Date of Award
3-26-2020
Document Type
Thesis
Degree Name
Master of Science in Operations Research
Department
Department of Operational Sciences
First Advisor
Raymond R. Hill, PhD
Abstract
This study uses multivariate analysis methods to find relationships between nutrition and wellness and nutrition and performance. The nutrition, daily wellness, and weight and bodyfat data are from a study performed by the STRONG lab in the 711th Human Performance Wing. Electronically collected nutrition data along with survey data for 19 individuals over a 12-week study period are examined with a focus on health, fitness, and nutrition. Factor analysis and linear regression are performed and inferences are drawn regarding what effects calories and macronutrient intake have on subjects perceived wellness, weight, and body fat percentage. These insights are discussed in the context of past studies and nutrition subject matter expert opinions. The findings indicate that an increase in total calorie intake is associated with increased motivation, stronger feelings of recovery, increased satiety, and increased body fat percentage. Increased stress and decreased sleep quality are associated with an increase in total calorie intake. An increase in total body weight is associated with an increased intake of fat and carbohydrates. Further conclusions and recommendations are offered.
AFIT Designator
AFIT-ENS-MS-20-M-177
DTIC Accession Number
AD1101497
Recommended Citation
Tinucci, Kayla N., "Multivariate Analysis of Human Performance STRONG Lab Data" (2020). Theses and Dissertations. 3203.
https://scholar.afit.edu/etd/3203