title: Energy intake estimation from counts of chews and swallows.
abstract: 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.
authors.affiliation: Electrical and Computer Engineering Department, The University of Alabama, Tuscaloosa, AL 35487, United States.
authors.forename: Juan M
authors.initials: JM
authors.lastname: Fontana
authors.affiliation: Department of Pediatrics, University of Colorado Anschutz Medical Center, Aurora, CO 80045, United States.
authors.forename: Janine A
authors.initials: JA
authors.lastname: Higgins
authors.affiliation: Department of Electrical and Computer Engineering, Clarkson University, Potsdam, NY 13699, United States.
authors.forename: Stephanie C
authors.initials: SC
authors.lastname: Schuckers
authors.affiliation: Nutritional Epidemiology Research Unit- UMR U557 INSERM, U1125 INRA, CNAM, CRNH-IdF, Paris 13 University, Bobigny, 93017, France.
authors.forename: France
authors.initials: F
authors.lastname: Bellisle
authors.affiliation: Research Institute, Children's Hospital Colorado, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, United States.
authors.forename: Zhaoxing
authors.initials: Z
authors.lastname: Pan
authors.affiliation: Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, United States; Division of Geriatric Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, United States.
authors.forename: Edward L
authors.initials: EL
authors.lastname: Melanson
authors.affiliation: Department of Biomedical Engineering, Michigan Technological University, Houghton, MI 49931, United States.
authors.forename: Michael R
authors.initials: MR
authors.lastname: Neuman
authors.affiliation: Electrical and Computer Engineering Department, The University of Alabama, Tuscaloosa, AL 35487, United States. Electronic address: esazonov@eng.ua.edu.
authors.forename: Edward
authors.initials: E
authors.lastname: Sazonov
mesh_terms: D000328:Adult; D000818:Animals; D015992:Body Mass Index; D003679:Deglutition / Q000502:physiology*; D004032:Diet; D015930:Diet Records; D004435:Eating / Q000502:physiology; D002149:Energy Intake; D005260:Female; D006801:Humans; D008297:Male; D008409:Mastication / Q000502:physiology*; D062407:Meals; D008875:Middle Aged; D055815:Young Adult
keywords: Chewing; Dietary assessment; Energy intake models; Self-report; Swallowing; Wearable sensors