The Impact of Pesticides - Academy Publish

scenarios were simulated, assuming that a urine sample was always collected in themorning (at 7:00 am) and that all the measured exposure had occurred the previousday: ingestion of a bolus NOEL at dinner (6:00 pm); ingestion of 1/3 NOEL at each daily meal, i.e. breakfast (7:00 am),lunch (noon) and dinner (6:00 pm); an 8-h dermal exposure to the NOEL, starting at 7:00 am.The resulting NBEs were respectively 106, 127 and 40 nmol/kg bw for MPmetabolites, whereas those for EP metabolites were 87, 52 and 32 nmol/kg bw.Accounting for the body weight of each child, AP measurements made in each urinevoid collected could thus be compared to these values to assess whether or not eachchild had likely been exposed to a dose exceeding the NOEL the day prior to urinesampling. As indicated in Figure 7, which computes distributions of ratios of the APurinary measurements over the relevant NBEs, this occurred only for one of the 442samples collected when looking at urinary concentrations of MP metabolites andassuming a more conservative (but less likely) dermal exposure scenario (Valcke andBouchard 2009). The same observation could be made when the sum of ratiosobtained for both MP and EP metabolites were calculated in order to consider thepossible co-exposure to multiple OPs, given that they all share a common mechanismof toxicity (AChE inhibition of activity).Several authors have used non-toxicokinetic approaches to pesticide dose estimates(and resulting risks) from urinary biomonitoring data in spot urine samples typical ofnon-occupational settings. Such approaches rely on the underlying assumptions thatpesticide exposure follows steady-state conditions and that daily creatinine excretion isconstant, two assumptions that allow estimating pesticide exposure dose from theurinary measurements of parent compounds (Acquavella et al., 2004; Alexander et al.,2007) or the metabolites (Fenske et al., 2000; Mage et al., 2004; Curwin et al., 2007;Mage et al., 2008). Furthermore, biomonitoring equivalents (BEs), which correspondto a metabolite concentration in different matrices associated to steady-state exposureto a reference dose, have also been determined for several pesticides i.e. DDT/DDE,deltamethrin, hexachlorobenzene, triclosan, cyfluthrin and 2,4-D (Angerer et al.,2011). BEs were actually suggested as a prioritization tool for risk management ofpopulation exposure to chemicals, including pesticides (Hays et al., 2007).A particularly interesting feature of the toxicokinetic approach described in thischapter is that by relying on amounts of metabolites excreted in urine rather than theirconcentrations, the toxicokinetics of the substance can be accounted for adequately,leading to robust internal dose estimates. This is true as long as a sufficient volume ofurine is collected. Indeed, less uncertainty is associated with greater volumes collected;thus collection of first morning voids is suggested as they better reflect 24-h excretionvolumes (Scher et al., 2007). This sampling strategy also reduces the uncertaintyassociated with the daily excretion rates of creatinine, which are known to exhibitsignificant intra- and inter-individual variability (Mage et al., 2004; Fortin et al., 2008;Mage et al., 2008). As a result, biomonitoring data can be interpreted both individuallyand at a population scale.CONCLUDING REMARKSIn summary, this chapter showed the applicability of a toxicokinetic approach for thederivation of convenient BRVs for various types of pesticides. The various presentedAcademyPublish.org - The Impact of Pesticides120