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1.
J Race Ethn City ; 3(1): 70-94, 2022.
Article in English | MEDLINE | ID: mdl-35992214

ABSTRACT

Housing discrimination and racial segregation have a long history in the United States. The 1930's Home Owners' Loan Corporation (HOLC) "residential security maps," recently digitized, have become a popular visualization of Depression era mortgage lending risk patterns across American cities. Numerous housing policies have since been instituted, including the Home Mortgage Disclosure Act (HMDA), but mortgage lending bias persists. The degree to which detailed spatial patterns of bias have persisted or changed along with urban change is not well understood. We compare historic HOLC grades and contemporary levels of mortgage lending bias using spatially detailed HMDA data. We further examine the relationship between HOLC risk grades and contemporary racial and ethnic settlement patterns. Results suggest that historical mortgage lending risk categorizations and settlement patterns are associated with contemporary mortgage lending bias and racial and ethnic settlement patterns. Concerted and deliberate efforts will be needed to change these patterns.

2.
J Glob Health ; 12: 04032, 2022.
Article in English | MEDLINE | ID: mdl-35493778

ABSTRACT

Background: The global burden of cervical cancer is concentrated in low-and middle-income countries (LMICs), with the greatest burden in Africa. Targeting limited resources to populations with the greatest need to maximize impact is essential. The objectives of this study were to geocode cervical cancer data from a population-based cancer registry in Kampala, Uganda, to create high-resolution disease maps for cervical cancer prevention and control planning, and to share lessons learned to optimize efforts in other low-resource settings. Methods: Kampala Cancer Registry records for cervical cancer diagnoses between 2008 and 2015 were updated to include geographies of residence at diagnosis. Population data by age and sex for 2014 was obtained from the Uganda Bureau of Statistics. Indirectly age-standardized incidence ratios were calculated for sub-counties and estimated continuously across the study area using parish level data. Results: Overall, among 1873 records, 89.6% included a valid sub-county and 89.2% included a valid parish name. Maps revealed specific areas of high cervical cancer incidence in the region, with significant variation within sub-counties, highlighting the importance of high-resolution spatial detail. Conclusions: Population-based cancer registry data and geospatial mapping can be used in low-resource settings to support cancer prevention and control efforts, and to create the potential for research examining geographic factors that influence cancer outcomes. It is essential to support LMIC cancer registries to maximize the benefits from the use of limited cancer control resources.


Subject(s)
Uterine Cervical Neoplasms , Female , Humans , Incidence , Poverty , Spatial Analysis , Uganda/epidemiology , Uterine Cervical Neoplasms/epidemiology , Uterine Cervical Neoplasms/prevention & control
3.
J Clin Oncol ; 39(25): 2749-2757, 2021 09 01.
Article in English | MEDLINE | ID: mdl-34129388

ABSTRACT

PURPOSE: The objective was to examine the relationship between contemporary redlining (mortgage lending bias on the basis of property location) and survival among older women with breast cancer in the United States. METHODS: A redlining index using Home Mortgage Disclosure Act data (2007-2013) was linked by census tract with a SEER-Medicare cohort of 27,516 women age 66-90 years with an initial diagnosis of stage I-IV breast cancer in 2007-2009 and follow-up through 2015. Cox proportional hazards models were used to examine the relationship between redlining and both all-cause and breast cancer-specific mortality, accounting for covariates. RESULTS: Overall, 34% of non-Hispanic White, 57% of Hispanic, and 79% of non-Hispanic Black individuals lived in redlined tracts. As the redlining index increased, women experienced poorer survival. This effect was strongest for women with no comorbid conditions, who comprised 54% of the sample. For redlining index values of 1 (low), 2 (moderate), and 3 (high), as compared with 0.5 (least), hazard ratios (HRs) (and 95% CIs) for all-cause mortality were HR = 1.10 (1.06 to 1.14), HR = 1.27 (1.17 to 1.38), and HR = 1.39 (1.25 to 1.55), respectively, among women with no comorbidities. A similar pattern was found for breast cancer-specific mortality. CONCLUSION: Contemporary redlining is associated with poorer breast cancer survival. The impact of this bias is emphasized by the pronounced effect even among women with health insurance (Medicare) and no comorbid conditions. The magnitude of this neighborhood level effect demands an increased focus on upstream determinants of health to support comprehensive patient care. The housing sector actively reveals structural racism and economic disinvestment and is an actionable policy target to mitigate adverse upstream health determinants for the benefit of patients with cancer.


Subject(s)
Breast Neoplasms/mortality , Ethnicity/statistics & numerical data , Health Status Disparities , Housing/statistics & numerical data , Racism/statistics & numerical data , Aged , Aged, 80 and over , Breast Neoplasms/economics , Breast Neoplasms/epidemiology , Cohort Studies , Comorbidity , Female , Follow-Up Studies , Humans , Medicare , Prognosis , Residence Characteristics , Survival Rate , United States/epidemiology
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