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Statistical Analysis Aiming at Predicting Respiratory Tract Disease Hospital Admissions from Environmental Variables in the City of Sao Paulo

de Sousa Zanotti Stagliorio Coelho, Micheline ; Luiz Teixeira Goncalves, Fabio ; do Rosario Dias de Oliveira Latorre, Maria Carpenter, David O.

Journal of Environmental and Public Health, 2010, Vol.2010, p.209270-11 [Periódico revisado por pares]

United States: Hindawi Limiteds

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Título:
Statistical Analysis Aiming at Predicting Respiratory Tract Disease Hospital Admissions from Environmental Variables in the City of Sao Paulo
Autor: de Sousa Zanotti Stagliorio Coelho, Micheline ; Luiz Teixeira Goncalves, Fabio ; do Rosario Dias de Oliveira Latorre, Maria
Carpenter, David O.
Assuntos: Air Pollutants - adverse effects ; Air Pollutants - analysis ; Air pollution ; Atmospheric sciences ; Brazil ; Child ; Child, Preschool ; Climate change ; Cold ; Environmental conditions ; Hospitals ; Humans ; Infant ; Mathematical models ; Meteorological Concepts ; Models, Biological ; Outdoor air quality ; Patient Admission - statistics & numerical data ; Poisson Distribution ; Pollutants ; Public health ; Respiratory Tract Diseases - etiology ; Risk ; Stochastic Processes ; Studies ; Temperature ; Variables
É parte de: Journal of Environmental and Public Health, 2010, Vol.2010, p.209270-11
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
Academic Editor: David O. Carpenter
Descrição: 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.
Editor: United States: Hindawi Limiteds
Idioma: Inglês

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Statistical Analysis Aiming at Predicting Respiratory Tract Disease Hospital Admissions from Environmental Variables in the City of Sao Paulo

de Sousa Zanotti Stagliorio Coelho, Micheline ; Luiz Teixeira Goncalves, Fabio ; do Rosario Dias de Oliveira Latorre, Maria Carpenter, David O.

United States: Hindawi Limiteds

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