Date of Award

5-2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Legacy Department

Human Factors Psychology

Committee Member

Dr. Eric R. Muth, Committee Chair

Committee Member

Dr. Adam W. Hoover

Committee Member

Dr. Elliot D. Jesch

Committee Member

Dr. DeWayne D. Moore

Abstract

Obesity continues to be a leading health risk throughout the world, and there is a need for tools to assess free-living eating behavior for both researchers attempting to study how specific eating behaviors contribute to obesity outside the lab and for individuals to use as self-monitoring aids. This study sought to examine how variance in individual traits and eating behaviors can be used to understand and predict the kilocaloric content of specific bites of food (KPB). It was hypothesized that meal duration, pre-meal satiety, food enjoyment, eating rate, age, gender, mouth volume, and body metrics would significantly predict KPB. Seventy-two participants were asked to eat two meals, consisting of three food items each. Participants were randomly assigned to two of five possible meals, never eating the same meal twice. Multi-level linear modelling was used to examine predictors of KPB: time in meal, time since last bite, food item enjoyment, pre-meal satiety, BMI, body fat percentage, waist-to-hip ratio, gender, mouth volume, and age. Additionally, the following mediation effects were hypothesized: the effect of time in meal would be mediated by time since last bite, satiety would be mediated by food item enjoyment, and the three body metrics would be mediated by food item enjoyment. Food enjoyment, pre-meal satiety, time in meal, and eating rate surfaced as the strongest predictors of KPB. The effect of time in meal on KPB appears to be partially mediated by time since last bite. However, there is no evidence that the effect of satiety is mediated by food item enjoyment. Additionally, a train-and-test analysis for model validation was performed, with one of each participant's meals being used to train the model and the other used to test the model. The resulting model was found to perform better than previously derived models of KPB. While this study offers some new insight into predictors of KPB, additional work will be necessary before an accurate and applicable model of KPB can be derived from easily measured variables.

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