Abstract
This article develops a model based on time-series analysis for investigating health outcome, such as disease or death, in relation to levels of air pollution. The model is built under assumption that any health outcome belongs to multivariate hierarchical system and depends on meteorology, pollution, geophysical and socio-cultural variables in it. The possible connections in this system are considered and mathematically formalized by means of trigonometric and polynomial functions. The model is tested by two simulations: (1) with count outcomes taken from Philadelphia daily mortality records for the period from 1974 to 1980; (2) with the individual outcomes taken from the peak flow measurements in 48 adults with vulnerable respiratory system in Leipzig, Germany, October 1990 – April 1991.
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References
Health Effects Institute. Particulate Air Pollution and Daily Mortality: Replication and Validation of the Selected Studies. Andover, Mass. Health Effects Institute, August (1995).
Goldsmith, J.R,, Friger, M.D. and Abramson, M.: Associations Between Health and Air Pollution an Time-Series Analyses Arch. Environ. Health (1996): Vol.51: 358–367.
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© 2001 Springer-Verlag Berlin Heidelberg
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Friger, M., Novack, Y., Ranft, U. (2001). Quasi-Fourier Modeling Individual and Count Outcomes. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_14
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DOI: https://doi.org/10.1007/3-540-45497-7_14
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