个性化营养:对数据使用和融合的挑战,机会和指导原则的观点
Sharon M Donovan1, Mariette Abrahams2, Joshua C Anthony3
1Personalized Nutrition Initiative, Carl R. Woese Institute for Genomic Biology, and the Department of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, IL, USA.
Critical reviews in food science and nutrition
|February 5, 2025
概括
个性化营养 (PN) 使用综合数据为量身定制的健康指导. 通过协作和标准化解决数据挑战,可以提高PN的可访问性和有效性.
科学领域:
- 营养科学 营养科学
- 数据科学数据科学数据科学
- 公共卫生 公共卫生
背景情况:
- 个性化营养 (PN) 通过整合健康,生活方式和行为数据提供量身定制的饮食指导.
- 技术进步增加了数据的可用性,但在数据收集,集成和分析方面带来了挑战.
- 研讨会确定了个性化营养的关键数据领域和挑战.
研究的目的:
- 探索个性化营养数据中的挑战和机遇.
- 确定必要的数据领域,以有效实施PN.
- 提出在PN中负责任的数据集成和使用策略.
主要方法:
- 专家研讨会召开了.
- 讨论三个核心数据领域:健康/生物,社会/行为/环境和消费者购买.
- 探索数据标准化,安全共享和融合技术.
主要成果:
- 强调需要跨学科的合作,以标准化数据收集,并实现安全共享.
- 强调了尊重隐私的数据融合技术的重要性,以建立信任.
- 强调需要具有代表性的数据集,包括服务不足的人群,以获得公平的PN服务.
结论:
- 通过合作和负责任的整合来解决数据挑战对PN至关重要.
- 标准化,安全和代表性的数据集是提高PN有效性的关键.
- 公平获得个性化营养需要克服与数据相关的障碍.
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