INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.
INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.
Authors: Sheylla Nadjane Batista Lacerda; Rayrla Cristina de Abreu Temoteo; Tânia Maria Ribeiro Monteiro de Figueiredo; Fernanda Darliane Tavares de Luna; Milena Alves Nunes de Sousa; Luiz Carlos de Abreu; Fernando Luiz Affonso Fonseca Journal: Int Arch Med Date: 2014-07-12
Authors: Mirna de Abreu E Silva; Cláudia Di Lorenzo Oliveira; Rafael Gonçalves Teixeira Neto; Paulo Augusto Camargos Journal: BMC Public Health Date: 2016-09-01 Impact factor: 3.295
Authors: Guy Harling; Antonio S Lima Neto; Geziel S Sousa; Marcia M T Machado; Marcia C Castro Journal: BMC Public Health Date: 2017-05-25 Impact factor: 3.295
Authors: Teresa Gomes; Solange Alves Vinhas; Bárbara Reis-Santos; Moisés Palaci; Renata Lyrio Peres; Paola P Aguiar; Fabiola Karla Correa Ribeiro; Hebert Silva Marques; Valdério do Valle Dettoni; John L Johnson; Lee W Riley; Ethel Leonor Maciel Journal: PLoS One Date: 2013-10-02 Impact factor: 3.240