Connecting past to present: Examining different approaches to linking historical redlining to present day health inequities

In the 1930's, the Home Owner Loan Corporation (HOLC) drafted maps to quantify variation in real estate credit risk across US city neighborhoods. The letter grades and associated risk ratings assigned to neighborhoods discriminated against those with black, lower class, or immigrant residents a...

Full description

Saved in:
Bibliographic Details
Published in:PloS one 2022-05, Vol.17 (5), p.e0267606-e0267606
Main Authors: Noelke, Clemens, Outrich, Michael, Baek, Mikyung, Reece, Jason, Osypuk, Theresa L, McArdle, Nancy, Ressler, Robert W, Acevedo-Garcia, Dolores
Format: Article
Language:English
Subjects:
Biology and Life Sciences
Boundaries
Censuses
Classification
Diabetes
Discrimination in credit cards
Earth Sciences
Evaluation
Health risks
Home ownership
Machine learning
Management
Medicine and Health Sciences
Neighborhoods
Prevention
Racism
Ratings & rankings
Real estate
Research and Analysis Methods
Risk assessment
Segregation
Social Sciences
Validity
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In the 1930's, the Home Owner Loan Corporation (HOLC) drafted maps to quantify variation in real estate credit risk across US city neighborhoods. The letter grades and associated risk ratings assigned to neighborhoods discriminated against those with black, lower class, or immigrant residents and benefitted affluent white neighborhoods. An emerging literature has begun linking current individual and community health effects to government redlining, but each study faces the same measurement problem: HOLC graded area boundaries and neighborhood boundaries in present-day health datasets do not match. Previous studies have taken different approaches to classify present day neighborhoods (census tracts) in terms of historical HOLC grades. This study reviews these approaches, examines empirically how different classifications fare in terms of predictive validity, and derives a predictively optimal present-day neighborhood redlining classification for neighborhood and health research.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0267606