A practical application of probabilistic modelling in assessment of dietary exposure of fruit consumers to pesticide residues

In 1996, studies on a range of organophosphate and carbamate pesticide resi dues in fruit that may be eaten as single items reported variability. The u sual point estimate exposure model did not take account of the variation in residue levels between items or variation in consumption patterns of indiv idual consumers. Using only the highest residue levels and consumption valu es for each of the multiple sources (different fruit) could lead to overest imates of residue intakes which would indicate higher than actual levels of risk. Probabilistic simulation was identified as a tool that could utilize all the available information from the variability studies and fruit consu mption data collected from dietary surveys. The estimation of exposure of t oddlers to carbaryl is shown as an example. The number of samples represent ing some combinations of fruit in the toddler dietary survey was particular ly low and the validity of extrapolating from these was unknown. Therefore, consumption values were simulated using the data for frequency and amount eaten from the whole database. The data indicated that there were some weak positive associations between consumption levels of the different fruit. H owever, inclusion of correlated sampling in the model simulation was consid ered too conservative. The profiles of carbaryl residues in different retai l batches differed. Therefore a model was constructed that differentiated b etween different residue profiles and sampled separate residue levels for e ach item assumed to be eaten. Two simpler models, both ignoring the effect of re-sampling from the same batch, were also used to estimate exposure. Al l three models were considered to give realistic views of the likely short- term intakes and the outputs were useful as an aid to decision-making in te rms of necessary regulatory action.