Abstract
Food portion size influences energy intake and sustained high-energy intake often leads to obesity. Virtual portion creation tasks (VPCTs), in which a participant creates portions of food on a computer screen, predict intake in healthy individuals. The objective of this study was to determine whether portions created in VPCTs are stable over time (test-retest reliability) and responsive to factors known to influence food intake, such as eating contexts and food types, and to determine if virtual portions can predict weight loss. Patients with obesity scheduled for bariatric surgery (n = 29), and individuals with a normal BMI (18.5-24.9 kg/m(2), controls, n = 29), were instructed to create virtual portions of eight snack foods, which varied in energy density (low and high) and taste (sweet and salty). Portions were created in response to the following eating situations, or "contexts": What they would a) eat to stay healthy (healthy), b) typically eat (typical), c) eat to feel comfortably satisfied (satisfied), d) consider the most that they could tolerate eating (maximum), and e) eat if nothing was limiting them (desired). Tasks were completed before, and 3 months after, surgery in patients, and at two visits, 3 months apart, in controls. Body weight (kg) was recorded at both visits. Virtual portions differed significantly across groups, visits, eating contexts, energy densities (low vs. high), and tastes (sweet vs. salty). Portions created by controls did not change over time, while portions created by patients decreased significantly after surgery, for all contexts except healthy. For patients, desired and healthy portions predicted 3-month weight loss. VPCTs are replicable, responsive to foods and eating contexts, and predict surgical weight loss. These tasks could be useful for individual assessment of expectations of amounts that are eaten in health and disease and for prediction of weight loss.