杂货DB:在杂货店中加工食品的流行情况
Babak Ravandi1, Gordana Ispirova2, Michael Sebek1
1Network Science Institute and Department of Physics, Northeastern University, Boston, USA.
medRxiv : the preprint server for health sciences
|June 17, 2024
概括
杂货数据库 (GroceryDB) 是一个包含5万多种食品的新数据库,它揭示了食品的加工程度. 这种资源使消费者和政策制定者能够做出更健康的食物选择,并改革食品供应.
科学领域:
- 营养科学 营养科学
- 数据科学数据科学数据科学
- 消费者健康 消费者健康
背景情况:
- 消费者的饮食选择显著影响长期健康.
- 关于食品加工水平的信息往往不易获得,这阻碍了明智的决策.
- 高度加工食品与不良健康结果有关.
研究的目的:
- 引入GroceryDB,这是一个对食品及其加工水平的全面数据库.
- 展示大数据如何用于评估食品加工,并为消费者和决策者提供信息.
- 系统地了解食品加工的程度,并确定更健康的替代品.
主要方法:
- 编制了一个数据库 (GroceryDB),包含来自主要零售商 (沃尔玛,Target,全食) 的5万多种食品.
- 分析了配料清单和营养数据,以确定食品加工的程度.
- 按商店,食品类别和价格范围分类处理数据.
- 量化了1000多种成分对超级加工的贡献.
主要成果:
- 在不同食品类别和零售商店中观察到食品加工程度的显著差异.
- GroceryDB提供了对原料模式和加工水平的可扩展分析.
- 该数据库量化了单个成分对整体食品加工的影响.
结论:
- GroceryDB提供对食品加工信息的系统访问,赋予消费者和决策者权力.
- 这些发现突显出需要在食品加工中提高透明度.
- 可访问的数据可以引导消费者选择更少加工的选择,并为食品供应改革提供信息.
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