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Background: Intakes of glutamate can be derived from its natural occurrence as a constituent of proteins, from the presence of free glutamate in certain fermented foods, and from the addition of glutamic acid and glutamates to foods as flavor-enhancing additives., Summary: Intakes of glutamate following hydrolysis of dietary proteins can be as high as 440 mg/kg bw/day for toddlers and small children. High-level intakes of glutamate from its natural occurrence  in foods or from the use of food additives, given very conservative assumptions about conditions of use, are -similar at around 80 mg/kg bw/day for toddlers and small children. Key Messages: The use of glutamic acid and glutamates as food additives makes a marginal contribution to total intakes of glutamate from all sources., (© 2018 The Author(s) Published by S. Karger AG, Basel.)

The 2018 Dietary Glutamate Workshop was organized and sponsored by the International Glutamate Technical Committee to provide a platform for a broad expert discussion on all relevant aspects of glutamate metabolism and safety in human nutrition. The participants reached a consensus with previous safety evaluations conducted by the global expert bodies, but contradicted the 2017 re-evaluation of dietary glutamates by the European Food Safety Authority, which proposed a group acceptable daily intake (ADI) of 30 mg/kg body weight per day. The participants of the Workshop concluded that the present knowledge on metabolism, kinetics, developmental and general toxicity of dietary glutamates did not warrant a change in the previous ADI of "not specified.", (© 2018 The Author(s) Published by S. Karger AG, Basel.)

European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database.

Fruit and vegetables make an important contribution to health, partly due to the composition of phytonutrients, such as carotenoids and polyphenols. The aim of the present study was to quantify the intake of fruit and vegetables across different European countries using food consumption data of increasing complexity: food balance sheets (FBS); the European Food Safety Authority (EFSA) Comprehensive Database; individual food consumption data from the UK National Diet and Nutrition Survey (NDNS). Across Europe, the average consumption of fruit and vegetables ranged from 192 to 824 g/d (FBS data). Based on EFSA data, nine out of fourteen countries consumed < 400 g/d (recommended by the WHO), although even in the highest-consuming countries such as Spain, 36 % did not reach the target intake. In the UK, the average consumption of fruit and vegetables was 310 g/d (NDNS data). Generally, phytonutrient intake increased in accordance with fruit and vegetable intake across all European countries with the exception of lycopene (from tomatoes), which appeared to be higher in some countries that consumed less fruit and vegetables. There were little differences in the average intake of flavanols, flavonols and lycopene in those who did or did not meet the 400 g/d recommendation in the UK. However, average intakes of carotenoid, flavanone, anthocyanidin and ellagic acid were higher in those who consumed >400 g/d of fruit and vegetables compared with those who did not. Overall, intakes of phytonutrients are highly variable, suggesting that while some individuals obtain healthful amounts, there may be others who do not gain all the potential benefits associated with phytonutrients in the diet.

Current guidelines for assessing human exposures to nutrients and other substances used in animal feed are based on methods used for veterinary pharmaceuticals. These methods assume high-level daily consumption of animal products and do not take account of differences between species or between consuming humans. A more detailed dietary modelling approach is described, which takes these factors into account as well as high-level consumption by different age groups. The proposed approach is evaluated in three case studies, iodine, selenium and astaxanthin, which have previously undergone thorough evaluation by EU authorities. When applied in a tiered approach, the proposed model provides results that are consistent with previous assessments and with results obtained using other modelling techniques. The results indicate that the method has the potential to provide a conservative, reliable and flexible alternative to existing approaches to intake estimation.

In some cases a single dose above an acceptable daily intake could elicit an adverse effect. In other cases a cumulative dose over several days may be necessary before an effect is expressed. Estimates of acute intake must relate to what is known about the toxicokinetics of the substance, in relation to the toxicological studies associated with the relevant end point. This is because estimates of intake can vary considerably over even a few days in some circumstances. Acute reference doses should therefore be qualified by an exposure interval. Default values can introduce considerable conservatism into intake estimates. Techniques for estimating acute intakes are very varied. They can range in complexity from conservative screening methods to sophisticated techniques designed to simulate real situations. Monte Carlo models allow for the distributions of chemical concentrations and food consumption patterns to be taken into account. For acute dietary risk assessments very high upper percentile cutoffs are sometimes applied, even as high as 99.9%. However, assumptions applied in such methods can lead to misleading results. Great care must also be used when interpreting such statistics because uncertainty and inaccuracy in the data increase considerably in the upper "tail" of the distribution.