Background To avoid the usual problems of multi-population correlation studies of air pollution and mortality, and for reasons of convenience, daily time-series mortality studies within single populations have recently become popular in air pollution epidemiology.
Such studies describe how the short-term distribution of deaths relates to short-term fluctuations in air pollution levels.
The regression-based risk coefficients from these acute-effects studies have been widely used to estimate the excess annual mortality within a population with a specified average level of air pollution.
Such calculations are inappropriate.
Since daily time-series data provide no simple direct information about the degree of life-shortening associated with the excess daily deaths (many of which are thought to be due to exacerbation of well-advanced disease, especially cardiovascular disease), such data cannot contribute to the estimation of the effects of air pollution upon chronic disease incidence and long-term death rates.
Yet it is that category of effect that is of most public health importance.
Conclusion Such effects are best estimated from long-term cohort studies that incorporate good knowledge of local (or personal) exposure to air pollutants and of potential confounders. (...)
Mots-clés Pascal : Pollution air, Santé et environnement, Court terme, Long terme, Epidémiologie, Mortalité, Facteur risque, Méthodologie, Homme
Mots-clés Pascal anglais : Air pollution, Health and environment, Short term, Long term, Epidemiology, Mortality, Risk factor, Methodology, Human
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 98-0394857
Code Inist : 002B30A02A. Création : 25/01/1999.