食品和你:个性化营养的数字队列
Harris Héritier1, Chloé Allémann1, Oleksandr Balakiriev1
1Digital Epidemiology Lab, School of Life Sciences, School of Computer and Communication Sciences, EPFL, Lausanne, Switzerland.
PLOS digital health
|November 30, 2023
概括
数字队伍通过远程收集每日数据来实现个性化的营养研究. "食物与你"研究显示了高保留率和数据质量,为未来的营养科学验证了这种方法.
科学领域:
- 营养科学 营养科学
- 生物技术是生物技术.
- 数字健康数字健康
背景情况:
- 营养对健康有重大影响,微生物群和饮食反应之间的联系正在出现.
- 个性化营养需要详细的,现实世界的个人数据,这是很难通过传统的临床研究获得的.
- 数字队列为现场,日常数据收集提供解决方案,但在参与者保留和数据完整性方面面临挑战.
研究的目的:
- 描述该协议的协议.
- 食物与你 食物与你
- 个性化营养的数字队列研究.
- 报告参与者保留率,评估收集数据的质量和可靠性.
- 评估数字队列对个性化营养研究的可行性.
主要方法:
- "食物与你"研究为1000多名参与者注册了2至4周的时间.
- 参与者通过数字工具远程跟踪食物摄入量,体育活动,肠道微生物群和血糖.
- 通过各种验证工作,严格评估数据质量.
主要成果:
- 从315126道菜中收集了超过4600万卡路里的营养数据.
- 记录了1,470,030次血糖测量和49,110次调查反应.
- 实现了高保留率 (>60%) 和可靠的,高分辨率的饮食数据.
结论:
- 数字队列对于在个性化营养研究中收集全面,高质量的数据是有效的.
- "食物与你"研究表明参与者保留率高,数据可靠性高.
- 这种方法为数字队列作为个性化营养研究的标准铺平了道路.
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