A critical review on sleep assessment methodologies in athletic populations: factors to be considered

Vlahoyiannis, Angelos; Sakkas, Giorgos K.; Manconi, Mauro; Aphamis, George; Giannaki, Christoforos D.

doi:10.1016/j.sleep.2020.07.029

Cited by 16 publications

(13 citation statements)

References 149 publications

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“…34,35,37,40,47,48 Namely, three of the existing studies used polysomnography, 37,47,48 which is considered as the gold standard of sleep measurements. 69 In this direction, others have used less complex and more practical methods of nap recording, such as actigraphy or accelerometers. 34,35,40 By contrast, the majority of the studies (71%) have provided napping opportunity without 29,30,33,42,49 or with 31,32,43,45,46 subjective measures of nap recording; thus, in these studies the exact amount of sleep was not adequately quantified.…”

Section: Limitationsmentioning

confidence: 99%

The impact of daytime napping on athletic performance – A narrative review

Botonis

Koutouvakis

Toubekis

2021

Scandinavian Med Sci Sports

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Due to its physiological and psychological recuperative effects, sleep is an integral part of recovery for human beings and for athletes particularly. 1 Recent recommendations suggest that healthy adults should obtain 7-9 h, 2 while athletes should receive 9-10 h of total sleep to cope with the increased need for recovery. 3 However, research studies that have investigated the effects of nocturnal sleep quantity on athletic performance indicate that due to numerous constraints, athletes do not receive an adequate nighttime sleep. 4 The poor sleep quantity has been attributed to several reasons such as the training schedule and training load, light exposure, nervousness and mood disturbances as well as increases in physical and mental stress. [5][6][7] In addition to the inadequate quantity of sleep, many athletes present low sleep quality. 8,9 For instance, Knufinke et al. 9 showed that sleep efficiency of elite-level athletes was below 85% during 2 out of 7 nights, which is considered the upper limit of poor recovery. 10

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Section: Limitationsmentioning

confidence: 99%

The impact of daytime napping on athletic performance – A narrative review

Botonis

Koutouvakis

Toubekis

2021

Scandinavian Med Sci Sports

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“…Several potential limitations of this meta-analysis need to be considered. A common constraint in meta-analyses is heterogeneity of the included studies [61]. In the current meta-analysis, the estimates for clinical trials that monitored sleep after a CHO-related intervention were relatively homogenous, and efforts have been made to compare clinical trials with similar design.…”

Section: Discussionmentioning

confidence: 99%

A Systematic Review, Meta-Analysis and Meta-Regression on the Effects of Carbohydrates on Sleep

et al. 2021

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This study aimed to assess the effects of quantity, quality and periodization of carbohydrates consumption on sleep. PubMed, SCOPUS and Cochrane Library were searched through October 2020. Data were pooled using random-effects meta-analysis. Eleven articles were included in the meta-analysis which consisted of 27 separate nutrition trials, resulting in 16 comparison data sets (sleep quantity n = 11; sleep quality n = 5). Compared to high carbohydrate (HCI), low carbohydrate intake (LCI) moderately increased duration and proportion of N3 sleep stage (ES = 0.37; 95% CI = 0.18, 0.56; p < 0.001 and ES = 0.51; 95% CI = 0.33, 0.69; p < 0.001, respectively). HCI prolonged rapid eye movement (REM) stage duration (ES = −0.38; 95% CI = 0.05, −8.05; p < 0.001) and proportion (ES = −0.46; 95% CI = −0.83, −0.01; p < 0.001), compared to LCI. The quality of carbohydrate intake did not affect sleep stages. Meta-regression showed that the effectiveness of carbohydrate quantity and quality in sleep onset latency was significantly explained by alterations of carbohydrate intake as a percentage of daily energy intake (R2 = 25.87, p = 0.018) and alterations in the glycemic load (R2 = 50.8, p = 0.048), respectively. Alterations in glycemic load partially explained the variance of the effectiveness of carbohydrate quality in sleep efficiency (R2 = 89.2, p < 0.001) and wake after sleep onset (R2 = 64.9, p = 0.018). Carbohydrate quantity was shown to affect sleep architecture, and especially N3 and REM sleep stages. Alterations in both quantity and quality of carbohydrate intake showed a significant effect on sleep initiation. Variations in carbohydrate quality significantly affected measures of sleep continuation. Further studies are needed to assess the effect of long-term carbohydrate interventions on sleep.

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“…It would be of interest to investigate the effect of daytime napping on movements implementing the whole body. One of the positive points to mention is that electroencephalography-based devices were used in 13 (86.6%) of the 15 studies included in the present systematic review which-in spite of the fact that it is a complex and uncomfortable technique-gives a clear insight into sleep stages and more precise sleep duration and efficiency (Scott et al, 2020;Vlahoyiannis et al, 2020).…”

Section: Methodological Considerationsmentioning

confidence: 99%

“…It is important to point out that those results were taken from an average of two nights in the laboratory, which is an unfamiliar place to older adults, compared to the first part of the study which took place in their beds at home. The study also used polysomnography, which can be a complex and uncomfortable technique for the participants (Vlahoyiannis et al, 2020). All these factors might affect older adults' sleep and therefore could explain the decrease of TST in nap condition.…”

Section: Was Nocturnal Sleep a Ected By Daytime Napping?mentioning

confidence: 99%

Benefits and risks of napping in older adults: A systematic review

Souabni

Souabni²,

Romdhani³

et al. 2022

Front. Aging Neurosci.

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A growing body of evidence indicates that napping is common among older adults. However, a systematic review on the effect of napping on the elderly is lacking. The aim of this systematic review was to (i) determine how studies evaluated napping behavior in older adults (frequency, duration and timing); (ii) explore how napping impacts perceptual measures, cognitive and psychomotor performance, night-time sleep and physiological parameters in the elderly (PROSPERO CRD42022299805). A total of 738 records were screened by two researchers using the PICOS criteria. Fifteen studies met our inclusion criteria with a mean age ranging from 60.8 to 78.3 years and a cumulative sample size of n = 326. Daytime napping had an overall positive impact on subjective measures (i.e., sleepiness and fatigue), psychomotor performances (i.e., speed and accuracy) and learning abilities (i.e., declarative and motor learning). Additionally, studies showed (i) consistency between nap and control conditions regarding sleep duration, efficiency and latency, and proportion of sleep stages, and (ii) increase of 24 h sleep duration with nap compared to control condition. Based on the findings of the present review, there is minimal evidence to indicate that napping is detrimental for older adults' nighttime sleep. Future studies should consider involving repeated naps during a micro-cycle in order to investigate the chronic effect of napping on older adults.Systematic review registrationidentifier: CRD42022299805.

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A critical review on sleep assessment methodologies in athletic populations: factors to be considered

Cited by 16 publications

References 149 publications

The impact of daytime napping on athletic performance – A narrative review

The impact of daytime napping on athletic performance – A narrative review

A Systematic Review, Meta-Analysis and Meta-Regression on the Effects of Carbohydrates on Sleep

Benefits and risks of napping in older adults: A systematic review

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