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汇总统计数据的高暴露量(HESS):在欧洲食品安全局综合欧洲食品消费数据库中的应用

High Exposure from Summary Statistics (HESS): application to the EFSA comprehensive European food consumption database.

作者信息

Dempsey Paul

机构信息

a Dazult, Maynooth , Co. Kildare , Ireland.

出版信息

Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2018 Jan;35(1):20-28. doi: 10.1080/19440049.2017.1400695. Epub 2017 Nov 21.

Abstract

While intake and exposure assessments can be readily carried out for a number of countries using complete datasets, the majority of European intake data are only available in the form of summary statistics published by the European Food Safety Authority (EFSA). Only EFSA have access to the complete datasets which are used in scientific opinions it issues. The proposed High Exposure from Summary Statistics (HESS) method is derived from first principles, and compared to existing models used to estimate high consumer exposures from the EFSA Comprehensive European Food Consumption Database. The method is applied to recent US consumption data to test its usefulness for deterministic and probabilistic exposure models, where comparisons between model results and detailed exposure assessments are possible. HESS is shown to provide a modest overestimation of the actual high consumer exposure, with a level of consistency and predictability that is much better than existing methods used with the EFSA Comprehensive European Food Consumption Database.

摘要

虽然利用完整数据集可以很容易地对多个国家进行摄入量和暴露评估,但大多数欧洲摄入量数据仅以欧洲食品安全局(EFSA)发布的汇总统计数据形式提供。只有EFSA能够获取其发布的科学意见中所使用的完整数据集。拟议的汇总统计数据高暴露量(HESS)方法是从第一原理推导出来的,并与用于从EFSA综合欧洲食品消费数据库估计高消费者暴露量的现有模型进行了比较。该方法应用于美国近期的消费数据,以测试其对确定性和概率性暴露模型的实用性,在这些模型中可以对模型结果与详细暴露评估进行比较。结果表明,HESS对实际高消费者暴露量有适度高估,其一致性和可预测性水平远优于与EFSA综合欧洲食品消费数据库一起使用的现有方法。

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