A Comparison of Lifestyle Behaviors Between Student-Athletes and Non-Athletes Alyssa Stefanadis & Eddie T. C. Lam Department of Health & Human Performance, Cleveland State University Introduction The National Collegiate Athletic Association (NCAA) has enforced many alcohol and substance abuse prevention plans for its member organizations. In 2001, the NCAA released a study analyzing substance use and abuse habits of college student-athletes (Green, Uryasz, Petr, & Bray, 2001). The study revealed that 80.5% of student-athletes had consumed alcohol in the past 12 months, followed by marijuana at 28.4% (Gary, 2001). Research conducted by Berning, Adams, DeBeliso, Stamford, and Newman (2008) examined anabolic androgenic steroid (AAS) use of non-athlete students at the collegiate level. Although these students were not involved in varsity athletics, 48% of AAS users expressed a desire to improve physical performance, and 45% of users wanted to enhance their physical appearance (Berning et al., 2008). Further, Harmer (2009) argues that participation in sports may actually prevent the use of AAS in student-athletes. Sleep deprivation can cause physical and cognitive impairment. Buboltz, Jenkins, Soper, Woller, Johnson, & Faes (2009) found that in a self-reported study concerning sleep habits of college students, more than 65.9% if the respondents reported occasional sleep habits. Additionally, nearly 23% of survey responders experienced poor sleep quality. Findings of this study will not only assess risky behavior of the student-body population, but also promote a healthy lifestyle. Purpose The purpose of this study was to determine if student-athletes from a NCAA university in the Midwestern region of the United States have a healthier lifestyle based on alcohol consumption, marijuana use, anabolic steroid use, sleep patterns and exercise frequency compared to regular collegiate students from the same institution. These results could help create a more effective substance prevention program for student-athletes or traditional students. Method The data collection design is a self-reported, anonymous, retrospective survey. Respondents were queried of their lifestyle habits pertaining to alcohol consumption, exercise frequency, sleep habits, anabolic steroid use, and marijuana use. Results (Continued) However, significant (p <.05) main effect was found on student- athlete status. Student-athletes had a lower level of alcohol consumption and marijuana use, but a higher level of exercise than their counterparts (Figure 1). Likewise, the main effect of gender was significant (p <.05). Females had a closer association with marijuana than males. However, males were more likely to use steroids than females, and exercise more (Figure 2). Conclusion Based on the results of this study, it was suggested that student- athletes have a healthier lifestyle based on exercise frequency and decreased association with alcohol and marijuana use. Thus, non- athletes should be the target population to help decrease undesirable lifestyle behavior. Programs pertaining to decreasing steroid use should be aimed towards male students at Baldwin Wallace University. The target population for decreasing marijuana use should be aimed towards females and non-athletes. References Berning, J. M., Adams, K. J., DeBeliso, M., Stamford, B. A., & Newman, I. M. (2008). Anabolic androgenic steroids: Use and perceived use in nonathlete college students. Journal of American College Health, 56(5), Buboltz, W., Jr., Jenkins, S. M., Soper, B., Woller, K., Johnson, P., & Faes, T. (2009). Sleep habits and patterns of college students: An expanded study. Journal of College Counseling, 12(2), Gary, G. (2001). NCAA study of substance use and abuse habits of college student-athletes. Clinical Journal of Sport Medicine, 11(1), Green, G. A., Uryasz, F. D., Petr, T. A., & Bray, C. D. (2001). NCAA study of substance use and abuse habits of college student- athletes. Clinical Journal of Sport Medicine, 11(1), Harmer, P. (2009). Anabolic-androgenic steroid use among young male and female athletes: Is the game to blame? British Journal of Sports Medicine, 44(1), Figure 1. Mean scores between student-athletes and non-athletes concerning their lifestyle behaviors of alcohol consumption, exercise frequency, sleep patterns, steroid use, and marijuana use. Figure 2. Mean scores between males and females concerning their lifestyle behaviors of alcohol consumption, exercise frequency, sleep patterns, steroid use, and marijuana use. Table 1: Pattern Matrix of the Five-Factor Lifestyle Behaviors (N = 123) IIIIIIIVV I. Alcohol 1. Alcohol has negatively affected my academic performance I have been trouble with the law because of alcohol I drink 24 hours before I workout I drink more than 3 nights a week I drink to "black out"0.86 II. Exercise 1. I exercise on a regular basis I exercise for more than 30 minutes I exercise to look good I exercise to increase physical performance I exercise at a high intensity level (12 min mile, etc.)0.89 III. Sleep 1. My sleep habits have negatively affected academic performance My sleep habits have negatively affected athletic performance I wake up feeling tired0.77 IV. Anabolic Steroids 1. I use steroids to improve physical performance I use steroids to enhance aesthetics I know people who use steroids In the past 12-months, I have used steroids multiple times0.98 V. Marijuana 1. Marijuana has negatively affected on academic performance Marijuana has negatively affected on athletic performance I smoke marijuana to relax I smoke marijuana because my friends do I smoke marijuana on a monthly basis 0.96 Note. For clarity purpose, only factor coefficients of.40 or higher are shown. Method (Continued) The survey was distributed to students of Baldwin Wallace University using a random cluster sampling technique to make sure different sections of campus had been covered. Participants were asked to fill out the 25-item survey and put it in a confidential envelope. The survey was distributed for two weeks in March Items were based on a 5-point Likert scale (e.g., 1 = Strongly disagree, 3 = neutral, 5 = strongly agree). SPSS 11.5 for Windows (SPSS, 2004) and Factorial ANOVA were used for data analysis. The researcher compared the main effects of gender and student-athlete status of subjects, as well as the interaction of the main effects. Results A factorial 2 (gender) × 2 (student-athlete status) between-subjects ANOVA was used to compare interaction and main effects based on the following variables: alcohol consumption, exercise frequency, sleep patterns, steroid use, and marijuana use. The results showed that there was no significant (p >.05) interaction between gender and student-athlete status.