Evidence map›Paper›PMID 40233138›Full record

ArticleCancer2025

Contemporary neighborhood redlining and racial mortgage lending bias and disparities in prostate cancer survival.

Wayne R Lawrence, Neal D Freedman, Jennifer K McGee-Avila, Hyokyoung G Hong, Scarlett L Gomez, Andrew P Loehrer, Kirsten M M Beyer, Yuhong Zhou, Jared W Magnani, Harold W Neighbors and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Wayne R LawrenceDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.ORCID https://orcid.org/0000-0002-2992-5897
Neal D FreedmanDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Jennifer K McGee-AvilaDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Hyokyoung G HongDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
Scarlett L GomezDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA.ORCID https://orcid.org/0000-0002-5143-4867
Andrew P LoehrerGeisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA.ORCID https://orcid.org/0000-0001-7747-224X
Kirsten M M BeyerInstitute for Health & Equity, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.ORCID https://orcid.org/0000-0002-7513-8528
Yuhong ZhouInstitute for Health & Equity, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Jared W MagnaniDepartment of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Harold W NeighborsHealth Behavior and Health Equity, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA.
Jarrett A JohnsonDivision of Community Health and Population Science, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland, USA.
Ziqiang LinDepartment of Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China.ORCID https://orcid.org/0000-0003-1990-6788
Amy J DavidoffDivision of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.ORCID https://orcid.org/0000-0001-8141-9249
Adana A M LlanosDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.ORCID https://orcid.org/0000-0001-9954-9121
Meredith S ShielsDivision of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.ORCID https://orcid.org/0000-0001-8390-6091

Funding

Geospatial drivers of cancer care disparities and their susceptibility to health policy changesK08CA263546 · NCI · DARTMOUTH-HITCHCOCK CLINIC · PI Andrew Phillip Loehrer · 2022 to 2026
$869k
Patient-oriented research mentoring in access and adherence to anticoagulation for atrial fibrillationK24HL160527 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Jared W. Magnani · 2022 to 2026
$602k
Intramural NIH HHS Z99 CA999999NCI NIH HHS HHSN261201800009CNCI NIH HHS HHSN261201800009INCI NIH HHS HHSN261201800015CNCI NIH HHS HHSN261201800015INCI NIH HHS HHSN261201800032CNCI NIH HHS HHSN261201800032INCI NIH HHS K08 CA263546NCI NIH HHS K08CA263546NCI NIH HHS Y99 CA999999NHLBI NIH HHS K24 HL160527NHLBI NIH HHS K24HL160527NIH HHS Z99 CA999999
6 · The paper itself

Abstract

backgroundMortgage lending bias is a critical driver of residential segregation, and may contribute to disparities in cancer survival. This study investigated the association between contemporary redlining and racial lending bias and prostate cancer survival.

methodsThis cohort study used a Surveillance, Epidemiology, and End Results-Medicare database that included 34,163 Black and White men diagnosed with prostate cancer between 2010 and 2013. Home Mortgage Disclosure Act data were used to calculate the census-tract redlining index (the systematic denial of mortgages based on property location) and racial lending bias index (the systematic denial of a mortgage application for a Black applicant compared with a White applicant in the local area). Both indices were assessed continuously and categorically (low, moderate, or high). Multivariable-adjusted Cox models were used to estimate hazard ratios (HRs) for prostate cancer-specific and all-cause mortality.

resultsOverall, as the redlining index increased, men experienced poorer prostate cancer survival. Compared to men residing in low-redlined neighborhoods, those in high-redlined neighborhoods had an increased risk of prostate cancer-specific mortality (HR, 1.21; 95% confidence interval [CI], 1.03-1.42) and all-cause mortality (HR, 1.25; 95% CI, 1.17-1.34). Similar results were observed for redlining in a race-stratified analysis among Black and White men. Among White men, compared with those residing in low racial lending bias neighborhoods, those in high racial lending bias neighborhoods had an increased all-cause mortality risk (HR, 1.11; 95% CI, 1.03-1.21).

conclusionsContemporary redlining was associated with poorer prostate cancer survival in the overall population. However, an association between racial lending bias and elevated mortality was only observed among White men. Findings suggest that mortgage lending discrimination may contribute to disparities in prostate cancer survival.

Indexed as

Health Status DisparitiesNeighborhood CharacteristicsProstatic NeoplasmsRacismAgedAged, 80 and overBlack or African AmericanHumansMaleMedicareSEER ProgramUnited StatesWhitecancer survivorshipeconomic disparities in healthhealth inequitiesinstitutional racismresidential segregationsocial determinants of healthstructural racism

Identifiers

PMID40233138
PMCPMC12001745

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.