Date of Award


Level of Access

Open-Access Thesis

Degree Name

Master of Science (MS)


Food Science and Human Nutrition


Adrienne A. White

Second Committee Member

Alfred A. Bushway

Third Committee Member

Richard A. Cook


Little is known about the impact of sleep on quality of life and anthropometrics in young adults. College students (n=218) were recruited through a variety of methods for a study on weight management for obesity prevention and randomized into control (n=108) or treatment (n=110) groups. Of those, 152 (71%) completed pre- and post-tests, including the Pittsburg Sleep Quality Index (PSQI), scored 0-4 =normal and 5-21=disordered, (a=0.80), the General Health Questionnaire-12 (GHQ), scored from 0-14=good quality of life to 15-36=poor quality of life, (ct=0.87), and anthropometrics. Statistical analyses included linear regression, one way ANOVA, chi-square analysis, and Pearson's Product-Moment Correlation. Significance was set at a P5, indicating disordered sleep quality; for GHQ, 12% had scores >15 indicating poor quality of life. As sleep quality became more disordered, post-test BMI increased (P=0.008). For every increase in sleep quality score, BMI increased by P=0.29 (CI=0.08-.5, P=0.008). Disordered sleepers had higher post-test waist circumferences (88.7 cm±8.9 cm) than normal sleepers (81.7 cm±4.9 cm) (P=0.007). As age increased waist circumference also increased (P=0.031) by a factor of β=1.38. Disordered sleep quality was associated with approximately a 400% increased risk of poor quality of life at post-test (OR=4.11, 95% Cl=1.6-10.4, P=0.003). For every increase in year of age there was a 57% increase in the risk for a poor quality of life (OR=1.57, 95% CI=1.01-2.46, P=0.045). Quality of life decreased for subjects who got(short sleepers) compared to those who slept 7-9 hours per night (normal sleepers) (P=0.005). Regardless of test time there were significant correlations between sleep quality and quality of life, and sleep quality and anthropometric data. Sleep duration was negatively correlated with weight for the total sample and specifically for males (p=0.01). Based on the findings from this study, sleep should be addressed in wellness programming on university campuses, including its long-term implications on health.