Purpose. The primary purpose was to determine the effect of sleep time on performance during a 3-day multistage ultra-endurance triathlon (stage 1: 10km swim, 144.8km bike; stage 2: 275.8km bike; stage 3: 84.4km run). Methods. Eighteen triathletes (age: 37±7.9y; height: 175±7cm; weight: 70±9kg) partook in sleep analysis pre, during, and post triathlon using an actigraphy wristband. Participants wore the band to record sleep time for five days (1-2 days pre-race, 3 race days, 1-day post-race), except during racing. Bands were collected before each stage to download the previous night’s data, then re-distributed after each stage. Performance times were recorded after each stage and following total completion of the race. The data were analyzed via linear regression. Results. Using a one-way repeated measures analysis of variance, total minutes of sleep (mean±SD; pre-race: 393.9±81.1min, pre-stage 1: 342.0±90.2min, pre-stage 2: 347.5±54.6min, pre-stage 3: 299.7±107.0min, post-race: 308.8±86.3min) significantly decreased over time (p<0.05). Using a hierarchal regression, a p value approaching significance was found in pre-stage 2, sleep latency, when added to the prediction model of stage 2 performance. This p value approaching significance may have explained 6.1% of the variation in stage 2 performance (R2=0.061, p=0.064). A p-value approaching significance was found in stage 1 performance time when added to the prediction model of pre-stage 2 sleep latency. This p value approaching significance may have explained 10.3% of the variation in pre-stage 2 sleep latency (R2=0.103, p=0.58). Finally, significance was found in stage 2 performance time, when added to the prediction model of pre-stage 3 minutes of sleep. This model explained 48.1% of the variance in pre-stage 3 minutes of sleep (R2=0.48, p=0.002). Total race sleep time (Pre-stage 1, 2, and 3) was averaged; 33% of the variation in total finishing time can be predicted by average total racing sleep time (R2=0.33, p=0.015). No additional relationships were seen. A cutoff value was found at 401.6 min of average total race-night sleep time, indicating the top 25% of race finishers slept for ≥401.6 min. Conclusions. We found at specific time points, sleep latency may have been associated with changes in performance time, and exercise performance may have been associated with changes in minutes of sleep and sleep latency. Additionally, based on our results, average total race-night sleep time of roughly 402 min (6.7h/night) leads to faster finishing time in the Ultraman Florida. / A Thesis submitted to the Department of Nutrition, Food and Exercise Sciences in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester 2018. / March 21, 2018. / Includes bibliographical references. / Michael Ormsbee, Professor Directing Thesis; Lynn Panton, Committee Member; Graig Chow, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_653451 |
| Contributors | Kisiolek, Jacob Norbert (author), Ormsbee, Michael J. (professor directing thesis), Panton, Lynn B. (committee member), Chow, Graig Michael (committee member), Florida State University (degree granting institution), College of Human Sciences (degree granting college), Department of Nutrition, Food, and Exercise Science (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, master thesis |
| Format | 1 online resource (69 pages), computer, application/pdf |
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