A statistical model for FEV1 response to arbitrary dynamic ozone exposure conditions

Lung function response to inhaled ozone at ambient air pollution levels is known to be a function of ozone concentration, exposure duration, and minut e ventilation. Most data-driven exposure-response models address exposures under static condition (i.e., with a constant ozone concentration and exerc ise pattern). Such models are simplifications, as both ambient ozone concen trations and normal human activity patterns change with time. The purpose o f this study was to develop a dynamic model of response with the advantages of a statistical model (a relatively simple structure with few parameters) . A previously proposed mechanistic model for changes in specific airways r esistance was adapted to describe the percent change in forced expiratory v olume in one second (FEV1). This model was then reduced using the fit to th ree existing exposure-response data sets as criterion. The resulting model consists of a single linear differential equation together with an algebrai c logistic equation. Under restricted static conditions the model reduces t o a logistic model presented earlier by the authors.