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vol.73 issue2The EMECAM project: spanish multicenter study on the relationship between air pollution and the death rate. Background data, participants, objectives and methodsThe short-term impact of air pollution on the mortality: results of the EMECAM project in two cities in Asturias Spain author indexsubject indexarticles search
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Revista Española de Salud Pública

Print version ISSN 1135-5727

Abstract

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 1135-5727.  http://dx.doi.org/10.1590/S1135-57271999000200007.

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.

Keywords : Pollution; Mortality; Poisson regression; Times series.

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