Proportion Of White Residents Research Articles

A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing

Decision-makers often observe the occurrence of events through a reporting process. City governments, for example, rely on resident reports to find and then resolve urban infrastructural problems such as fallen street trees, flooded basements, or rat infestations. Without additional assumptions, there is no way to distinguish events that occur but are not reported from events that truly did not occur--a fundamental problem in settings with positive-unlabeled data. Because disparities in reporting rates correlate with resident demographics, addressing incidents only on the basis of reports leads to systematic neglect in neighborhoods that are less likely to report events. We show how to overcome this challenge by leveraging the fact that events are spatially correlated. Our framework uses a Bayesian spatial latent variable model to infer event occurrence probabilities and applies it to storm-induced flooding reports in New York City, further pooling results across multiple storms. We show that a model accounting for under-reporting and spatial correlation predicts future reports more accurately than other models, and further induces a more equitable set of inspections: its allocations better reflect the population and provide equitable service to non-white, less traditionally educated, and lower-income residents. This finding reflects heterogeneous reporting behavior learned by the model: reporting rates are higher in Census tracts with higher populations, proportions of white residents, and proportions of owner-occupied households. Our work lays the groundwork for more equitable proactive government services, even with disparate reporting behavior.

Gentrification and Neighborhood Housing Wealth: How Gentrification Reproduces the Racial Stratification of Urban Neighborhoods

Few researchers have considered how gentrification affects inequalities of housing wealth between Black and White neighborhoods. Drawing on the U.S. census and the American Community Survey, I test the hypothesis that home values rise more slowly in gentrifying neighborhoods that are majority Black compared to those that are majority White. I find that home values appreciate more quickly in gentrifying neighborhoods that are majority Black, particularly those that are experiencing significant change in their racial-ethnic composition. The findings further suggest that Black gentrifying neighborhoods experiencing racial transition—a large increase in the proportion of White residents and a large decrease in the proportion of Black residents—experience higher rates of home value appreciation than those not experiencing racial transition. I argue that gentrification reproduces the racial stratification of urban neighborhoods because large increases to housing wealth tend to be coupled with the arrival of the White middle-class.

Association of Academic Medical Center Presence With Clinical Outcomes at Neighboring Community Hospitals Among Medicare Beneficiaries

Studies suggest that academic medical centers (AMCs) have better outcomes than nonteaching hospitals. However, whether AMCs have spillover benefits for patients treated at neighboring community hospitals is unknown. To examine whether market-level AMC presence is associated with outcomes for patients treated at nonteaching hospitals within the same markets. This retrospective, population-based cohort study assessed traditional Medicare beneficiaries aged 65 years and older discharged from US acute care hospitals between 2015 and 2017 (100% sample). Data were analyzed from August 2021 to December 2022. The primary exposure was market-level AMC presence. Health care markets (ie, hospital referral regions) were categorized by AMC presence (percentage of hospitalizations at AMCs) as follows: no presence (0%), low presence (>0% to 20%), moderate presence (>20% to 35%), and high presence (>35%). The primary outcomes were 30-day and 90-day mortality and healthy days at home (HDAH), a composite outcome reflecting mortality and time spent in facility-based health care settings. There were 22 509 824 total hospitalizations, with 18 865 229 (83.8%) at non-AMCs. The median (IQR) age of patients was 78 (71-85) years, and 12 568 230 hospitalizations (55.8%) were among women. Of 306 hospital referral regions, 191 (62.4%) had no AMCs, 61 (19.9%) had 1 AMC, and 55 (17.6%) had 2 or more AMCs. Markets characteristics differed significantly by category of AMC presence, including mean population, median income, proportion of White residents, and physicians per population. Compared with markets with no AMC presence, receiving care at a non-AMC in a market with greater AMC presence was associated with lower 30-day mortality (9.5% vs 10.1%; absolute difference, -0.7%; 95% CI, -1.0% to -0.4%; P < .001) and 90-day mortality (16.1% vs 16.9%; absolute difference, -0.8%; 95% CI, -1.2% to -0.4%; P < .001) and more HDAH at 30 days (16.49 vs 16.12 HDAH; absolute difference, 0.38 HDAH; 95% CI, 0.11 to 0.64 HDAH; P = .005) and 90 days (61.08 vs 59.83 HDAH; absolute difference, 1.25 HDAH; 95% CI, 0.58 to 1.92 HDAH; P < .001), after adjustment. There was no association between market-level AMC presence and mortality for patients treated at AMCs themselves. AMCs may have spillover effects on outcomes for patients treated at non-AMCs, suggesting that they have a broader impact than is traditionally recognized. These associations are greatest in markets with the highest AMC presence and persist to 90 days.

Where is environmental justice? A review of US urban forest management plans

The distribution of trees and access to nature is rarely equitable across urban neighborhoods. This injustice is present in many cities, and its origins are predominantly rooted in enduring procedural and recognitional injustices. The purpose of this research was to systematically investigate Urban Forest Management Plans (UFMPs) prepared by municipalities across the United States (107 total) for their mention and explanation of environmental justice themes relevant to urban forestry. UFMPs describe municipal urban tree-planting and stewardship goals as well as pathways for both implementation and monitoring. Using a mixed-method approach that combines qualitative content analysis and quantitative measurement, we interrogated UFMPs for reference to three specific environmental justice pillars: distribution, procedure, and recognition. Mentions and explanations of these concepts were identified and counted for all UFMPs. Summary counts were then investigated for association with a UFMP’s publication year, its municipal population, and its racial composition. The frequency of reference to environmental justice themes was greater in UFMPs published more recently and whose authoring municipalities have a larger population. A positive association exists between the proportion of Black residents in a city with an UFMP and the frequency of identified distributional justice explanations. While a positive association with procedural justice mentions was found with the proportion of white residents in UFMP authoring cities, environmental justice, overall, is not a central theme across most UFMPs published to date. More generally, we discovered that where UFMPs referenced environmental justice concepts, it was often brief and lacking in substance; recognitional justice themes were absent in almost all documents. Improving environmental justice goals and implementation strategies in UFMPs that validate the perspectives and experiences of residents can strengthen accountability between urban foresters and the communities they serve.

Racial/ethnic disparities in nationwide PM2.5 exposure: perils of assuming a linear relationship

BACKGROUND AND AIM Studies of racial/ethnic disparities in air pollution exposure assume an equal magnitude of disparity across the demographic distribution, which may under- or over-estimate the true disparity. Further, historic practices such as racist zoning policies could plausibly drive non-linear relationships between racial/ethnic composition and air pollution exposure. We aimed to conduct a nationwide analysis in urban areas allowing for non-linearity in the relationship between racial/ethnic composition and ambient particulate matter less than 2.5 micrometers (PM₂.₅), and test whether racial segregation modified this relationship. METHODS We obtained tract-level demographic information from the 2010 Census and computed the multi-group dissimilarity index, a metropolitan-area level measure of racial segregation. Ambient PM₂.₅ data was obtained from a publicly available source. We evaluated the relationship between percent non-Hispanic Black and percent non-Hispanic White residents and ambient PM₂.₅ using natural splines. RESULTS In 58,029 U.S. urban census tracts in 2010, we observed first a very steep and then a plateauing relationship between percent non-Hispanic Black residents and ambient PM₂.₅ concentration. Moving from the 25th percentile (1%) to the median (5%) of non-Hispanic Black residents was associated with a 0.58 &amp;#x3bc;g/m³ (95% CI: 0.56, 0.60) increase in PM₂.₅, while moving from the median to the 75th percentile (16% non-Hispanic Black) was associated with a 0.005 &amp;#x3bc;g/m³ (95% CI: -0.012, 0.020) increase. Reciprocally, in predominantly White census tracts, increases in the proportion of White residents was associated with a rapid decrease in ambient PM₂.₅. Segregation modified these relationships in a non-monotonic manner. CONCLUSIONS Our results suggest larger than previously reported Black-White disparities in exposure to PM₂.₅, especially in communities with a modest Black population, which make up the majority of urban census tracts in the US. KEYWORDS Racial/ethnic disparities; Air pollution; Particulate Matter; Environmental justice

Abstract 12208: Ecological Analysis of the Temporal Trends in the Association of Social Vulnerability and Race/Ethnicity With County-Level COVID-19 Incidence and Outcomes in the United States

Background: The COVID-19 pandemic adversely affected socially vulnerable and minority communities in the US initially, but the temporal trends during the year-long pandemic remain unknown. Objective: We examined temporal association between county-level Social Vulnerability Index (SVI), a percentile-based measure of social vulnerability to disasters, its subcomponents and race/ethnic composition with COVID-19 incidence and mortality in US in the year starting in March 2020. Methods: Counties (n=3091) with &gt; 50 COVID-19 cases by March 6th, 2021 were included. Associations between SVI (and its subcomponents) and county level racial composition with incidence and death per capita were assessed using a negative-binomial mixed-effects model. This model was used to examine potential time varying associations between weekly number of cases/deaths and SVI or racial composition. Data was adjusted for percentage of population aged ≥65 years, state level testing rate, county-level comorbidities, and environmental factors. Results: Higher SVI, indicative of greater social vulnerability, was independently associated with higher COVID-19 incidence (adjusted incidence rate ratio [IRR] per-10 percentile increase:1.02, (95% CI 1.02, 1.03, p&lt;0.001), and death per capita (1.04, (95% CI 1.04, 1.05, p&lt;0.001). SVI became an independent predictor of incidence starting from March 2020, but this association became weak or insignificant by winter, a period that coincided with sharp increase in infection rates and mortality, and when counties with higher proportion of White residents were disproportionately represented (“third wave”). By Spring 2021, SVI was again a predictor of COVID-19 outcomes. Counties with greater proportion of Blacks also observed similar temporal trends in COVID-19-related adverse outcomes. Counties with greater proportion of Hispanics had worse outcomes throughout the duration of the analysis. Conclusion: Except for winter “third wave” when majority White communities had highest incidence of cases, counties with greater social vulnerability and higher minority populations, experienced worse COVID-19 outcomes.

Analyzing disparities in COVID-19 testing trends according to risk for COVID-19 severity across New York City

BackgroundGiven the interplay between race and comorbidities on COVID-19 morbidity and mortality, it is vital that testing be performed in areas of greatest need, where more severe cases are expected. The goal of this analysis is to evaluate COVID-19 testing data in NYC relative to risk factors for COVID-19 disease severity and demographic characteristics of NYC neighborhoods.MethodsCOVID-19 testing and the racial/ethnic composition of NYC Zip Code Tabulation Areas (ZCTA) were obtained from the NYC Coronavirus data repository and the American Community Survey, respectively. The prevalence of neighborhood-level risk factors for COVID-19 severity according to the Centers for Disease Control and Prevention criteria for risk of severe illness and complications from COVID-19 were used to create a ZCTA-level risk index. Poisson regressions were performed to study the ratio of total tests relative to the total ZCTA population and the proportion of positive tests relative to the total tests performed over time.ResultsFrom March 2nd-April 6th, the total tests/population (%) was positively associated with the proportion of white residents (IRRadj: 1.0003, 95% CI: 1.0003–1.0004) and the COVID risk index (IRRadj: 1.038, 95% CI: 1.029–1.046). The risk index (IRRadj: 1.017, 95% CI: 0.939–1.101) was not associated with total tests performed from April 6th-May 12th, and inversely associated from May 12th-July 6th (IRRadj: 0.862, 95% CI: 0.814–0.913). From March 2nd-April 6th the COVID risk index was not statistically associated (IRRadj: 1.010, 95% CI: 0.987–1.034) with positive tests/total tests. From April 6th-May 12th, the COVID risk index was positively associated (IRRadj: 1.031, 95% CI: 1.002–1.060), while from May 12th-July 6th, the risk index was inversely associated (IRRadj: 1.135, 95% CI: 1.042–1.237) with positivity.ConclusionsTesting in NYC has suffered from the lack of availability in high-risk populations, and was initially limited as a diagnostic tool for those with severe symptoms, which were mostly concentrated in areas where vulnerable residents live. Subsequent time periods of testing were not targeted in areas according to COVID-19 disease risk, as these areas still experience more positive tests.

A Neighborhood Analysis of Time Trends in COVID-19 Infection in NYC.

To understand how observed COVID-19 diagnostic testing disparities across New York City (NYC) have impacted infection rates and COVID-19 spread, we examined neighborhood-level factors associated with, and the spatial distribution of, antibody test and infection rates, and compared changes over time by NYC ZIP code tabulation area (ZCTA). Data were obtained from 2019 American Community Survey 5-year estimates to create an SES index by ZCTA. Other predictors obtained from 2018 census data were the proportions of white residents, Hispanic residents and residents ≥ 65 years old. Multivariable Poisson regressions were performed to assess the rate of change for antibody testing and positivity, and to assess the independent associations with SES, race and age. Results: There was a significant association between the rate of antibody tests and SES quartiles (Q1: βadj = 0.04, Q2: βadj = 0.03 and Q3: βadj = − 0.03, compared to Q4), and the proportion of residents who are white (βadj = 0.004, p < .0001), Hispanic (βadj = 0.001, p < .0001), and ≥ 65 years (βadj = 0.01, p < .0001). Total number of positive antibody tests was significantly inversely associated with SES quartile (Q1: βadj = 0.50, Q2: βadj = 0.48 and Q3: βadj = 0.29, compared to Q4), and proportion of white residents (β = − 0.001, p < .0001) and ≥ 65 years (β = − 0.02, p < .0001), and significantly positively associated with proportion of Hispanic residents (β = 0.003, p < .0001). There are disparities in antibody testing and positivity, reflecting disproportionate impacts and undercounts of COVID-19 infection across NYC ZCTAs. Future public health response should increase testing in these vulnerable areas to diminish infection spread.

The Environmental and Social Determinants of Health Matter in a Pandemic: Predictors of COVID-19 Case and Death Rates in New York City.

Our research objective was to determine which environmental and social factors were predictive of coronavirus disease 2019 (COVID-19) case and death rates in New York City (NYC), the original epicenter of the pandemic in the US, and any differential impacts among the boroughs. Data from various sources on the demographic, health, and environmental characteristics for NYC zip codes, neighborhoods, and boroughs were analyzed along with NYC government’s reported case and death rates by zip code. At the time of analysis, the Bronx had the highest COVID-19 case and death rates, while Manhattan had the lowest rates. Significant predictors of a higher COVID-19 case rate were determined to be proportion of residents aged 65 years plus; proportion of residents under 65 years with a disability; proportion of White residents; proportion of residents without health insurance; number of grocery stores; and a higher ozone level. For COVID-19 death rates, predictors include proportion of residents aged 65 years plus; proportion of residents who are not US citizens; proportion on food stamps; proportion of White residents; proportion of residents under 65 years without health insurance; and a higher level of ozone. Results across boroughs were mixed, which highlights the unique demographic, socioeconomic, and community characteristics of each borough. To reduce COVID-19 inequities, it is vital that the NYC government center the environmental and social determinants of health in policies and community-engaged interventions adapted to each borough.

Racial Residential Segregation and Race Differences in Ideal Cardiovascular Health among Young Men.

Background: Race disparities in cardiovascular disease (CVD) related morbidity and mortality are evident among men. While previous studies show health in young adulthood and racial residential segregation (RRS) are important factors for CVD risk, these factors have not been widely studied in male populations. We sought to examine race differences in ideal cardiovascular health (CVH) among young men (ages 24–34) and whether RRS influenced this association. Methods: We used cross-sectional data from young men who participated in Wave IV (2008) of the National Longitudinal Survey of Adolescent to Adult Health (N = 5080). The dichotomous outcome, achieving ideal CVH, was defined as having ≥4 of the American Heart Association’s Life’s Simple 7 targets. Race (Black/White) and RRS (proportion of White residents in census tract) were the independent variables. Descriptive and multivariate analyses were conducted. Results: Young Black men had lower odds of achieving ideal CVH (OR = 0.67, 95% CI = 0.49, 0.92) than young White men. However, RRS did not have a significant effect on race differences in ideal CVH until the proportion of White residents was ≥55%. Conclusions: Among young Black and White men, RRS is an important factor to consider when seeking to understand CVH and reduce future cardiovascular risk.

Racial Patterns in Mortgage Lending Outcomes During and After the Subprime Boom

ABSTRACTThe racial contours of the United States’ subprime lending boom, foreclosure crisis, and subsequent recovered market illustrate that the benefits and risks of homeownership were unevenly distributed. Existing studies reveal general lending patterns in these periods but fail to scrutinize racially homogeneous neighborhoods where outcomes often diverge from aggregate trends. Using 2005 and 2015 U.S. Home Mortgage Disclosure Act mortgage application data, I construct a series of logistic regression models estimating lending outcomes in neighborhoods grouped by racial composition to reveal new patterns of differences in borrower outcomes. In both time periods the gap between white borrowers’ comparatively high application approval rates and minority borrowers’ lower approval rates grows as the proportion of white residents in a target neighborhood increases. In 2005 the likelihood of a borrower of any race receiving subprime terms generally increased as the proportion of white residents in a target neighborhood decreased. However, Asian borrowers experience comparatively favorable outcomes in homogeneously nonwhite neighborhoods. Additionally, applicants in homogeneously white neighborhoods experience less favorable results than those in slightly more diverse neighborhoods. Collectively, these findings suggest that outcomes in homogeneously white and nonwhite neighborhoods do not uniformly align with previously identified trends and warrant closer inspection.

Inequities in tobacco retailer sales to minors by neighbourhood racial/ethnic composition, poverty and segregation, USA, 2015

ObjectiveTobacco retailers are an important source of tobacco products for minors. Previous research shows racial discrimination in sales to minors, but no national study has examined neighbourhood correlates of retailer...

Long-Term Exposure To PM2.5 And Mortality In 207 Us Cities: Modification By Population Characteristics

Introduction: Although the association between long-term PM2.5 exposures and mortality has been consistently reported in the literature, these estimates vary spatially. We conducted a study to assess whether community-level variables, including socioeconomic status (SES) indicators and temperature modify the association between long term exposure to PM2.5 and mortality. Methods: We used data from =35 million Medicare enrollees living in 207 U.S. cities (2000–2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites, as the exposure of interest. We used a variation of a causal modeling approach, fitting Cox models, separately within each city, and we pooled the city-specific effects using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education, %black residents, % developed land etc. modify the association between long term exposure to PM2.5 and mortality. Results: We found a significant association between long-term PM2.5 effects and survival (HR = 1.19; 95%CI: 1.11–1.28 and 1.17; 95%CI: 1.05–1.31 per 10 μg/m3 increase in the annual and 2-year PM2.5 average concentrations). We observed significant effect modification by temperature, with higher effect estimates in warmer cities. Furthermore, we observed increasing effects with increasing obesity rates, percent of residents and families in poverty, proportion of black residents and percent of the population without a high school degree, and lower effects with increasing median household income and proportion of white residents. Conclusions: To our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the association between long-term PM2.5 exposures and survival. Our findings suggest that living in cities with higher temperatures and communities with low SES is associated with higher effect estimates.

Closing and Opening Schools: The Association between Neighborhood Characteristics and the Location of New Educational Opportunities in a Large Urban District

ABSTRACT:New charter schools can potentially provide disenfranchised students with enhanced academic opportunities while simultaneously serving as neighborhood anchors that reinforce neighborhood socioeconomic growth. However, for both of these arguments to be true, charter schools would have to replace low-performing public schools in currently disadvantaged, but revitalizing, neighborhoods. Using data from the Chicago Public Schools, the Common Core, and the Census, we examine the neighborhood and school-level factors that account for where elementary schools closed and opened in Chicago during the late 1990s and 2000s. We find that schools in disadvantaged neighborhoods were more likely to close, but only because these were also underperforming and under-enrolled schools. After controlling for educational demand, new schools were more likely to open in neighborhoods that showed signs of socioeconomic revitalization and declining proportions of white residents.

Documentation of Ethnicity

The comparison of the ethnic composition of an intermediate care facility with several Hispanic residents and the general population was hindered by the absence of categorization of ethnicity according to the United States Census. If all Hispanic residents of the facility were white, then 55% of the facility population were white, a proportion comparable to the 58.2% white population of the general population. On the other hand, if all the Hispanic residents were not white, then 27.5% of the facility residents were white. In that case, the proportion of white residents of the facility is much less than in the general population. Therefore, a Demographic Coding Form was developed to capture the essential data to make direct comparisons and contrasts with the general population recorded by the United States Census. Since the United States Census records Hispanic ethnic minority status as a separate category independent from all other ethnic groups, the design of experiments to investigate the possible effects of ethnicity on populations wisely incorporates the administration of a Demographic Coding Form to capture the key ethnic data to permit direct comparison with the general population.

Rapid Communication: Sociodemographic Differences between Counties with High and Low Utilization of a Regional Poison Control Center

A retrospective review of data from the New Jersey Poison Information and Education System (NJPIES) was conducted to determine whether differences exist in the sociodemographic characteristics between counties with high or low utilization of the regional poison control center (PCC). The goal was to generate hypotheses about the potential reasons for the variances in the utilization rates by different subpopulations, in order to develop culturally sensitive educational and preventive strategies in an effort to enhance the use of PCC services. Data from the NJPIES 2002 computerized medical records were analyzed to estimate the utilization rates (number of calls to NJPIES per 1000 of population) for each county in New Jersey. This information was then combined with county sociodemographic data from the 2000 U.S. Census. Sociodemographic characteristics were compared between the counties with high and low utilization rates and statistically significant differences were found. Counties with low utilization of PCC had significantly higher population density per square mile, smaller proportion of White residents, larger proportion of residents of "other race," and larger proportion of Black, Asian, and Hispanic and Latino residents. Further study is needed to examine the underlying reasons for the underutilization of PCC among such populations and to explore methods for improving their awareness and use of the services provided by PCC.

Park Hill, Denver

Greater Park Hill is a uniquely integrated neighborhood in Denver, Colorado. Although the proportion of White residents in the city declined from 66.7 percent to 61.4 percent between 1980 and 1990, Park Hill's White population remained stable at about 36 percent. By 1980, under the assumption that Park Hill had already passed a racial tipping point, many urban researchers predicted imminent resegregation. This has not occurred. In fact, one developing trend finds more White Anglos and White Hispanics moving into predominantly African-American neighborhoods.

Ecological Determinants of White and Black Inmigration To Small Areas in Central Cities, 1965 To 1970

White and Negro inmigration rates into central city census tracts of five Virginia metropolitan areas were analyzed in terms of ecological characteristics-socioeconomic, demographic, and housing quality characteristics and the heterogeneity of these characteristics. As hypothesized, white inmigration rates exceeded Negro rates. Both white and Negro rates were higher in tracts with higher socioeconomic levels and better housing quality, and with smaller shares of Negro population but larger shares of families in child-rearing stages. Diversity of ecological characteristics proved to be less important than the tract characteristics, themselves, in the analysis of net relationships. Although the explained variance in Negro inmigration rates was much lower than that for whites, comparisons of the pattern of ecological determinants for the two races showed more similarities than differences. The loss of population, particularly white population, in the central cities of larger metropolitan areas has challenged policy-makers at all levels of government to retain current residents and to attract inmigrants to revitalize the central city. A second concern with the current patterns of population deconcentration stems from the resulting racial composition. Declining proportions of white residents yield racially segregated neighborhoods and public schools. Rejection of busing policies has turned attention to other means to integrate schools, such as strategies to integrate neighborhoods. While a wealth of migration literature specifies the nature of demographic, economic, and industrial characteristics of larger areal unitscities, metropolitan areas, states, and regions-which differentially attract migrants, little attention has been given to the ecological characteristics of small areas within the city which serve to attract inmigrants. I Yet, it is empirical generalizations at the level of the small area which are needed to provide guidelines for policy designed to upgrade the quality of specific neighborhood environments to attract white migrants and migrants of higher SES to central city rather than ring destinations. This study then is directed to discern the demographic, socioeconomic, and housing characteristics of small areas within the central cities of Virginia metropolitan areas which differentially attracted inmigrants from 1965 to 1970. We compare the ecological determinants of white and Negro inmigration rates in order to derive racial differentials in the patterns of determinants important to each type of inmigration. *The authors are grateful to the Population Division of the National Institute of Child Health and Human Development, who supported this research (grant no. 5RO1 HD0627 1).