Dataset Information

Structural Racism and Breast Cancer-specific Survival: Impact of Economic and Racial Residential Segregation.

ABSTRACT:

Objective

To analyze the effect of economic and racial/ethnic residential segregation on breast cancer-specific survival (BCSS) in South Florida, a diverse metropolitan area that mirrors the projected demographics of many United States regions.

Summary background data

Despite advances in diagnosis and treatment, racial and economic disparities in BCSS. This study evaluates these disparities through the lens of racial and economic residential segregation, which approximate the impact of structural racism.

Methods

Retrospective cohort study of stage I to IV breast cancer patients treated at our institution from 2005 to 2017. Our exposures include index of concentration at the extremes, a measurement of economic and racial neighborhood segregation, which was computed at the census-tract level using American Community Survey data. The primary outcome was BCSS.

Results

Random effects frailty models predicted that patients living in low-income neighborhoods had higher mortality compared to those living in high-income neighborhoods [hazard ratios (HR): 1.56, 95% confidence interval (CI): 1.23-2.00]. Patients living in low-income non-Hispanic Black and Hispanic neighborhoods had higher mortality compared to those living in high-income non-Hispanic White (NHW) neighborhoods (HR: 2.43, 95%CI: 1.72, 3.43) and (HR: 1.99, 95%CI: 1.39, 2.84), after controlling for patient characteristics, respectively. In adjusted race-stratified analysis, NHWs living in low-income non-Hispanic Black neighborhoods had higher mortality compared to NHWs living in high-income NHW neighborhoods (HR: 4.09, 95%CI: 2.34-7.06).

Conclusions

Extreme racial/ethnic and economic segregation were associated with lower BCSS. We add novel insight regarding NHW and Hispanics to a growing body of literature that demonstrate how the ecological effects of structural racism-expressed through poverty and residential segregation-shape cancer survival.

SUBMITTER: Goel N

PROVIDER: S-EPMC9102835 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Structural Racism and Breast Cancer-specific Survival: Impact of Economic and Racial Residential Segregation.

Goel Neha N Westrick Ashly C AC Bailey Zinzi D ZD Hernandez Alexandra A Balise Raymond R RR Goldfinger Erica E Antoni Michael H MH Stoler Justin J Kesmodel Susan B SB Kobetz Erin N EN

Annals of surgery 20220401 4

<h4>Objective</h4>To analyze the effect of economic and racial/ethnic residential segregation on breast cancer-specific survival (BCSS) in South Florida, a diverse metropolitan area that mirrors the projected demographics of many United States regions.<h4>Summary background data</h4>Despite advances in diagnosis and treatment, racial and economic disparities in BCSS. This study evaluates these disparities through the lens of racial and economic residential segregation, which approximate the impa ...[more]

PMID: 35081560

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Project description:ImportanceResidential segregation is a structural risk factor for poor cancer outcomes. Previous research examining the association of residential segregation with cancer outcomes was limited by older data, restricted geographic areas, and few cancer sites. To guide targeted interventions, a comprehensive evaluation of the association between segregation and cancer outcomes is needed.ObjectiveTo examine the association of residential racial and economic segregation with cancer mortality at the US county level for all cancers combined and for the 13 cancer types that represent the top 10 causes of cancer deaths in males or females.Design, setting, and participantsThis ecological study used county-level sociodemographic data from the 2015-2019 American Community Survey linked with 2015-2019 county-level mortality data. Data analysis was performed from September 2021 to April 2022.ExposuresResidential racial and economic segregation measured by the Index of Concentration at the Extremes (ICE) and categorized into quintiles 1 (most deprived) through 5 (most privileged).Main outcomes and measuresAge-adjusted cancer mortality was the outcome. Multilevel linear mixed modeling was used to calculate the adjusted mortality rate ratio (aRR).ResultsA total of 3110 counties were included. The age-adjusted mortality rates of all cancers combined were 179.8, 177.3, 167.6, 159.6, and 146.1 per 100 000 population (P < .001 for trend) for the 5 ICE categories (most deprived to least deprived), respectively. Compared with the least deprived counties, aRRs for all cancers combined were 1.22 (95% CI, 1.20-1.24) for the most deprived counties, followed by 1.17 (95% CI, 1.15-1.19), 1.10 (95% CI, 1.09-1.12), and 1.06 (95% CI, 1.04-1.08) for the other 3 quintiles, respectively (P < .001 for trend). Segregation was associated with increased mortality from 12 of 13 selected cancer sites, in which aRRs ranged from 1.06 (95% CI, 1.02-1.09) for brain and other nervous system cancer to 1.49 (95% CI, 1.43-1.54) for lung and bronchus cancer.Conclusions and relevanceThe findings of this ecological study suggest that residential racial and economic segregation is associated with higher cancer mortality at the county level, highlighting opportunities for geographically targeted cancer prevention and control efforts.

Project description:Black birthing people are twice as likely to experience severe maternal morbidity (SMM) as their white counterparts. Structural racism provides a framework for understanding root causes of perinatal health disparities. Our objective was to investigate associations between measures of structural racism and severe maternal morbidity (SMM) among Black birthing people in the US. We linked delivery hospitalizations for Black birthing people in the National Inpatient Sample (2008-2011) with data from the American Community Survey 5-year estimates and the Vera Institute of Justice Incarceration Trends datasets (2008-2011). Structural racism measures included the Index of Concentration at the Extremes for race and income (i.e., racialized economic segregation) and Black-white incarceration inequality, assessed as quintiles by hospital county. Multilevel logistic regression assessed the relationship between these county-level indicators of structural racism and SMM. Black birthing people delivering in quintiles 5 (concentrated deprivation; OR = 1.45, 95% CI = 1.16-1.81) and 3 (OR = 1.27, 95% CI = 1.04-1.56) experienced increased odds of SMM compared to those in quintile 1 (concentrated privilege). After adjusting for individual characteristics, obstetric comorbidities, and hospital characteristics the odds of SMM remained elevated for Black birthing people delivering in quintiles 5 (aOR = 1.32, 95% CI = 1.02-1.71) and 3 (aOR = 1.24, 95% CI = 1.02-1.51). Delivering in the quintile with the highest incarceration inequality (Q5) was not significantly associated with SMM (aOR = 0.95, 95% CI = 0.72-1.25) compared to those delivering in counties with the lowest incarceration inequality (Q1). In this national-level study, racialized economic segregation was associated with SMM among Black birthing people. Our findings highlight the need to promote maternal and perinatal health equity through actionable policies that prioritize investment in communities experiencing deprivation.

Project description:ImportanceResearch suggests the social, physical, and socioeconomic contexts of residing in segregated neighborhoods may negatively affect mental health.ObjectiveTo assess the association between racial residential segregation and prenatal mental health among Asian, Black, Hispanic, and White individuals.Design, setting, and participantsThis population-based cross-sectional study was conducted in Kaiser Permanente Northern California (KPNC), an integrated health care delivery system. Participants included self-identified Asian, Black, Hispanic, and White pregnant individuals who attended at least 1 prenatal care visit at KPNC between January 1, 2014, and December 31, 2019. Data were analyzed from January 14, 2023, to August 15, 2024.ExposuresRacial residential segregation, defined by the local Getis-Ord Gi* statistic, was calculated in each racial and ethnic group and categorized as low (<0), medium (0-1.96), or high (>1.96). A positive Gi* statistic indicates overrepresentation (greater clustering or segregation) of the racial and ethnic group in an index census tract and neighboring tracts compared with the larger surrounding geographic area.Main outcomes and measuresPrenatal depression and anxiety defined by diagnoses codes documented in the electronic health record between the first day of the last menstrual period and the day prior to birth.ResultsAmong the 201 115 participants included in the analysis (mean [SD] age, 30.8 [5.3] years; 26.8% Asian, 6.6% Black, 28.0% Hispanic, and 38.6% White), prenatal depression and anxiety were highest in Black individuals (18.3% and 18.4%, respectively), followed by White (16.0% and 18.2%, respectively), Hispanic (13.0% and 14.4%, respectively), and Asian (5.7% and 6.4%, respectively) individuals. Asian (40.8% vs 31.1%) and Black (43.3% vs 22.6%) individuals were more likely to live in neighborhoods with high vs low segregation, while Hispanic individuals were equally likely (34.3% vs 34.7%). High compared with low segregation was associated with greater odds of prenatal depression (adjusted odds ratio [AOR], 1.25 [95% CI, 1.10-1.42]) and anxiety (AOR, 1.14 [95% CI, 1.00-1.29]) among Black individuals. High segregation was associated with lower odds of prenatal depression among Asian (AOR, 0.75 [95% CI, 0.69-0.82]), Hispanic (AOR, 0.88 [95% CI, 0.82-0.94]), and White (AOR, 0.91 [95% CI, 0.86-0.96]) individuals. Similar associations were found for anxiety among Asian (AOR, 0.80 [95% CI, 0.73-0.87]) and Hispanic (AOR, 0.88 [95% CI, 0.82-0.93]) but not White (AOR, 0.95 [95% CI, 0.90-1.00]) individuals.Conclusions and relevanceIn this cross-sectional study, racial and ethnic residential segregation was associated with worse prenatal mental health for Black individuals but better mental health for Asian, Hispanic, and White individuals. Policies reducing segregation and its impact may improve mental health outcomes in pregnant Black individuals.

Project description:ImportanceStudies elucidating determinants of residential neighborhood-level health inequities are needed.ObjectiveTo quantify associations of structural racism indicators with neighborhood prevalence of chronic kidney disease (CKD), diabetes, and hypertension.Design, setting, and participantsThis cross-sectional study used public data (2012-2018) and deidentified electronic health records (2017-2018) to describe the burden of structural racism and the prevalence of CKD, diabetes, and hypertension in 150 residential neighborhoods in Durham County, North Carolina, from US census block groups and quantified their associations using bayesian models accounting for spatial correlations and residents' age. Data were analyzed from January 2021 to May 2023.ExposuresGlobal (neighborhood percentage of White residents, economic-racial segregation, and area deprivation) and discrete (neighborhood child care centers, bus stops, tree cover, reported violent crime, impervious areas, evictions, election participation, income, poverty, education, unemployment, health insurance coverage, and police shootings) indicators of structural racism.Main outcomes and measuresOutcomes of interest were neighborhood prevalence of CKD, diabetes, and hypertension.ResultsA total of 150 neighborhoods with a median (IQR) of 1708 (1109-2489) residents; median (IQR) of 2% (0%-6%) Asian residents, 30% (16%-56%) Black residents, 10% (4%-20%) Hispanic or Latino residents, 0% (0%-1%) Indigenous residents, and 44% (18%-70%) White residents; and median (IQR) residential income of $54 531 ($37 729.25-$78 895.25) were included in analyses. In models evaluating global indicators, greater burden of structural racism was associated with greater prevalence of CKD, diabetes, and hypertension (eg, per 1-SD decrease in neighborhood White population percentage: CKD prevalence ratio [PR], 1.27; 95% highest density interval [HDI], 1.18-1.35; diabetes PR, 1.43; 95% HDI, 1.37-1.52; hypertension PR, 1.19; 95% HDI, 1.14-1.25). Similarly in models evaluating discrete indicators, greater burden of structural racism was associated with greater neighborhood prevalence of CKD, diabetes, and hypertension (eg, per 1-SD increase in reported violent crime: CKD PR, 1.15; 95% HDI, 1.07-1.23; diabetes PR, 1.20; 95% HDI, 1.13-1.28; hypertension PR, 1.08; 95% HDI, 1.02-1.14).Conclusions and relevanceThis cross-sectional study found several global and discrete structural racism indicators associated with increased prevalence of health conditions in residential neighborhoods. Although inferences from this cross-sectional and ecological study warrant caution, they may help guide the development of future community health interventions.

Project description:ImportanceNeighborhood segregation and poverty may be important drivers of health inequities. Epigenomic factors, including DNA methylation clocks that may mark underlying biological aging, have been implicated in the link between social factors and health.ObjectiveTo examine the associations of neighborhood segregation and poverty with 4 DNA methylation clocks trained to capture either chronological age or physiological dysregulation.Design, setting, and participantsThis cohort study uses data from the Multi-Ethnic Study of Atherosclerosis (MESA), a longitudinal study that started in 2000 to 2002, with follow-up in 2002 to 2004, 2004 to 2005, 2005 to 2007, and 2010 to 2012. In 2000 to 2002, adults who identified as White or Black race or Hispanic or Chinese ethnicity in 6 US sites (Baltimore, Maryland; Chicago, Illinois; Forsyth County, North Carolina; Los Angeles County, California; Northern Manhattan, New York; and St. Paul, Minnesota) were sampled for recruitment. A random subsample of 4 sites (Maryland, North Carolina, New York, and Minnesota) were selected for inclusion in the MESA epigenomics ancillary study at examination 5 (2010-2012). Participants who identified as White or Black race or Hispanic ethnicity, were aged 45 to 84 years, and did not have clinical cardiovascular disease were included in this analysis. Data were analyzed from May 2021 to October 2023.ExposureInformation on 2000 census tract poverty and Getis-Ord G statistic segregation of Hispanic residents, non-Hispanic Black residents, or non-Hispanic White residents were linked to participant addresses at examination 1 (2000-2002).Main outcomes and measuresAt examination 5, DNA methylation was measured in purified monocytes. DNA methylation age acceleration was calculated using 4 clocks trained on either chronological age or physiological dysregulation. Linear regressions were used to test associations.ResultsA total of 1102 participants (mean [SD] age, 69.7 [9.4] years; 562 [51%] women) were included, with 348 Hispanic participants, 222 non-Hispanic Black participants, and 533 non-Hispanic White participants. For non-Hispanic Black participants, living in tracts with greater segregation of Black residents was associated with GrimAge DNA methylation age acceleration, a clock designed to capture physiological dysregulation. A 1-SD increase in segregation was associated with 0.42 (95% CI, 0.20-0.64) years age acceleration (P < .001); this association was not observed with other clocks. This association was particularly pronounced for participants living in high poverty tracts (interaction term, 0.24; 95% CI, 0.07-0.42; P = .006). In the overall sample, census tract poverty level was associated with GrimAge DNA methylation age acceleration (β = 0.45; 95% CI, 0.20-0.71; adjusted P = .005).Conclusions and relevanceThese findings suggest that epigenomic mechanisms may play a role in the associations of segregated and poor neighborhoods with chronic conditions.

Dataset Information

Structural Racism and Breast Cancer-specific Survival: Impact of Economic and Racial Residential Segregation.

Objective

Summary background data

Methods

Results

Conclusions

Publications

Structural Racism and Breast Cancer-specific Survival: Impact of Economic and Racial Residential Segregation.

Similar Datasets

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