Purpose: Studies have found a variety of evidence regarding the association between residential segregation measures and health outcomes in the United States. Some have focused on any individuals living in residentially segregated places, whereas others have examined whether persons of specific races or ethnicities living in places with high segregation of their own race or ethnicity have differential outcomes. This article compares and contrasts these two approaches in the study of predictors of late-stage colorectal cancer (CRC) diagnoses in a cross-national study. We argue that it is very important when interpreting results from studies like this to carefully consider the geographic scope of the analysis, which can significantly change the context and meaning of the results.
Methods: We use US Cancer Statistics Registry data from 40 states to identify late-stage diagnoses among over 500,000 CRC cases diagnosed during 2004-2009. We pool data over the states and estimate a multilevel model with person, county, and state levels and a random intercepts specification to ensure robust effect estimates. The isolation index of residential segregation is defined for racial and ethnic groups at the county level using Census 2000 data. The association between isolation indices and late-stage CRC diagnosis was measured by (1) anyone living in minority-segregated areas (place-centered approach) and by (2) individuals living in areas segregated by one's own racial or ethnic peers (person-centered approach).
Results: Findings from the place-centered approach suggest that living in a highly segregated African American community is associated with lower likelihood of late-stage CRC diagnosis, whereas the opposite is true for people living in highly segregated Asian communities, and living in highly segregated Hispanic communities has no significant association. Using the person-centered approach, we find that living in places segregated by one's racial or ethnic peers is associated with lower likelihood of late-stage CRC diagnosis.
Conclusions: In a model that covers a large geographic area across the nation, the place-centered approach is most likely picking up geographic disparities that may be deepened by targeted interventions in minority communities. By contrast, the person-centered approach provides a national average estimate suggesting that residential isolation may confer community cohesion or support that is associated with better CRC prevention.
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http://dx.doi.org/10.1016/j.annepidem.2016.11.008 | DOI Listing |
J Urban Health
January 2025
Instituto de Medicina Social, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil.
Neighborhoods or residential environments have physical and social attributes which may contribute to inequalities in the overweight and obesity pandemic. We examined the longitudinal associations of baseline neighborhood-level income and racial residential segregation (using the Gi* statistic: low, medium, high) with changes in body mass index (BMI in kg/m), using geocoded data from 1821 civil servants in the municipality of Rio de Janeiro, Brazil, followed-up for approximately 13 years (baseline wave 1: 1999, wave 2: 2001-2002, wave 3: 2006-2007, wave 4: 2012-2013). Linear mixed effects models using BMI measured in all four study waves were performed, accounting for gender, race, length of residence, education and time-dependent age, and per capita family income.
View Article and Find Full Text PDFCancer Causes Control
January 2025
Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, State University of New York at Buffalo, 265 Farber Hall, Buffalo, NY, 14214, USA.
Purpose: Historical redlining, a 1930s-era form of residential segregation and proxy of structural racism, has been associated with breast cancer risk, stage, and survival, but research is lacking on how known present-day breast cancer risk factors are related to historical redlining. We aimed to describe the clustering of present-day neighborhood-level breast cancer risk factors with historical redlining and evaluate geographic patterning across the US.
Methods: This ecologic study included US neighborhoods (census tracts) with Home Owners' Loan Corporation (HOLC) grades, defined as having a score in the Historic Redlining Score dataset; 2019 Population Level Analysis and Community EStimates (PLACES) data; and 2014-2016 Environmental Justice Index (EJI) data.
Am J Prev Med
December 2024
Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX; Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX.
Introduction: To examine the associations of neighborhood socioeconomic status (nSES), ethnic enclaves, residential Black segregation with screening for breast, cervical and colorectal (CRC) cancers across the state of Texas (TX).
Methods: Using an ecologic study design, spatial clustering of low breast, cervical and CRC screening rates were identified across TX census tracts using local Moran's I statistics. Binomial spatial probit regression was used to estimate the associations between nSES, Hispanic/Latino and Asian American (AA) ethnic enclave neighborhoods and residential Black segregation with geospatial clusters of low screening, adjusting for behavioral characteristics.
Open Forum Infect Dis
January 2025
Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.
Disparities in coronavirus disease 2019 mortality are driven by inequalities in group-specific incidence rates (IRs), case fatality rates (CFRs), and their interaction. For emerging infections, such as severe acute respiratory syndrome coronavirus 2, group-specific IRs and CFRs change on different time scales, and inequities in these measures may reflect different social and medical mechanisms. To be useful tools for public health surveillance and policy, analyses of changing mortality rate disparities must independently address changes in IRs and CFRs.
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