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. 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.
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. 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.
Entities:
Keywords:
Causes Of Death; Critique; Death Rate; Demographic Factors; Environment; Environmental Degradation; Environmental Pollution; Estimation Technics; Evaluation; Longterm Effects; Mortality; Mortality Determinants; Population; Population Dynamics; Research Methodology; Time Factors; World
Authors: Thomas D Matte; Aaron Cohen; Fred Dimmick; Jonathan Samet; Jeremy Sarnat; Fuyuen Yip; Nicholas Jones Journal: Air Qual Atmos Health Date: 2009-12-31 Impact factor: 3.763