10.6084/m9.figshare.5670358.v1 Alessandra Gonçalves Lisbôa Pereira Alessandra Gonçalves Lisbôa Pereira Roberto de Andrade Medronho Roberto de Andrade Medronho Claudia Caminha Escosteguy Claudia Caminha Escosteguy Luis Iván Ortiz Valencia Luis Iván Ortiz Valencia Mônica de Avelar Figueiredo Mafra Magalhães Mônica de Avelar Figueiredo Mafra Magalhães Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil SciELO journals 2017 Tuberculosis, epidemiology Spatial Analysis Risk Factors Socioeconomic Factors Linear Models 2017-12-05 14:50:40 Dataset https://scielo.figshare.com/articles/dataset/Spatial_distribution_and_socioeconomic_context_of_tuberculosis_in_Rio_de_Janeiro_Brazil/5670358 <div><p>OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.</p></div>