Analysis of the spatial distribution of amyotrophic lateral sclerosis in Virginia

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.

Keywords:

• ALS
• spatial cluster
• spatial analysis
• Bayesian

Acknowledgement

The authors would like to acknowledge the ALS Association for assistance with the dataset that was analysed in this study.

Author contributions

Joseph Boyle- data analysis, manuscript preparation; David C. Wheeler- contributed to the concept and design of the study, data analysis, manuscript preparation; Ryan Naum- contributed to the concept and design of the study; Paula Brockenbrough- contributed to the concept and design of the study; Michelle Gebhardt- contributed to the concept and design of the study; LaVon Smith- contributed to the concept and design of the study; Tremetris Harrell- contributed to data acquisition; Danielle Stewart- contributed to data acquisition; Kelly Gwathmey- contributed to the concept and design of the study, manuscript preparation

Declaration of interest Statement

The authors have no conflicts of interest to declare.

Statement of ethics

This study protocol was reviewed and approved by the Virginia Commonwealth University Office of Research and Innovation Institutional Review Board. The approval ID number is HM20022720. Patient initially consented to provide their data to the ALS Association. For the purposes of this study, waiver of consent was granted as the data was de-identified apart from location at time of diagnosis.

Data availability Statement

Per VCU IRB Data Confidentiality and Storage policy, as this study required a Data Management Plan, the data at the conclusion of the study was destroyed. The original ALS Association Administrative data must be requested directly from the ALS Association.

Additional information

Funding

There was no extramural or internal funding for this study apart from Harper’s Hope Fund for ALS which is a nonprofit VCU fund that support ALS research.