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 residues in fruit that may be eaten as single items reported variability. The usual point estimate exposure model did not take account of the variation in residue levels between items or variation in consumption patterns of individual consumers. Using only the highest residue levels and consumption values for each of the multiple sources (different fruit) could lead to overestimates 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 consumption data collected from dietary surveys. The estimation of exposure of toddlers to carbaryl is shown as an example. The number of samples representing some combinations of fruit in the toddler dietary survey was particularly 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. However, inclusion of correlated sampling in the model simulation was considered too conservative. The profiles of carbaryl residues in different retail batches differed. Therefore a model was constructed that differentiated between different residue profiles and sampled separate residue levels for each 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. All 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 terms of necessary regulatory action.
Hamey
P Y
PY
p.y.hamey@psd.maff.gsi.gov.uk
D012721:Carbaryl; D002675:Child, Preschool; D005506:Food Contamination / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007306:Insecticides; D015233:Models, Statistical; D010573:Pesticide Residues; D011336:Probability; D018570:Risk Assessment / Q000379:methods; D019685:Rosales
D007306:Insecticides; D010573:Pesticide Residues; D012721:Carbaryl