DYNAMIC MODELING OF FOOD TO FUEL CONVERSION AND ITS EFFECT ON INDIVIDUAL WEIGHT GAIN
Open Access
- Author:
- Pechin, Bradford Andrew
- Area of Honors:
- Mechanical Engineering
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Kathleen Loralee Keller, Thesis Supervisor
Dr. Sean N Brennan, Thesis Honors Advisor
Dr. Jacqueline Antonia O'Connor, Faculty Reader - Keywords:
- modeling
simulation
digestion
obesity - Abstract:
- Obesity is an impactful issue across the globe, especially in America, and a simple explanation for the increase in obesity rates is that people are eating more. However, this thesis hypothesizes that caloric intake alone does not fully explain differences in weight gain due to food type. Americans’ diets have changed in recent decades, and historical changes in the types of food consumed appear to relate to trends in obesity. In particular, the increase in consumption of carbohydrates is notable. This thesis examines very simple models of human digestion to explore the possible connection between consumed carbohydrates and weight gain due to rapid digestion of them by the body. To explore this potential relation, the body’s uptake of nutrients from consumed food is modeled as a first order low-pass filter, with varying time constants for the uptake dependent on the food type. Food mass is modeled as eating events where the digestive process preserves input/output mass flow, modeling input and output of mass as a time-delayed effect. It is assumed as well that the individual strives to maintain homeostasis by associating hunger with instantaneous caloric deficit at the time of food ingestion, eating a quantity of food proportional to perceived hunger. The model includes the known effect that metabolic detection of caloric content during eating is delayed by a very small amount of time. It also includes a first-order dynamic model of the body’s conversion of excess food energy into fat, as well as a similar model for the conversion of body fat into energy for cellular use. Via this simulation, different food inputs are tested with different digestive rates to compare their effects on potential weight gain and loss. The developed model exhibits strong variation in bodily response to different food types, based particularly on the different magnitudes of instantaneous available energy. These examples lend strength to the thesis’s hypothesis by showing how differently the body reacts to different types of foods, with the goal to bring awareness to the potential weight-gain consequences of sugar and similarly rapidly-digested foods.