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Intake, g kgbw 1 day 1 0.022 0.057 0.061 0.037 0.100 0.277
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Exposure, % 8 21 22 13 36 100
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Reference 67.
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TABLE 2.1.3 Summary of some exposure estimates for acrylamide. Estimated dietary intake, g kgbw 1 day 1 Organization, country BfR, Germany (68) NFAS, Norway (69) Population/Sex (age) All, 15 18 Males Females Males (13) Females (13) All (>15) All (3 14) All (18 74) All (1 97) All (1 6) All (7 18) Males (19 64) Females (19 64) All (1.5 4.5) All (2+) All (2 5) Mean 1.1 0.49 0.46 0.52 0.49 0.5 1.25 0.45 0.48 1.04 0.71 0.4 0.3 1.0 0.44 1.06 High-level 3.2a 1.04b 0.86b 1.35b 1.2b 0.98a 2.54a 1.03a 0.60a 1.1a 0.9a 0.6c 0.6c 1.8c 0.95b 2.33b
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AFSSA, France (70) SNFA, Sweden (71) WVA, the Netherlands (72) FSA, UK (73)
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The UK estimate is for consumers only; other estimates are mostly for the entire population. a 95th percentile. a 90th percentile. a 97.5th percentile.
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There have been many estimates of acrylamide intake, some of which are detailed in Table 2.1.3 (68 74). When comparing dietary exposure estimates, it is important to remember their limitations. Exposure may be calculated using deterministic models (actual acrylamide concentrations are combined with consumption data) or by using probabilistic models (here the distribution of acrylamide concentrations is combined with the distribution of consumption data). When using deterministic models to estimate dietary exposure (where a mean, or possibly a maximum, contaminant concentration is assumed), one must be aware of how the distribution of contaminant concentrations may affect the estimated exposure (cf. Fig. 2.1.1 which shows the wide spread of acrylamide concentrations found in samples of French fries recorded in the European Union acrylamide monitoring database). There are many limitations to exposure estimates. The main limitations focus around data collection and the size of occurrence and consumption datasets. Any estimate will only be valid for those members of the population whose eating habits have been studied. If small datasets for occurrence and consumption data are used, the resulting exposure estimate will not necessarily be representative for people outside of the studied population. Any exposure estimate also makes a number of assumptions concerned with what foods are consumed and how contaminant concentrations might be affected by process-
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ing, and a number of other assumptions used to simplify calculations. In short, it is prudent to remember that exposure estimates are always only estimates. Direct comparison of exposure estimates is not always possible. Differences between estimates can occur owing to different methods being used to calculate exposure (including data collection and estimate calculation) and because different statistical approaches are used (exposure can be calculated for entire populations, or for those parts of the population that actually consume the foods of interest). Such differences must be taken into account before considering how differences between national diets might relate to differences in actual exposures. Table 2.1.3 shows that acrylamide exposures range from 0.3 to 3.2 g kgbw 1 day 1. There is considerable variation in the estimated exposures. Of course, there is considerable error involved when estimating an average exposure across all populations: dietary habits vary greatly from country to country. In addition, individual country estimates will have been performed in different ways. However, an average mean intake can be taken to be ca. 0.4 g kgbw 1 day 1 and an average intake for a high-level consumer to be ca. 1 g kgbw 1 day 1. Those foods that contribute most to dietary intake will differ from country to country, according to the national diet and the way in which foods are prepared. Generally, the foods that contribute the most to dietary intake of acrylamide are fried potato products (such as French fries and crisps), readyto-eat breakfast cereals, bread and bakery products, and coffee. Closer inspection of national intake estimates reveals how overall dietary intake of acrylamide varies from region to region. For example, potatoes (and potato products) are estimated to contribute 38% to the total dietary intake of acrylamide for US consumers; contributions from bread (toast and soft bread) and coffee are 9% and 7%, respectively (75). Conversely, the contribution by bread and coffee is higher in Europe. Potatoes (fried, crisps, and French fries) have been estimated to contribute 33% of total intake in Norway, while coffee and bread were shown to contribute 28% and 20.1%, respectively (69). This trend for higher dietary intakes from consumption of coffee and bread was also observed in Sweden (71). However, higher contribution from potatoes was observed in the Netherlands: potatoes (French fries and comparable products, and crisps) were estimated to contribute an astonishing 52% of the total acrylamide intake (entire population, 1 97 years of age); the contributions were found to be even higher for children: 58% for 1-year-olds and 69% for 7- to 18-year-olds (72). Several studies have been undertaken to investigate the effects of reducing the concentrations of acrylamide in food on dietary intake. In 2004 the US FDA presented work on the potential impact of reducing acrylamide levels in different food groups (76). The 2004 US exposure assessment for the entire population was rerun several times; each rerun assumed that one of the major food groups contributing to acrylamide exposure contained no acrylamide. Their investigations demonstrated that reducing acrylamide levels in just one food group would have little impact on the overall dietary intake of acrylamide
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