Medicine and Health Sciences Commons^™

Exercise Participation During Weight Loss On A High Protein – Low Carbohydrate Diet Plan In Females Aged 15-25 Years, Margaret Mobley-Meulman

Electronic Theses and Dissertations

Weight gain due to poor diet and lack of exercise is responsible for over 300,000 deaths each year (U.S. Department of Health and Human Services, 2010). Obese adults have an increased risk for serious health conditions including high blood pressure and cholesterol, type 2 diabetes, coronary heart disease, stroke, gallbladder disease, osteoarthritis, sleep apnea, respiratory problems, and certain cancers (National Cancer Institute, 2012). Participation in exercise can help control weight, strengthen muscles and bones, and reduce the incidence of cardiac events, stroke, hypertension, type 2 diabetes, colon and breast cancers, osteoporotic fractures, gallbladder disease, obesity, depression, anxiety, and delay mortality …

Blood Glucose Responses To Type, Intensity, Duration, And Timing Of Exercise, Sheri R. Colberg, Manuel J. Hernandez, Fatima Shahzad

Human Movement Studies & Special Education Faculty Publications

[First Paragraph] The Big Blue Test (BBT) is an annual initiative by the Diabetes Hands Foundation to raise awareness of the importance of physical activity in managing diabetes. Individuals with diabetes voluntarily exercise and record self-monitored blood glucose levels. During the 2012 BBT, 5,157 diabetic participants (~90% insulin users) anonymously entered exercise type, intensity, duration, time elapsed since last meal, and blood glucose readings before and after one or more bouts of exercise separately through www.BigBlueTest.org or an Iphone app.

Development And Validation Of A Predictive Model Of Acute Glucose Response To Exercise In Individuals With Type 2 Diabetes, Bryan S. Gibson, Sheri R. Colberg, Paul Poirier, Denise Maria Martins Vancea, Jason Jones, Robin Marcus

Human Movement Studies & Special Education Faculty Publications

Background: Our purpose was to develop and test a predictive model of the acute glucose response to exercise in individuals with type 2 diabetes.

Design and methods: Data from three previous exercise studies (56 subjects, 488 exercise sessions) were combined and used as a development dataset. A mixed-effects Least Absolute Shrinkage Selection Operator (LASSO) was used to select predictors among 12 potential predictors. Tests of the relative importance of each predictor were conducted using the Lindemann Merenda and Gold (LMG) algorithm. Model structure was tested using likelihood ratio tests. Model accuracy in the development dataset was assessed by leave-one-out cross-validation. …