Methodological aspects related to aggregate and cumulative exposures to contaminants with common mechanisms of toxicity.

Consumers can be simultaneously exposed to more than one substance having a similar mechanism of toxicity. In those cases the total exposure should be computed (cumulative exposure). Computing aggregate and cumulative exposure requires the introduction of data about when the exposures occur and how much occurs simultaneously or within a given time frame for each substance. For example, in evaluating food exposures, ideally residues of all substances of interest will be measured in the same sample of food. Estimates of the decline in residues will be useful in circumstances where exposures do not begin and end at the same time. Typically, 'worst case' assumptions and models are too blunt to provide useful information about cumulative exposures. Therefore, data and algorithms that allow more realistic (if still conservative) assessment of aggregate and cumulative exposures are required. Several approaches, including Monte Carlo assessment methods are presented along with an evaluation of the strengths and limitations of each using a case study to illustrate the methodology and the data requirements. Understanding the major contributors to the estimated exposures is complicated and available tools and techniques will be demonstrated.