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欧洲市场研究数据在食品添加剂膳食暴露建模中的潜在应用。

The potential application of European market research data in dietary exposure modelling of food additives.

作者信息

Tennant David Robin, Bruyninckx Chris

机构信息

a Food Chemical Risk Analysis , East Sussex , UK.

b SR&Q Consult , Kampenhout , Belgium.

出版信息

Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2018 Mar;35(3):412-424. doi: 10.1080/19440049.2017.1400187. Epub 2017 Nov 21.

DOI:10.1080/19440049.2017.1400187
PMID:29098949
Abstract

Consumer exposure assessments for food additives are incomplete without information about the proportions of foods in each authorised category that contain the additive. Such information has been difficult to obtain but the Mintel Global New Products Database (GNPD) provides information about product launches across Europe over the past 20 years. These data can be searched to identify products with specific additives listed on product labels and the numbers compared with total product launches for food and drink categories in the same database to determine the frequency of occurrence. There are uncertainties associated with the data but these can be managed by adopting a cautious and conservative approach. GNPD data can be mapped with authorised food categories and with food descriptions used in the EFSA Comprehensive European Food Consumption Surveys Database for exposure modelling. The data, when presented as percent occurrence, could be incorporated into the EFSA ANS Panel's 'brand-loyal/non-brand loyal exposure model in a quantitative way. Case studies of preservative, antioxidant, colour and sweetener additives showed that the impact of including occurrence data is greatest in the non-brand loyal scenario. Recommendations for future research include identifying occurrence data for alcoholic beverages, linking regulatory food codes, FoodEx and GNPD product descriptions, developing the use of occurrence data for carry-over foods and improving understanding of brand loyalty in consumer exposure models.

摘要

如果没有关于每个授权类别中含有该添加剂的食品比例的信息,食品添加剂的消费者暴露评估就是不完整的。此类信息一直难以获取,但英敏特全球新产品数据库(GNPD)提供了过去20年欧洲各地产品发布的信息。可以搜索这些数据,以识别产品标签上列出特定添加剂的产品,并将这些数量与同一数据库中食品和饮料类别的总产品发布数量进行比较,以确定出现频率。这些数据存在不确定性,但可以通过采取谨慎和保守的方法来管理。GNPD数据可以与授权食品类别以及欧洲食品安全局综合欧洲食品消费调查数据库中用于暴露建模的食品描述进行映射。当以出现百分比表示数据时,可以以定量方式纳入欧洲食品安全局食品添加剂和营养源添加物专家委员会的“品牌忠诚/非品牌忠诚暴露模型”。防腐剂、抗氧化剂、色素和甜味剂添加剂的案例研究表明,在非品牌忠诚的情况下,纳入出现数据的影响最大。对未来研究的建议包括确定酒精饮料的出现数据、将监管食品代码、FoodEx和GNPD产品描述联系起来、开发结转食品出现数据的用途以及提高对消费者暴露模型中品牌忠诚度的理解。

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