Document Type
Thesis
Degree Name
Master of Arts (MA)
Department
Geography & Environmental Studies
Faculty/School
Faculty of Arts
First Advisor
Sean Doherty
Advisor Role
Thesis Supervisor
Abstract
In this thesis, time series models are developed to explore the correlates of blood glucose (BG) fluctuation of diabetic patients. In particular, it is investigated whether certain human activities and lifestyle events (e.g. food and medication consumption, physical activity, travel and social interaction) influence BG, and if so, how. A unique dataset is utilized consisting of 40 diabetic patients who participated in a 3-day study involving continuous monitoring of blood glucose (BG) at five minute intervals, combined with measures for sugar; carbohydrate; calorie and insulin intake; physical activity; distance from home; time spent traveling via public transit and private automobile; and time spent with other people, dining and shopping. Using a dynamic regression model fitted with autoregressive integrated moving average (ARIMA) components, the influence of independent predictive variables on BG levels is quantified, while at the same time the impact of unknown factors is defined by an error term. Models were developed for individuals with overall findings demonstrating the potential for continuous monitoring of diabetic (DM) patients who are trying to control their BG. Model results produced significant BG predicting variables that include food consumption, exogenous insulin administration and physical activity.
Recommended Citation
Sadowski, Eric A., "A Time Series Analysis: Exploring the Link between Human Activity and Blood Glucose Fluctuation" (2010). Theses and Dissertations (Comprehensive). 1021.
https://scholars.wlu.ca/etd/1021
Convocation Year
2010