Sleep Quality but Not Quantity Altered With a Change in Training Environment in Elite Australian Rules Football Players

2017 ◽  
Vol 12 (1) ◽  
pp. 75-80 ◽  
Author(s):  
Nathan W. Pitchford ◽  
Sam J. Robertson ◽  
Charli Sargent ◽  
Justin Cordy ◽  
David J. Bishop ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Repeated Measures ◽  
Perceived Exertion ◽  
Sleep Onset ◽  
Sleep Time ◽  
Rating Of Perceived Exertion ◽  
Training Environment ◽  
Time In Bed ◽  
Australian Rules Football ◽  
The Relationship

Purpose:To assess the effects of a change in training environment on the sleep characteristics of elite Australian Rules football (AF) players.Methods:In an observational crossover trial, 19 elite AF players had time in bed (TIB), total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) assessed using wristwatch activity devices and subjective sleep diaries across 8-d home and camp periods. Repeated-measures ANOVA determined mean differences in sleep, training load (session rating of perceived exertion [RPE]), and environment. Pearson product–moment correlations, controlling for repeated observations on individuals, were used to assess the relationship between changes in sleep characteristics at home and camp. Cohen effect sizes (d) were calculated using individual means.Results:On camp TIB (+34 min) and WASO (+26 min) increased compared with home. However, TST was similar between home and camp, significantly reducing camp SE (–5.82%). Individually, there were strong negative correlations for TIB and WASO (r = -.75 and r = -.72, respectively) and a moderate negative correlation for SE (r = -.46) between home and relative changes on camp. Camp increased the relationship between individual s-RPE variation and TST variation compared with home (increased load r = -.367 vs .051, reduced load r = .319 vs –.033, camp vs home respectively).Conclusions:Camp compromised sleep quality due to significantly increased TIB without increased TST. Individually, AF players with higher home SE experienced greater reductions in SE on camp. Together, this emphasizes the importance of individualized interventions for elite team-sport athletes when traveling and/or changing environments.

Pacing and Hazard Score of Elite Open Water Swimmers During a 5-km Indoor Pool Race

2020 ◽  
pp. 1-6 ◽  
Author(s):  
Roberto Baldassarre ◽  
Cristian Ieno ◽  
Marco Bonifazi ◽  
Maria Francesca Piacentini
Keyword(s):  
Swimming Speed ◽  
Repeated Measures ◽  
Perceived Exertion ◽  
Open Water ◽  
Rating Of Perceived Exertion ◽  
Mixed Analysis ◽  
Pacing Strategies ◽  
Main Effect ◽  
Within Subjects ◽  
The Relationship

Purpose: The sensation of fatigue experienced at a certain point of the race is an important factor in the regulation of pacing. The rating of perceived exertion (RPE) is considered one of the main mediators utilized by athletes to modify pacing. The aim was to analyze the relationship between pacing and RPE of elite open water swimmers during national indoor pool championships. Methods: A total of 17 elite open water swimmers (males, n = 9; females, n = 8) agreed to provide RPE every 500 m during the finals of the national championships 5-km indoor pool race. Time splits, stroke rate, and RPE were collected every 500 m. The Hazard score was calculated by multiplying the momentary RPE by the remaining fraction of the race. Athletes were placed in one of two categories: medalists or nonmedalists. For all variables, separate mixed analysis of variances (P ≤ .05) with repeated measures were used considering the splits (ie, every 500 m) as within-subjects factor and the groups (ie, medalists and nonmedalists) as between-subjects factor. Results: Average swimming speed showed a significant main effect for split for both males and females (P < .001). A significant interaction was observed between average swimming speed and groups for females (P = .032). RPE increased in both groups (P < .001) with no difference observed between groups. However, the female nonmedalists showed a disproportionate nonlinear increase in RPE (5.20 [2.31]) halfway through the event that corresponded to the point where they started significantly decreasing speed. Conclusions: The results of the present study show different pacing strategies adopted by medalists and nonmedalists despite a similar RPE.

scholarly journals Associations of Actigraphic Sleep Parameters With Fatigability in Older Adults

2020 ◽  
Vol 75 (9) ◽  
pp. e95-e102 ◽  
Author(s):  
Alfonso J Alfini ◽  
Jennifer A Schrack ◽  
Jacek K Urbanek ◽  
Amal A Wanigatunga ◽  
Sarah K Wanigatunga ◽  
...  
Keyword(s):  
Older Adults ◽  
Perceived Exertion ◽  
Sleep Onset ◽  
Later Life ◽  
Sleep Time ◽  
Community Dwelling ◽  
Rating Of Perceived Exertion ◽  
Poor Sleep ◽  
Wrist Actigraphy ◽  
Sleep Parameters

Abstract Background Poor sleep may increase the likelihood of fatigue, and both are common in later life. However, prior studies of the sleep–fatigue relationship used subjective measures or were conducted in clinical populations; thus, the nature of this association in healthier community-dwelling older adults remains unclear. We studied the association of actigraphic sleep parameters with perceived fatigability—fatigue in response to a standardized task—and with conventional fatigue symptoms of low energy or tiredness. Methods We studied 382 cognitively normal participants in the Baltimore Longitudinal Study of Aging (aged 73.1 ± 10.3 years, 53.1% women) who completed 6.7 ± 0.9 days of wrist actigraphy and a perceived fatigability assessment, including rating of perceived exertion (RPE) after a 5-minute treadmill walk or the Pittsburgh Fatigability Scale (PFS). Participants also reported non-standardized symptoms of fatigue. Results After adjustment for age, sex, race, height, weight, comorbidity index, and depressive symptoms, shorter total sleep time (TST; &lt;6.3 hours vs intermediate TST ≥6.3 to 7.2 hours) was associated with high RPE fatigability (odds ratio [OR] = 2.56, 95% confidence interval [CI] = 1.29, 5.06, p = .007), high PFS physical (OR = 1.88, 95% CI = 1.04, 3.38, p = .035), and high mental fatigability (OR = 2.15, 95% CI = 1.02, 4.50, p = .044), whereas longer TST was also associated with high mental fatigability (OR = 2.19, 95% CI = 1.02, 4.71, p = .043). Additionally, longer wake bout length was associated with high RPE fatigability (OR = 1.53, 95% CI = 1.14, 2.07, p = .005), and greater wake after sleep onset was associated with high mental fatigability (OR = 1.14, 95% CI = 1.01, 1.28, p = .036). Conclusion Among well-functioning older adults, abnormal sleep duration and sleep fragmentation are associated with greater perceived fatigability.

Effects of a 2-Week High-Intensity Training Camp on Sleep Activity of Professional Rugby League Athletes

2017 ◽  
Vol 12 (7) ◽  
pp. 928-933 ◽  
Author(s):  
Heidi R. Thornton ◽  
Grant M. Duthie ◽  
Nathan W. Pitchford ◽  
Jace A. Delaney ◽  
Dean T. Benton ◽  
...  
Keyword(s):  
Sleep Onset ◽  
Sleep Time ◽  
Rugby League ◽  
Training Camp ◽  
High Intensity Training ◽  
Time In Bed ◽  
Nighttime Sleep ◽  
Relationship Of ◽  
The Relationship ◽  
And Training

Purpose:To investigate the effects of a training camp on the sleep characteristics of professional rugby league players compared with a home period.Methods:During a 7-d home and 13-d camp period, time in bed (TIB), total sleep time (TST), sleep efficiency (SE), and wake after sleep onset were measured using wristwatch actigraphy. Subjective wellness and training loads (TL) were also collected. Differences in sleep and TL between the 2 periods and the effect of daytime naps on nighttime sleep were examined using linear mixed models. Pearson correlations assessed the relationship of changes in TL on individuals’ TST.Results:During the training camp, TST (–85 min), TIB (–53 min), and SE (–8%) were reduced compared with home. Those who undertook daytime naps showed increased TIB (+33 min), TST (+30 min), and SE (+0.9%). Increases in daily total distance and training duration above individual baseline means during the training camp shared moderate (r = –.31) and trivial (r = –.04) negative relationships with TST.Conclusions:Sleep quality and quantity may be compromised during training camps; however, daytime naps may be beneficial for athletes due to their known benefits, without being detrimental to nighttime sleep.

scholarly journals Sleep Quality in Family Caregivers and Matched Non-Caregiving Controls: The REGARDS Study

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 818-818
Author(s):  
Marcela Blinka ◽  
Adam Spira ◽  
Orla Sheehan ◽  
Tansu Cidav ◽  
J David Rhodes ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Family Caregivers ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Care Recipient ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Time In Bed ◽  
Regards Study

Abstract The high levels of stress experienced by family caregivers may affect their physical and psychological health, including their sleep quality. However, there are few population-based studies comparing sleep between family caregivers and carefully-matched controls. We evaluated differences in sleep and identified predictors of poorer sleep among the caregivers, in a comparison of 251 incident caregivers and carefully matched non-caregiving controls, recruited from the national REasons for Geographic and Racial Differences in Stroke (REGARDS) Study. Incident caregivers and controls were matched on up to seven demographic and health factors (age, sex, race, education level, marital status, self-rated health, and self-reported serious cardiovascular disease history). Sleep characteristics were self-reported and included total sleep time, sleep onset latency, wake after sleep onset, time in bed, and sleep efficiency. Family caregivers reported significantly longer sleep onset latency, before and after adjusting for potential confounders, compared to non-caregiving controls (ps &lt; 0.05). Depressive symptoms in caregivers predicted longer sleep onset latency, greater wake after sleep onset, and lower sleep efficiency. Longer total sleep time in caregivers was predicted by employment status, living with the care recipient, and number of caregiver hours. Employed caregivers and caregivers who did not live with the care recipient had shorter total sleep time and spent less time in bed than non-employed caregivers. Additional research is needed to evaluate whether sleep disturbances contributes to health problems among caregivers.

Losing Sleep Over It: Sleep in Basketball Players Affected by Game But Not Training Workloads

2020 ◽  
Vol 15 (8) ◽  
pp. 1117-1124
Author(s):  
Jordan L. Fox ◽  
Aaron T. Scanlan ◽  
Robert Stanton ◽  
Cody J. O’Grady ◽  
Charli Sargent
Keyword(s):  
Heart Rate ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Sleep Onset ◽  
Onset Time ◽  
Rating Of Perceived Exertion ◽  
Self Report ◽  
Basketball Players ◽  
Time In Bed ◽  
The Impact

Purpose: To examine the impact of workload volume during training sessions and games on subsequent sleep duration and sleep quality in basketball players. Methods: Seven semiprofessional male basketball players were monitored across preseason and in-season phases to determine training session and game workloads, sleep duration, and sleep quality. Training and game data were collected via accelerometers, heart-rate monitors, and rating of perceived exertion (RPE) and reported as PlayerLoad™ (PL), summated heart-rate zones, and session RPE (sRPE). Sleep duration and sleep quality were measured using wrist-worn activity monitors in conjunction with self-report sleep diaries. For daily training sessions and games, all workload data were independently sorted into tertiles representing low, medium, and high workload volumes. Sleep measures following low, medium, and high workloads and control nights (no training/games) were compared using linear mixed models. Results: Sleep onset time was significantly later following medium and high PL and sRPE game workloads compared with control nights (P < .05). Sleep onset time was significantly later following low, medium, and high summated heart-rate-zones game workloads, compared with control nights (P < .05). Time in bed and sleep duration were significantly shorter following high PL and sRPE game workloads compared with control nights (P < .05). Following low, medium, and high training workloads, sleep duration and quality were similar to control nights (P > .05). Conclusions: Following high PL and sRPE game workloads, basketball practitioners should consider strategies that facilitate longer time in bed, such as napping and/or adjusting travel or training schedules the following day.

scholarly journals Differential Effects of DHA- and EPA-Rich Oils on Sleep in Healthy Young Adults: A Randomized Controlled Trial

Nutrients ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 248
Author(s):  
Michael J. Patan ◽  
David O. Kennedy ◽  
Cathrine Husberg ◽  
Svein Olaf Hustvedt ◽  
Philip C. Calder ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Controlled Trial ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Omega 3 ◽  
Double Blind ◽  
Differential Effects ◽  
Positive Effects ◽  
Time In Bed ◽  
Oily Fish

Emerging evidence suggests that adequate intake of omega-3 polyunsaturated fatty acids (n-3 PUFAs), which include docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), might be associated with better sleep quality. N-3 PUFAs, which must be acquired from dietary sources, are typically consumed at suboptimal levels in Western diets. Therefore, the current placebo-controlled, double-blind, randomized trial, investigated the effects of an oil rich in either DHA or EPA on sleep quality in healthy adults who habitually consumed low amounts of oily fish. Eighty-four participants aged 25–49 years completed the 26-week intervention trial. Compared to placebo, improvements in actigraphy sleep efficiency (p = 0.030) and latency (p = 0.026) were observed following the DHA-rich oil. However, these participants also reported feeling less energetic compared to the placebo (p = 0.041), and less rested (p = 0.017), and there was a trend towards feeling less ready to perform (p = 0.075) than those given EPA-rich oil. A trend towards improved sleep efficiency was identified in the EPA-rich group compared to placebo (p = 0.087), along with a significant decrease in both total time in bed (p = 0.032) and total sleep time (p = 0.019) compared to the DHA-rich oil. No significant effects of either treatment were identified for urinary excretion of the major melatonin metabolite 6-sulfatoxymelatonin. This study was the first to demonstrate some positive effects of dietary supplementation with n-3 PUFAs in healthy adult normal sleepers, and provides novel evidence showing the differential effects of n-3 PUFA supplements rich in either DHA or EPA. Further investigation into the mechanisms underpinning these observations including the effects of n-3 PUFAs on sleep architecture are required.

scholarly journals Usefulness of Linear Mixed-Effects Models to Assess the Relationship between Objective and Subjective Internal Load in Team Sports

2021 ◽  
Vol 18 (2) ◽  
pp. 392
Author(s):  
Alice Iannaccone ◽  
Daniele Conte ◽  
Cristina Cortis ◽  
Andrea Fusco
Keyword(s):  
Heart Rate ◽  
Perceived Exertion ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Team Sports ◽  
Rating Of Perceived Exertion ◽  
Subjective Measures ◽  
Internal Load ◽  
Random Slopes ◽  
The Relationship

Internal load can be objectively measured by heart rate-based models, such as Edwards’ summated heart rate zones, or subjectively by session rating of perceived exertion. The relationship between internal loads assessed via heart rate-based models and session rating of perceived exertion is usually studied through simple correlations, although the Linear Mixed Model could represent a more appropriate statistical procedure to deal with intrasubject variability. This study aimed to compare conventional correlations and the Linear Mixed Model to assess the relationships between objective and subjective measures of internal load in team sports. Thirteen male youth beach handball players (15.9 ± 0.3 years) were monitored (14 training sessions; 7 official matches). Correlation coefficients were used to correlate the objective and subjective internal load. The Linear Mixed Model was used to model the relationship between objective and subjective measures of internal load data by considering each player individual response as random effect. Random intercepts were used and then random slopes were added. The likelihood-ratio test was used to compare statistical models. The correlation coefficient for the overall relationship between the objective and subjective internal data was very large (r = 0.74; ρ = 0.78). The Linear Mixed Model using both random slopes and random intercepts better explained (p < 0.001) the relationship between internal load measures. Researchers are encouraged to apply the Linear Mixed Models rather than correlation to analyze internal load relationships in team sports since it allows for the consideration of the individuality of players.

121 Behavioral Attention Relationships Vary Between Demographic Groups Across Sleep Loss and Recovery

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A49-A50
Author(s):  
Caroline Antler ◽  
Erika Yamazaki ◽  
Tess Brieva ◽  
Courtney Casale ◽  
Namni Goel
Keyword(s):  
Sleep Deprivation ◽  
Repeated Measures ◽  
Age Groups ◽  
Response Speed ◽  
Sleep Loss ◽  
Demographic Groups ◽  
Time In Bed ◽  
Median Split ◽  
The Relationship ◽  
High Bmi

Abstract Introduction The Psychomotor Vigilance Test (PVT) is a behavioral attention measure widely used to describe sleep loss deficits. Although there are reported differences in PVT performance for various demographic groups, no study has examined the relationship between measures on the 10-minute PVT (PVT10) and the 3-minute PVT (PVT3) within sex, age, and body mass index (BMI) groups throughout a highly controlled sleep deprivation study. Methods Forty-one healthy adults (mean±SD ages, 33.9±8.9y) participated in a 13-night experiment [2 baseline nights (10h-12h time in bed, TIB) followed by 5 sleep restriction (SR1-5) nights (4h TIB), 4 recovery nights (R1-R4; 12h TIB), and 36h total sleep deprivation (TSD)]. A neurobehavioral test battery, including the PVT10 and PVT3 was completed every 2h during wakefulness. Repeated measures correlation (rmcorr) compared PVT10 and PVT3 lapses (reaction time [RT] &gt;355ms [PVT3] and &gt;500ms [PVT10]) and response speed (1/RT) by examining correlations by day (e.g., baseline day 2) and time point (e.g., 1000h-2000h) within sex groups (18 females), within age groups defined by a median split (median=32, range=21-49y), and within BMI groups defined by a median split (median=25, range=17-31). Results PVT10 and PVT3 1/RT was significantly correlated at all study days and time points excluding at baseline for the younger group and at R2 for the higher BMI group. PVT10 and PVT3 lapses showed overall lower correlations across the study relative to 1/RT. Lapses were not significantly correlated at baseline for any group, for males across recovery (R1-R4), for the high BMI group at R2-R4, for the older group at R2-R3, or for the younger group at SR5 or R3. Conclusion Differentiating participants based on age, sex, or BMI revealed important variation in the relationship between PVT10 and PVT3 measures across the study. Surprisingly, lapses were not significantly correlated at baseline for any demographic group or across recovery for males or the high BMI or older group. Thus, PVT10 and PVT3 lapses may be less comparable in certain populations when well-rested. These findings add to a growing literature suggesting demographic factors may be important factors to consider when evaluating the effects of sleep loss. Support (if any) ONR Award N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243; NIHR01DK117488

507 Clinical Impression of Excessive Daytime Sleepiness (EDS) at initial Sleep Medicine (SM) consultation and its clinical correlates

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A199-A200
Author(s):  
Leon Rosenthal ◽  
Raúl Aguilar Roblero
Keyword(s):  
Lower Energy ◽  
Energy Levels ◽  
Sleep Onset ◽  
Sleep Time ◽  
Clinical Impression ◽  
Sleep Onset Latency ◽  
Convenience Sample ◽  
Time In Bed ◽  
Number Of Patients ◽  
Cardinal Symptom

Abstract Introduction EDS represents a cardinal symptom in SM. Use of subjective scales are prevalent, which have a modest correlation with the MSLT. While the Clinical Global Impression has been used in research, reports of clinical impression (CI) in medical practice are lacking. We report on the CI of EDS in a convenience sample of patients undergoing initial consultation. Methods Patients reported primary, secondary symptoms and completed the Sleep Wake Activity Inventory (SWAI) prior to Tele-Medicine consultation. A SM physician completed the assessment which included ascertainment of CI of EDS (presence S+ / absence S-). Results There were 39 ♂and 13 ♀. The CI identified 26 patients in each group (S+/S-). Age (52 [14]), BMI (33 [7]), reported time in bed, sleep time, sleep onset latency and # of awakenings did not differ. All identified a primary symptom (S-: 21, S+: 19 reported snoring or a previous Dx of OSA). Sleepiness as a 1ry or 2ry symptom was identified by 0 in the S- and by 13 in the S+ groups. Refreshing quality of sleep differed (χ2 &lt;0.05): un-refreshing sleep was reported by 7 (S-) and by 13 (S+). Naps/week: 0.7 [1.5] and 1.57 [1.5] for the S-, S+ groups respectively (p&lt;0.05). A main effect (p&lt;0.01) was documented on the SWAI. We report on the Sleepiness [SS] and Energy Level [EL] scales (lower scores on the SS reflect higher sleepiness while lower scores on EL denote higher energy). Higher sleepiness (p&lt;0.01) 43 [12] and lower energy levels 24 [6] (p&lt;0.05) were documented on the S+ group (S- 61 [17], and 18 [6] respectively). Available spouse’s Epworth score on 29 patients: S- patients 5.8 [4] and S+ 10.2 [6] (p&lt;0.05). Dx of OSA was identified among all but 1 in the S+ group. Also, Insomnia was diagnosed among 11 (S-) and 19 (S+) patients (p&lt;0.05) despite only 3 and 7 (respectively) identifying it as a presenting symptom. Conclusion While snoring or previous Dx of OSA were prevalent motivations for consultation, sleepiness and insomnia were clinically relevant among a substantial number of patients. Unrefreshing sleep, daytime naps, lower energy, and higher sleepiness were ubiquitous among S+ patients. Support (if any):

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