Literature DB >> 24709483

A novel tool to predict food intake: the Visual Meal Creator.

Adrian Holliday1, Chris Batey2, Frank F Eves2, Andrew K Blannin2.   

Abstract

Subjective appetite is commonly measured using an abstract visual analogue scale (VAS) technique, that provides no direct information about desired portion size or food choice. The purpose of this investigation was to develop and validate a user-friendly tool - the Visual Meal Creator (VIMEC) - that would allow for independent, repeated measures of subjective appetite and provide a prediction of food intake. Twelve participants experienced dietary control over a 5-hour period to manipulate hunger state on three occasions (small breakfast (SB) vs. large breakfast (LB) vs. large breakfast + snacks (LB+S)). Appetite measures were obtained every 60 minutes using the VIMEC and VAS. At 4.5 hours, participants were presented with an ad libitum test meal, from which energy intake (EI) was measured. The efficacy of the VIMEC was assessed by its ability to detect expected patterns of appetite and its strength as a predictor of energy intake. Day-to-day reproducibility and test-retest repeatability were assessed. Between- and within-condition differences in VAS and VIMEC scores (represented as mm and kcal of the "created" meal, respectively) were significantly correlated with one another throughout. Between- and within-condition changes in appetite scores obtained with the VIMEC exhibited a stronger correlation with EI at the test meal than those obtained with VAS. Pearson correlation coefficients for within-condition comparisons were 0.951, 0.914 and 0.875 (all p < 0.001) for SB, LB and LB+S respectively. Correlation coefficients for between-condition differences in VIMEC and EI were 0.273, 0.940 (p < 0.001) and 0.525 (p < 0.05) for SB - LB+S, SB - LB and LB - LB+S respectively. The VIMEC exhibited a similar degree of reproducibility to VAS. These findings suggest that the VIMEC appears to be a stronger predictor of energy intake than VAS.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Appetite; Eating behaviour; Energy intake; Food photography

Mesh:

Year:  2014        PMID: 24709483     DOI: 10.1016/j.appet.2014.04.001

Source DB:  PubMed          Journal:  Appetite        ISSN: 0195-6663            Impact factor:   3.868


  5 in total

1.  Validity of assessing child feeding with virtual reality.

Authors:  Susan Persky; Megan R Goldring; Sara A Turner; Rachel W Cohen; William D Kistler
Journal:  Appetite       Date:  2017-12-23       Impact factor: 3.868

2.  Children's Portion Selection Is Predicted by Food Liking and Is Related to Intake in Response to Increased Portions.

Authors:  Hanim E Diktas; Kathleen L Keller; Liane S Roe; Barbara J Rolls
Journal:  J Nutr       Date:  2022-10-06       Impact factor: 4.687

3.  Satiety of Edible Insect-Based Food Products as a Component of Body Weight Control.

Authors:  Magdalena Skotnicka; Aleksandra Mazurek; Kaja Karwowska; Marcin Folwarski
Journal:  Nutrients       Date:  2022-05-21       Impact factor: 6.706

4.  Building healthy eating habits in childhood: a study of the attitudes, knowledge and dietary habits of schoolchildren in Malaysia.

Authors:  Kazi Enamul Hoque; Megat Ahmad Kamaluddin; Ahmad Zabidi Abdul Razak; Afiq Athari Abdul Wahid
Journal:  PeerJ       Date:  2016-11-24       Impact factor: 2.984

Review 5.  Expected Satiety: Application to Weight Management and Understanding Energy Selection in Humans.

Authors:  Ciarán G Forde; Eva Almiron-Roig; Jeffrey M Brunstrom
Journal:  Curr Obes Rep       Date:  2015-03
  5 in total

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