Philippe Verger

Estimated dietary exposure to principal food mycotoxins from The First French Total Diet Study

This study reports estimates on dietary exposure from the first French Total Diet Study (FTDS) and compares these estimates with both existing tolerable daily intakes for these toxins and the intakes calculated during previous French studies. To estimate the dietary exposure of the French population to the principal mycotoxins in the French diet (as consumed), 456 composite samples were prepared from 2280 individual samples and analysed for aflatoxins, ochratoxin A, trichothecenes, zearalenone, fumonisins and patulin. Average and high percentile intakes were calculated taking account of different eating patterns for adults, children and vegetarians. The results showed that contaminant levels observed in the foods examined ‘as consumed’ complied fully with current European legislation. However, particular attention needs to be paid to the exposure of specific population groups, such as children and vegans/macrobiotics, who could be exposed to certain mycotoxins in quantities that exceed the tolerable or weekly daily intake levels. This observation is particularly relevant with respect to ochratoxin A, deoxynivalenol and zearalenone. For these mycotoxins, cereals and cereal products were the main contributors to high exposure.

Methodological characteristics of the national dietary surveys carried out in the European Union as included in the European Food Safety Authority (EFSA) Comprehensive European Food Consumption Database

In 2009 competent organisations in the European Union provided the European Food Safety Authority (EFSA) with data from the most recent national dietary survey at the level of individuals’ consumption. Twenty different Member States provided EFSA with data from 22 different national dietary surveys, with consumption figures for adults and, when available, for children. Member States’ dietary data were assembled into the EFSA Comprehensive European Food Consumption Database. In this paper an overview of the methodologies and protocols employed in the different national dietary surveys is provided. Specifically, details about dietary assessment methods, interview administration, sampling design, portion size estimation, dietary software, evaluation of under-reporting and non-dietary information collected are described. This information is crucial to evaluate the level of accuracy of food consumption data and to anticipate and acknowledge the utmost important sources of heterogeneity of national databases included in the Comprehensive Database. The Comprehensive Database constitutes a unique resource for the estimation of consumption figures across the European Union and represents a useful tool to assess dietary exposure to hazardous substances and nutrient intake in Europe. Nevertheless, the many substantial methodological differences that characterise the Comprehensive Database are acknowledged and critically discussed.

Reevaluate Pesticides for Food Security and Safety

Generic pesticides, vital in the developing world, present assessment challenges. With global population projected to increase above 9 billion by 2050, food security—the availability of food and ones access to it—is increasingly important (1). Crop-protection products can help reduce yield losses caused by pests, pathogens, and weeds, to help feed the worlds population sustainably. Given potential harm for human health and the environment, regulation of pesticide use in agriculture has been controversial.

New approach for the assessment of cluster diets

Dietary risk assessment is a major public health concern, positioned in the context of establishing overall food safety policy. It requires some understanding of population food choices although geographical location and social-cultural environment are variable. Several years ago, a cluster analysis based on FAO consumption data, ranging from 1990 to 1994, was at the origin of the 13, so called, GEMS/Food cluster diets. This analysis required the initial identification of 19 food markers based on geographical and cultural differences. This paper proposes a new modelling of FAO food consumption database in order to define new cluster diets based on updated consumption data from 2002 to 2007 and better adapted statistical methods. Two statistical methods were combined to extract, consumption systems that generate a substructure from the initial food consumption database and then by deriving a clustering of countries according to their consumption system profiles. The clustering resulted in 17 cluster diets composed of 2 up to 30 countries. The few discrepancies between these new clusters and former ones may be due to more recent data, and to the fact that the new approach is based on another mathematical modelling which does not require any initial identification of food markers.

World Health Organization estimates of the global and regional disease burden of four foodborne chemical toxins, 2010 : a data synthesis

Background Chemical exposures have been associated with a variety of health effects; however, little is known about the global disease burden from foodborne chemicals. Food can be a major pathway for the general population’s exposure to chemicals, and for some chemicals, it accounts for almost 100% of exposure. Methods and Findings Groups of foodborne chemicals, both natural and anthropogenic, were evaluated for their ability to contribute to the burden of disease. The results of the analyses on four chemicals are presented here - cyanide in cassava, peanut allergen, aflatoxin, and dioxin. Systematic reviews of the literature were conducted to develop age- and sex-specific disease incidence and mortality estimates due to these chemicals. From these estimates, the numbers of cases, deaths and disability adjusted life years (DALYs) were calculated. For these four chemicals combined, the total number of illnesses, deaths, and DALYs in 2010 is estimated to be 339,000 (95% uncertainty interval [UI]: 186,000-1,239,000); 20,000 (95% UI: 8,000-52,000); and 1,012,000 (95% UI: 562,000-2,822,000), respectively. Both cyanide in cassava and aflatoxin are associated with diseases with high case-fatality ratios. Virtually all human exposure to these four chemicals is through the food supply. Conclusion Chemicals in the food supply, as evidenced by the results for only four chemicals, can have a significant impact on the global burden of disease. The case-fatality rates for these four chemicals range from low (e.g., peanut allergen) to extremely high (aflatoxin and liver cancer). The effects associated with these four chemicals are neurologic (cyanide in cassava), cancer (aflatoxin), allergic response (peanut allergen), endocrine (dioxin), and reproductive (dioxin).

Population effects and variability

Chemical risk assessment for human health requires a multidisciplinary approach through four steps: hazard identification and characterization, exposure assessment, and risk characterization. Hazard identification and characterization aim to identify the metabolism and elimination of the chemical (toxicokinetics) and the toxicological dose-response (toxicodynamics) and to derive a health-based guidance value for safe levels of exposure. Exposure assessment estimates human exposure as the product of the amount of the chemical in the matrix consumed and the consumption itself. Finally, risk characterization evaluates the risk of the exposure to human health by comparing the latter to with the health-based guidance value. Recently, many research efforts in computational toxicology have been put together to characterize population variability and uncertainty in each of the steps of risk assessment to move towards more quantitative and transparent risk assessment. This chapter focuses specifically on modeling population variability and effects for each step of risk assessment in order to provide an overview of the statistical and computational tools available to toxicologists and risk assessors. Three examples are given to illustrate the applicability of those tools: derivation of pathway-related uncertainty factors based on population variability, exposure to dioxins, dose-response modeling of cadmium.

Characterizing chronic and acute health risks of residues of veterinary drugs in food: latest methodological developments by the joint FAO/WHO expert committee on food additives

Abstract The risk assessment of residues of veterinary drugs in food is a field that continues to evolve. The toxicological end-points to be considered are becoming more nuanced and in light of growing concern about the development of antimicrobial resistance, detailed analysis of the antimicrobial activity of the residues of veterinary drugs in food is increasingly incorporated in the assessment. In recent years, the Joint FAO/WHO Expert Committee on Food Additives (JECFA) has refined its approaches to provide a more comprehensive and fit-for-purpose risk assessment. This publication describes in detail the consideration of acute and chronic effects, the estimation of acute and chronic dietary exposure, current approaches for including microbiological endpoints in the risk assessment, and JECFA’s considerations for the potential effects of food processing on residues from veterinary drugs. JECFA now applies these approaches in the development of health-based guidance values (i.e. safe exposure levels) for residues of veterinary drugs. JECFA, thus, comprehensively addresses acute and chronic risks by using corresponding estimates for acute and chronic exposure and suitable correction for the limited bioavailability of bound residues by the Gallo-Torres model. On a case-by-case basis, JECFA also considers degradation products that occur from normal food processing of food containing veterinary drug residues. These approaches will continue to be refined to ensure the most scientifically sound basis for the establishment of health-based guidance values for veterinary drug residues.

Model averaging quantiles from data censored by a limit of detection.

In chemical risk assessment, it is important to determine the quantiles of the distribution of concentration data. The selection of an appropriate distribution and the estimation of particular quantiles of interest are largely hindered by the omnipresence of observations below the limit of detection, leading to left-censored data. The log-normal distribution is a common choice, but this distribution is not the only possibility and alternatives should be considered as well. Here, we focus on several distributions that are related to the log-normal distribution or that are seminonparametric extensions of the log-normal distribution. Whereas previous work focused on the estimation of the cumulative distribution function, our interest here goes to the estimation of quantiles, particularly in the left tail of the distribution where most of the left-censored data are located. Two different model averaged quantile estimators are defined and compared for different families of candidate models. The models and methods of selection and averaging are further investigated through simulations and illustrated on data of cadmium concentration in food products. The approach is extended to include covariates and to deal with uncertainty about the values of the limit of detection. These extensions are illustrated with (134) cesium measurements from Fukushima Prefecture, Japan. We can conclude that averaged models do achieve good performance characteristics in case no useful prior knowledge about the true distribution is available; that there is no structural difference in the performance of the direct and indirect method; and that, not surprisingly, only the true or closely approximating model can deal with extremely high percentages of censoring.

Parametric and semi-nonparametric model strategies for the estimation of distributions of chemical contaminant data

The determination of an appropriate distribution for concentration data is of major importance in chemical risk assessment. The selection and the estimation of an appropriate distribution is hindered by observations below the limit-of-detection and the limit-of-quantification, leading to left-censored and interval-censored data. The log-normal distribution is a typical choice, owing its popularity from the use of the log transform in daily laboratory practice, in combination with the nice mathematical and computational properties of the normal distribution. But the log-normal should not be the only choice and other distributions need to be considered as well. Here we focus on several families of distributions that are related to the log-normal distribution in some direct or indirect way, and that are parametric or semi-nonparametric extensions of the log-normal distribution: the log-skew-normal, the log-t, the log-skew-t, the Weibull, the gamma, the generalized-gamma, and the semi-nonparametric estimator of Zhang and Davidian (Biometrics 64(2):567–669, 2008). Whereas Nysen et al. (Stat Med 31:2374–2385, 2012) developed methodology to test the goodness-of-fit of a particular hypothesized distribution, our interest here goes to model selection and model averaging, using all parametric models only or in addition the series of extensions of the log-normal underlying the semi-nonparametric estimator. The models and methods of selection and averaging are further investigated through simulations and illustrated on data of cadmium concentration in food products.

Mycotoxin contamination of sorghum and its contribution to human dietary exposure in four sub-Saharan countries

ABSTRACT This research aimed at evaluating the safety, and the type, level and prevalence of mycotoxins in grain sorghum of four sub-Saharan African (SSA) countries (Burkina Faso, Ethiopia, Mali and Sudan). A multi-analyte LC-MS/MS method for quantification of 23 mycotoxins (nivalenol, deoxynivalenol, fusarenon X, neosolaniol, 3-acetyl deoxynivalenol, 15-acetyl deoxynivalenol, diacetoxyscirpenol, roquefortine C, HT-2 toxin, alternariol, T-2 toxin, FB1, FB2, FB3, zearalenone, aflatoxin G1, aflatoxin G2, aflatoxin B1, aflatoxin B2, sterigmatocystin, OTA, altenuene, alternariol monomethylether) was applied to different sorghum matrices. Of the 1533 analysed samples, 33% were contaminated with at least one of the following mycotoxins: aflatoxins, fumonisins, sterigmatocystin, Alternaria toxins, OTA and zearalenone. Country of origin, colour, source and collection period of sorghum samples significantly influenced the type, level and prevalence of mycotoxins. Sterigmatocystin (15%), fumonisins (17%) and aflatoxins (13%) were the most prevalent. FB1 (274 ± 585 µg/kg) had the highest mean concentration followed by FB2 (214 ± 308 µg/kg) while diacetoxyscirpenol (8.12 ± 19.2 µg/kg) and HT-2 (11.9 ± 0.00 µg/kg) had the lowest concentrations. Neosolaniol, fusarenon-X, 3-acetyl deoxynivalenol, 15-acetyl deoxynivalenol, T-2 toxin, nivalenol and roquefortine C were not detected in any of the samples. Sudan had the lowest prevalence and mean concentration of all mycotoxins. Pink sorghum had the highest concentrations of fumonisins and aflatoxins. Mycotoxins from Aspergillus spp. and Alternaria spp. are the mycotoxins of concern in SSA grain sorghum with regard to prevalence, concentration and possible health risk from exposure. Based on the performed risk characterisation, daily consumption of sorghum containing aflatoxins, alternariol, alternariol monomethyl ether, sterigmatocystin and OTA could result in exceeding the established health-based guidance values for these toxins.