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Living Well: Do Health Education College Students Sleep Better?Ben Smith, MS, North Carolina State UniversityEllen Smith, MS, Indiana UniversityBarbara Phillips, MD, MSPH, FCCP, University of Kentucky

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Background/Rationale

Aims and Hypotheses

Methods

Online Survey

Data Analysis

Results Results

Conclusions

•In this small, homogenous group of college students:

•Both napping and “make-up” sleep were prevalent•Sleep duration did not correlate with other health behaviors or with GPA•Heavier students had lower GPAs and higher Epworth Sleepiness Scores, even though most students were of normal weight. •Higher Epworth Sleepiness Scores (ESS) were associated with self-reported crash in college students. Although ESS has been shown to predict crash in several populations, we believe this is a new finding in college students. •Despite being enrolled in a health and wellness course emphasizing physical activity, this small homogeneous group of students did not appear to have healthier sleep habits than historical controls.

Aims•To assess sleep behaviors of college students in a Health and Wellness Class•To correlate sleep behaviors with other lifestyle and health factors.

Hypotheses•College students in a Health and Wellness Class will have healthier sleep habits than their peers.•Good sleep behaviors will correlate with good health and lifestyle behaviors.

Students enrolled in an elective general education “Living Well” class in the school of Health, Physical Education and Recreation were asked to take a voluntary, anonymous, online survey about sleep and health behaviors. The survey was offered during the Fall (2010) and Spring (2011) semesters. The survey was announced in class as during a lecture about healthy sleep. In each semester, the survey was open and data were collected for about one month. This project received IRB exemption from Indiana University and the University of Kentucky.The website was active to collect data fromOctober 14-November 13, 2010 and February 2-March 20, 2011.

http://li75-152.members.linode.com/sleepsurvey/

College students are widely believed to be sleep-deprived, but students who chose an elective Health and Wellness course may self-select healthier behaviors. We sought to learn about the sleep and health habits of Health and Wellness students at a major US University (Indiana University).

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Of a possible 117 students enrolled in both semesters, 61 students completed the survey.

Demographics (means)Women: 70.5%Age: 19BMI: 23.5Epworth Score: 9.1High School GPA: 3.7College GPA: 3.3

Lifestyle CharacteristicsSmokers 6.6%Work (less than 20 hours/week) 39%

Sleep Characteristics

•39% reported getting 6 or fewer hours of sleep on week nights,•80% reported getting 7 or fewer hours of sleep on week nights.•55% slept an hour or longer on weekends compared with week nights. •Most (82%) napped at least a few times a week. •Women were more likely than men to get 7 or more hours of sleep a night (p<0.01)•Both high school and college GPA’s were negatively correlated with BMI (the higher the BMI the lower the GPA ; p<0.00001 and, p<0.05, respectively).• Epworth Sleepiness Score was positively associated with having been the driver in a car accident (p<0.03), and students with Epworth scores > 10 were about 3 times as likely to report having had a crash in which they were the driver. • Age was positively associated with BMI; the older the student, the higher the BMI (p<0.0000001)• BMI was positively correlated with Epworth score (p<0.05).• Heavy nappers ( >3 hours per week) were slightly morelikely to have been a driver in a car accident p<0.10) and wereon average a year younger than those who napped less. • There were no differences in reported crash, exercise, napping, age, GPA or BMI for students who reported sleeping 7 or more or 8 or more hours of sleep than for those who reported sleepiness less.

• We performed our statistical analyses using the R statistical package v2.9.2. http://www.r-project.org.

• Some data in the form were corrupt; students sometimes gave nonsensical answers in the text-based inputs. We cleaned the dataset to address these issues.

• Fisher’s Exact Test and other odds ratio statistics calculated using the Epitools R package.

• Indicator variables were created for drinkers, heavy drinkers, and students who didn’t nap.