Association of number of bites and eating speed with energy intake: Wearable technology results under free-living conditions.
Association of number of bites and eating speed with energy intake: Wearable technology results under free-living conditions.
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DOI：
10.1016/j.appet.2021.105653
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发表时间：
2021-12-01
期刊：
影响因子：
5.4
通讯作者：
Lin AW
中科院分区：
文献类型：
--
作者：
Alshurafa N;Zhang S;Romano C;Zhang H;Pfammatter AF;Lin AW
个性化的体重管理策略越来越受到关注。然而，关于饮食习惯和与能量摄入的关联的知识有限，并且当前的技术限制了自由生活情况下的评估。我们在自由生活条件下使用可穿戴相机评估了饮食行为和一天中的时间与能量摄入之间的关联，并探讨了肥胖是否会改变这种关联。16名参与者（50%患有肥胖症）使用可穿戴鱼眼相机记录了14天的自由生活饮食行为。视频由受过训练的注释者观看，他们确认了每次进食的叮咬次数、进食速度和时间。能量摄入量由一名训练有素的营养师进行24小时饮食回忆。在所有参与者中，更大的叮咬次数、降低的进食速度和增加的BMI显著预测了更高的能量摄入（P < 0.05）。肥胖与叮咬次数、进食速度或一天中的时间之间没有显著的相互作用（p > 0.05）。在没有肥胖的参与者中，更大的叮咬次数和降低的进食速度与更高的能量摄入显著相关。结果表明，在自由生活的条件下，更多的叮咬和较慢的进食速度预测更高的能量摄入量时，检查消费的食物与饮料。肥胖并没有改变这些关联。研究结果强调了饮食行为如何影响能量平衡，并可以使用可穿戴技术为体重管理干预提供信息。
Personalized weight management strategies are gaining interest. However, knowledge is limited regarding eating habits and association with energy intake, and current technologies limit assessment in free-living situations. We assessed associations between eating behavior and time of day with energy intake using a wearable camera under free-living conditions and explored if obesity modifies the associations. Sixteen participants (50% with obesity) recorded free-living eating behaviors using a wearable fish-eye camera for 14 days. Videos were viewed by trained annotators who confirmed number of bites, eating speed, and time of day for each eating episode. Energy intake was determined by a trained dietitian performing 24-h diet recalls. Greater number of bites, reduced eating speed, and increased BMI significantly predicted higher energy intake among all participants (P < 0.05, each). There were no significant interactions between obesity and number of bites, eating speed, or time of day (p > 0.05). Greater number of bites and reduced eating speed were significantly associated with higher energy intake in participants without obesity. Results show that under free-living conditions, more bites and slower eating speed predicted higher energy intake when examining consumption of foods with beverages. Obesity did not modify these associations. Findings highlight how eating behaviors can impact energy balance and can inform weight management interventions using wearable technology.
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