Update of Dietary Supplement Label Database Addressing on Coding in Italy

IF 2.2 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Data Pub Date : 2023-09-13 DOI:10.3390/data8090142
Giorgia Perelli, Roberta Bernini, Massimo Lucarini, Alessandra Durazzo
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引用次数: 0

Abstract

Harmonized composition data for foods and dietary supplements are needed for research and for policy decision making. For a correct assessment of dietary intake, the categorization and the classification of food products and dietary supplements are necessary. In recent decades, the marketing of dietary supplements has increased. A food supplements-based database has, as a principal feature, an intrinsic dynamism related to the continuous changes in formulations, which consequently leads to the need for constant monitoring of the market and for regular updates of the database. This study presents an update to the Dietary Supplement Label Database in Italy focused on dietary supplements coding. The updated dataset here, presented for the first time, consists of the codes of 216 dietary supplements currently on the market in Italy that have functional foods as their characterizing ingredients, throughout the two commonly most used description and classification systems: LanguaLTM and FoodEx2-. This update represents a unique tool and guideline for other compilers and users for applying classification coding systems to dietary supplements. Moreover, this updated dataset represents a valuable resource for several applications such as epidemiological investigations, exposure studies, and dietary assessment.
意大利膳食补充剂标签数据库地址编码的更新
研究和决策需要统一的食品和膳食补充剂成分数据。为了正确评估膳食摄入量,对食品和膳食补充剂进行分类和分类是必要的。近几十年来,膳食补充剂的市场营销有所增加。以食品补充剂为基础的数据库的主要特点是具有与配方不断变化有关的内在动力,因此需要不断监测市场和定期更新数据库。本研究更新了意大利膳食补充剂标签数据库,重点关注膳食补充剂编码。本文首次发布的更新数据集包括目前意大利市场上以功能食品为特征成分的216种膳食补充剂的代码,涵盖了两种最常用的描述和分类系统:LanguaLTM和FoodEx2-。该更新为其他编译者和用户提供了将分类编码系统应用于膳食补充剂的独特工具和指南。此外,这个更新的数据集为流行病学调查、暴露研究和饮食评估等几个应用提供了宝贵的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Data
Data Decision Sciences-Information Systems and Management
CiteScore
4.30
自引率
3.80%
发文量
0
审稿时长
10 weeks
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