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This paper is devoted to the statistical analysis of a stochastic model introduced in [P. Bertail, S. Clemencon, 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. [ABSTRACT FROM AUTHOR]

Les données de consommation en acides gras polyinsaturés (AGPI) de la femme allaitante sont rares bien qu’essentielles pour évaluer le niveau d’apport en acides gras du nourrisson et éventuellement orienter la mère vers une alimentation adaptée voire vers une supplémentation en acides gras essentiels. Les données INCA 2 concernant les femmes allaitantes ont été combinées aux données de composition nutritionnelle des aliments de la base de données Ciqual 2013 pour évaluer leurs apports en acides gras. Bien qu’il s’agisse d’un échantillon limité d’individus enquêtés il y a 12 ans, ces données restent malgré tout intéressantes à analyser et à comparer aux recommandations actuelles de l’Anses. Elles montrent que la consommation en AGPI n-3 n’est pas suffisante au regard des recommandations. Par ailleurs, il a été démontré que la composition en acides gras du lait maternel est un marqueur reconnu de la consommation des lipides alimentaires et un bon reflet du niveau de consommation des AGPI n-6 et n-3. Or, les données épidémiologiques relatives à la quantité et à la qualité des lipides consommés en France sont rares. Dans le cadre de différentes études cliniques conduites sur le lait maternel, l’ITERG a pu ainsi estimer l’évolution des habitudes alimentaires des Français depuis près de 17 ans. Un travail de synthèse a repris l’ensemble des données acquises au cours de 4 études cliniques menées entre 1997 et 2014. Cette synthèse a mis en évidence une évolution positive des proportions en AGPI n-3 en 17 ans (1997–2014). Toutefois, les proportions d’acide alpha-linolénique (ALA) et d’acide docosahexaénoïque (DHA) dans le lait maternel restent en deçà des recommandations nutritionnelles pour le nouveau-né.

L’Anses a mis à disposition en accès libre en septembre 2014 l’ensemble des données brutes obtenues dans l’étude individuelle nationale sur les consommations alimentaires 2006–2007 (INCA 2). Terres Univia, a fait réaliser une étude statistique détaillée des apports en acides gras de la population française et de la place des matières grasses végétales dans ces apports. Ces apports ont pu être comparés aux apports nutritionnels conseillés (ANC) pour les acides gras définis par l’Anses en mars 2010. L’étude révèle que, pour la population adulte, l’apport total moyen quotidien en lipides est de 38,0 % de l’apport énergétique total sans alcool (AESA), ce qui est conforme aux ANC (35–40 % de l’AESA). Pour autant, l’analyse détaillée montre que l’apport de certains acides gras est parfois éloigné des valeurs recommandées par l’Anses. Il est donc important de savoir choisir ses matières grasses. En septembre 2015, l’Anses a publié son propre rapport sur les apports en acides gras de la population vivant en France et leur comparaison aux ANC 2010. Les résultats de l’Anses sont semblables à ceux de Terres Univia.

The evaluation of plant and animal growth, separately for genetic and environmental effects, is necessary for genetic understanding and genetic improvement of environmental responses of plants and animals. We propose to extend an existing approach that combines nonlinear mixed-effects model (NLMEM) and the stochastic approximation of the Expectation-Maximization algorithm (SAEM) to analyze genetic and environmental effects on plant growth. These tools are widely used in many fields but very rarely in plant biology. During model formulation, a nonlinear function describes the shape of growth, and random effects describe genetic and environmental effects and their variability. Genetic relationships among the varieties were also integrated into the model using a genetic relationship matrix. The SAEM algorithm was chosen as an efficient alternative to MCMC methods, which are more commonly used in the domain. It was implemented to infer the expected growth patterns in the analyzed population and the expected curves for each variety through a maximum-likelihood and a maximum-a-posteriori approaches, respectively. The obtained estimates can be used to predict the growth curves for each variety. We illustrate the strengths of the proposed approach using simulated data and soybean plant growth data obtained from a soybean cultivation experiment conducted at the Arid Land Research Center, Tottori University. In this experiment, plant height was measured daily using drones, and the growth was monitored for approximately 200 soybean cultivars for which whole-genome sequence data were available. The NLMEM approach improved our understanding of the determinants of soybean growth and can be successfully used for the genomic prediction of growth pattern characteristics., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Delattre et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In a risk assessment perspective, this work aims to assess the bioaccessibility of PCBs in meat. A standardised in vitro static digestion protocol was set up and coupled with extraction, clean-up and GC × GC-ToF/MS multianalyte method to monitor the fate of PCBs in meat during digestion. Starting with spiked meat, PCB bioaccessibility in 11% fat medium-cooked meat varied in adults from 20.6% to 30.5% according to congeners. PCB bioaccessibility increased to 44.2-50.1% in 5% fat meat and decreased to 6.2-9.1% and to 14.6-19.4% in digestion conditions mimicking infants and elderly, respectively. Intense cooking also decreased PCB bioaccessibility to 18.0-26.7%. Bioaccessibility data obtained with spiked meat were validated with measurements carried out in incurred meat samples. Finally, mean uptake distributions are obtained from a modular Bayesian approach. These distributions feature a lower mode when the fat content is higher, the meat is well-done cooked, and the consumers are older., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Biodiversity has undergone a major decline throughout recent decades, particularly in farmland. Agricultural practices are recognized to be an important pressure on farmland biodiversity, and pesticides are suspected to be one of the main causes of this decline in biodiversity. As part of the national plan for reduction of pesticides use (Ecophyto), the French ministry of agriculture launched the 500 ENI (nonintended effects) monitoring program in 2012 in order to assess the unintended effects of agricultural practices, including pesticide use, on biodiversity represented by several taxonomic groups of interest for farmers. This long-term program monitors the biodiversity of nontargeted species (earthworms, plants, coleoptera, and birds), together with a wide range of annual data on agricultural practices (crop rotation, soil tillage, weed control, fertilizers, chemical treatments, etc.). Other parameters (e.g., landscape and climatic characteristics) are also integrated as covariates during the analyses. This monitoring program is expected to improve our understanding of the relative contribution of the different drivers of population and community trends. Here, we present the experience of setting up the 500 ENI network for this ambitious and highly complex monitoring program, as well as the type of data it collects. The issue of data quality control and some first results are discussed. With the aim of being useful to readers who would like to set up similar monitoring schemes, we also address some questions that have arisen following the first five years of the implementation phase of the program., Competing Interests: There are no conflicts of interest., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Scope: The aim of this study is to examine whether postprandial (PP) triglyceride-rich lipoproteins (TGRL) secreted after a moderate fat intake would activate platelets differently according to their fatty acid (FA) composition., Methods and Results: In a parallel single-blind randomized trial, 30 women with type 2 diabetes are assigned a breakfast containing 20 g lipids from butter versus hazelnut-cocoa spread (HCS) rich in palm oil. Blood samples are collected at fasting and 4 h PP. FA composition of fasting and PP TGRL and their effects on the activation of platelets from healthy blood donors are assessed. Both breakfasts similarly increase plasma ApoB-48, plasma, and TGRL triglycerides (p < 0.05). TGRL mean diameter increases after both breakfasts and is greater after the butter breakfast. Both breakfasts are rich in palmitic acid, and the HCS breakfast contains 45% oleic acid. TGRL FA composition reflects the dietary FA composition. Pre-incubation of platelets with fasting and PP TGRL increases collagen-stimulated aggregation (p < 0.01 vs control). Fasting and PP TGRL similarly increase agonist-induced thromboxane B 2 concentrations, and this effect is concentration-dependent for PP TGRL., Conclusion: PP TGRL from type 2 diabetic women after a palm-oil spread versus butter-based mixed meal induce similar acute in vitro platelet activation., (© 2020 Wiley-VCH GmbH.)

To assess human health risks related to the environment, it is necessary to aggregate exposure from multiple sources. The objective of this paper was to propose a relevant approach to combine data from heterogeneous populations and methodologies. Five different methods based on Monte-Carlo simulations were tested and compared. Differences were: taking into account or not stratification variable, timeline to assign exposure factors and concentration and way to account for concentration correlations. The methods were applied to estimate lead exposure from food, dust, soil, air, and tap water or French children aged between six months and three years old. Comparing results' uncertainty, it is recommended to 1) select a reference population representative of the target population, 2) select stratification variables to combine surveys, and 3) simulate a new population by randomly sampling individuals in the reference population and simultaneously assigning human exposure factors and environmental concentrations from other surveys in integrating correlations (MC1S). No difference was observed when taking into account correlations using vectors of determinist data from one survey or rank of correlations with the Iman-Conover method. Regardless the methods used to combine data, dust was the main exposure source, followed by soil and in a less extent by food. Exposures from air and tap water were found to be insignificant for most children., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Purpose: This paper deals with the dietary daily intakes of main polyunsaturated fatty acids (PUFA) in French children and adolescents., Methods: Dietary intakes of main PUFA were determined from a general French population of 1500 children (3-10 years) and adolescents (11-17 years) by using the most recent set of national robust data on food (National Survey INCA 2 performed in 2006 and 2007)., Results: Main results showed that mean daily intakes of total fat and n-6 PUFA linoleic acid (LA, 18:2n-6) were close to current recommended values for children and adolescent populations. However, 80% (children) to 90% (adolescents) of our French populations not only ingested low quantities of n-3 long-chain PUFA (docosahexaenoic (22:6n-3) and eicosapentaenoic (20:5n-3) acids) but also very low quantities of alpha-linolenic acid (ALA, 18:3n-3) at the origin of a non-balanced n-6/n-3 ratio. Inadequate consumption of EPA + DHA was also observed in subgroups of infants and adolescent who consumed more than two servings/week of fish., Conclusions: Such disequilibrium in PUFA dietary intakes in favor of n-6 PUFA could have adverse impact on cell membrane incorporation of long-chain n-3 PUFA and deleterious impacts on the health of children and adolescents. Promoting the consumption of both vegetable oils and margarines rich in ALA, and oily fish rich in long-chain n-3 PUFA might improve such PUFA disequilibrium.

Background: The French National survey INCA2 pointed out that the majority of the French population (children, adolescents, adults and elderly) ingest low quantities of n-3 polyunsaturated fatty acid (PUFA) in the form of both precursor (alpha-linolenic acid, ALA) and long-chain (mainly docosahexaenoic acid, DHA). However, we don't know whether such inadequate n-3 PUFA consumption is also found again in pregnant and lactating women., Methods: Dietary lipid and PUFA intakes were determined from 28 pregnant and 21 lactating French women by using the most recent set of national robust data on food (National Survey INCA2 performed in 2006 and 2007), and compared with that of 742 women of childbearing age., Results: Main results showed that mean daily intakes of n-3 PUFA were very low in this French woman population because no pregnant and lactating women met recommended dietary intakes (RDIs). Moreover, some of them ingested quantities 4 times (ALA) to 10 times (DHA) lower than RDIs. Very similar dietary intakes were observed in women of childbearing age., Conclusion: French pregnant and lactating women did not change their dietary habits to favor ALA and n-3 long-chain PUFA consumption via rich-ALA vegetable oils and fish and oily fish consumption, and have low n-3 PUFA dietary consumption typical of French women of childbearing age. Such PUFA intakes could have adverse impact on long-chain n-3 PUFA incorporation in brain membranes of fetus and infants, but also on cognitive and visual development of infants during the first years of life., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

In this paper, exposure to Polychlorinated biphenyls (PCBs) related to bovine meat consumption is assessed based on multiples sources of data, namely data collected within the national research project "SoMeat" that objectively assesses the potential risks and benefits of organic and conventional food production systems in terms of contaminants respective contents. The work focuses on dioxin like PCBs in bovine meat in France. A modular Bayesian approach is proposed including measures after production, effect of cooking, levels and frequency of consumption and effect of digestion. In each module, a model is built and prior information can be integrated through previously acquired data commonly used in food risk assessment or vague priors. The output of the global model is the exposure including both production modes (organic and conventional) for three different cooking intensities (rare, medium, and well-done), before digestion and after digestion. The main results show that organic meat is more contaminated than conventional meat in mean after production stage and after cooking although cooking reduces the contamination level. This work is a first step of refined risk assessment integrating different steps such as cooking and digestion in the context of chemical risk assessment similarly to current microbiological risk assessments., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Quantity and quality of fatty acids (FA) in diet influence CVD risk. Consequently, health authorities promote recommended dietary intakes for FA, looking for optimal intakes in a primary prevention of CVD perspective. In parallel, a few data are available detailing intakes in national populations. The objective of the present study was to perform a large analysis combining the data of the French National Survey INCA 2 on food consumption performed in 2006 and 2007, and the nutritional content of food consumed in France updated in 2013 by the French Information Centre on Food Quality, to explore in details the FA intakes in French adults using the most recent available data. To compare the discrepancies in the observed intake levels with the French recommended levels, a weighted fat adherence score was built combining intakes of the different FA. Individual scores were computed in relation to official recommendations, and potential explanatory factors were identified. These data show that SFA intakes are persistently higher than national recommendations, combined with low intakes of MUFA and PUFA, particularly long-chain n-3 FA. Only 14·6 % of the French population met DHA intake recommendation, 7·8 % for EPA and 21·6 % for SFA. This situation remains unfavourable in terms of primary prevention of CVD. Consuming fish and other sources of n-3 FA, living in the south of France, being female, having a higher education level, and low alcohol consumption were associated with a healthier fat adherence score.

The identification of the major associations of pesticides to which the population is exposed is the first step for the risk assessment of mixtures. Moreover, the interpretation of the mixtures through the individuals' diet and the characterization of potentially high-risk populations constitute a useful tool for risk management. This paper proposes a method based on Non-Negative Matrix Factorization which allows the identification of the major mixtures to which the French population is exposed and the connection between this exposure and the diet. Exposure data of the French population are provided by the Second French Total Diet Study. The NMF is implemented on consumption data to extract consumption systems which are combined with the residue levels to link dietary behavior with exposure to mixtures of pesticides. A clustering of the individuals is achieved in order to highlight clusters of individuals with similar exposure to pesticides/consumption habits. The model provides 6 main consumption systems, 6 associated mixtures of pesticides and the description of the population which is most exposed to each mixture. Two different ways to estimate the matrix providing the mixtures of pesticides to which the population is exposed are suggested. Their advantages in different contexts of risk assessment are discussed., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

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.

This article introduces an original methodology based on empirical likelihood, which aims at combining different food contamination and consumption surveys to provide risk managers with a risk measure, taking into account all the available information. This risk index is defined as the probability that exposure to a contaminant exceeds a safe dose. It is naturally expressed as a nonlinear functional of the different consumption and contamination distributions, more precisely as a generalized U-statistic. This nonlinearity and the huge size of the data sets make direct computation of the problem unfeasible. Using linearization techniques and incomplete versions of the U-statistic, a tractable "approximated" empirical likelihood program is solved yielding asymptotic confidence intervals for the risk index. An alternative "Euclidean likelihood program" is also considered, replacing the Kullback-Leibler distance involved in the empirical likelihood by the Euclidean distance. Both methodologies are tested on simulated data and applied to assess the risk due to the presence of methyl mercury in fish and other seafood.

This paper presents the study of a continuous-time piecewise-deterministic Markov process for describing the temporal evolution of exposure to a given food contaminant. The quantity X of food contaminant present in the body evolves through its accumulation after repeated dietary intakes on the one hand, and the pharmacokinetics behavior of the chemical on the other hand. In the dynamic modeling considered here, the accumulation phenomenon is modeled by a simple marked point process with positive i.i.d. marks, and elimination in between intakes occurs at a random linear rate theta X, randomness of the coefficient theta accounting for the variability of the elimination process due to metabolic factors. Via embedded chain analysis, ergodic properties of this extension of the standard compound Poisson dam with (deterministic) linear release rate are investigated, the latter being of crucial importance in describing the long-term behavior of the exposure process (X(t))t> or =0 and assessing values such as the proportion of time the contaminant body burden is over a certain threshold. We also highlight the fact that the exposure process is generally not directly observable in practice and establish a validity framework for simulation-based statistical methods by coupling analysis. Eventually, applications to methyl mercury contamination data are considered.

This article proposes statistical tools for quantitative evaluation of the risk due to the presence of some particular contaminants in food. We focus on the estimation of the probability of the exposure to exceed the so-called provisional tolerable weekly intake (PTWI), when both consumption data and contamination data are independently available. A Monte Carlo approximation of the plug-in estimator, which may be seen as an incomplete generalized U-statistic, is investigated. We obtain the asymptotic properties of this estimator and propose several confidence intervals, based on two estimators of the asymptotic variance: (i) a bootstrap type estimator and (ii) an approximate jackknife estimator relying on the Hoeffding decomposition of the original U-statistics. As an illustration, we present an evaluation of the exposure to Ochratoxin A in France.