为预防疾病提供个性化的饮食建议:概念和经验
1School of Life Sciences, Technical University of Munich, 85354, Freising, Germany. contact@hdaniel.de.
Pflugers Archiv : European journal of physiology
|January 24, 2025
概括
个性化营养 (PN) 最初专注于遗传学,但后来使用生物医学数据的尝试取得了有限的成功. 新的方法整合了环境数据和人工智能,以提供更有效,更容易获得的饮食和生活方式建议.
科学领域:
- 营养科学 营养科学
- 基因组学就是基因组学.
- 公共卫生 公共卫生
背景情况:
- 个性化营养 (PN) 是人类基因组项目后出现的,最初使用遗传数据为饮食和生活方式建议.
- 随后的PN试验包括微生物组和持续的葡萄糖监测,但科学评估显示显著优势有限.
- 批评强调PN的公共卫生影响有限,吸引了狭窄的人口.
研究的目的:
- 探索个性化饮食建议的新途径,超越纯粹的生物医学数据.
- 评估将食品环境和数字技术整合到定制推中的潜力.
- 利用人工智能开发复杂的,按需的饮食和生活方式指导.
主要方法:
- 评估个体的整个食物环境,包括能力和限制.
- 利用数字环境进行数据收集和双向通信.
- 应用人工智能方法用于复杂的决策和定制建议的产生.
主要成果:
- 基于有限的遗传数据的早期PN方法显示出混合的结果.
- 包含额外的生物医学措施并不总是比通用建议带来显著的好处.
- 结合环境因素和人工智能的新PN策略显示出更广泛应用的希望.
结论:
- 个性化营养需要一个整体的方法,超越遗传学和基本的生物医学数据.
- 整合食品环境数据和人工智能可以创造更有效和更容易获得的个性化饮食和生活方式干预措施.
- 未来的PN战略应侧重于更广泛的公共卫生影响和可访问性.
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