Open Access
December 2017 Multivariate spatiotemporal modeling of age-specific stroke mortality
Harrison Quick, Lance A. Waller, Michele Casper
Ann. Appl. Stat. 11(4): 2165-2177 (December 2017). DOI: 10.1214/17-AOAS1068

Abstract

Geographic patterns in stroke mortality have been studied as far back as the 1960s when a region of the southeastern United States became known as the “stroke belt” due to its unusually high rates. While stroke mortality rates are known to increase exponentially with age, an investigation of spatiotemporal trends by age group at the county level is daunting due to the preponderance of small population sizes and/or few stroke events by age group. In this paper, we implement a multivariate space–time conditional autoregressive model to investigate age-specific trends in county-level stroke mortality rates from 1973 to 2013. In addition to reinforcing existing claims in the literature, this work reveals that geographic disparities in the reduction of stroke mortality rates vary by age. More importantly, this work indicates that the geographic disparity between the “stroke belt” and the rest of the nation is not only persisting, but may in fact be worsening.

Citation

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Harrison Quick. Lance A. Waller. Michele Casper. "Multivariate spatiotemporal modeling of age-specific stroke mortality." Ann. Appl. Stat. 11 (4) 2165 - 2177, December 2017. https://doi.org/10.1214/17-AOAS1068

Information

Received: 1 August 2016; Revised: 1 June 2017; Published: December 2017
First available in Project Euclid: 28 December 2017

zbMATH: 1383.62285
MathSciNet: MR3743292
Digital Object Identifier: 10.1214/17-AOAS1068

Keywords: Age disparities in health , Bayesian methods , geographic disparities in health , nonseparable models , small area analysis

Rights: Copyright © 2017 Institute of Mathematical Statistics

Vol.11 • No. 4 • December 2017
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