Fontana Juan M, Higgins Janine A, Schuckers Stephanie C, Bellisle France, Pan Zhaoxing, Melanson Edward L, Neuman Michael R, Sazonov Edward
Electrical and Computer Engineering Department, The University of Alabama, Tuscaloosa, AL 35487, United States.
Department of Pediatrics, University of Colorado Anschutz Medical Center, Aurora, CO 80045, United States.
Appetite. 2015 Feb;85:14-21. doi: 10.1016/j.appet.2014.11.003. Epub 2014 Nov 7.
Current, validated methods for dietary assessment rely on self-report, which tends to be inaccurate, time-consuming, and burdensome. The objective of this work was to demonstrate the suitability of estimating energy intake using individually-calibrated models based on Counts of Chews and Swallows (CCS models). In a laboratory setting, subjects consumed three identical meals (training meals) and a fourth meal with different content (validation meal). Energy intake was estimated by four different methods: weighed food records (gold standard), diet diaries, photographic food records, and CCS models. Counts of chews and swallows were measured using wearable sensors and video analysis. Results for the training meals demonstrated that CCS models presented the lowest reporting bias and a lower error as compared to diet diaries. For the validation meal, CCS models showed reporting errors that were not different from the diary or the photographic method. The increase in error for the validation meal may be attributed to differences in the physical properties of foods consumed during training and validation meals. However, this may be potentially compensated for by including correction factors into the models. This study suggests that estimation of energy intake from CCS may offer a promising alternative to overcome limitations of self-report.
目前,经过验证的膳食评估方法依赖于自我报告,而自我报告往往不准确、耗时且繁琐。这项工作的目的是证明基于咀嚼和吞咽次数(CCS模型)的个体校准模型用于估计能量摄入的适用性。在实验室环境中,受试者食用了三顿相同的餐食(训练餐)和一顿内容不同的第四餐(验证餐)。通过四种不同的方法估计能量摄入:称重食物记录(金标准)、饮食日记、照片食物记录和CCS模型。使用可穿戴传感器和视频分析来测量咀嚼和吞咽次数。训练餐的结果表明,与饮食日记相比,CCS模型的报告偏差最低且误差较小。对于验证餐,CCS模型显示的报告误差与日记法或照片法无异。验证餐误差的增加可能归因于训练餐和验证餐期间所食用食物的物理特性差异。然而,这可能通过在模型中纳入校正因子来潜在地弥补。这项研究表明,通过CCS估计能量摄入可能为克服自我报告的局限性提供一种有前景的替代方法。