A practitioner's guide to geospatial analysis in a neuroimaging context
Document Type
Journal Article
Publication Date
1-1-2023
Journal
Alzheimer's & dementia (Amsterdam, Netherlands)
Volume
15
Issue
1
DOI
10.1002/dad2.12413
Keywords
brain imaging; epidemiologic methods; magnetic resonance imaging
Abstract
INTRODUCTION: Health disparities arise from biological-environmental interactions. Neuroimaging cohorts are reaching sufficiently large sample sizes such that analyses could evaluate how the environment affects the brain. We present a practical guide for applying geospatial methods to a neuroimaging cohort. METHODS: We estimated brain age gap (BAG) from structural magnetic resonance imaging (MRI) from 239 city-dwelling participants in St. Louis, Missouri. We compared these participants to population-level estimates from the American Community Survey (ACS). We used geospatial analysis to identify neighborhoods associated with patterns of altered brain structure. We also evaluated the relationship between Area Deprivation Index (ADI) and BAG. RESULTS: We identify areas in St. Louis, Missouri that were significantly associated with higher BAG from a spatially representative cohort. We provide replication code. CONCLUSION: We observe a relationship between neighborhoods and brain health, which suggests that neighborhood-based interventions could be appropriate. We encourage other studies to geocode participant information to evaluate biological-environmental interaction.
APA Citation
Wisch, Julie K.; Babulal, Ganesh M.; Petersen, Kalen; Millar, Peter R.; Shacham, Enbal; Scroggins, Stephen; Boerwinkle, Anna H.; Flores, Shaney; Keefe, Sarah; Gordon, Brian A.; Morris, John C.; and Ances, Beau M., "A practitioner's guide to geospatial analysis in a neuroimaging context" (2023). GW Authored Works. Paper 2576.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/2576
Department
Clinical Research and Leadership