在基于应用程序的食物日记中观察到的卡路里补偿模式
Amruta Pai1, Ashutosh Sabharwal1
1Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
Nutrients
|September 28, 2023
概括
这项研究引入了一种新的方法来跟踪日常生活中的卡路里补偿,使用食物日记应用程序. 它揭示了个人的饮食模式,并确定了与不健康的体重增加相关的行为.
科学领域:
- 行为科学 行为科学
- 营养科学 营养科学
- 计算健康 计算健康
背景情况:
- 对食物摄入的自我调节对于体重管理至关重要.
- 卡路里补偿,根据之前的餐饮调整摄入量,是自我调节的一个关键方面.
- 以前的研究主要使用受控预加载测试,限制了对现实世界补偿行为的理解.
研究的目的:
- 提出和验证一种新的方法来测量自由生活条件下的卡路里补偿概况,使用基于应用程序的食品日记数据.
- 分析个人补偿模式,包括补偿不足,超额,非补偿和精确补偿.
- 识别与不良补偿性饮食和潜在体重增加相关的行为表型.
主要方法:
- 利用了来自1622名MyFitnessPal用户的广泛观察性食物日记数据.
- 开发了一种方法来分析薪酬概况作为随时间的分布,而不是单个指数.
- 验证了四周的数据足以准确地描述用户补偿概况.
主要成果:
- 餐点补偿比一天级补偿更为普遍.
- 晚餐补偿比午餐补偿更频繁.
- 用户倾向于过度补偿错过的卡路里,而不是多余的卡路里,精确的补偿是最不常见的.
- 糟糕的补偿行为与较低的每日卡路里目标的坚持相关.
结论:
- 提出的方法有效地描述了自由生活环境中的个人卡路里补偿配置.
- 确定了餐点和日间补偿的具体模式,以及过度/不足补偿的趋势.
- 这种方法可以识别早期体重增加标志物的行为表型,有助于预防策略.
相关概念视频
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01:30Regulation of Food Intake
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01:25Metabolic Rate
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01:18Metabolic States of the Body: The Postabsorptive State
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01:28Compensation Mechanisms
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