Publication Date:
Author(s): John W. Long, Paige M. Cunningham, Sara J. Maksi, Kathleen Loralee Keller, Timothy R. Brick, Alexander Klippel, Lee Boot, Charissa S.L. Cheah, Caitlyn G. Edwards, Barbara J. Rolls, Travis D. Masterson
Publication Type: Conference Proceeding
Page Range: 27-35
Abstract:
Innovative methods are needed to understand associations between food selection and intake across different contexts. We explored whether the energy density (ED, kilocalories per gram) of meals selected in an immersive virtual reality (iVR) food buffet predicted the ED consumed and overall energy intake in measured laboratory meals. In a secondary analysis, 91 adults (64 female, aged 18 to 71 years) selected foods for a meal in our iVR buffet before consuming a standard laboratory meal once a week for two weeks. The iVR buffet contained 30 foods varying in ED, ranging from 0.3 to 4.9 kcal per gram, including entrees, sides, soups, and desserts. The laboratory meals consisted of pasta, rolls, chicken, broccoli, grapes, and cookies, with ED values ranging from 0.4 to 4.8 kcal per gram. Linear mixed-effect models were used to examine associations between food selections in iVR meals and intake in laboratory meals. We found that the ED selected in iVR significantly predicted the ED consumed in laboratory meals. The ED consumed in laboratory meals and the ED selected in IVR meals were both positively associated with energy intake in laboratory meals. In addition, the carbohydrates, fats, and protein selected in iVR meals were each significantly associated with their respective intake in laboratory meals. The significant associations between food selections in iVR meals and intake in laboratory meals demonstrate the predictive validity of iVR. These findings highlight the utility of iVR as an innovative method to assess associations between food selection and intake across diverse contexts.