Simulants, food concentration data

One of the main issues with concentration data is how the non-detectable (ND) values are treated. In many instances the substance(s) of interest is non-detectable in either food simulants or real foodstuffs. In a UK FSA survey (2000) for BADGE (bisphenol A diglycidyl ether) in caimed foodstuffs, in more than 95% (105 of III targeted samples tested) of the foodstuffs tested the levels were non-detectable. Using targeted foodstuffs in any surveillance will always skew any results to a higher level, in that only foodstuffs considered most likely to contain the substance will typically be analysed. 

Food surveillance surveys give concentration values in either p,g/kg (ppb) or mg/kg (ppm). However, concentration data derived using simulants normally give results in pg/dm or mg/dm, therefore in order to relate these values to concentrations in foodstuffs it is necessary to know the actual surface to... 

The USFDA approach to assessing exposure to migrants from FCMs is explained in CFSAN/Office of Food Additive Safety, April 2002 and is available on their web site (http //www.cfsan.fda.gov/). It describes the use of exposure estimates for use in food contact notifications (FCNs) which would normally be based upon simulant rather than food migration data, as is the case for new materials. The USFDA approach is described in more detail in Chapter 2. In the USFDA approach a consumption factor is combined with a food distribution factor and concentration data to derive an estimate of exposure from all food types and all FCMs containing the substance of interest. 

AFBi dietary exposure estimates were assessed in Japan based on food consumption data from the 2005 National Health and Nutrition Survey for 2 consecutive days (17 827 individuals). Surveillance data on AFBi concentration levels were available from a retail food survey, with samples purchased in a random manner from local supermarkets and small retail shops in all parts of Japan from the summer of 2004 to the winter of 2006 (Sugita-Konishi et al., 2007). Foods analysed included peanut, peanut butter, chocolate, pistachio, spices, almond, job s tears tea and buckwheat. A probabilistic approach was used to simulate the dietary exposure distributions in each age group with three different scenarios of MLs of AFT in tree nuts (10, 15 and 20 pg/kg), following the same methodology as described previously for the EFSA opinion and assuming a lognormal distribution for occurrence data. 

THERdbASE contains two major modules, namely a Database Module and a Model Base Module. The Database Module relates information from exposure, dose and risk-related data files, and contains information about the following population distributions, location/activity patterns, food-consumption patterns, agent properties, agent sources (use patterns), environmental agent concentrations, food contamination, physiological parameters, risk parameters and miscellaneous data files. The Model Base Module provides access to exposure dose and risk-related models. The specific models included with the software are as follows Model 101, subsetting activity pattern data Model 102, location patterns (simulated) Model 103, source (time application) Model 104, source (instantaneous application) Model 105, indoor air (two zones) Model 106, indoor air (n zones) Model 107, inhalation exposure (BEAM) Model 108, inhalation exposure (multiple chemicals) Model 109, dermal dose (film thickness) Model 110, dose scenario (inhalation/dermal) Model 201, soil exposure (dose assessment). 

FIGURE 7.1 Approximate mean BPA concentrations in baby bottles and canned food or beverages compared to that in plasma and the placenta (Schonfelder et al., 2002). Sources Canned food data is based on Cao et al. s (2011) study. Canned beverage data is from Geens et al. s (2010) study. Baby bottle data are variable because of the different temperatures, leach times, and simulants used. 

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