utilização da modelagem inteiramente bayesiana na detecção de padrões de variação de risco relativo de mortalidade infantil no rio grande do sul, brasil utilization of fully bayesian modeling to detect patterns in relative risk variation for infant mortality in rio grande do sul state, brazil

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ID: 136525
2009
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Abstract
Neste artigo são analisados os fatores possivelmente associados à mortalidade infantil nos 496 municípios do Rio Grande do Sul, Brasil, com base em dados acumuladas entre os anos de 2001 a 2004, obtidos pela análise de regressão utilizando modelagem inteiramente bayesiana como alternativa para superar a autocorrelação espacial e a instabilidade dos estimadores clássicos, como a taxa bruta e a SMR (Standardised Mortality Ratio). Foram comparadas diferentes especificações de componente espacial e covariáveis, provenientes dos blocos do Índice de Desenvolvimento Sócio-econômico da Fundação de Economia e Estatística (IDESE/FEE-2003). Verificou-se que o modelo que utiliza a estrutura espacial além da covariável educação apresenta melhor desempenho, quando comparado pelo critério DIC (Deviance Information Criterion). Comparando as estimativas das SMR com os riscos relativos obtidos pela modelagem inteiramente bayesiana, foi possível observar um ganho substancial na interpretação e na detecção de padrões de variação do risco de mortalidade infantil nos municípios do Rio Grande do Sul ao utilizar essa modelagem. A região da Serra Gaúcha destacou-se com baixo risco relativo e estimativas muito homogêneas.
The infant mortality rate is one of the key indicators used to measure a population's quality of life. The State of Rio Grande do Sul has a social and economic indicator called the Socioeconomic Development Index (IDESE). Most studies analyze the infant mortality rate in relation to risk factors, visually aided by maps. This study presents the methodology and an application of a Spatial Epidemiology method called the ecological correlation, using hierarchical Bayesian procedures. The article discusses the main problems found in ecological correlations, such as spatial autocorrelation and the estimator's instability for small areas. To overcome these difficulties, the relative risk estimate obtained by spatial regression analysis using fully Bayesian estimation is presented. The infant mortality rate is analyzed in all 496 municipalities of Rio Grande do Sul for the years 2001 to 2004. Several models with spatial component and different variables from the IDESE/2003 were compared. The model using spatial structure along with the variable "education" was considered the best choice. With this methodology, it was possible to obtain a more interpretable pattern of infant mortality risk in Rio Grande do Sul.
Reference Key
kato2009cadernosutilizao Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Sérgio Kakuta Kato;Diego de Matos Vieira;Jandyra Maria Guimarães Fachel
Journal iberian conference on information systems and technologies, cisti
Year 2009
DOI
10.1590/S0102-311X2009000700008
URL
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-311X2009000700008
Keywords
Statistical Analysis infant mortality

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