Identification of the main pesticide residue mixtures to which the French population is exposed.

Owing to the intensive use of pesticides and their potential persistence in the environment, various pesticide residues can be found in the diet. Consumers are therefore exposed to complex pesticide mixtures which may have combined adverse effects on human health. By modelling food exposure to multiple pesticides, this paper aims to determine the main mixtures to which the general population is exposed in France. Dietary exposure of 3337 individuals from the INCA2 French national consumption survey was assessed for 79 pesticide residues, based on results of the 2006 French food monitoring programmes. Individuals were divided into groups with similar patterns of co-exposure using the clustering ability of a Bayesian nonparametric model. In the 5 groups of individuals with the highest exposure, mixtures are formed by pairs of pesticides with correlations above 0.7. Seven mixtures of 2-6 pesticides each were characterised. We identified the commodities that contributed the most to exposure. Pesticide mixtures can either be components of a single plant protection product applied together on the same crop or be from separate products that are consumed together during a meal. Of the 25 pesticides forming the mixtures, two--DDT and Dieldrin--are known persistent organic pollutants. The approach developed is generic and can be applied to all types of substances found in the diet in order to characterise the mixtures that should be studied first because of their adverse effects on health.

The PERICLES research program: an integrated approach to characterize the combined effects of mixtures of pesticide residues to which the French population is exposed.

Due to the broad spectrum of pesticide usages, consumers are exposed to mixtures of residues, which may have combined effects on human health. The PERICLES research program aims to test the potential combined effects of pesticide mixtures, which are likely to occur through dietary exposure. The co-exposure of the French general population to 79 pesticide residues present in the diet was first assessed. A Bayesian nonparametric model was then applied to define the main mixtures to which the French general population is simultaneously and most heavily exposed. Seven mixtures made of two to six pesticides were identified from the exposure assessment. An in vitro approach was used for investigating the toxicological effects of these mixtures and their corresponding individual compounds, using a panel of cellular models, i.e. primary rat and human hepatocytes, liver, intestine, kidney, colon and brain human cell lines. A set of cell functions and corresponding end-points were monitored such as cytotoxicity, real-time cell impedance, genotoxicity, oxidative stress, apoptosis and PXR nuclear receptor transactivation. The mixtures were tested in equimolar concentrations. Among the seven mixtures, two appeared highly cytotoxic, five activated PXR and depending on the assay one or two were genotoxic. In some experiments, the mixture effect was quantitatively different from the effect expected from the addition concept. The PERICLES program shows that, for the most pesticides mixtures to which the French general population is exposed, the toxic effects observed on human cells cannot be easily predicted based on the toxic potential of each compound. Consequently, additional studies should be carried on in order to more accurately define the mixtures of chemicals to which the consumers are exposed, as well as to improve the investigation, prediction and monitoring of their potential human health effects.

Statistical analysis of a dynamic model for dietary contaminant exposure.

This paper is devoted to the statistical analysis of a stochastic model introduced in [P. Bertail, S. Clémençon, and J. Tressou, A storage model with random release rate for modelling exposure to food contaminants, Math. Biosci. Eng. 35 (1) (2008), pp. 35-60] for describing the phenomenon of exposure to a certain food contaminant. In this modelling, the temporal evolution of the contamination exposure is entirely determined by the accumulation phenomenon due to successive dietary intakes and the pharmacokinetics governing the elimination process inbetween intakes, in such a way that the exposure dynamic through time is described as a piecewise deterministic Markov process. Paths of the contamination exposure process are scarcely observable in practice, therefore intensive computer simulation methods are crucial for estimating the time-dependent or steady-state features of the process. Here we consider simulation estimators based on consumption and contamination data and investigate how to construct accurate bootstrap confidence intervals (CI) for certain quantities of considerable importance from the epidemiology viewpoint. Special attention is also paid to the problem of computing the probability of certain rare events related to the exposure process path arising in dietary risk analysis using multilevel splitting or importance sampling (IS) techniques. Applications of these statistical methods to a collection of data sets related to dietary methyl mercury contamination are discussed thoroughly.

Integration of time as a description parameter in risk characterisation: application to methyl mercury.

Within the food risk assessment procedure, the characterisation of the risk consists in the comparison of the dietary exposure with a health based guidance value established in a previous step. One of the identified weaknesses of this comparison is that the time is not considered in the description. The aim of this paper is to describe the dietary exposure as a dynamic process determined by the accumulation phenomenon due to successive dietary intakes and by the pharmacokinetics ruling the elimination process in between intakes. Such a process belong to the category of piecewise deterministic Markov processes, which are widely used in a large variety of applications in insurance risk or in operations research, ranging from queuing systems to inventory/storage models. The inputs of the Kinetic Dietary Exposure Model are the probability distributions governing intakes and inter-intake times, as well as the half-life of the contaminant in the human body. In this paper, an application to methyl mercury is considered, with exponential distributions for both the intakes and the inter-intake times, fitted from the French national consumption survey INCA, and a fixed half-life of 6 weeks for the elimination process. Within this framework, the process settles to a steady-state after approximately 5 years. A "Kinetic Tolerable Intake" (KTI), derived from the "Provisional Tolerable Weekly Intake" (PTWI) of 1.6 microg/kg bw, is set to 14.6 microg/kg and the probability of exceeding this threshold in the long run in the French adult female population is 1.22 E-15.

Dietary exposure of Brazilian consumers to dithiocarbamate pesticides--a probabilistic approach.

A probabilistic estimation of the exposure of the Brazilian population to the dithiocarbamate pesticides was performed using the Monte Carlo Risk Assessment program (MCRA 3.5). Residue data, as CS2, for 3821 samples were obtained from the Brazilian national monitoring program on pesticide residues and from the monitoring program conducted in the Distrito Federal on rice, beans and nine fruits and vegetables. Food consumption data were obtained from a Brazilian household budget survey conducted between 2002 and 2003. Processing factors for washing, peeling or cooking were applied to the residues found in the crops. Daily intakes at the highest percentiles for the general population reached a maximum of 2.0 microg CS2/kg body weight per day (upper band of the 95% confidence interval at P99.99). Tomato, rice, apple and lettuce were the commodities which contributed most to the intake. Based on the registered uses and the toxicological profile of dithiocarbamates, the risk from exposure was evaluated assuming that all residues came from the use of ethylene-bis-dithiocarbamate (EBDC) or that a fraction of it came from the use of propineb. For this last scenario, a cumulative risk assessment was conducted. In the first scenario, the highest intake reached up to 11.9% EBDC ADI for the general population and up to 31.1% ADI for children. When 30% of the residues were considered as coming from propineb use, the values were 15.2% and 39.7% ADI, respectively.

Probabilistic assessment of the cumulative acute exposure to organophosphorus and carbamate insecticides in the Brazilian diet.

In the present study, the cumulative exposure of 25 acetylcholinesterase (AChE) inhibiting pesticides through the consumption of nine fruits and vegetables by the Brazilian population was assessed. Food consumption data were obtained from a household budget survey conducted in all Brazilian states from July 2002 to June 2003. Residue data from 4001 samples were obtained from the Brazilian national monitoring program on pesticide residues. Relative potency factors (RPF) were calculated with methamidophos or acephate as index compounds (IC), using BMD(10) or NOAEL for AChE inhibition, mostly in rat brain, obtained from national and international pesticide evaluations. Monocrotophos and triazophos, in addition to aldicarb, had the highest calculated RPF in any scenario. The exposure to AChE inhibiting pesticides for the general population at P99.9, represented 33.6% of the ARfD as methamidophos and 70.2% ARfD as acephate. The exposure calculated as acephate could exceed the ARfD at the upper bound of the 95% confidence interval for this percentile. Exposure for children aged up to 6 years were, on average, 2.4 times higher than the exposure for the general population. Tomato represented about 67% of the total intake of AChE inhibiting pesticides. The highest calculated equivalent residues in tomato, which drove most of the estimated intakes at the high percentiles, were related to the illegal use of monocrotophos and triazophos in this crop.

Some recent advances in modelling dietary exposure to ochratoxin A.

One of the key questions when assessing the exposure to contaminants is the choice of the method and the impact of this choice on the result to be compared with the toxicological reference value. This problem is particularly significant in the case of ochratoxin A (OTA) for which the use of crude estimates can provide results close to the current provisional tolerable weekly intake (PTWI). This paper compares different exposure assessment models for OTA using the same data set for food consumption (i.e. French INCA survey 1999) for the same groups of the population (i.e. adults excluding under-reporters and children 3-14 years-old) but with various ways of handling the occurrence of OTA in food. The consumption and contamination data were combined through 11 different scenarios based on parametric and non-parametric modelling and on the use of analytical results obtained on raw commodities or on foodstuffs ready-to-eat. In order to assess exposure to OTA using data on consumption of processed and composite foods it was necessary to use recipe information in order to utilize available contamination data which only exists for raw materials. The impact of such an adjustment appears to be essential to avoid an overestimation of the exposure. The impact of the other assumptions and the choice of mathematical models influence the results less but should be considered and detailed carefully in future dietary exposure assessments.

Management options to reduce exposure to methyl mercury through the consumption of fish and fishery products by the French population.

This paper presents an updated assessment of exposure in France to methyl mercury through the consumption of fish and fishery products, and proposes several management scenarios which could reduce this exposure through changes to fish contamination levels or fish consumption patterns. The exposure model was applied in line with previous methodological results [Tressou, J., Crépet, A., Bertail, P., Feinberg, M.H., Leblanc J.Ch., 2004a. Probabilistic exposure assessment to food chemicals based on extreme value theory: application to heavy metals from fish and sea products. Food Chem. Toxicol. 42, 1349-1358; Tressou, J., Leblanc, J.Ch., Feinberg, M., Bertail, P., 2004b. Statistical methodology to evaluate food exposure to a contaminant and influence of sanitary limits: application to ochratoxin A. Regul. Toxicol. Pharmacol. 40, 252-263] so as to obtain a realistic estimate of probability and confidence intervals (95% CI) concerning French consumers exposed to levels exceeding the revised fixed provisional tolerable weekly intake (PTWI) for methyl mercury of 1.6 microg/week/kg of body weight, established by the Joint FAO/WHO Expert Committee on Food Additives in 2003. The results showed that young children aged between 3 and 6 years old or 7 and 10 years old, and women of childbearing age were at the risk groups. With respect to these groups and according to the fish consumers patterns (consumers of predatory fish only or consumers of predatory and nonpredatory fish), the results suggested that strategies to diminish MeHg exposure by reducing the amount of predatory fish consumed would be more efficient in significantly decreasing the probability of exceeding the PTWI than the implementation of international standards.

Statistical methodology to evaluate food exposure to a contaminant and influence of sanitary limits: application to Ochratoxin A.

This paper presents some statistical methodologies to evaluate the food exposure to a contaminant and quantify the outcome of a new maximum limit on a food item. Our application deals with Ochratoxin A (OTA). We focus on the quantitative evaluation of the distribution of exposure based on both consumption data and contamination data. One specific aspect of contamination data is left censorship due to the limits of detection. Three calculation procedures are proposed: [P1] a deterministic method using means of contamination; [P2] a probabilistic method using a parametric adjustment of the distributions of contamination taking into account the left censorship; and [P3] a non-parametric method which consists in randomly selecting the consumption data and the contamination values. Our main result shows that a non-parametric probabilistic approach is well adapted for the purpose of exposure assessment, when large samples are available. In the application to OTA, the probability to exceed a safe level is high, particularly for children. Simulations show that the impact of the existing standards on cereals and the currently proposed standards on wine generally do not significantly reduce the risk to be overexposed to OTA.

Probabilistic exposure assessment to food chemicals based on extreme value theory. Application to heavy metals from fish and sea products.

This paper presents new statistical methods in the field of exposure assessment. We focus on the estimation of the probability for the exposure to exceed a fixed safe level such as the provisional tolerable weekly intake (PTWI), when both consumption data and contamination data are independently available. Various calculations of exposure are proposed and compared. For many contaminants, PTWI belongs to the exposure tail distribution, which suggests the use of extreme value theory (EVT) to evaluate the risk. Our approach consists in modelling the exposure tail by a Pareto type distribution characterized by a Pareto index which may be seen as a measure of the risk of exceeding the PTWI. Using propositions by EVT specialists, we correct the bias of the usual Hill estimator to accurately estimate this risk index. We compare the results with an empirical plug-in method and show that the Pareto adjustment is relevant and efficient when exposure is low compared to the PTWI while the plug-in method should be used when exposure is higher. To illustrate our approach, we present some exposure assessment for heavy metals (lead, cadmium, mercury) via sea product consumption.