Inappropriate use of daily mortality analyses to estimate longer-term mortality effects of air pollution.

<bold>Background: </bold>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.<bold>Conclusion: </bold>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. Time-series studies, properly evaluated, can identify the existence of acute toxic effects of transient peak levels of air pollution; they are thus useful for monitoring acute toxicity and for identifying the most noxious pollutants. However, to quantify the long-term health impacts of air pollution we cannot use acute-effects data. [ABSTRACT FROM AUTHOR]