Energy intake estimation from counts of chews and swallows
•Energy intake estimates were obtained for three identical meals and a different meal.•Suitability of models based on Counts of Chews and Swallows (CCS) was evaluated.•Compared to traditional methods, CCS models showed the lowest bias for repeated meals.•Food properties may affect the performance of...
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Veröffentlicht in: | Appetite 2015-02, Vol.85, p.14-21 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Energy intake estimates were obtained for three identical meals and a different meal.•Suitability of models based on Counts of Chews and Swallows (CCS) was evaluated.•Compared to traditional methods, CCS models showed the lowest bias for repeated meals.•Food properties may affect the performance of CCS models.•Energy intake estimation by CCS does not require user input.
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. |
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ISSN: | 0195-6663 1095-8304 |
DOI: | 10.1016/j.appet.2014.11.003 |