• Journal Article

Use of a pilot study for designing a large scale probability study of personal exposure to aerosols

Citation

Clayton, C., Pellizzari, E., & Wiener, R. W. (1991). Use of a pilot study for designing a large scale probability study of personal exposure to aerosols. Journal of Exposure Analysis and Environmental Epidemiology, 1(4), 407-421.

Abstract

The major objective of the U.S. Environmental Protection Agency's (EPA's) Particle Total Exposure Assessment Methodology (PTEAM) Study is to estimate the frequency distribution of aerosol exposures of a target population of individuals. This objective requires the use of probability sampling techniques for selecting a representative sample of participants from a prescribed target population. To design such a population exposure study in a cost-effective fashion, a number of issues must be addressed. For instance, when and for how long and for whom should personal samples be obtained? What other samples are needed or desirable? Issues like these must be considered from several perspectives--from the point of view of data collection costs, burden on participants, precision and representativeness of resultant estimates, etc. To help address such design issues for the PTEAM population exposure study, we generated descriptive statistics and performed statistical analyses on data from a preliminary nine-home pilot study conducted in March 1989 in the San Gabriel Valley area of Southern California. The analyses showed large temporal variation, with day versus night being a major component (generally higher daytime concentrations); large systematic time-of-week differences were not found. Large house-to-house and person-to-person variabilities were evident, with high exposure levels noted especially in homes with tobacco smoking. Within many homes, there appeared to be little variability in the particulate concentrations among different rooms. The results of the pilot were used to make decisions regarding the spatial and temporal sampling units, the benefits of stratification, and the overall allocation of resources (e.g., multiple monitors within a home versus more homes and participants) for the subsequent population study