108 Board #6 June 1, 9:30 AM - 11:30 AM Effects Of An Increased Exercise Program On Sleep In Elderly People Yoshinori Kitabatake. Saitama Prefectural University, Koshigaya, Japan. Email: email@example.com (No relationships reported) Sleep disorders have been reported as a risk factor for mortality, coronary heart disease, hypertension, obesity, diabetes, depression, and dementia. The acquisition of quality sleep is considered useful for the prevention of Non-Communicable Disease as well as the prevention of sleep disorders. It is our hypothesis that sleep can be induced by light fatigue from physical activity during daytime. Previous studies reported that exercise as non-drug therapy is effective as a means of preventing a sleep disorder. But exercise intensity using an exercise program is too strong in gray-zone Japanese people. PURPOSE: To examine the effect of an exercise program on sleep in elderly people. METHODS: Fifty-one subjects met the inclusion criteria for this study. We recommended that these subjects participate in a sleep seminar. These subjects were assigned to intervention (exercise n=26) or control (n=25) groups (randomized control trial). The exercise program consisted of an increase in physical activity for 10 minutes more than the activity amount of their former daily life as well as a lecture on sleep. The subjects were encouraged to perform physical activity at home every day. The control group attended a seminar lecture. The seminar was held every week (90 minutes per seminar). The study period was 4-weeks. Sleep condition was examined using the Pittsburgh sleep quality index (PSQI). Two-way analysis of variables was used to examine intervention effects on sleep. RESULTS: The rate of compliance with this program was 92% in the intervention group and 84% in the control group. The average attendance rate at the seminars was 94% in the intervention group and 96% in the control group. The PSQI score was 9.7 before and 9.0 after in the intervention group, and 9.2 before and 7.4 after in the control group. The interaction was not significant between the intervention group and the control group. CONCLUSIONS: The intervention program had high participation, but there were not so many positive results. In conclusion, our study did not confirm our hypothesis. We expected that satisfying sleep would be obtained in the intervention program, but this was not the case. However, we suggested that our expected result could be achieved with an increase in the exercise program`s duration and intensity. 109 Board #7 June 1, 9:30 AM - 11:30 AM Concurrent Associations Of Physical Activity And Screen-based Sedentary Behaviors On Sleep Duration Among Us Adolescents: A Latent Class Analysis Approach Youngdeok Kim, Masataka Umeda, Marc Lochbaum, Steven Stegemeier. Texas Tech University, Lubbock, TX. Email: firstname.lastname@example.org (No relationships reported) Adolescence is a vulnerable period for experiencing insufficient sleep due to puberty-related changes in circadian rhythm and increasing sleep deprivation during school days. Physical activity (PA) and sedentary behaviors (SB) are well-documented, modifiable sleep hygiene behaviors independently associated with sleep duration; however, scarce data are available regarding their concurrent associations in adolescents. PURPOSE: This study examined the concurrent associations of PA and screen-based SB on sleep duration in US adolescents using a latent class analysis (LCA) approach. METHODS: A total of 11,204 adolescents who participated in the 2013 Youth Risk Behavior Survey were analyzed. The outcome variables of interest included self-reported PA regarding 1) moderate and vigorous-intensity PA ≥ 60 minutes/day; 2) sport team participation ≥ 1 per year; and 3) muscle-strengthening exercise ≥ 3 days/week; and selfreported screen-based SB regarding 4) watching TV ≥ 3 hours/day; and 5) using a computer/playing video games ≥ 3 hours/day. Self-reported sleep durations on average school nights was obtained to determine the sufficient sleep (≥8 hours). A LCA model was developed 1) to identify the latent subgroups with varying response probabilities of each PA and screen-based SB items; and 2) to examine the associations of latent subgroups with likelihood of having sufficient sleep. RESULTS: Four latent subgroups with varying levels of PA and screen-based SB were identified. Using the estimated response probability ≥ .50 as a threshold to determine ‘High’ level of respective PA and screen-based SB items, four latent subgroups were characterized as the High PA/Low SB (26.06%), High PA/High SB (23.23%), Low PA/Low SB (29.41%), and Low PA/High SB (21.29%). The likelihoods of having sufficient sleep was greater for the High PA/Low SB when comparing to the High PA/High SB (OR = 1.51) and Low PA/Low SB (OR = 1.49), whereas no difference was found when comparing to the Low PA/High SB. CONCLUSIONS: The results demonstrated the complexity of concurrent associations of PA and screen-based SB with sleep duration in adolescents. However, the findings generally implied that increasing PA and reducing screen-based SB would yield greater likelihood of having sufficient sleep in this population. 110 Board #8 June 1, 9:30 AM - 11:30 AM The Relationship between Sleep Quantity and Quality and Cardiovascular Disease Risk Factors in Children Caroline T. Case. University of New England, Biddeford, ME. (No relationships reported) Duration of sleep has been declining over the past two decades in both adults and children which has paralleled the rise in obesity in our society along with other negative health outcomes. The threshold in which we observe negative health outcomes based on quantity (total sleep time (TST)) and quality (number of sleep interruptions (NSI) and total sleep interruption time (TSIT)) is not clearly understood in children. PURPOSE: The purpose of this study was twofold- 1) determine if children have a greater overall cardiovascular (CV) risk profile with decreased sleep duration and quality, and 2) determine if there is a threshold point where sleep quantity and quality is associated with an increased CV risk profile. METHODS: Four hundred and seventy six fourth grade students from the Cardiovascular Health Intervention Program went through a CV risk factor analysis (256 females, 219 males, mean age 9.2(years), height 142(cm) and weight 38(kg)). Participants completed a fasting blood lipid and glucose profile, height, weight, grip strength, resting blood pressure and 20m Pacer test. Sleep data was collected using an Actigraph GT3X accelerometer wrist band that was measured for 5 days and measured TST, NSI, and TSIT. Sleep quantity and sleep quality were compared to each individual CV assessment listed above and total CV risk factors. RESULTS: TST was inversely related to BMI (p<.05), percent body fat (p<.01), NSI (p<.001) and TSIT (p<.0001). Number of interruptions was inversely related to total sleep time (p<.007) and TSIT was positively related to BMI (p<.002), waist circumference (p<.0001), percent body fat (p<.003), TSIT (p<.000) and NSI (p<.001). When analyzing the sleep thresholds for CV risk we observed that those who slept 8-9 hours had a lower percent body fat versus sleeping <8 hours (p8 hours (p9 hours also had the greatest TSIT (p<.02) CONCLUSION: Based on the sleep data, the best range of TST for children is 8-9 hours per night. Students who slept 8-9 hours had the lowest risk factor values compared to those who slept 9 hours. Funding was provided by the Clark Charitable Foundation 11 Copyright © 2016 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.