title: Spatial analysis of Tuberculosis in Rio de Janeiro in the period from 2005 to 2008 and associated socioeconomic factors using micro data and global spatial regression models.
abstract: The present study analyses the spatial pattern of tuberculosis (TB) from 2005 to 2008 by identifying relevant socioeconomic variables for the occurrence of the disease through spatial statistical models. This ecological study was performed in Rio de Janeiro using new cases. The census sector was used as the unit of analysis. Incidence rates were calculated, and the Local Empirical Bayesian method was used. The spatial autocorrelation was verified with Moran's Index and local indicators of spatial association (LISA). Using Spearman's test, variables with significant correlation at 5% were used in the models. In the classic multivariate regression model, the variables that fitted better to the model were proportion of head of family with an income between 1 and 2 minimum wages, proportion of illiterate people, proportion of households with people living alone and mean income of the head of family. These variables were inserted in the Spatial Lag and Spatial Error models, and the results were compared. The former exhibited the best parameters: R2 = 0.3215, Log-Likelihood = -9228, Akaike Information Criterion (AIC) = 18,468 and Schwarz Bayesian Criterion (SBC) = 18,512. The statistical methods were effective in the identification of spatial patterns and in the definition of determinants of the disease providing a view of the heterogeneity in space, allowing actions aimed more at specific populations.
authors.affiliation: Instituto de Comunicação e Informação Científica e Tecnologia em Saúde, Fiocruz. Av. Brasil 4365, Manguinhos. 21040-360 Rio de Janeiro RJ Brasil. monica.avelar.magalhaes@gmail.com.
authors.forename: Monica de Avelar Figueiredo Mafra
authors.initials: MA
authors.lastname: Magalhães
authors.affiliation: Instituto de Estudos em Saúde Coletiva, UFRJ. Rio de Janeiro RJ Brasil.
authors.forename: Roberto de Andrade
authors.initials: RA
authors.lastname: Medronho
mesh_terms: D001499:Bayes Theorem; D001938:Brazil / Q000453:epidemiology; D006801:Humans; D015233:Models, Statistical; D012044:Regression Analysis; D012307:Risk Factors; D012959:Socioeconomic Factors; D062206:Spatial Analysis; D000068916:Spatial Regression; D018709:Statistics, Nonparametric; D014376:Tuberculosis / Q000453:epidemiology*