Evaluating Methods for Mapping Historical Redlining to Census Tracts for Health Equity Research.

Geospatial methods Health equity Population health Redlining

Journal

Journal of urban health : bulletin of the New York Academy of Medicine
ISSN: 1468-2869
Titre abrégé: J Urban Health
Pays: United States
ID NLM: 9809909

Informations de publication

Date de publication:
22 Mar 2024
Historique:
medline: 23 3 2024
pubmed: 23 3 2024
entrez: 23 3 2024
Statut: aheadofprint

Résumé

Neighborhood characteristics including housing status can profoundly influence health. Recently, increasing attention has been paid to present-day impacts of "redlining," or historic area classifications that indicated less desirable (redlined) areas subject to decreased investment. Scholarship of redlining and health is emerging; limited guidance exists regarding optimal approaches to measuring historic redlining in studies of present-day health outcomes. We evaluated how different redlining approaches (map alignment methods) influence associations between redlining and health outcomes. We first identified 11 existing redlining map alignment methods and their 37 logical extensions, then merged these 48 map alignment methods with census tract life expectancy data to construct 9696 linear models of each method and life expectancy for all 202 redlined cities. We evaluated each model's statistical significance and R

Identifiants

pubmed: 38519804
doi: 10.1007/s11524-024-00841-3
pii: 10.1007/s11524-024-00841-3
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : The MITRE Corporation
ID : MITRE Innovation Program

Informations de copyright

© 2024. The New York Academy of Medicine.

Références

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Auteurs

Hannah De Los Santos (H)

The MITRE Corporation, McLean, VA, USA. hdelossantos@mitre.org.

Carla P Bezold (CP)

The MITRE Corporation, McLean, VA, USA.

Karen M Jiang (KM)

The MITRE Corporation, McLean, VA, USA.

Jarvis T Chen (JT)

Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Cassandra A Okechukwu (CA)

The MITRE Corporation, McLean, VA, USA.
Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Classifications MeSH