Department of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences, University of São Paulo, Rua do Matão, Cidade Universitária, São Paulo, SP, Brazil.
J Environ Public Health. 2010;2010:209270. doi: 10.1155/2010/209270. Epub 2010 Jul 18.
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.
本研究旨在通过泊松回归创建一个名为巴西气候与健康模型（BCHM）的随机模型，以预测医院呼吸道疾病入院（十三岁以下儿童）的发生情况，其影响因素包括空气污染物、气象变量和热舒适指数（有效温度，ET）。本研究使用的数据集来自巴西圣保罗市，时间范围为 1997 年至 2000 年。呼吸道疾病分为三类：URI（上呼吸道疾病）、LRI（下呼吸道疾病）和 IP（流感和肺炎）。URI、LRI 和 IP 的总体结果与 SO₂ 和 CO、PM₁₀ 和 O₃ 以及所有三种疾病组的 ETw4（有效温度）都有明显的相关性。本研究结果对于巴西人口最多的城市的政府来说极其重要，可为其提供有价值的信息，帮助其更好地管理资源，以代表圣保罗市的全体市民，特别是那些低收入人群的利益。
