title: Statistical analysis aiming at predicting respiratory tract disease hospital admissions from environmental variables in the city of São Paulo.
abstract: This study is aimed at creating a stochastic model, named Brazilian Climate and Health Model (BCHM), through Poisson regression, in order to predict the occurrence of hospital respiratory admissions (for children under thirteen years of age) as a function of air pollutants, meteorological variables, and thermal comfort indices (effective temperatures, ET). The data used in this study were obtained from the city of São Paulo, Brazil, between 1997 and 2000. The respiratory tract diseases were divided into three categories: URI (Upper Respiratory tract diseases), LRI (Lower Respiratory tract diseases), and IP (Influenza and Pneumonia). The overall results of URI, LRI, and IP show clear correlation with SO₂ and CO, PM₁₀ and O₃, and PM₁₀, respectively, and the ETw4 (Effective Temperature) for all the three disease groups. It is extremely important to warn the government of the most populated city in Brazil about the outcome of this study, providing it with valuable information in order to help it better manage its resources on behalf of the whole population of the city of Sao Paulo, especially those with low incomes.
authors: Department of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences, University of São Paulo, Rua do Matão, Cidade Universitária, São Paulo, SP, Brazil. coelhomicheline@gmail.com
authors: Micheline
authors: M
authors: de Sousa Zanotti Stagliorio Coêlho
authors: Fabio
authors: F
authors: Luiz Teixeira Gonçalves
authors: Maria
authors: M
authors: do Rosário Dias de Oliveira Latorre
mesh_terms: D000393:Air Pollutants / Q000009:adverse effects* / Q000032:analysis; D001938:Brazil; D002648:Child; D002675:Child, Preschool; D006801:Humans; D007223:Infant; D008685:Meteorological Concepts; D008954:Models, Biological; D010343:Patient Admission / Q000706:statistics & numerical data*; D016012:Poisson Distribution; D012140:Respiratory Tract Diseases / Q000209:etiology*; D012306:Risk; D013269:Stochastic Processes; D013696:Temperature
chemical_list: D000393:Air Pollutants