. Methods Data were extracted from 129 African American females ages 13 to 19 years (mean = 15.6 years [SD = 1.9]). Obesity was measured via body mass index (BMI). Asthma status was based on clinical diagnosis and/or results of the International Study of Asthma and Allergies during Childhood (ISAAC) questionnaire. The concentrated disadvantage index (CDI) assessed neighbourhood disadvantage. Results Findings showed that 21.5% (n = 28) of participants were clinically defined as having asthma, 76.2% (n = 99) had obesity, and 24.9% (n = 31) were classified without obesity. The mean BMI was 35.1 (SD = 9.1) and the mean CDI was 1.0 (SD = 0.9). CDI and obesity were significantly associated in participants without asthma, but not in those with asthma. Multivariable linear regression results showed a significant interaction between CDI and asthma (t value = 2.2, P = .03). Conclusion In sum, results from this study found that asthma moderated the relationship between neighbourhood disadvantage and obesity.

This study explores the association between neighborhood characteristics, alcohol outlets, other micro-places, and neighborhood violence rates. Prior studies that examined the alcohol availability and violence associations suggested that alcohol outlets play an important role in violent outcomes, yet we know less about the larger environment in which alcohol outlets are located, including how the availability of other types of places that exist side by side with alcohol outlets in neighborhoods could influence the alcohol-violence relationships. I collected publicly available data on simple and aggravated assaults, neighborhood characteristics (concentrated disadvantage, concentrated immigration, residential stability, and ethnic heterogeneity), on- and off-premise outlets, and other micro-places (colleges and universities, primary and secondary schools, financial services, gas stations, hotels and motels, laundromats, parks and playgrounds, and rooming houses) and subsequently aggregated the data to Milwaukee, Wisconsin census block groups. I estimated spatially lagged regression models to test these associations and compared the results across the models. The findings show that some neighborhood characteristics and some micro-places are important predictors of neighborhood violence. Importantly, off-premise alcohol outlets have a consistently significant positive relationship with simple and aggravated assaults, even when the influence of the neighborhood characteristics and micro-places is accounted for in the models. This study contributes to the environmental criminology theories and alcohol availability theory by highlighting the importance of off-premise outlets as crime attractors and crime generators to explain violence.

Social research has long argued that collective resources and major events like disasters have an important impact on violent crime, but it has been difficult to show their effects because data are scarce. We conducted a large survey in New Orleans after Hurricane Katrina that included questions about collective resources. We aggregated our sample to the census tract level and merged it with data on concentrated disadvantage and violent crime. Our analyses show that bridging social networks are associated with lower levels of violent crime, while bonding social networks are associated with higher levels. Social trust is associated with lower levels of violent crime, but civic engagement has no impact. Concentrated disadvantage is associated with higher levels of violent crime. Finally, our results suggest that disaster recovery increased the importance of collective resources but not concentrated disadvantage on violent crime.

Introduction This study’s objective was to examine the association of the percentage of county population residing in concentrated disadvantage and Black-concentrated census tracts with county-level confirmed COVID-19 deaths in the USA, concentrated disadvantage and Black concentration at census tract-level measure socioeconomic segregation and racial segregation, respectively. Methods We performed secondary data analysis using tract (N = 73,056) and county (N = 3142) level data from the US Census Bureau and other sources for the USA. Confirmed COVID-19 deaths per 100,000 population was our outcome measure. We performed mixed-effect negative binomial regression to examine the association of county population’s percentage residing in concentrated disadvantage and Black-concentrated tracts with COVID-19 deaths while controlling for several other characteristics. Results For every 10% increase in the percentage of county population residing in concentrated disadvantage and Black-concentrated tracts, the rate for confirmed COVID-19 deaths per 100,000 population increases by a factor of 1.14 (mortality rate ratio [MMR] = 1.14; 95% confidence interval [CI]:1.11, 1.18) and 1.11 (MMR = 1.11; 95% CI:1.08, 1.14), respectively. These relations stayed significant in all models in further sensitivity analyses. Moreover, a joint increase in the percentage of county population residing in racial and socioeconomic segregation was associated with a much greater increase in COVID-19 deaths. Conclusions It appears that people living in socioeconomically and racially segregated neighborhoods may be disproportionately impacted by COVID-19 deaths. Future multilevel and longitudinal studies with data at both individual and aggregated tract level can help isolate the potential impacts of the individual-level characteristics and neighborhood-level socioeconomic and racial segregation with more precision and confidence. Supplementary Information The online version contains supplementary material available at 10.1007/s40615-021-00965-1.

Perceived unsafety, fear of crime, and avoidance were studied in relation to different types of crime, crime in different time perspectives, concentrated disadvantage, collective efficacy, urbanity, age structure, and neighborhood disorder. Four data sources were used on a large Swedish city; a community survey from 2012 and 2015 among residents, census data on socio-demographics, police data on reported violent (assault and robbery in the public environment), and property crimes (arson, property damage, theft, vehicle theft, and residential burglary) and geographical information on local bus stops and annual passengers visiting these bus stops. Collective efficacy primarily, but also concentrated disadvantage, was strongly related to perceived unsafety, across 102 neighborhoods. Collective efficacy was strongly related to fear of crime. It was not viable to relate the neighborhood variables with avoidance, however. Fear of specific violent crimes was different from fear of specific property crimes and should for future reference be examined separately. Crime, visible disorder, urbanity, and age structure do not seem as important.

Despite its egalitarian past, in recent decades Israel followed the footsteps of the United States in terms of growing inequality levels and reduced welfare arrangements. It is assumed, therefore, to have followed similar trends of increasing residential segregation between income groups. This study focuses on the metropolitan area of Tel-Aviv, Israel’s financial and cultural centre and examines the change in the spatial distribution of income groups between the years 1995–2008. It identifies trends in segregation between top and bottom income earners, as well as those between other income groups, given corresponding trends in income inequality. In addition, it examines spatial patterns of affluence and poverty concentration and assesses the influence of concentrated disadvantage among specific income and religious groups on overall segregation trends.

Research has found that drug markets tend to cluster in space, potentially because of the profit that can be made when customers are drawn to areas with multiple suppliers. But few studies have examined how these clusters of drug markets&mdash, which have been termed &ldquo, agglomeration economies&rdquo, &mdash, may be related to accidental overdose deaths, and in particular, the spatial distribution of mortality from overdose. Focusing on a large neighborhood in Philadelphia, Pennsylvania, known for its open-air drug markets, this study examines whether deaths from accidental drug overdose are clustered around street corners controlled by drug trafficking gangs. This study incorporates theoretically-informed social and physical environmental characteristics of street corner units into the models predicting overdose deaths. Given a number of environmental changes relevant to drug use locations was taking place in the focal neighborhood during the analysis period, the authors first employ a novel concentration metric&mdash, the Rare Event Concentration Coefficient&mdash, to assess clustering of overdose deaths annually between 2015 and 2019. The results of these models reveal that overdose deaths became less clustered over time and that the density was considerably lower after 2017. Hence, the predictive models in this study are focused on the two-year period between 2018 and 2019. Results from spatial econometric regression models find strong support for the association between corner drug markets and accidental overdose deaths. In addition, a number of sociostructural factors, such as concentrated disadvantage, and physical environmental factors, particularly blighted housing, are associated with a higher rate of overdose deaths. Implications from this study highlight the need for efforts that strategically coordinate law enforcement, social service provision and reductions in housing blight targeted to particular geographies.

Close social networks provide older persons with resources, including social support, that maintain their well-being. While scholarship shows how networks change over time, a dearth of research investigates changing social contexts as causes of network dynamics. Using the first two waves of the National Social Life, Health, and Aging Project survey ( N = 1,776), this study shows how rising neighborhood-level concentrated disadvantage through the Great Recession of 2007–2009 was associated with smaller close networks, largely due to fewer new close ties gained, among older Americans. Worsening neighborhood circumstances pose obstacles to older residents’ acquisition of new close ties, including heightened fear, lower generalized trust, stress and depression, and declines in local institutions that attract both residents and nonresidents.

Background Traumatic injury is not evenly distributed across race and class in America. Black men are marginalized in society, often live in disadvantaged neighborhoods, and are at higher risk for injury mortality and ongoing physical and psychological problems following injury, including post-traumatic stress disorder (PTSD) and depression. While much research has examined individual factors associated with increased post-injury psychological symptoms, the contribution of the social and physical environment has been relatively-understudied. Purpose The purpose was to examine the contribution of neighborhood characteristics to PTSD and depressive symptom severity in Black men following serious injury. Methods A secondary analysis of 451 seriously injured men living in Philadelphia were drawn from a prospective cohort study. Study participants were linked by a geographic information system (GIS) to characteristics in their neighborhood in order to spatially model the factors that contribute to increased psychological symptom severity at 3 months post-injury. Factor analysis identified underlying constructs of 32 neighborhood predictors, which were entered in a generalized estimating equation (GEE) regression analysis. Covariates included mechanism of injury, severity of injury, age, and health insurance. Results Neighborhood characteristics loaded onto 4 constructs: neighborhood disconnectedness; concentrated disadvantage; crime, violence, and vacancy; and race/ethnicity. Higher PTSD symptom severity was reported by 36.8% and associated with neighborhood crime, violence, and vacancy, and higher depressive symptom severity was reported by 30.4% and associated with neighborhood disconnectedness. Both PTSD and depressive symptoms were associated with intentional mechanisms of injury, such as gunshot wounds, stabbing, and assault; and with having Medicaid or no insurance. Higher severity of injury was associated with depressive symptoms. Conclusions Findings suggest that neighborhood characteristics such as neighborhood disconnectedness and crime, violence, and vacancy have measurable associations with psychological symptoms after injury. The evidence supports the need for interventions to improve post-injury mental health by modifying the urban environment.

Statement of Purpose Child maltreatment has lifelong impacts on health and well-being, which can result in serious injuries and death. The objective of this study was to identify the incidence and risk factors of child maltreatment-related injuries resulting in hospitalizations for children under three for the population of Washington State. Methods/Approach A prospective cohort study utilizing retrospective linked administrative data for all children born in Washington State between 1999 and 2013 (N=1,271,419). The data set comprised of linked birth discharge and hospitalization records for the entire state. Child maltreatment-related hospitalizations were identified using ICD-9 codes, both specifically attributed to and suggestive of maltreatment. Incidence rates were calculated for the overall population, by year, sex, maltreatment type, and child age. Risk and protective factors were identified using hierarchical linear modeling to test community-level poverty/disadvantage simultaneously with sociodemographic variables from the birth record. Results A total of 4,078 hospitalizations related to child maltreatment were identified for an incidence rate of 3.21 per 1,000 births. More than half of all hospitalizations were related to neglect. Children whose mother resided in a census tract with high concentrated disadvantage at the time of the child’s birth experienced child maltreatment-related hospitalizations at 1.2 times the rate of children who did not reside in high concentrated disadvantage census tracts. Conclusions Hospitalizations can be a useful source of population-based child maltreatment surveillance. These population-based data suggest that the community context, in addition to individual-level factors, contributes to the risk of a child being hospitalized for child maltreatment-related reasons. Significance and Contributions to Injury and Prevention Science The identification of neglect-related hospitalizations as the most common sub-type, and likely the result of supervisory neglect, are important findings for the development and implementation of prevention programming.

We investigate how distinct residential environments uniquely influence chronic child disease. Aggregating over 200,000 pediatric geocoded medical records to the census tract of residence and linking them to neighborhood-level measures, we use multiple data analysis techniques to assess how heterogeneous exposures of social and environmental neighborhood conditions influence an index of child chronic disease (CCD) prevalence for the neighborhood. We find there is a graded relationship between degree of overall neighborhood disadvantage and children’s chronic disease such that the highest neighborhood CCD scores reside in communities with the highest concentrated disadvantage. Finally, results show that higher levels of neighborhood concentrated disadvantage and air pollution exposure associate with higher risks of having at least one chronic condition for children after also considering their individual- and family-level characteristics. Overall, our analysis serves as a comprehensive start for future researchers interested in assessing which neighborhood factors matter most for child chronic health conditions.

I denna studie beräknas våld vid busshållplatser samt våld vid busshållplatser relativt antalet busspassagerare i Malmö. En riskterrängmodell (RTM) genomförs också för att beräkna vad som kännetecknar busshållplatser med mycket våld. Resultaten visar att det är mest våld i centrum, men att risken är högst i utsatta områden med låg kollektiv förmåga. Geographic forecasting of crime can be done by considering prior crime or by considering spatial risk factors, e.g., using risk terrain modeling (RTM). The present paper tests both methods, but primarily focuses on RTM and on increasing our understanding of forecasting by attempting to compare the spatial risk factors for where the number of crimes is high with the spatial risk factors for where the risk of victimization is high. This is performed by fitting negative binomial models on crime around bus stops and comparing them to the same models with the number of bus passengers as exposure variable. The models also take the surrounding environment into account by fitting multi-level models with neighborhood level predictors of concentrated disadvantage and collective efficacy. The results show that some types of facilities are risk factors for crime, but not for victimization. This results in new insights into how flows of people impact on forecasting, as for instance a school is a spatial risk factor for crime, while not being associated with an elevated risk per person. The results also show that the neighborhood level of collective efficacy is a stable and significant risk factor both for crime and for risk of victimization, highlighting a potential for better crime forecasting by combining different spatial and theoretical perspectives.

We proposed a multilevel model of structural influences on HIV-risky sexual partnerships in a diverse sample of 1,793 youth residing in 23 states and the District of Columbia. We examined the influence of concentrated disadvantage, HIV stigma, and sexual and gender minority stigma on engagement in HIV risky sexual partnerships and whether youth’s participation in opportunity structures, anticipation of HIV stigma, and perceptions of their community as youth-supportive settings mediated structural effects. After controlling for age, HIV status, and race, we found structural HIV stigma had deleterious indirect effects on youth’s participation in HIV-risky sexual partnerships. Concentrated disadvantage and structural sexual and gender minority stigma had direct negative effects on youth’s perceptions of their communities as supportive and on their participation in prosocial activity. Support perceptions had direct, protective effects on avoidance of HIV-risky sexual partnerships. Structural stigma undermines youth’s belief that their communities invest in their safety and well-being.

Telomeres are repetitive nucleotide sequences located at the ends of chromosomes that protect genetic material. We use data from the Fragile Families and Child Wellbeing Study to analyze the relationship between exposure to spatially concentrated disadvantage and telomere length for white and black mothers. We find that neighborhood disadvantage is associated with shorter telomere length for mothers of both races. This finding highlights a potential mechanism through which the unique spatially concentrated disadvantage faced by African Americans contributes to racial health disparities. We conclude that equalizing the health and socioeconomic status of black and white Americans will be very difficult without reducing levels of residential segregation in the United States.

Prior research has suggested that children living in a disadvantaged neighborhood have lower achievement test scores, but these studies typically have not estimated causal effects that account for neighborhood choice. Recent studies used propensity score methods to account for the endogeneity of neighborhood exposures, comparing disadvantaged and nondisadvantaged neighborhoods. We develop an alternative propensity function approach in which cumulative neighborhood effects are modeled as a continuous treatment variable. This approach offers several advantages. We use our approach to examine the cumulative effects of neighborhood disadvantage on reading and math test scores in Los Angeles. Our substantive results indicate that recency of exposure to disadvantaged neighborhoods may be more important than average exposure for children’s test scores. We conclude that studies of child development should consider both average cumulative neighborhood exposure and the timing of this exposure.

Objective While scholars treat neighborhoods as important contexts of inequality, few studies explore the social processes that create disparities in neighborhoods’ political capacities. How does neighborhood social organization affect rates of political participation? Methods We combine surveys from the U.S. Census and Boston Neighborhood Survey (BNS), and administrative data from the City of Boston. Accounting for spatial dependence, we fit a series of regression models investigating the relationship between neighborhood social structure and four forms of political engagement: community meeting attendance, contacting local government for services, and voter turnout in a local and a national midterm election. Results We find higher rates of political participation in more stable neighborhoods, and lower rates of participation in neighborhoods with higher concentrations of immigrants. The relationship between collective efficacy and rates of political participation is not statistically significant in our models. We find a positive association between concentrated disadvantage and city election turnout, but this association is nonlinear: beyond a certain threshold, increases in disadvantage are associated with decreasing rates of participation. Conclusion We argue that neighborhoods are indeed political places, and residential stability, immigrant concentration, and—to a lesser extent—concentrated disadvantage are important factors affecting the civic capacity of urban communities.

This study contributes to previous research by advancing a &ldquo, racialized structural vulnerability&rdquo, framework and presenting a new empirical analysis of the relationship between neighborhood Asian, Black, and Latinx composition, extrinsic and intrinsic vulnerability, and PM2.5 exposures in California with secondary data from 2004&ndash, 2014. Principal component analyses revealed that tract Latinx composition was highly correlated with extrinsic vulnerability (economic disadvantage and limited English-speaking ability), and that tract Black composition was highly correlated with intrinsic vulnerability (elevated prevalence of asthma-related emergency department visits and low birth weight). Spatial lag regression models tested hypotheses regarding the association between Asian, Black, and Latinx population vulnerability factors and the 2009&ndash, 2011 annual average PM2.5 percentile rankings, net of emissions and spatial covariates. Results indicated that the percent Latinx population, followed by the regional clustering of PM2.5, and the percent of non-Latinx Black and non-Latinx Asian population were the strongest positive multivariable correlates of PM2.5 percentile rankings, net of other factors. Additional analyses suggested that despite shifting demographic and spatial correlates of 2012&ndash, 2014 PM2.5 exposures, the tracts&rsquo, Black and Latinx composition and location in the San Joaquin Valley remain important vulnerability factors with implications for future research and policy.

Triple Negative Breast Cancer (TNBC) is an aggressive, heterogeneous subtype of breast cancer, which is more frequently diagnosed in African American (AA) women than in European American (EA) women. The purpose of this study is to investigate the role of social determinants in racial disparities in TNBC. Data on Louisiana TNBC patients diagnosed in 2010–2012 were collected and geocoded to census tract of residence at diagnosis by the Louisiana Tumor Registry. Using multilevel statistical models, we analyzed the role of neighborhood concentrated disadvantage index (CDI), a robust measure of physical and social environment, in racial disparities in TNBC incidence, stage at diagnosis, and stage-specific survival for the study population. Controlling for age, we found that AA women had a 2.21 times the incidence of TNBC incidence compared to EA women. Interestingly, the incidence of TNBC was independent of neighborhood CDI and adjusting for neighborhood environment did not impact the observed racial disparity. AA women were more likely to be diagnosed at later stages and CDI was associated with more advanced stages of TNBC at diagnosis. CDI was also significantly associated with poorer stage-specific survival. Overall, our results suggest that neighborhood disadvantage contributes to racial disparities in stage at diagnosis and survival among TNBC patients, but not to disparities in incidence of the disease. Further research is needed to determine the mechanisms through which social determinants affect the promotion and progression of this disease and guide efforts to improve overall survival.

Quantitative segregation research focuses almost exclusively on the spatial sorting of demographic groups. This research largely ignores the structural characteristics of neighborhoods – such as crime, job accessibility, and school quality – that likely help determine important household outcomes. This paper summarizes the research on segregation, neighborhood effects, and concentrated disadvantage, and argues that we should pay more attention to neighborhood structural characteristics, and that the data increasingly exist to include measures of spatial segregation and neighborhood opportunity. The paper concludes with a brief empirical justification for the inclusion of data on neighborhood violence and a discussion on policy applications.

Context Childhood lead exposure has been associated with criminal behavior later in life. The current study aimed to analyze the association between elevated blood lead levels (n=59,645) and crime occurrence (n=90,433) across census tracts within St. Louis, Missouri. Design Longitudinal ecological study. Setting Saint Louis, Missouri. Exposure measure Blood lead levels. Main outcome measure Violent, Non-violent, and total crime at the census tract level. Results Spatial statistical models were used to account for the spatial autocorrelation of the data. Greater lead exposure at the census-tract level was associated with increased violent, non-violent, and total crime. In addition, we examined whether non-additive effects existed in the data by testing for an interaction between lead exposure and concentrated disadvantage. Some evidence of a negative interaction emerged, however, it failed to reach traditional levels of statistical significance (supplementary models, however, revealed a similar negative interaction that was significant). Conclusions More precise measurements of lead exposure in the aggregate, produced additional evidence that lead is a potent predictor of criminal outcomes.

Several recent spatial analyses conclude the strong positive association typically found between neighborhood concentrated disadvantage and crime in cross–sectional studies significantly differs across neighborhoods. It is possible this spatial variation is due to within–neighborhood dynamics of continuity and change, as suggested by ecological theories of neighborhood crime. Using ordinary least–squares and geographically weighted regression models, I explore the role of within–neighborhood change on the disadvantage–homicide relationship across Chicago neighborhoods and find that controlling for historical changes in disadvantage within neighborhoods reduces—but does not eliminate—spatial variation in the cross–sectional relationship. Within–neighborhood changes in concentrated disadvantage from 1970 to 2000 are positively related to homicide rates, net of the level of disadvantage in 2000. This suggests the relationship is influenced to some degree by temporal continuity or change in the neighborhood ecological structure, consistent with the dynamic conceptualization of neighborhoods inherent to ecological theories of crime like social disorganization.

Background Racial variation in the relationship between blood glucose and hemoglobin A1c (HbA1c) complicates diabetes diagnosis and management in racially mixed populations. Understanding why HbA1c is persistently higher in blacks than whites could help reduce racial disparity in diabetes outcomes. Objective Test the hypothesis that neighborhood disadvantage is associated with inflammation and poor metabolic control in a racially mixed population of pediatric type 1 diabetes patients. Methods Patients (n = 86, 53 white, 33 black) were recruited from diabetes clinics. Self-monitored mean blood glucose (MBG) was downloaded from patient glucose meters. Blood was collected for analysis of HbA1c and C-reactive protein (CRP). Patient addresses and census data were used to calculate a concentrated disadvantage index (CDI). High CDI reflects characteristics of disadvantaged neighborhoods. Results HbA1c and MBG were higher (p < 0.0001) in blacks [10.4% (90.3 mmol/mol), 255 mg/dL] than whites [8.9% (73.9 mmol/mol), 198 mg/dL). CDI was higher in blacks (p < 0.0001) and positively correlated with HbA1c (r = 0.40, p = 0.0002) and MBG (r = 0.35, p = 0.0011) unless controlled for race. CDI was positively associated with CRP by linear regression within racial groups. CRP was not different between racial groups, and was not correlated with MBG, but was positively correlated with HbA1c when controlled for race (p = 0.04). Conclusions Neighborhood disadvantage was associated with inflammation and poor metabolic control in pediatric type 1 diabetes patients. Marked racial differences in potential confounding factors precluded differentiation between genetic and environmental effects. Future studies should recruit patients matched for neighborhood characteristics and treatment regimen to more comprehensively assess racial variation in HbA1c.

Background: Non-Hispanic Black (NHB) and Hispanic patients with Acute Myeloid Leukemia (AML) have higher mortality rates than non-Hispanic white (NHW) patients despite lower incidence, more favorable genetics, and a younger age at presentation (Darbinyan, Blood Adv. 2017). We performed a multilevel analysis of disparities in AML patients to investigate the contribution of structural violence, specifically neighborhood SES, on racial/ethnic differences in leukemia-specific survival. Methods: Adult AML (non-APL) patients diagnosed between 2012 and 2018 at six academic cancer centers in the Chicago area were included. Census tract data was collected using the FFIEC Geocoding/Mapping System and computed tract disadvantage and tract affluence scores were categorized into distribution tertiles (low, moderate, high). Time to relapse and death from leukemia were examined, adjusting for age, gender and race/ethnicity (baseline models), and for potential mediators of racial disparities including distal (Charlson Comorbidity Index (CCI), obesity, concentrated disadvantage and affluence, health insurance status), and proximal mediators (somatic mutations, and European Leukemia Network (ELN) prognostic score categories). Results Patient characteristics are shown in Table 1 (n = 822). Significant heterogeneity in age and comorbidities at diagnosis was observed, with Hispanic patients being the youngest and with the lowest CCI. Morbid obesity was more prevalent in NHB and Hispanic (23% and 20%, respectively) compared with NHW (11%) patients. Payer source also differed significantly; private insurance was twice as frequent among NHW than NHB (51% vs. 25%) patients, while the largest uninsured population was Hispanic. ELN adverse risk disease was most prevalent in NHW subjects, NPM1 mutations were least prevalent in Hispanic patients, and p53 mutations more prevalent in NHB (26%) compared to NHW (12%) and Hispanics (9%) although due to low numbers this did not reach significance (p=0.10). NHB and Hispanic patients tended to reside in more disadvantaged and less affluent areas. Treatment data was available for 764 patients (Table 2); 75% received intensive induction therapy and choice of first-line treatment did not differ by race or tract disadvantage. Allogeneic transplant rates however differed by race, age, insurance status, tract disadvantage, and ELN score. Treatment complications of induction chemotherapy, as reflected by ICU admissions during induction, were significantly lower in NHW (25%) compared to NHB (39%) and Hispanic (42%) patients. ICU admission rates were significantly higher in patients with morbid obesity and low tract affluence. Minority (vs. NHW) ethnicity was associated with a 42% increased hazard of death from leukemia (HR=1.42, 95% CI: 1.09, 1.85), and a 36% increased hazard of death from all causes (HR=1.36, 95% CI: 1.07, 1.72), each after controlling for age, gender and study site. Adjustment for continuous tract disadvantage and affluence and their interaction lowered both the hazard of leukemia and all cause death to 1.18 (95% CI: 0.88, 1.60) and 1.14 (95% CI: 0.88, 1.49), respectively. In formal mediation analysis, neighborhood SES accounted for 37% (p=0.09) and 50% (p=0.02) of the racial disparity in death from leukemia and all causes, respectively. Discussion: This study is the first to integrate data at the individual patient level with neighborhood characteristics, using census tract level variables to examine their contribution to AML patient outcomes. To date, formal mediation methods had not been employed to disentangle race/ethnic disparities in adult AML survival. Notably, our mediation analysis shows that census tract level SES explains a substantial proportion of the disparity in hazard of leukemia death. In addition, the observed disparities in treatment complications of induction chemotherapy, as reflected by ICU admissions, and the continued disparity in allogeneic transplant utilization all warrant further study. These results draw attention to the need for deeper investigation into the social and economic barriers to successful treatment outcomes for leukemia patients and represent an important first step toward designing strategies to mitigate these persistent health inequities. Disclosures Altman: Janssen: Consultancy; Syros: Consultancy; Genentech: Research Funding; Novartis: Consultancy; Amphivena: Research Funding; Amgen: Research Funding; Aprea: Research Funding; ImmunoGen: Research Funding; Celgene: Research Funding; Boehringer Ingelheim: Research Funding; Fujifilm: Research Funding; Kartos: Research Funding; AbbVie: Other: advisory board, Research Funding; Kura Oncology: Other: Scientific Advisory Board - no payment accepted, Research Funding; BioSight: Other: No payment but was reimbursed for travel , Research Funding; Daiichi Sankyo: Other: Advisory Board - no payment but was reimbursed for travel; Agios: Other: advisory board, Research Funding; Glycomimetics: Other: Data safety and monitoring committee; Astellas: Other: Advisory Board, Speaker (no payment), Steering Committee (no payment), Research Funding; Theradex: Other: Advisory Board; Immune Pharmaceuticals: Consultancy; Bristol-Myers Squibb: Consultancy; France Foundation: Consultancy; PeerView: Consultancy; PrIME Oncology: Consultancy; ASH: Consultancy; Cancer Expert Now: Consultancy. Stock:Research to Practice: Honoraria; UpToDate: Honoraria; Adaptive Biotechnologies: Consultancy, Membership on an entity's Board of Directors or advisory committees; American Society of Hematology: Honoraria; Leukemia and Lymphoma Society: Research Funding; Novartis: Research Funding; Abbvie: Honoraria, Research Funding; Morphosys: Consultancy, Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Servier: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Quigley:Alnylam: Speakers Bureau; Agios: Speakers Bureau; Amgen: Other: Advisory board. Khan:Celgene: Consultancy; Incyte: Honoraria; Takeda: Research Funding; Amgen: Consultancy.