The mathematical sciences including engineering, statistics, computer science, physics, econometrics, psychometrics, epidemiology, and mathematics qua mathematics are increasingly being applied to advance our understanding of the causes, consequences, and alleviation of obesity. These applications do not merely involve routine well-established approaches easily implemented in widely available commercial software. Rather, they increasingly involve computationally demanding tasks, use and in some cases development of novel analytic methods and software, new derivations, computer simulations, and unprecedented interdigitation of two or more existing techniques. Such advances at the interface of the mathematical sciences and obesity research require bilateral training and exposure for investigators in both disciplines. Yet, no ongoing resource exists to provide such training and role models of scientists who regularly can and do traverse these disciplines are in short supply at most institutions. The proposed annual five day short course on the mathematical sciences in obesity research features some of the world's finest scientists working in this domain to fill this unmet need by providing nine topic driven modules designed to bridge the disciplines. Each module will begin with a mathematical method applied in obesity research. This introduction will be followed by a lecture on a completed application of the method. Directly after the completed application, participants will be engaged in a guided interactive session performing calculations using software or analysis pertaining to the module topic. Finally, the module closes with a lecture on remaining open questions. In recognition of the challenges in successfully managing an interdisciplinary career, each day of the short course will contain a two hour long interactive working session guided by established senior researchers in building the next step. Participants may choose to use this interactive session to begin develop an abstract for submission at national level obesity conferences or plan an application for a small interdisciplinary group of researchers to advance their ideas at the National Institute of Mathematical and Biological Synthesis in Knoxville, TN. Based on the degree of completion, ten participants will be selected to present their work on the last day of the short course. The NIH and the scientific community at large has voiced the need for more training at the interface of the mathematical science and key biomedical domains, and we request the opportunity to be part of the solution.

Public Health Relevance

Obesity affects more than one-third of the US population generating a need for novel interdisciplinary strategies to resolve growing obesity related negative health outcomes. Advanced mathematical methods play a critical role on numerous fronts in obesity research from evaluating the effect of population wide obesity prevention policy measures to monitoring patients during lifestyle interventions. The proposed course will develop connections between mathematical scientists and obesity researchers to address research challenges with novel approaches.

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Education Projects (R25)
Project #
1R25DK099080-01
Application #
8549549
Study Section
Diabetes, Endocrinology and Metabolic Diseases B Subcommittee (DDK)
Program Officer
Podskalny, Judith M,
Project Start
2013-07-01
Project End
2018-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
1
Fiscal Year
2013
Total Cost
$109,475
Indirect Cost
$8,109
Name
University of Alabama Birmingham
Department
None
Type
Schools of Public Health
DUNS #
063690705
City
Birmingham
State
AL
Country
United States
Zip Code
35294
Pavela, Greg; Wiener, Howard; Fontaine, Kevin R et al. (2015) Packet randomized experiments for eliminating classes of confounders. Eur J Clin Invest 45:45-55
Dawson, John A; Hall, Kevin D; Thomas, Diana M et al. (2014) Novel mathematical models for investigating topics in obesity. Adv Nutr 5:561-2
Dawson, John A; Hall, Kevin D; Thomas, Diana M et al. (2014) Novel mathematical models for investigating topics in obesity. Adv Nutr 5:561-2