Sleep Abnormalities in Multiple Sclerosis

Purpose of review: This review summarizes the most well-documented sleep disorders seen in patients with multiple sclerosis (MS), with a special focus on the impact on quality of life. Recent findings: Sleep abnormalities in patients with MS are a multifactorial and relatively complex issue affecting approximately 60% of the patients while the pathophysiology of these symptoms is not fully understood. Circadian rhythm disorders and increased levels of pro-inflammatory cytokines have been recognized as potential players in affecting sleep homeostasis in MS patients. Medication-related side effects such as in immunotherapy and other factors such as lesion load can contribute to the disruption of normal sleep patterns. Summary: Most frequently encountered sleep disorders are insomnia, sleep-related movement disorders, sleep-related breathing disorders, and circadian rhythm disorders affecting both adults and paediatric MS populations. Aetiology still remains unknown with treatment options focusing on behavioural cognitive therapy and lifestyle modification including improvement in sleep hygiene as well as melatonin supplementation. Given MS prevalence is still rising affecting millions of people, more personalized medicine applications should possibly form the key approach for improving patients’ quality of life and quality years. © 2019, Springer Science+Business Media, LLC, part of Springer Nature

High-intensity Interval Training Frequency: Cardiometabolic Effects and Quality of Life

The effects of high intensity interval training (HIIT) frequency on cardiometabolic health and quality of life were examined in 35 healthy inactive adults (age: 31.7±2.6 yrs, VO 2 peak: 32.7±7.4 ml · kg -1 · min -1). Participants were randomly assigned to a control (CON) and two training groups, which performed 10×60-s cycling at ~83% of peak power, two (HIIT-2) or three times per week (HIIT-3) for eight weeks. Compared with CON, both training regimes resulted in similar improvements in VO 2 peak (HIIT-2: 10.8%, p=0.048, HIIT-3: 13.6%, p=0.017), waist circumference (HIIT-2: -1.4 cm, p=0.048, HIIT-3: -2.4 cm, p=0.028), thigh cross-sectional area (HIIT-2: 11.4 cm 2, p=0.001, HIIT-3: 9.3 cm 2, p=0.001) and the physical health component of quality of life (HIIT-2: 8.4, p=0.001, HIIT-3: 12.2, p=0.001). However, HIIT-3 conferred additional health-related benefits by reducing total body and trunk fat percentage (p<0.05, compared with CON), total cholesterol and low-density lipoprotein-cholesterol (p<0.02, compared with CON) and by improving the mental component of quality of life (p=0.045, compared with CON). In conclusion, performing HIIT only twice per week is effective in promoting cardiometabolic health-related adaptations and quality of life in inactive adults. However, higher HIIT frequency is required for an effect on fat deposits, cholesterol and mental component of well-being. © Georg Thieme Verlag KG Stuttgart New York

Effects of high-intensity interval training frequency on perceptual responses and future physical activity participation

The effectiveness of high-intensity interval training (HIIT) in inducing positive physiological adaptations is well documented. However, its impact on perceptual responses and on future physical activity (PA) engagement is less evaluated. The present study aimed to examine the effects of HIIT frequency on perceptual responses, health-related quality of life (HRQOL), and its influence in future PA participation. Thirty-five inactive adults were randomly assigned to a control (CON) and to 2 training groups that performed HIIT (10 × 60 s cycling, ~83% peak power output) for 2 (HIIT-2) or 3 (HIIT-3) times per week for 8 weeks. Following the HIIT intervention, exercise enjoyment, HRQOL, and the intention to implement HIIT in the future were evaluated. Eight weeks after cessation of training, follow-up evaluations of HRQOL and PA were performed. Following the intervention, both training frequencies induced high levels of enjoyment (HIIT-2: 6.0 ± 1.1, HIIT-3: 6.0 ± 1.1, scale 1–7), improved HRQOL (HIIT-2: p = 0.040; HIIT-3: p = 0.024), and reported intention to implement HIIT in the future (HIIT-3: 100%, HIIT-2: 93% of participants). At follow-up, HIIT-3 participants reported higher completion of HIIT compared with HIIT-2 and CON (p < 0.05). Both training groups sustained improved HRQOL and increased vigorous and total PA (p < 0.05). This study showed that performing HIIT either 2 or 3 times per week is an enjoyable exercise modality that promotes a sustainable increase in habitual PA levels and improves HRQOL. Moreover, the higher training frequency resulted in greater HIIT completion in the 8-week period following the cessation of training. © 2019, Canadian Science Publishing. All rights reserved

Exploring the Associations between Functional Capacity, Cognitive Function and Well-Being in Older Adults

Background: The present study aimed to explore the associations between functional capacity and global cognition, executive function and well-being in older adults. Methods: Ninety-seven older adults (age 80.6 ± 8.2 years) were examined for global cognitive function (Mini-Mental State Examination), executive function (symbol cancellation test), functional capacity (sit-to-stand tests, 6 min walk test, timed up-and-go test and handgrip strength test) and well-being (quality of life, fatigue levels, sleep quality and daily sleepiness). Adjusted partial correlations were computed to examine the associations between variables. Mediation analyses were conducted to evaluate whether functional capacity would mediate the relationships between age and cognitive or executive function. Results: Greater levels of functional capacity were associated with better performance in cognitive and executive function tests (p < 0.05). Mediation analyses revealed that functional capacity partially mediated the effects of age on global cognition and executive function (indirect effect: β = −0.11, 95% CI = −0.20 to −0.03; β = 0.34, 95% CI = 0.13 to 0.57, respectively). Increased levels of functional capacity were also associated with higher quality of life (p < 0.05, r = 0.32 to 0.41), lower fatigue levels (p < 0.05, r = 0.23 to 0.37), and better sleep quality (p < 0.05, r = 0.23 to 0.24). Conclusions: Functional capacity can mediate the effects of age on global cognition and executive function in older adults and greater levels of functional capacity are associated with improved quality of life, better sleep quality, and lower fatigue levels. © 2022 by the authors

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

A growing body of research focus on athletes' sleep in order to investigate the effects of sleep in sports performance and recovery or the prevalence of sleep disorders in athletes. At the same time, several sleep monitoring tools have been developed and used in athletic populations for fulfilling these purposes. This review aimed to provide critical assessment to the most used by athletes' methodological approaches and compared them with the gold standard approach. Advantages and disadvantages of the various sleep monitoring tools were critically discussed. Literature related to aspects of athletes' sleep was reviewed. From the shortlisted studies, several factors that seem to affect sleep in athletes were identified using objective methods such as polysomnography/electroencephalography and actigraphy. These factors were associated to sleep (eg such as sleep environment, familiarization procedures and napping) and daily habits (eg nutrition, fluid consumption, alcohol and caffeine intake, tobacco use). The selected studies that evaluated sleep objectively were screened according the reporting rates of these variables. The majority of the screened studies were found to underreport these variables. Practical issues were addressed and recommendations about reporting sleep-related factors were made in order to improve studies’ quality assessment and allow for more robust comparisons between studies. © 2020 Elsevier B.V

Restless legs syndrome in adolescents: Relationship with sleep quality, cardiorespiratory fitness and body fat

Objective: The aim of the current study was to investigate the relationship between restless legs syndrome (RLS) and cardiorespiratory fitness, body composition and sleep quality in a sample of adolescents. Methods: One hundred fifty seven volunteer adolescents (16.6 ± 0.7 yrs) participated in the study. Sleep quality was assessed by the Pittsburg sleep quality index. Cardiorespiratory fitness was assessed by the 20 m shuttle run test and body composition by bioelectrical impedance analysis. Results: The prevalence of RLS was 5.1%. The adolescents with RLS were found to exhibit significantly higher body fat levels (p=0.019) and poorer sleep quality score (p=0.000) compared with their free-RLS counterparts. Conclusions: Adolescents with RLS are subjects of higher body fat and impaired sleep quality compared with adolescents without RLS. Early diagnosis and appropriate management of RLS is essential in the adolescents

A systematic review, meta-analysis and meta-regression on the effects of carbohydrates on sleep

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 &lt; 0.001 and ES = 0.51; 95% CI = 0.33, 0.69; p &lt; 0.001, respectively). HCI prolonged rapid eye movement (REM) stage duration (ES = −0.38; 95% CI = 0.05, −8.05; p &lt; 0.001) and proportion (ES = −0.46; 95% CI = −0.83, −0.01; p &lt; 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 &lt; 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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Athletes’ sleep assessment: from lifestyle to pharmacological interventions and vice versa

[No abstract available

Deconstructing athletes’ sleep: A systematic review of the influence of age, sex, athletic expertise, sport type, and season on sleep characteristics

Purpose: This systematic review aimed to describe objective sleep parameters for athletes under different conditions and address potential sleep issues in this specific population. Methods: PubMed and Scopus were searched from inception to April 2019. Included studies measured sleep only via objective evaluation tools such as polysomnography or actigraphy. The modified version of the Newcastle–Ottawa Scale was used for the quality assessment of the studies. Results: Eighty-one studies were included, of which 56 were classified as medium quality, 5 studies as low quality, and 20 studies as high quality. A total of 1830 athletes were monitored over 18,958 nights. Average values for sleep-related parameters were calculated for all athletes according to sex, age, athletic expertise level, training season, and type of sport. Athletes slept on average 7.2 ± 1.1 h/night (mean ± SD), with 86.3% ± 6.8% sleep efficiency (SE). In all datasets, the athletes’ mean total sleep time was &lt;8 h. SE was low for young athletes (80.3% ± 8.8%). Reduced SE was attributed to high wake after sleep onset rather than sleep onset latency. During heavy training periods, sleep duration and SE were on average 36 min and 0.8% less compared to pre-season and 42 min and 3.0% less compared to in-season training periods, respectively. Conclusion: Athletes’ sleep duration was found to be short with low SE, in comparison to the general consensus for non-athlete healthy adults. Notable sleep issues were revealed in young athletes. Sleep quality and architecture tend to change across different training periods. © 202