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Analysis of the spatial distribution of amyotrophic lateral sclerosis in Virginia.

Authors :
Boyle J
Wheeler DC
Naum R
Burke Brockenbrough P
Gebhardt M
Smith L
Harrell T
Stewart D
Gwathmey K
Source :
Amyotrophic lateral sclerosis & frontotemporal degeneration [Amyotroph Lateral Scler Frontotemporal Degener] 2023 Jul 14, pp. 1-9. Date of Electronic Publication: 2023 Jul 14.
Publication Year :
2023
Publisher :
Ahead of Print

Abstract

Objective : Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that is usually fatal. Environmental exposures have been posited in the etiology of ALS, but few studies have modeled the spatial risk of ALS over large geographic areas. In this paper, our goal was to analyze the spatial distribution of ALS in Virginia and identify any areas with significantly elevated risk using Virginia ALS Association administrative data. Methods : We used Bayesian hierarchical spatial regression models to estimate the relative risk for ALS in Virginia census tracts, adjusting for several covariates posited to be associated with the disease. We used an intrinsic conditional autoregressive prior to allow for spatial correlation in the risk estimates and stabilize estimates over space. Results : Considerable variation in ALS risk existed across Virginia, with greater relative risk found in the central and western parts of the state. We identified significantly elevated relative risk in a number of census tracts. In particular, Henrico, Albemarle, and Botetourt counties all contained at least four census tracts with significantly elevated risk. Conclusions : We identified several areas with significantly elevated ALS risk across Virginia census tracts. These results can inform future studies of potential environmental triggers for the disease, whose etiology is still being understood.

Details

Language :
English
ISSN :
2167-9223
Database :
MEDLINE
Journal :
Amyotrophic lateral sclerosis & frontotemporal degeneration
Publication Type :
Academic Journal
Accession number :
37452450
Full Text :
https://doi.org/10.1080/21678421.2023.2236653