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vol.73 número2El proyecto EMECAM: estudio multicéntrico español sobre la relación entre la contaminación atmosférica y la mortalidad. Antecedentes, participantes, objetivos y métodologíaEfectos a corto plazo de la contaminación atmosférica sobre la mortalidad: resultados del proyecto EMECAM en dos ciudades de Asturias índice de autoresíndice de assuntospesquisa de artigos
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Revista Española de Salud Pública

versão On-line ISSN 2173-9110versão impressa ISSN 1135-5727

Resumo

PEREZ-HOYOS, Santiago et al. Short-term effect of air pollution on mortality: the EMECAM project protocol. Rev. Esp. Salud Publica [online]. 1999, vol.73, n.2, pp.177-185. ISSN 2173-9110.

The aim of this study is to show the protocol of analysis which was set out as part of the EMECAM Project, illustrating the application thereof to the effect of  pollution has on the mortality in the city of Valencia. The response variables considered will be the daily mortality resulting from all causes, except external ones. The explicative variables are the daily series of different pollutants (black smoke, SO2, NO2, CO, O3). As possible confusion variables, weather factors, structural factors and weekly cases of flu are taken into account. A Poisson regression model is built up for each one of the four deaths series in two stages. In the first stage, a baseline model is fitted using the possible confusion-causing variables. In the second stage, the pollution variables or the time lags thereof are included, controlling the residual autocorrelation by including mortality time lags. The process of fitting the baseline model is as follows: 1) Include the significant sinusoidal terms up to the sixth order. 2) Include the significant temperature or temperature squared terms with the time lags thereof up to the 7th power. 3) Repeat this process with the relative humidity. 4) Add in the significant terms of calendar years, daily tendency and tendency squared. 5) The days of the week as dummy variables are always included in the model. 6) Include the holidays and the significant time lags of up to two weeks of flu. Following the reassessment of the model, each one of the pollutants and the time lags thereof up to the fifth order are proven out. The impact is analyzed by six-month periods, including interaction terms.

Palavras-chave : Pollution; Mortality; Poisson regression; Times series.

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