Validation of a probabilistic model of dietary exposure to selected pesticides in Dutch infants

A probabilistic model for dietary exposure to pesticides was validated. For this, we evaluated the agreement of dietary exposure to six pesticides as estimated with the model with exposures measured in duplicate diet samples (=‘real intake’) and those calculated with the point estimate. To calculate the exposure with the model and point estimate, consumption data of the duplicate diet survey and pesticide residue measurements from Dutch monitoring programmes in 2000 and 2001 were used. The model was considered validated when the outcome was both higher than the real intake and lower than the point estimate. Results showed that exposures estimated with the model were closer to the real intake than those of the point estimate, and that the model outcome was lower than the point estimate. Furthermore, it was shown that the probabilistic approach can address the exposure to a pesticide via the consumption of different food products, while the point estimate only estimates the exposure through the consumption of one product. The model validated is a valuable asset when estimating the dietary exposure to pesticides in both the authorization of new pesticides and the evaluation of exposures using monitoring data.

[1]  M. Skidmore,et al.  Pesticides report 31: Effects of storage and processing on pesticide residues in plant products (Technical Report) , 1994 .

[2]  H. van der Voet,et al.  Validation of Monte Carlo models for estimating presticide intake of Dutch infants , 2003 .

[3]  Barbara J. Petersen,et al.  Pesticide degradation : Exceptions to the rule , 1996 .

[4]  C. Rueda,et al.  Validation and sensitivity analysis of a probabilistic model for dietary exposure assessment to pesticide residues with a Basque Country duplicate diet study , 2003, Food additives and contaminants.

[5]  C. Harris,et al.  The variation of pesticide residues in fruits and vegetables and the associated assessment of risk. , 1999, Regulatory toxicology and pharmacology : RTP.

[6]  S. Kunç,et al.  Degradation of some pesticides in the field and effect of processing , 1995 .

[7]  Á. Ambrus.  Within and between field variability of residue data and sampling implications , 2000, Food additives and contaminants.

[8]  C McNamara,et al.  Design, development and validation of software for modelling dietary exposure to food chemicals and nutrients , 2003, Food additives and contaminants.

[9]  G R Stephenson,et al.  The distribution of nine pesticides between the juice and pulp of carrots and tomatoes after home processing. , 1998, Food additives and contaminants.

[10]  M J Gibney,et al.  Introduction to the Monte Carlo project and the approach to the validation of probabilistic models of dietary exposure to selected food chemicals , 2003, Food additives and contaminants.

[11]  P. Hammond.  Book Review: Guidelines for Predicting Dietary Intake of Pesticide Residues , 1991 .

[12]  J. Doucet,et al.  Pesticide residues in the Canadian Market Basket Survey 1992 to 1996 , 2000, Food additives and contaminants.

[13]  Wout Slob,et al.  Uncertainty Analysis in Multiplicative Models , 1994 .

[14]  L R Muenz,et al.  An alternative approach to dietary exposure assessment. , 1994, Risk analysis : an official publication of the Society for Risk Analysis.

[15]  A. Angioni,et al.  Pesticide residues in raisin processing , 1998 .

[16]  Marko van Dooren,et al.  Conversie van consumeerbare voedingsmiddelen naar primaire agrarische produkten , 1995 .

[17]  F B Suhre,et al.  Pesticide residues and acute risk assessment the US EPA approach , 2000, Food additives and contaminants.

[18]  M. Zabik,et al.  Reduction of azinphos-methyl, chlorpyrifos, esfenvalerate, and methomyl residues in processed apples. , 2000, Journal of agricultural and food chemistry.

[19]  R. E. Duggan,et al.  Pesticide Residues in Food , 1973 .