个性化营养中的数据:跨越生物医学,心理行为和食品环境方法,实现全人口影响
Jakob Linseisen1, Britta Renner2, Kurt Gedrich3
1Epidemiology, Medical Faculty, University of Augsburg, University Hospital Augsburg, Augsburg, Germany; Institute of Information Processing, Biometry and Epidemiology, Ludwig-Maximilians University, Munich, Germany.
Advances in nutrition (Bethesda, Md.)
|January 22, 2025
概括
个性化营养 (PN) 显示有限的成功,但可以改进. 整合生物医学,行为和环境数据的自适应系统提供了动态的,广泛可访问的饮食指导,以获得更好的健康结果.
科学领域:
- 营养科学 营养科学
- 数字健康数字健康
- 行为科学 行为科学
背景情况:
- 个性化营养 (PN) 旨在通过个人数据为健康改善量身定制饮食建议.
- 目前的PN方法在广泛改变饮食或条件管理方面取得了有限的成功.
- 普尼经常针对特定的子群体,缺乏广泛的人口影响.
研究的目的:
- 解决当前个性化营养策略的局限性.
- 引入适应型个性化营养咨询系统的概念.
- 概述一个全面的方法,以有效,人口一级PN.
主要方法:
- 整合生物医学/健康表型,行为特征和食品环境数据.
- 使用先进的数字工具 (如传感器) 和人工智能.
- 开发用于目标和行为变化过程的动态,实时和现场适应系统.
主要成果:
- 拟议的自适应系统将静态和动态数据混合在一起,以实现个性化的目标和行为改变.
- 综合数据集成允许定制"什么"和"如何"改变饮食.
- 先进的数字和人工智能方法对于成功的数据集成至关重要.
结论:
- 适应型个性化营养咨询系统为目前的PN缺陷提供了一个有希望的解决方案.
- 这种综合的方法可以将PN从精英重点转变为广泛可访问的健康工具.
- 基于个人数据的动态适应是有意义的人口水平健康益处的关键.
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