Uses and limits of empirical data in measuring and modeling human lead exposure

This paper examines the uses and limits oi empirical data in evaluating mea surement and modeling approaches to human lead exposure. Empirical data fro m experiment or observation or both have been used in studies of lead expos ure. For example, experimental studies have elucidated and quantified physi ologic or biokinetic parameters of lead exposure under controlled condition s. Observation, i.e., epidemiology, has been widely applied to study popula tion exposures to lead. There is growing interest in the use of lead exposu re prediction models and their evaluation before use in risk assessment. Em pirical studies of lead exposure must be fury understood, especially their limits, before they are applied as "standards" or reference information for evaluation of exposure models, especially the U.S. Environmental Protectio n Agency's lead biokinetic model that is a focus oi this article. Empirical and modeled datasets for lead exposure may not agree due to a) problems wi th the observational data or bi problems with the model; caution should be exercised before either a model or observational data are rejected. There a re at least three sources of discordance in cases where there is lack of ag reement: a) empirical data are accurate but the model is flawed, b) the mod el is valid but reference empirical data are inaccurate; or c) neither empi rical data nor model is accurate, and each is inaccurate in different ways. This paper evaluates some of the critical empirical inputs to biokinetic m odels, especially lead bioavailability.