title: [Patterns of variation in the infant mortality rate in Rio Grande do Sul State, Brazil: comparison of empirical Bayesian and fully Bayesian approaches].
abstract: Infant mortality is considered a sensitive health indicator, and knowledge of its geographical profile is essential for formulating appropriate public health policies. Disease mapping aims to describe the geographical distribution of disease incidence and mortality rates. Due to the heavy instability of crude rates in small areas, methods involving Bayesian smoothing of rates are used, drawing on information for the whole area or neighborhood to estimate the event rate. The current study compares empirical Bayesian (EB) and fully Bayesian (FB) methods for infant mortality rates (accumulated data from 2001 to 2004) in Rio Grande do Sul State, Brazil. This study highlights the advantages of Bayesian estimators for viewing and interpreting maps. For the problem at hand, EB and FB methods showed quite similar results and had the great advantage of easy use by health professionals, since they evenly highlight the main spatial patterns in the mortality rate in the State during the target period.
authors.affiliation: Programa de Pós-graduação em Epidemiologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil. sassalelenash@yahoo.com.br
authors.forename: Sabrina Letícia Couto da
authors.initials: SL
authors.lastname: Silva
authors.forename: Jandyra Maria Guimarães
authors.initials: JM
authors.lastname: Fachel
authors.forename: Sergio Kakuta
authors.initials: SK
authors.lastname: Kato
authors.forename: Sergio Luiz
authors.initials: SL
authors.lastname: Bassanesi
mesh_terms: D001499:Bayes Theorem; D001938:Brazil / Q000453:epidemiology; D004812:Epidemiologic Methods; D006801:Humans; D007226:Infant Mortality / Q000639:trends*; D007231:Infant, Newborn