After extensive discussion, the committee concluded that the most reliable and defensible results for the purpose of risk assessment are those based on the K-power model. The argument for this conclusion is as follows. In dose-response settings like those with MeHg, when there are no internal controls (i.e., no unexposed individuals) and where the dose response is relatively flat, the data will often be fit equally well by linear, square-root and log models. The models can yield very different results for BMD calculations, however, because these calculations necessitate extrapolating to estimate the mean response at zero exposure level. Both the square-root and the log models take on a supralinear shape at low doses, that is, they postulate a steeper slope at low doses. Thus, they tend to lead to lower estimates of the BMD than linear or K-power models. From a toxicological perspective, the K-power model has greater biological plausibility, because it allows for the dose response to take on a sublinear form, if appropriate. Sublinear models would be appropriate, for instance, in the presence of a threshold. The K-power model is typically fit under the constraint that K ≥ 1, so that supralinear models are ruled out. Figure 7-4 contrasts several classes of dose-response models.

The model sensitivity described here might seem in conflict with the concept, put forward by Crump and others, that by estimating risks at moderate levels, such as 5% or 10%, the BMD should be relatively robust to model specification. As discussed by Budtz-Jørgensen and colleagues, key to understanding this apparent contradiction is that the Faroe Islands study does not include any true controls (i.e., subjects with