A practitioner's guide to geospatial analysis in a neuroimaging context.

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.
Competing Interests: J.K.W., G.M.B., K.P., P.M., E.S., S.S., A.H.B., S.F., S.K., and B.M.A. report no disclosures. B.A.G. receives research support from Eli Lilly and Avid Radiopharmaceuticals. Neither J.C.M. nor his family own stock or has equity interest (outside of mutual funds or other externally directed accounts) in any pharmaceutical or biotechnology company. All participants (ages 23–89) completed written informed consent. This study was approved by the WUSTL Institutional Review Board. Author disclosures are available in the supporting information.
(© 2023 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.)