Percentage Of Black Population Research Articles

Uncovering Representation Bias in Large‐scale Cellular Phone‐based Data: A Case Study in North Carolina

Large cellular phone‐based mobility datasets are an important new data source for research on human movement. We investigate and illustrate bias in representation in a large mobility data set at the census block group, tract, and county levels. We paired American Community Survey (ACS) 2019 data with SafeGraph (SG) cell phone mobility data to elucidate potential bias in SG data by examining ACS estimated population against the number of devices in the SG data, stratifying by key sociodemographic variables such as income, percent Black population, percent of population over 55 years, percent of population 18–65 years, percent of people living in crowded living conditions, and urbanization level. We evaluated whether the bias varied over time by examining a 10‐month period. This bias changes with key demographic characteristics and changes over time. Specifically, we see underrepresentation in areas that have the highest percentage of Black population at all aggregation levels. We also see underrepresentation at all levels in areas with the highest percentage of working age residents as well as areas with the lowest median incomes. Researchers should be cautious when using mobility datasets because of bias differential on key sociodemographic factors and collection time.

BEYOND REDLINING: LAW, PROPERTY VALUES, RACIAL INEQUITIES, AND LTSS

Abstract This presentation will provide background regarding the social construction of property values and the interactive role that public and private institutions have played in creating racial disparities in property values. I will discuss known and proposed mechanisms through which this form of structural racism affects access to long-term services and supports (LTSS) and implications for the health of older adults and their care partners, presenting a specific example from my own research, which found that assisted living communities are located in 30% of communities in America. However, among communities with the highest percent Black population in their county, 31% of those located in counties with a low gap in Black-White economic mobility had access to assisted living, while less than 15% of those located within a county with a high Black-White gap in economic mobility had such access. I will describe how policymakers can use law to address racial disparities in geographic access by developing policies that 1) provide financial incentives for private investors to develop assisted living and other forms of LTSS in neighborhoods that otherwise wouldn’t see development due to low property values; 2) prioritize the location of new buildings in historically marginalized communities; 3) implement anti-displacement measures; 4) incorporate community input and engagement; and 5) ensure accessibility and affordability. Finally, I will describe how policymakers may consider the various actors and institutions that shape the housing market and how they interact with each other to produce outcomes that may reinforce or challenge structural racism.

Evolution of COVID-19 Health Disparities in Arizona.

COVID-19 burdens are disproportionally high in underserved and vulnerable communities in Arizona. As the pandemic progressed, it is unclear if the initial associated health disparities have changed. This study aims to elicit the dynamic landscape of COVID-19 disparities at the community level and identify newly emerging vulnerable subpopulations. Findings from this study can inform interventions to increase health equity among minoritized communities in the Southwest, other regions of the US, and globally. We compiled biweekly COVID-19 case counts of 274 zip code tabulation areas (ZCTAs) in Arizona from October 21, 2020, to November 25, 2021, a time spanning multiple waves of COVID-19 case growth. Within each biweekly period, we tested the associations between the growth rate of COVID-19 cases and the population composition in a ZCTA including race/ethnicity, income, employment, and age using multiple regression analysis. We then compared the associations across time periods to discover temporal patterns of health disparities. The association between the percentage of Latinx population and the COVID-19 growth rate was positive before April 2021 but gradually converted to negative afterwards. The percentage of Black population was not associated with the COVID-19 growth rate at the beginning of the study but became positive after January 2021 which persisted till the end of the study period. Young median age and high unemployment rate emerged as new risk factors around mid-August 2021. Based on these findings, we identified 37 ZCTAs that were highly vulnerable to future fast escalation of COVID-19 cases. As the pandemic progresses, vulnerabilities associated with Latinx ethnicity improved gradually, possibly bolstered by culturally responsive programs in Arizona to support Latinx. Still communities with disadvantaged social determinants of health continued to struggle. Our findings inform the need to adjust current resource allocations to support the design and implementation of new interventions addressing the emerging vulnerabilities at the community level.

Disparity in initiation of checkpoint inhibitors among metastatic melanoma and lung cancer.

1583 Background: Checkpoint inhibitors are transforming cancer care. However, the high prices of these medicines raise concerns over their affordability and disparity in use. The objective of this study is to describe the disparity in initiating checkpoint inhibitors and examine patient- and area-level factors associated with delayed initiation. Methods: This study is a retrospective cohort study using Optum data. We identified commercially insured patients newly diagnosed with metastatic lung cancer and melanoma since the introduction of checkpoint inhibitors in these cancers (lung cancer cohort: diagnosed between January 2015 and December 2020; melanoma cohort: diagnosed between January 2011 and December 2020). Time from metastatic cancer diagnosis to initiating checkpoint inhibitors was analyzed using Cox proportional hazard models. Independent variables included county-level measures (percentage of black population, percentage of Hispanic population, percentage of other minority, percentage of population living below poverty line, rurality, number of medical oncologist per population, and having a National Cancer Institute designated cancer center) and patient-level characteristics (age, sex, Charlson comorbidity index, any dual eligibility, Medicare Advantage, and year of diagnosis). We clustered standard errors at the county level. Results: The percentage of metastatic lung cancer and metastatic melanoma patients on checkpoint inhibitors increased from 23% to 52% from 2015 to 2020 and from 22% to 58% from 2011 to 2020. Counties with greater percentage of black, Hispanics, and other minorities were high urban with greater density of medical oncologists and NCI-designated cancer centers. However, greater percentage of Hispanic population in a county was associated with significantly slower initiation of checkpoint inhibitors for both the lung cancer and the melanoma cohorts (hazard ratios [HR]: 0.937 and 0.946, respectively; p-values: < 0.001 and 0.014, respectively). Percentage of other minority population in a county was associated with slower initiation for metastatic lung cancer (HR: 0.983; p-value: < 0.001). No other county-level factors had a significant coefficient from the multivariate Cox models. In terms of patient-level characteristics, older age, female, more comorbidities, any dual eligibility, and Medicare Advantage were associated with significantly slower initiation for the lung cancer cohort and older age and female were associated with significantly slower initiation for the melanoma cohort. Conclusions: Commercially insured metastatic lung cancer and melanoma patients who lived in counties with greater percentage of Hispanic population had slower initiation of checkpoint inhibitors after their cancer diagnosis, despite the fact that those counties had greater density of medical oncologists and NCI-designated cancer centers.

Neighborhood Deprivation is Associated with Increased Risk of Prenatal Smoke Exposure

Despite years of advisories against the behavior, smoking among pregnant women remains a persistent public health issue in the USA. Recent estimates suggest that 9.4% of women smoke before pregnancy and 7.1% during pregnancy in the USA. Epidemiological research has attempted to pinpoint individual-level and neighborhood-level factors for smoking during pregnancy, including educational attainment, employment status, housing conditions, poverty, and racial demographics. However, most of these studies have relied upon self-reported measures of smoking, which are subject to reporting bias. To more accurately and objectively assess smoke exposure in mothers during pregnancy, we used Bayesian index models to estimate a neighborhood deprivation index (NDI) for block groups in Durham County, North Carolina, and its association with cotinine, a marker of smoke exposure, in pregnant mothers (n = 887 enrolled 2005-2011). Results showed a significant positive association between NDI and log cotinine (beta = 0.20, 95% credible interval = [0.11, 0.29]) after adjusting for individual covariates (e.g., race/ethnicity and education). The two most important variables in the NDI according to the estimated index weights were percent females without a high school degree and percent Black population. At the individual level, Hispanic and other race/ethnicity were associated with lowered cotinine compared with non-Hispanic Whites. Higher education levels were also associated with lowered cotinine. In summary, our findings provide stronger evidence that the socio-geographic variables of educational attainment and neighborhood racial composition are important factors for smoking and secondhand smoke exposure during pregnancy and can be used to target intervention efforts.

A Mixed Methods Case Study of Food Shopping in a Community with High Infant Mortality.

In the U.S., preterm birth disproportionately impacts certain racial/ethnic groups, with Black women experiencing preterm birth at a rate 50% higher than other groups. Among the numerous factors that likely contribute to these increased rates are neighborhood characteristics, such as food environment. In this mixed-methods case study, we evaluated how pregnant women living in a predominately minority, lower income community with high preterm birth rates navigate and perceive their food environment. Qualitative interviews were performed to assess perceptions of food environment (n = 7) along with geographic and observational assessments of their food environment. Participants traveled an average of 2.10 miles (SD = 1.16) and shopped at an average of 3 stores. They emphasized the importance of pricing and convenience when considering where to shop and asserted that they sought out healthier foods they thought would enhance their pregnancy health. Observational assessments of stores’ nutrition environment showed that stores with lower nutritional scores were in neighborhoods with greater poverty and a higher percent Black population. Future policies and programmatic efforts should focus on improving nutrition during pregnancy for women living in communities with high rates of poor birth outcomes. Availability, affordability, and accessibility are key aspects of the food environment to consider when attempting to achieve birth equity.

Public Interest and Behavior Change in the United States Regarding Colorectal Cancer Following the Death of Chadwick Boseman: Infodemiology Investigation of Internet Search Trends Nationally and in At-Risk Areas.

Colorectal cancer (CRC) has the third highest cancer mortality rate in the United States. Enhanced screening has reduced mortality rates; however, certain populations remain at high risk, notably African Americans. Raising awareness among at-risk populations may lead to improved CRC outcomes. The influence of celebrity death and illness is an important driver of public awareness. As such, the death of actor Chadwick Boseman from CRC may have influenced CRC awareness. We sought to assess the influence of Chadwick Boseman's death on public interest in CRC in the United States, evidenced by internet searches, website traffic, and donations to prominent cancer organizations. We used an auto-regressive integrated moving average model to forecast Google searching trends for the topic "Colorectal cancer" in the United States. We performed bivariate and multivariable regressions on state-wise CRC incidence rate and percent Black population. We obtained data from the American Cancer Society (ACS) and the Colon Cancer Foundation (CCF) for information regarding changes in website traffic and donations. The expected national relative search volume (RSV) for colorectal cancer was 2.71 (95% CI 1.76-3.66), reflecting a 3590% (95% CI 2632%-5582%) increase compared to the expected values. With multivariable regression, the statewise RSV increased for each percent Black population by 1.09 (SE 0.18, P<.001), with 42% of the variance explained (P<.001). The American Cancer Society reported a 58,000% increase in CRC-related website traffic the weekend following Chadwick Boseman's death compared to the weekend before. The Colon Cancer Foundation reported a 331% increase in donations and a 144% increase in revenue in the month following Boseman's death compared to the month prior. Our results suggest that Chadwick Boseman's death was associated with substantial increases in awareness of CRC. Increased awareness of CRC may support earlier detection and better prognoses.

Dynamics of Covid-19 mortality and social determinants of health: a spatiotemporal analysis of exceedance probabilities

PurposeTo determine the association of social factors with Covid-19 mortality and identify high-risk clusters.MethodsData on Covid-19 deaths across 3,108 contiguous U.S. counties from the Johns Hopkins University and social determinants of health (SDoH) data from the County Health Ranking and the Bureau of Labor Statistics were fitted to Bayesian semi-parametric spatiotemporal Negative Binomial models, and 95% credible intervals (CrI) of incidence rate ratios (IRR) were used to assess the associations. Exceedance probabilities were used for detecting clusters.ResultsAs of October 31, 2020, the median mortality rate was 40.05 per 100, 000. The monthly urban mortality rates increased with unemployment (IRRadjusted:1.41, 95% CrI: 1.24, 1.60), percent Black population (IRRadjusted:1.05, 95% CrI: 1.04, 1.07), and residential segregation (IRRadjusted:1.03, 95% CrI: 1.02, 1.04). The rural monthly mortality rates increased with percent female population (IRRadjusted: 1.17, 95% CrI: 1.11, 1.24) and percent Black population (IRRadjusted:1.07 95% CrI:1.06, 1.08). Higher college education rates were associated with decreased mortality rates in rural and urban counties. The dynamics of exceedance probabilities detected the shifts of high-risk clusters from the Northeast to Southern and Midwestern counties.ConclusionsSpatiotemporal analyses enabled the inclusion of unobserved latent risk factors and aid in scientifically grounded decision-making at a granular level.

Erratum: Percentage of Black Population and Primary Care Shortage Areas Associated with Higher COVID-19 Case and Death Rates in Georgia Counties: Erratum.

[This corrects the article DOI: 10.14423/SMJ.0000000000001212.].

Firearm homicide mortality is influenced by structural racism in US metropolitan areas.

Metropolitan cities in the United States suffer from higher rates of gun violence. However, the specific structural factors associated with increased gun violence are poorly defined. We hypothesized that firearm homicide in metropolitan cities would be impacted by Black-White segregation index. This cross-sectional analysis evaluated 51 US metropolitan statistical areas (MSAs) using data from 2013 to 2017. Several measures of structural racism were examined, including the Brooking Institute's Black-White segregation index. Demographic data were derived from the US Census Bureau, US Department of Education, and US Department of Labor. Crime data and firearm homicide mortality rates were obtained from the Federal Bureau of Investigation and the Centers for Disease Control. Spearman ρ and linear regression were performed. Firearm mortality was associated with multiple measures of structural racism and racial disparity, including White-Black segregation index, unemployment rate, poverty rate, single parent household, percent Black population, and crime rates. In regression analysis, percentage Black population exhibited the strongest association with firearm homicide mortality (β = 0.42, p < 0.001). Black-White segregation index (β = 0.41, p = 0.001) and percent children living in single-parent households (β = 0.41, p = 0.002) were also associated with higher firearm homicide mortality. Firearm legislation scores were associated with lower firearm homicide mortality (β = -0.20 p = 0.02). High school and college graduation rates were not associated with firearm homicide mortality and were not included in the final model. Firearm homicide disproportionately impacts communities of color and is associated with measures of structural racism, such as White-Black segregation index. Public health interventions targeting gun violence must address these systemic inequities. Furthermore, given the association between firearm mortality and single-parent households, intervention programs for at-risk youth may be particularly effective. Epidemiological level II.

Coronavirus testing disparities associated with community level deprivation, racial inequalities, and food insecurity in West Virginia

PurposeSocial determinants of health and racial inequalities impact healthcare access and subsequent coronavirus testing. Limited studies have described the impact of these inequities on rural minorities living in Appalachia. This study investigates factors affecting testing in rural communities. MethodsPCR testing data were obtained for March through September 2020. Spatial regression analyses were fit at the census tract level. Model outcomes included testing and positivity rate. Covariates included rurality, percent Black population, food insecurity, and area deprivation index (a comprehensive indicator of socioeconomic status). ResultsSmall clusters in coronavirus testing were detected sporadically, while test positivity clustered in mideastern and southwestern WV. In regression analyses, percent food insecurity (IRR = 3.69×109, [796, 1.92×1016]), rurality (IRR=1.28, [1.12, 1.48]), and percent population Black (IRR = 0.88, [0.84, 0.94]) had substantial effects on coronavirus testing. However, only percent food insecurity (IRR = 5.98 × 104, [3.59, 1.07×109]) and percent Black population (IRR = 0.94, [0.90, 0.97]) displayed substantial effects on the test positivity rate. ConclusionsFindings highlight disparities in coronavirus testing among communities with rural minorities. Limited testing in these communities may misrepresent coronavirus incidence.

Percentage of Black Population and Primary Care Shortage Areas Associated with Higher COVID-19 Case and Death Rates in Georgia Counties.

We hypothesized that the proportion of Black individuals in a county would be associated with higher rates of coronavirus disease 2019 (COVID-19) cases and deaths, even after accounting for other high-risk socioecologic factors such as poverty, population density, and household crowding, and uninsured rates. We also expected that counties designated as primary care health professional shortage areas (PCHPSAs) would be associated with higher COVID-19 death rates, and the lack of primary care access would exacerbate racial disparities in death rates. We undertook this study to test these hypotheses and discern the independent effects of racial composition, socioecologic characteristics, and healthcare system factors on COVID-19 cases and deaths in Georgia counties. We used county-level COVID-19 cases and deaths on April 23, 2020 from the Johns Hopkins Coronavirus Resource Center and estimates of 2019 county-level populations from the US Census Bureau to calculate the cumulative event rates for the state of Georgia. We used multiple regression models to examine crude and adjusted associations of socioecologic and health system variables with county-level COVID-19 case and mortality rates. After adjustment, a 1% increase in the proportion of Black people in the county resulted in a 2.3% increase in the county COVID-19 confirmed case rate and a 3.0% increase in the death rate (relative risk 1.03, 95% confidence interval 1.01-1.05, P < 0.001). Primary care shortage areas had a 74% higher death rate (relative risk 1.74, 95% confidence interval 1.00-3.00, P = 0.049). These results highlight the impact of racial disparities on the spatial patterns of COVID-19 disease burden in Georgia, which can guide interventions to mitigate racial disparities. The results also support the need for robust primary care infrastructure throughout the state.

De norte a sul, de leste a oeste: mudança na identificação racial no Brasil

Num primeiro momento, este estudo atualiza e reconstrói, sob alguns aspectos, a análise realizada por Soares (2008) sobre o fenômeno da mudança na identificação racial que vem ocorrendo no Brasil desde o início dos anos 2000. Num segundo momento, expandindo tal análise, investiga-se a existência de diferenças regionais nesse processo. Os resultados mostram que os aumentos observados na porcentagem de negros no total do país e nas suas cinco macrorregiões foram devidos quase que exclusivamente à mudança ocorrida no modo como as próprias pessoas se veem. Quanto ao efeito da mudança na identificação racial sobre o aumento no número de negros, verificou-se que este varia consideravelmente de região para região,sendo mais forte no Sul e Sudeste. Por fim, argumenta-se que qualquer análise intertemporal, a partir dos anos 2000, que envolva autodeclaração de cor ou raça, é potencialmente afetada por esse processo de mudança na identificação racial.

Racial, Ethnic, and Geographic Disparities in Novel Coronavirus (Severe Acute Respiratory Syndrome Coronavirus 2) Test Positivity in North Carolina.

BackgroundEmerging evidence suggests that black and Hispanic communities in the United States are disproportionately affected by coronavirus disease 2019 (COVID-19). A complex interplay of socioeconomic and healthcare disparities likely contribute to disproportionate COVID-19 risk.MethodsWe conducted a geospatial analysis to determine whether individual- and neighborhood-level attributes predict local odds of testing positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We analyzed 29 138 SARS-CoV-2 tests within the 6-county catchment area for Duke University Health System from March to June 2020. We used generalized additive models to analyze the spatial distribution of SARS-CoV-2 positivity. Adjusted models included individual-level age, gender, and race, as well as neighborhood-level Area Deprivation Index, population density, demographic composition, and household size.ResultsOur dataset included 27 099 negative and 2039 positive unique SARS-CoV-2 tests. The odds of a positive SARS-CoV-2 test were higher for males (odds ratio [OR], 1.43; 95% credible interval [CI], 1.30–1.58), blacks (OR, 1.47; 95% CI, 1.27–1.70), and Hispanics (OR, 4.25; 955 CI, 3.55–5.12). Among neighborhood-level predictors, percentage of black population (OR, 1.14; 95% CI, 1.05–1.25), and percentage Hispanic population (OR, 1.23; 95% CI, 1.07–1.41) also influenced the odds of a positive SARS-CoV-2 test. Population density, average household size, and Area Deprivation Index were not associated with SARS-CoV-2 test results after adjusting for race.ConclusionsThe odds of testing positive for SARS-CoV-2 were higher for both black and Hispanic individuals, as well as within neighborhoods with a higher proportion of black or Hispanic residents—confirming that black and Hispanic communities are disproportionately affected by SARS-CoV-2.

COVID-19 Prevalence and Mortality Rates in Association with Black Race and Segregation in the United States April 1 to April 15, 2020

Background: COVID-19 may be experienced disproportionately among racial minorities but evidence is limited. The study objective was to determine whether COVID-19 prevalence and mortality rates were higher in the US population in association with race/ethnicity, racial segregation, and other population characteristics. Methods: The study used a repeated measures county-level ecological design including all US counties. Exposures included population characteristics including percent Black race, racial segregation, household income and income inequality, age, education, health insurance rates, primary care physician supply, and percent rural population. Outcomes were COVID-19 prevalence per 100,000 population, and death rates from COVID-19 per 100,000 between April 1 and April 15, 2020. Findings: Higher disease prevalence and death rates were found in association with higher racial segregation, higher percent Black population, income and income inequality, and lower percent rural population. The disparity among populations characterized by combined higher percent Black population and higher segregation significantly worsened between April 1 and April 15, 2020. Interpretation: Populations with a combination of higher percent of Black populations and greater racial segregation experienced higher COVID-19 prevalence and mortality, and this disparity increased significantly as the disease outbreak in the US worsened in the first half of April 2020. Current and future efforts to fight COVID-19 should address disproportionate risks in these communities. Funding Statement: The study received no funding from any public or private source. Declaration of Interests: None.

Racial, ethnic, and income disparities in air pollution: A study of excess emissions in Texas.

ObjectiveExcess emissions are pollutant releases that occur during periods of startups, shutdowns or malfunctions and are considered violations of the U.S. Clean Air Act. They are an important, but understudied and under-regulated, category of pollution releases given their frequency and magnitude. In this paper, we examine the demographic correlates of excess emissions, using data from industrial sources in Texas.MethodsWe conduct two complementary sets of analyses: one at the census tract level and one at the facility level. At the census tract level, we use a multinomial logit model to examine the relationships between racial, ethnic, and income characteristics and the incidence of excess emissions. At the facility level, we first estimate a logit model to examine whether these characteristics are associated with facilities that emit excess emissions, and then, conditional on the presence of excess emissions, we use ordinary least square regression to estimate their correlation with the magnitude of releases.ResultsAcross our analyses, we find that the percentage of Black population and median household income are positively associated with excess emissions; percentage of college graduate, population density, median housing value, and percentage of owner-occupied housing unit are negatively associated with excess emissions. We, however, have not found a clear and significant relationship between the percentage of Hispanic population and excess emissions.

Maternal Exposure to Greenness during Pregnancy and Birth Weight

Background/Aim: Exposure to greenness in the residential neighbourhood, measured through the normalized difference vegetation index (NDVI), has been shown to affect human health. In this study, we study the association between maternal exposure to NDVI during pregnancy and birth weight with adjustment for air pollution as well as other individual and neighbourhood confounders. Methods: For 684,266 births between 2001 and 2012 in Massachusetts, each birth was assigned an average NDVI during pregnancy using the 250 * 250 m grid cell for which the mother lived in. We regress birth weight against NDVI, particulate air pollution (PM2.5 at 1 * 1 km), and other covariates in generalized linear models. We adjust for nonlinearity in effect using splines. The full list of covariates are as follows: marital status, maternal education, government-supported prenatal care, maternal/paternal age and race, maternal cigarette smoking before/during pregnancy, parity, Kotelchuck Index for prenatal care, gestational/other diabetes and hypertension, mode of delivery, infant sex, clinical gestational age, and census-tract percent black population and median income. Results: In the linear model with NDVI and covariates, an interquartile range (IQR) increase in NDVI (0.225) was associated with a 13.87 (95% CI: 11.98, 15.75) gram increase in birth weight. After adjusting for PM2.5, an IQR increase in NDVI was associated with a 14.90 (12.91, 16.90) gram increase in birth weight. Including interactive terms between NDVI and each of government-supported prenatal care, maternal education, and infant sex did not significantly change the NDVI effect estimates. Conclusions: Maternal exposure to greenness measured through NDVI appears beneficial to newborn health as it is positively associated with birth weight, even after adjusting for highly-resolved particulate air pollution predictions and many individual / neighbourhood health and socioeconomic variables.

Social Determinants of HIV Disparities in the Southern United States and in Counties with Historically Black Colleges and Universities (HBCUs), 2013-2014.

HIV infection disproportionately affects Blacks in the southern United States (U.S.), a region where legal policies that may unintentionally impede earlier HIV detection and treatment are prevalent. Historically Black Colleges and Universities (HBCUs) have historically facilitated social change in communities of color and have been underexplored as partners for HIV prevention. We describe geographic and social determinants of health (SDH) in the southern U.S. to inform potential HBCU-public health partnerships that might improve HIV health equity. We evaluated the relationship between county-level HIV prevalences (2013), HBCU geographic coordinates, and SDH variables in the southern counties with HBCUs. U.S. Census-derived SDH variables included race/ethnicity (i.e., Black, White, Hispanic), unemployment, female head of household, poverty, percent owner-occupied housing units, urbanicity, and primary care provider rates. Associations were assessed using bivariate and multivariable linear regression. Of 104 HBCUs in the contiguous U.S., 100 (96%) were located in 69 southern counties with average Black populations of 40% and an average HIV prevalence of 615. 5 per 100,000, over two times the national rate (295.1 per 100,000). In bivariable analyses, higher HIV rates in these counties were associated with higher percent Black population, unemployment, female head of household, poverty, fewer owner-occupied housing units, and greater urbanicity (p < 0.05). In multivariable analyses, counties with higher HIV rates had higher percentages of Blacks, greater urbanicity, fewer owner-occupied housing units, and more female heads of households (p < 0.05). The southern U.S. is disproportionately affected by HIV, and many HBCUs are located in affected southern counties. HBCUs may be important public health partners for helping to develop structural interventions that strengthen HIV policies in support of health equity in these southern, mostly urban counties.

&lt;em&gt;Utility of V. O. Key’s Black Population Density Theory in the Desegregation of Southern U.S. Public Universities 1948–1963&lt;/em&gt;

Southern state colleges and universities' responses to African American applicants varied considerably from 1940 through 1963. Faced with qualified Black applicants backed by the NAACP, social movements, and federal authorities-some state and university officials admitted Black students with fairly little resistance, whereas others stonewalled, created new barriers, but eventually conceded. Arkansas was the first southern state to admit a Black student to a publicly funded state college, and South Carolina was last. What accounts for the sequence by which the eleven southern states admitted the first African Americans to state universities? This article provides an overview of the first Black entrants to southern state public colleges, analyzes the effects of United States Supreme Court rulings on higher education desegregation, and offers a provisional explanation for how state-level defenses to desegregation fell. The aim is to explain social and political factors that contributed to higher education desegregation in the 50s and 60s, thereby enabling individuals and organizations to formulate strategies to address present day inequities and injustices.To that end, this essay investigates the utility of V. O. Key's (1984) analytical framework in Southern Politics in State and Nation. Key posited that varying rates of Black population density within and across eleven Southern states affected local and regional political development in the mid-twentieth century. In Black Belt counties where African Americans lived and worked in higher numbers, White supremacist elites controlled political institutions to protect their economic and social interests at the state and national level (Key, 1984).Key's analysis showed that while race was part of the political debate, more importantly, the need to control labor in rural agricultural regions drove White elites to devise political strategies to resist federal intervention in southern state and local race-related policies. Elite Whites influenced national elections to ensure a unified bloc would veto Black civil rights legislation in the U.S. Congress. Key also noted that race was not a salient political factor in some areas of the southern states, particularly in cities, the highlands, and coastal areas, where the economy was not dependent on large-scale agriculture. Key noted that demographic and economic changes would eventually transform southern political culture.If Key is correct that the percentage of Black population determined the nature of political control in southern states, then one can estimate that states with the highest percentage of Blacks should offer massive resistance to desegregation because White political elites will influence education policy decisions. Questions raised in this essay are: In the realm of higher education desegregation, does Key's demographic theory explain state level variation in resistance to federal desegregation rulings? Did other social, political, and economic factors affect the timing and circumstances of desegregation in different states?The article begins with a brief history of southern Black education, a table outlining the first undergraduate or graduate Black applicant accepted into a southern public university in each southern state, a comparative analysis of state public universities' level of resistance to desegregation prior to and following the Brown v. Board Education (1954, 1955) rulings, and an examination of four case studies that represent all levels of state university resistance to desegregation. Not all of the first entrants remained at or graduated from these universities. In at least one case, the university accepted students on a segregated basis. This examination does not claim that higher education desegregation ended with the admittance of Black students as many institutions continued to find ways to exclude Black graduate and undergraduate students. The intent is to understand some of the social and political factors that impacted the initial puncture in southern public university desegregation. …

Abstract A07: Exploring the distribution of environmental cancer risk by air toxics using geographic information systems

Abstract We examined environmental cancer risk disparities in Metropolitan Charleston by determining the variability in cancer risk and outcomes geographically by racial and socioeconomic characteristics. We mapped total cancer risk from the 2005 National-Scale Air Toxics Assessment (NATA) and five-year (2006-2010) cancer outcomes (incidence and mortality) from the South Carolina Central Cancer Registry. Data were georeferenced to the 2000 Decennial United States Census tract boundaries in Metropolitan Charleston (i.e. Berkeley, Charleston, and Dorchester County). A Spearman's rank-order correlation was run to determine the relationship between cancer risk or cancer outcomes and characteristics of environmental justice (percent (%) Black, poverty, and low-income). Correlations were performed in SPSS 22.0. Bivariate choropleth maps were created in ArcGIS 10.2 to represent the geographic associations between cancer data and environmental justice variables. Our findings demonstrate an inverse relationship between cancer risk and five-year cancer incidence (rs = -1.90, p = .040). Cancer risk was positively correlated with % Black (rs = .324) and % poverty (rs = .474), yet negatively related to % income (rs = -.542). Bivariate maps showed that 80% of the tracts with high cancer incidence/high percent Black population were simultaneously high cancer mortality/high Black population tracts. None of the high incidence or high mortality tracts had simultaneously high cancer risk. Findings from this study have implications for reducing place-based environmental cancer disparities. With a better understanding of patterns of risk, public health professionals can tailor interventions and develop community-based environmental health programs that will inform policies to reduce cancer inequities. Citation Format: LaShanta J. Rice, Christopher T. Emrich, Heather M. Brandt, Lucy Annang Ingram, James W. Hardin, Sacoby M. Wilson, Chanita Hughes Halbert. Exploring the distribution of environmental cancer risk by air toxics using geographic information systems. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr A07.