Panel studies of acute health effects of air pollution. II. A methodologic study of linear regression analysis of asthma panel data.

Panel studies relating illness, such as asthma attacks, cardiopulmonary symptoms, and acute respiratory symptoms, to daily air pollution and weather are important in environmental epidemiology. A study of the practical robustness of multiple linear regression procedures, which have been the preferred statistical models in analyses, is presented. The study is based on data from three asthma panels in Chattanooga, Tennessee, collected in 1972-1973. Linear regression models, commonly used, which incorporate only minimum temperature and an air pollutant were found to be potentially misleading; such models are highly sensitive to reporting trends in the data and do not correct adequately for weather variables. Temporal and spatial control strategies were employed and proved to be useful in detecting problems in the data due to undiscovered intervening variables. True day-to-day relationships estimated by a pair-day analysis were frequently inconsistent with "daily" effects estimated by the usual regression models and suggested that, in fact, the asthma panel data contained no useful information concerning day-to-day relationships.