Alcohol abuse disorder prevalence and its distribution across Portugal. A disease mapping approach

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1 Citation (Scopus)

Abstract

Disease mapping is linked to two other scientific areas: small area estimation and ecological-spatial regression. This paper reviews similarities and differences among them. Bayesian hierarchical models are typically used in this context, using a combination of covariate data and a set of spatial random effects to represent the risk surface. The random effects are typically modeled by a conditional autoregressive prior distribution, and a number of alternative specifications have been proposed in the literature. The four models assessed here are applied to a study on alcohol abuse in Portugal, using data collected by the World Mental Health Survey Initiative.

Original languageEnglish
Pages (from-to)79-101
Number of pages23
JournalRevstat Statistical Journal
Volume13
Issue number1
Publication statusPublished - Mar 2015

Keywords

  • Alcohol abuse
  • Bayesian hierarchical models
  • Disease mapping
  • Generalized linear models
  • Small area estimation

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