Division of Human Nutrition, Wageningen University (WU), Wageningen NL-6703 HD, the Netherlands.
Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2010 Apr;27(4):433-46. doi: 10.1080/19440040903420614.
This study aimed to compare different methods of assessing dietary exposure to flavourings in the context of a stepwise approach. The dietary exposure to four flavourings--raspberry ketone, glycyrrhizinic acid, coumarin, and caffeine--was determined. When dietary exposure exceeded the safety limits, the need for more detailed assessment using less aggregated data was judged necessary. First, screening methods--maximized survey-derived daily intake (MSDI), single-portion exposure technique (SPET), and modified theoretical added maximum daily intake (mTAMDI)--were applied. Next, individual food consumption data were used for creating models with different levels of detail to identify the foods: a model based on food groups and models based on food items. These were collected from 121 Dutch adults using a standardized 2 x 24-h dietary recall (EPIC-Soft) in the European Food Consumption Validation (EFCOVAL) study. Three food item models were developed: without improvements of the flavouring descriptor built in the software; with improvements; and with use of non-specified flavour descriptors. Based on the results of at least one of the three screening methods, refined assessment was necessary for raspberry ketone, glycyrrhizinic acid, and caffeine. When applying the food group model, the need for refinement was indicated for the four flavourings. When applying the food item models, only glycyrrhizinic acid and caffeine presented dietary exposure above the safety limits. In the raspberry ketone case, dietary exposure increased when improvements in food description were considered. The use of non-specified flavour descriptors hardly changed the results. The collection of detailed food consumption data at the individual level is useful in the dietary exposure assessment of these flavourings.
本研究旨在比较不同方法来评估调味剂暴露情况,这些方法是分阶段进行的。本研究评估了四种调味剂——覆盆子酮、甘草酸、香豆素和咖啡因——的膳食暴露情况。当膳食暴露超过安全限量时,需要使用更详细的评估方法,这些方法使用的是较少聚合的数据。首先,应用了筛选方法——最大调查衍生日摄入量(MSDI)、单次暴露技术(SPET)和改良理论最大日摄入量(mTAMDI)。接下来,使用个体食物消费数据创建具有不同详细程度的模型,以确定食物:基于食物组的模型和基于食物项的模型。这些数据是在欧洲食品消费验证(EFCOVAL)研究中,使用标准化的 2×24 小时膳食回忆(EPIC-Soft)从 121 名荷兰成年人中收集的。为了评估覆盆子酮、甘草酸和咖啡因,开发了三种食物项模型:一种是在软件中没有改进调味剂描述的模型;一种是改进后的模型;还有一种是使用非特定的调味剂描述的模型。基于至少一种筛选方法的结果,需要对覆盆子酮、甘草酸和咖啡因进行更详细的评估。当应用食物组模型时,四种调味剂都需要进行细化。当应用食物项模型时,只有甘草酸和咖啡因的膳食暴露超过了安全限量。在考虑改进食物描述时,覆盆子酮的膳食暴露增加。使用非特定的调味剂描述几乎不会改变结果。在这些调味剂的膳食暴露评估中,收集个体层面的详细食物消费数据是有用的。