429 METHODS: 247 ALL survivors underwent a cardiopulmonary exercise test. They also completed a physical activity questionnaire and a battery of clinical exams. We calculated the odds ratio to obtain the preventive fraction in order to evaluate the effects of cardiorespiratory fitness and physical activity levels on health outcomes (i.e. obesity, metabolic health, cardiac health, cognitive health and mood, bone health) RESULTS: Despite their young age, 88% of the survivors presented at least one adverse health outcome, and 46% presented 3 or more adverse health outcomes. Their cardiorespiratory fitness had a median VO2 peak reaching 84% of predicted value, which was lower than expected. In the analyses regarding cardiorespiratory fitness, statistically significant preventive fractions were observed for obesity (30%), low HDL-cholesterol (21%) and depression (26%). In the physical activity level analyses, statistically significant preventive fractions were observed for obesity (55%), depression (81%) and low bone mineral density (60%). CONCLUSIONS: Our results indicated that a good cardiorespiratory fitness and physical activity level induced a preventive action for most health outcomes studied and was associated with a lower late adverse effects prevalence in ALL survivors. Clinicians and researchers have an important role to play in the reduction of late adverse effects in ALL survivors. This study provides additional evidence regarding the benefits of physical activity for cancer survivors C-49 Basic Science World Congress/Poster ‑ Circadian and Sleep Behavior in Adolescents Thursday, May 30, 2019, 7:30 AM - 12:30 PM Room: CC-Hall WA2 1554 Board #316 May 30 10:30 AM - 12:00 PM Descriptive Analysis of Objectively Measured Physical Activity and Sleep Activity in Adolescents: a Preliminary Analysis. Sarah N. Brown, Sarah E. Domoff, Aubrey L. Borgen, Ryan Foley, Rachael K. Nelson. Central Michigan University, Mount Pleasant, MI. (No relationships reported) Although growing evidence suggests a link between physical activity (PA) behavior and sleep quality in adolescents, a causal relationship between these two variables has yet to be elucidated. Methodological differences in data collection (subjective vs. objective) has been highlighted as a limiting factor in data interpretation. In fact, the majority of the literature includes subjective or subjective combined with objective data, with only two studies comparing objective measures of both PA and sleep in adolescents within the same analysis. PURPOSE: To objectively examine PA behavior and sleep activity in adolescents using accelerometers. METHODS: 7 males and 3 females, age: 10±1 yrs., BMI: 20±5 were recruited for this study. PA and sleep were monitored by Actigraph wGT3x accelerometers worn on participants’ non- dominant wrist to assess sedentary (SED), light-intensity (LPA), and moderate-to-vigorous activity (MVPA), as well as sleep activity including: total sleep time (TST), wake after sleep onset (WO), and average wake length (WL). Time spent awake and sedentary (aSED) was calculated as aSED = SED – TST. Participants were instructed to wear the accelerometer for 7 consecutive days only removing it while swimming, bathing, or playing contact sports. Our analysis only included data from participants who wore the accelerometer continuously for ≥4 days. RESULTS: On average participants accumulated 435±15 min/day of sleep equal to 7.3±0.3 hours per night. Participants also accumulated 473±24 min/day of MVPA, 371±29 min/day aSED, and 141±8 min/day LPA. There was not a significant difference between TST and MVPA per day (p=0.22). Participants spent the majority of their day sleeping (33% time/day) or engaged in MVPA (31%) followed by aSED (26%), and the fewest proportion of their day engaged in LPA (10%; p<0.01). We observed a negative association between LPA and. TST (p=0.01). However, we observed a positive association between LPA and WO (p=0.03) and WL (p=0.03). No other significant associations were observed between PA and sleep variables. CONCLUSION: Outcomes of this analysis suggest that adolescents accumulate less than the recommended 8-10 hours of sleep per night and parameters of sleep disturbance may be linked to engaging in higher amounts of light-intensity physical activity. 1555 Board #317 May 30 10:30 AM - 12:00 PM 24-hour Movement Behaviors, Body Composition And Cognitive Performance In Adolescents Erin K. Howie, Marilou D. Shreve, Connie Lamm, Matthew S. Ganio, FACSM. University of Arkansas, Fayetteville, AR. Email: ekhowie@uark.edu (No relationships reported) PURPOSE: The purpose of this pilot study was to examine associations between 24-hour movement behaviors (sleep, physical activity, and sedentary time), body composition, and executive functions in adolescents with and without obesity. METHODS: Adolescents between the ages of 12 and 18 years (n=30, n=14 girls, mean age=14.9 years) wore accelerometers on the hip for 24-hours to measure total night sleep time, minutes of moderate-to-vigorous physical activity (MVPA), and percentage of waking wear in sedentary activity. Body composition including lean mass, fat mass and bone mineral density was measured using dual-energy x-ray absorptiometry. Cognitive performance, particularly attention and inhibitory control, was tested using the Go/NoGo task. RESULTS: Mean sleep time was 487.2 (SD 80.0) minutes per night, median minutes of moderate-to-vigorous physical activity were 16 (10.2, 25.3 25 th to 75 th percentiles) minutes per day, and 68.5% (SD 6.95) of waking time was spent in sedentary activity. There were no differences in sleep or sedentary time in adolescents with and without obesity, however, adolescents with obesity participated in less MVPA compared to those without obesity (median 13.4 vs 23.3 minutes per day respectively, p=.024). In linear regression models with all three behaviours as independent variables adjusted for total body mass, sex, and age, total sleep time (minutes/day), but not sleep efficiency, was positively associated with total body percent fat (0.05, 95%CI: 0.002, 0.11, p=.043) and negatively associated with total lean mass (-37.8 grams, 95%CI: -71.7, -4.0, p=.030). Using negative binomial regression adjusted for age and sex, there were no associations of any of the movement behaviors with accuracy (errors of omission or commission) or reaction times. Body fat percentage (IRR 1.06, 95%CI: 1.01, 1.12), p=.026) and total lean mass (kg) (IRR 0.89, 95%CI, 0.80, 0.97, p=.013) were associated with omission errors of inattention. CONCLUSION: In this sample of adolescents, total sleep time was associated with body fat and lean mass. Body composition was associated with inattention. Novel interventions that integrate sleep strategies to improve health and cognitive performance in adolescents should be explored. 1556 Board #318 May 30 10:30 AM - 12:00 PM What Affects the Sleep of Youth? Results from the 2017 Youth Risk Behavior Surveillance Survey Hai Yan. University of Illinois at Urbana Champaign, Champaign, IL. (Sponsor: Weimo Zhu, FACSM) Email: haiyan2@illinois.edu (No relationships reported) BACKGROUND/PURPOSE: Sleep plays a critical role in metabolism, memory, learning, and other vital functions. Sleep deprivation is associated with an increased risk of developing diabetes, cardiovascular disease, and many other complications. However, evidence has shown that youth are sleeping less than before. Understanding what influences sleep time is extremely important in designing interventions to help to improve the sleep time and sleep quality of youth. The aim of this study was to examine the influencing factors of sleep for youth age from 12 to 18 yr. METHODS: The data were derived from the 2017 Youth Risk Behavior Surveillance System (YRBSS) and a total of 14,765 youth responded to the survey. Descriptive analysis was used to explore the sleep patterns and Pearson’s Chi-squared test was applied to examine the gender and race/ethnicity difference. Logistic regression was implemented to explore the impact of health- related behaviors such as physical activity (PA), playing video games (GAME), smoking (SMOKE), and drinking alcohol (DRINK) on sleep time. Copyright © 2019 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.