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Statistical analysis aiming at predicting respiratory tract disease hospital admissions from environmental variables in the city of São Paulo.

de Sousa Zanotti Stagliorio Coêlho M, Luiz Teixeira Gonçalves F, do Rosário Dias de Oliveira Latorre M - J Environ Public Health (2010)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: 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

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.

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Related in: MedlinePlus

IP Relative Risk (RR) for different explained variables: (a) PM10 and (b) ETw4.
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fig5: IP Relative Risk (RR) for different explained variables: (a) PM10 and (b) ETw4.

Mentions: The Relative Risk rises from 1 to 1.5 with CI95% ranging from −1 to +1 when PM10 varies from 0 to 160 μg/m3 (see Figure 5(a)). Regarding ETw4, the Relative Risk decreases from 1 to 0.6 with CI95% ranging from −1.0 to +0.8 when ETw4 varies from 0 to 16°C (see Figure 5(b)).


Statistical analysis aiming at predicting respiratory tract disease hospital admissions from environmental variables in the city of São Paulo.

de Sousa Zanotti Stagliorio Coêlho M, Luiz Teixeira Gonçalves F, do Rosário Dias de Oliveira Latorre M - J Environ Public Health (2010)

IP Relative Risk (RR) for different explained variables: (a) PM10 and (b) ETw4.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2913660&req=5

fig5: IP Relative Risk (RR) for different explained variables: (a) PM10 and (b) ETw4.
Mentions: The Relative Risk rises from 1 to 1.5 with CI95% ranging from −1 to +1 when PM10 varies from 0 to 160 μg/m3 (see Figure 5(a)). Regarding ETw4, the Relative Risk decreases from 1 to 0.6 with CI95% ranging from −1.0 to +0.8 when ETw4 varies from 0 to 16°C (see Figure 5(b)).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: 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

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.

Show MeSH
Related in: MedlinePlus