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CGMacros:一个试点科学数据集,用于个性化的营养和饮食监测

Anurag Das¹, David Kerr², Namino Glantz³

¹Texas A&M University, College Station, 77843, USA.

Scientific data

|September 25, 2025

概括

我们创建了CGMacros,这是一个独特的数据集,将食物摄入量,宏观营养素和持续葡萄糖监测 (CGM) 数据联系起来. 该资源支持个性化的营养研究和对2型糖尿病等疾病的自动饮食监测.

科学领域:

生物医学信息学生物医学信息学
营养科学营养科学
代谢性疾病研究研究

背景情况:

准确的食物摄入量跟踪对于管理2型糖尿病 (T2D) 和肥胖至关重要.
现有的公共数据集缺乏全面的数据,特别是食品宏观营养素和持续葡萄糖测量 (CGM).
拥有丰富营养和代谢数据的专有数据集限制了更广泛的研究可访问性.

研究的目的:

推出CGMacros,这是第一个公开可用的多式联运数据集.
弥合研究数据的差距,以实现个性化的营养和自动化饮食监测.
促进与饮食有关的疾病管理的学术研究.

主要方法:

在10天内从45名参与者 (健康,糖尿病前期,T2D) 收集了多式联络数据.
包括活动追踪器的数据,两个CGM,食物照片和宏观营养素信息.
收集了参与者的人口统计,人体统计,血液和肠道微生物组数据.

主要成果:

CGMacros提供了一个新的,综合数据集,将饮食摄入量与生理反应联系起来.
该数据集捕捉了自由生活的食物消费与已知的宏观营养素变化.
包含丰富的数据,包括各种健康状况的CGM,活动和微生物群概况.

结论:

CGMacros民主化了个性化营养和自动化饮食监测方面的研究.
这一数据集对于开发用于疾病预防和管理的算法至关重要.
鼓励创建更大的,类似的公共数据集,以促进营养科学.

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