The course is designed to explain the biochemical principles of the metabolism of macronutrients including carbohydrates, proteins and lipids. The dietary sources, requirements, and metabolism of these nutrients will be explained. The function of these nutrients will be explained. The deficiency and excess symptoms of these nutrients and how these conditions participate in metabolic disorders will be explained.
The purpose of this course is to explain the physiologic and metabolic alterations in chronic and acute illness and trauma requiring modifications in nutritional care; the current scientific basis for nutrition intervention measures; and the interrelationships between diet, other treatment modalities, and nutritional status.
Will examine in depth the sources, absorption, availability, metabolism and functions of micronutrients (vitamins and minerals). The interaction between minerals and vitamins will be discussed. Methods used to determine requirements, Recommended Dietary Allowance or amounts recognized as safe for these nutrients will be discussed.
This course will discuss nutrition as an important element for maintaining optimal health. The emphasis is to understand the importance of each nutrient based on their biochemical and physiological functions. Nutritional needs at specific stages in the life cycle will be studied, as well as the implication of nutrition in major health problems in the US, such as obesity, cardiovascular disease, hypertension, and cancer. Students will learn to determine nutritional status through dietary analysis and learn to evaluate nutritional information.
Provides a perspective on public health for students from a variety of health professions programs. As such, the specific relation to the overall program of studies differs depending on the student's program. Completion of the course should, regardless of program, provide students with an understanding of how their role within the health professions relates to and is part of the broader health care system and of how the health issues addressed in their program are influenced by population health issues. For students in academic programs focused in the School of Public Health and Health Professions, the course satisfies a School accreditation requirement for an Introduction to Public Health course.
This course is intended to train students on the art of giving seminars on sports medicine, nutritional or exercise science-related subjects and to develop their ability to critique seminars given by others. Students will be exposed to research in the field of Exercise Science and Nutrition by attending presentations arranged by the Department of Exercise and Nutrition Sciences, meeting with faculty and by reading and discussing peer-reviewed, scientific journal articles.
This lecture and discussion course teaches students the principles of grant writing. Each week of classes will typically consist of a lecture or student presentations, followed by group discussion facilitated by the instructor. This course is a required component of the Exercise Science PhD program because the ability to write grants successfully is an important skill for graduates. There are several components to a strong grant proposal. First, the subject must be creative, exciting, and worthy of funding. Then, the project must be developed through a rigorous, well-defined experimental plan. Finally, the information must be presented in clear language and follow the rules and guidelines detailed in the grant application instructions.
This course is designed for students concerned with medical data. The material covered includes the design of clinical trials and epidemiological studies, data collection, summarizing and presenting data, probability, standard error, confidence intervals and significance tests, techniques of data analysis including multifactorial methods and the choice of statistical methods, problems of medical measurement and diagnosis, vital statistics and calculation of sample size. The design and analysis of medical research studies will be illustrated. MINITAB is used to perform some data analysis. Descriptive statistics, probability distributions, estimation, tests of hypothesis, categorical data, regression model, analysis of variance, nonparametric methods, and others will be discussed as time permits.
This course presents statistical models for data mining, inference and prediction. The focus will be on supervised learning, which concerns outcome prediction from input data. Students will be introduced to a number of methods for supervised learning, including: linear and logistic regression, shrinkage methods, lasso, partial least squares, tree-based methods, model assessment and selection, model inference and averaging, and neural networks. Computational applications will be presented using R and high dimensional data to reinforce theoretical concepts.
Weekly discussion of the literature relevant to the student’s research interests.
This course is used for doctoral students who are conducting research prior to defending their dissertation proposal.
This course is used for the dissertation research once the student has completed his/her dissertation proposal and is considered a doctoral candidate.