Combining data from heterogeneous surveys for aggregate exposure: Application to children exposure to lead in France.

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.

Inadequate daily intakes of n-3 polyunsaturated fatty acids (PUFA) in the general French population of children (3-10 years) and adolescents (11-17 years): the INCA2 survey.

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.

Fatty acid dietary intake in the general French population: are the French Agency for Food, Environmental and Occupational Health & Safety (ANSES) national recommendations met?

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.

In vitro assessment of polychlorinated biphenyl bioaccessibility in meat: Influence of fat content, cooking level and consumer age on consumer uptake.

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.

A real-world implementation of a nationwide, long-term monitoring program to assess the impact of agrochemicals and agricultural practices on biodiversity.

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.

Postprandial Triglyceride-Rich Lipoproteins from Type 2 Diabetic Women Stimulate Platelet Activation Regardless of the Fat Source in the Meal.

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 B2 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.

Using empirical likelihood to combine data: application to food risk assessment.

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.

Very low inadequate dietary intakes of essential n-3 polyunsaturated fatty acids (PUFA) in pregnant and lactating French women: The INCA2 survey.

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.

Exposure assessment for dioxin-like PCBs intake from organic and conventional meat integrating cooking and digestion effects.

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.

Identification of pesticide mixtures and connection between combined exposure and diet.

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.

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.

A storage model with random release rate for modeling exposure to food contaminants.

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.

Incomplete generalized U-statistics for food risk assessment.

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.