Risk assessment of dietary exposure to pesticides using a Bayesian method.
Risk assessment of pesticides can be a statistically difficult problem because pesticides occur only occasionally, but they may occur on multiple components in the diet. A Bayesian statistical model is presented which incorporates multivariate modelling of food consumption and modelling of pesticide measurements which are for a large part below a measurement threshold. It is shown that Bayesian modelling is feasible for a limited number of food components, and that in a data-rich situation the model compares well with an empirical Monte Carlo modelling.
Paulo
M João
MJ
Biometris, Wageningen University and Research Centre, Wageningen, The Netherlands.
van der Voet
Hilko
H
Jansen
Michiel J W
MJ
ter Braak
Cajo J F
CJ
van Klaveren
Jacob D
JD
D001499:Bayes Theorem; D005506:Food Contamination; D006801:Humans; D008954:Models, Biological; D009010:Monte Carlo Method; D010573:Pesticide Residues / Q000633:toxicity*; D018570:Risk Assessment
D010573:Pesticide Residues