DOI
https://doi.org/10.25772/0WSZ-7B67
Author ORCID Identifier
https://orcid.org/0000-0002-1411-5584
Defense Date
2023
Document Type
Dissertation
Degree Name
Doctor of Philosophy
Department
Biostatistics
First Advisor
David C. Wheeler
Abstract
Many health outcomes result from accumulated exposures to one or more environmental factors. Accordingly, spatial risk studies have begun to consider multiple residential locations of participants, acknowledging that participants move and thus are exposed to environmental factors in several places. However, novel methods are needed to estimate cumulative spatial risk for disease while accounting for other risk factors. To this end, we propose a Bayesian model (LRK-MMM) that embeds a multiple membership model (MMM) into a low-rank kriging (LRK) model in order to estimate cumulative spatial risk at the point level while allowing for multiple residential locations per subject. The LRK approach offers a more computationally efficient means to analyze spatial risk at the point level compared with a Bayesian generalized additive model and enables increased precision in spatial risk estimates by analyzing point locations instead of administrative areas. Through a simulation study, we demonstrate the efficacy of the model and its improvement upon an existing multiple membership model that uses area-level spatial random effects to estimate risk. The results show that our proposed method provides greater spatial sensitivity and power to detect regions of elevated risk for disease across a range of exposure scenarios. We apply our model to case-control data to estimate cumulative spatial risk over time while adjusting for covariates. We then extend this model to simultaneously estimate chemical mixture effects and propose a different Bayesian model to estimate spatially-varying mixture effects, applying these models to a different case-control study. Taken together, the methods we develop here provide new tools to evaluate how unmeasured spatial risk and measured mixture effects vary over space, which can drive public health interventions and motivate follow-up investigations.
Rights
© The Author
Is Part Of
VCU University Archives
Is Part Of
VCU Theses and Dissertations
Date of Submission
5-8-2023