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Biological Trace Element Research Jan 2023To date, no study has critically reviewed the current literature on the association between magnesium (Mg) and sleep health. Therefore, we carried out a systematic...
To date, no study has critically reviewed the current literature on the association between magnesium (Mg) and sleep health. Therefore, we carried out a systematic review to assess the association between Mg and sleep patterns in adults' population through observational and interventional studies. We searched for relevant studies through PubMed ( http://www.ncbi.nlm.nih.gov/pubmed ), Scopus ( http://www.scopus.com ), and ISI Web of Science ( http://www.webofscience.com ) from the earliest available date until November 2021. Eligibility criteria for study selection were guided by the following components identified using the PI(E)CO (Population, Intervention (Exposure), Comparison, Outcome) framework: P (adult population), I(E) (high dietary intake or supplementation of Mg), C (low dietary intake of Mg or placebo group), and O (sleep pattern including sleep duration, sleep-onset latency, night awakenings, sleep stages, and sleep phases). The present study involved 7,582 subjects from 9 published cross-sectional, cohort, and RCT systematically reviewed the possible links between Mg and sleep quality (daytime falling asleep, sleepiness, snoring, and sleep duration) in an adult population. Observational studies suggested an association between Mg statuses and sleep quality, while the RCTs reported contradictory findings. This systematic review revealed an association between magnesium status and sleep quality (daytime falling asleep, sleepiness, snoring, and sleep duration) according to the observational studies, while the randomized clinical trials showed an uncertain association between magnesium supplementation and sleep disorders. The association between dietary magnesium and sleep patterns needs well-designed randomized clinical trials with a larger sample size and longer follow-up time (more than 12 weeks) to further clarify the relationship.
Topics: Adult; Humans; Magnesium; Snoring; Cross-Sectional Studies; Sleepiness; Sleep
PubMed: 35184264
DOI: 10.1007/s12011-022-03162-1 -
BMC Medical Education Feb 2021It has been previously shown that a high percentage of medical students have sleep problems that interfere with academic performance and mental health. (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
It has been previously shown that a high percentage of medical students have sleep problems that interfere with academic performance and mental health.
METHODS
To study the impact of sleep quality, daytime somnolence, and sleep deprivation on medical students, we analyzed data from a multicenter study with medical students in Brazil (22 medical schools, 1350 randomized medical students). We applied questionnaires of daytime sleepiness, quality of sleep, quality of life, anxiety and depression symptoms and perception of educational environment.
RESULTS
37.8% of medical students presented mild values of daytime sleepiness (Epworth Sleepiness Scale - ESS) and 8.7% presented moderate/severe values. The percentage of female medical students that presented ESS values high or very high was significantly greater than male medical students (p < 0.05). Students with lower ESS scores presented significantly greater scores of quality of life and perception of educational environment and lower scores of depression and anxiety symptoms, and these relationships showed a dose-effect pattern. Medical students reporting more sleep deprivation showed significantly greater odds ratios of presenting anxiety and depression symptoms and lower odds of good quality of life or perception of educational environment.
CONCLUSIONS
There is a significant association between sleep deprivation and daytime sleepiness with the perception of quality of life and educational environment in medical students.
Topics: Brazil; Female; Humans; Male; Perception; Quality of Life; Sleep Deprivation; Sleepiness; Students, Medical; Surveys and Questionnaires
PubMed: 33596885
DOI: 10.1186/s12909-021-02544-8 -
Revue Neurologique Oct 2023Narcolepsy type 1 (NT1) and type 2 (NT2), also known as narcolepsy with and without cataplexy, are sleep disorders that benefited from major scientific advances over the... (Review)
Review
Narcolepsy type 1 (NT1) and type 2 (NT2), also known as narcolepsy with and without cataplexy, are sleep disorders that benefited from major scientific advances over the last two decades. NT1 is caused by the loss of hypothalamic neurons producing orexin/hypocretin, a neurotransmitter regulating sleep and wake, which can be measured in the cerebrospinal fluid (CSF). A low CSF level of hypocretin-1/orexin-A is a highly specific and sensitive biomarker, sufficient to diagnose NT1. Orexin-deficiency is responsible for the main NT1 symptoms: sleepiness, cataplexy, disrupted nocturnal sleep, sleep-related hallucinations, and sleep paralysis. In the absence of a lumbar puncture, the diagnosis is based on neurophysiological tests (nocturnal and diurnal) and the presence of the pathognomonic symptom cataplexy. In the revised version of the International Classification of sleep Disorders, 3rd edition (ICSD-3-TR), a sleep onset rapid eye movement sleep (REM) period (SOREMP) (i.e. rapid occurrence of REM sleep) during the previous polysomnography may replace the diurnal multiple sleep latency test, when clear-cut cataplexy is present. A nocturnal SOREMP is very specific but not sensitive enough, and the diagnosis of cataplexy is usually based on clinical interview. It is thus of crucial importance to define typical versus atypical cataplectic attacks, and a list of clinical features and related degrees of certainty is proposed in this paper (expert opinion). The time frame of at least three months of evolution of sleepiness to diagnose NT1 was removed in the ICSD-3-TR, when clear-cut cataplexy or orexin-deficiency are established. However, it was kept for NT2 diagnosis, a less well-characterized disorder with unknown clinical course and absence of biolo biomarkers; sleep deprivation, shift working and substances intake being major differential diagnoses. Treatment of narcolepsy is nowadays only symptomatic, but the upcoming arrival of non-peptide orexin receptor-2 agonists should be a revolution in the management of these rare sleep diseases.
Topics: Humans; Cataplexy; Orexins; Sleepiness; Narcolepsy; Sleep
PubMed: 37634997
DOI: 10.1016/j.neurol.2023.08.001 -
Medicine and Science in Sports and... Feb 2023This study aimed to test the hypothesis that a novel nutritional blend composed of tryptophan, glycine, magnesium, tart cherry powder, and l -theanine enhances... (Randomized Controlled Trial)
Randomized Controlled Trial
PURPOSE
This study aimed to test the hypothesis that a novel nutritional blend composed of tryptophan, glycine, magnesium, tart cherry powder, and l -theanine enhances subjective and objective measures of sleep during free living conditions.
METHODS
In a randomized, repeated-measures crossover and double-blind deception design, participants ( n = 9 males and 7 females, age = 24 ± 3 yr, body mass = 69.8 ± 11.6 kg, stature = 170.8 ± 9.1 cm) completed a 3-d familiarization period, followed by 3-d intervention and placebo trials. Subjective Pittsburgh Quality Sleep Index, Core Consensus Sleep Diary, and Karolinska Sleepiness Scale survey tools, alongside objective actigraphy measures of sleep, were assessed, with daily nutritional intake, activity, and light exposure standardized between trials. Participants provided daily urine samples for assessment of targeted and untargeted metabolomes.
RESULTS
The intervention trial reduced sleep onset latency (-24 ± 25 min; P = 0.002), increased total sleep time (22 ± 32 min; P = 0.01), and increased sleep efficiency (2.4% ± 3.9%; P = 0.03), while also reducing morning sleepiness ( P = 0.02). Throughout the study, 75% of participants remained blinded to sleep assessment as a primary outcome measure, with 56% subjectively indicating improved sleep during the intervention trial. Metabolomic analysis highlighted several significantly altered metabolomes related to sleep regulation between trials, inclusive of 6-sulfatoxymelatonin, d -serine, and l -glutamic acid.
CONCLUSIONS
Data demonstrate that using the proposed blend of novel nutritional ingredients during free living conditions reduced sleep onset latency, increased total sleep duration, and increased sleep efficiency, leading to reduced perceptions of morning sleepiness. These effects may be mediated by the upregulation of key metabolites involved in the neurophysiological modulation of the sleep/wake cycle.
Topics: Male; Female; Humans; Young Adult; Adult; Sleep Latency; Sleepiness; Sleep; Actigraphy; Double-Blind Method; Deception
PubMed: 36094342
DOI: 10.1249/MSS.0000000000003040 -
Sleep Medicine Clinics Dec 2019This article reports on sleepiness, drowsiness, tiredness, and fatigue. An assessment of sleepiness can be done with electroencephalograms, electrooculograms, and... (Review)
Review
This article reports on sleepiness, drowsiness, tiredness, and fatigue. An assessment of sleepiness can be done with electroencephalograms, electrooculograms, and electromyograms in validated tests, such as the multiple sleep latency test and the maintenance of wakefulness test. These 2 tests serve as references for quantitative assessment of daytime sleepiness and drowsiness. Correlates for sleepiness, such as reaction time tests, can be used but are less reliable. Questionnaires are self-administered and popular measures for perceived sleepiness. Driver drowsiness assessment is an important part of sleep laboratory testing, because European Union regulations require assessments due to risk of accidents in patients with sleep disorders.
Topics: Automobile Driving; Electroencephalography; Electrooculography; Humans; Polysomnography; Reaction Time; Sleep Wake Disorders; Sleepiness
PubMed: 31640874
DOI: 10.1016/j.jsmc.2019.08.004 -
Journal of Global Health Dec 2023Unhealthy lifestyle and diet may contribute to the development of cardiovascular disease (CVD), but limited evidence exists regarding the association between sleep...
Interplay of sleep patterns and oxidative balance score on total cardiovascular disease risk: Insights from the National Health and Nutrition Examination Survey 2005-2018.
BACKGROUND
Unhealthy lifestyle and diet may contribute to the development of cardiovascular disease (CVD), but limited evidence exists regarding the association between sleep patterns, oxidative stress-related exposures to diet and lifestyle, and CVD risk.
METHODS
We analysed data from 10 212 adults in the National Health and Nutrition Examination Survey (NHANES) database (2005-2018). Self-report questionnaires were used to collect data on sleep duration, sleepiness, and trouble sleeping, classified into three categories: healthy, intermediate, and poor sleep patterns. Healthy sleep was defined as sleeping seven to nine hours per night with no self-reported sleepiness or trouble sleeping, while intermediate and poor sleep patterns indicated one and two to three sleep problems, respectively. The oxidative balance score (OBS) was calculated based on twenty oxidative stress-related exposures to dietary and lifestyle factors, with a higher score indicating greater antioxidant exposure. Survey-based multivariable-adjusted regression analysis was conducted to examine the association of sleep patterns or OBS alone and combined with the total and specific CVD risk.
RESULTS
Participants with poor sleep patterns had a higher likelihood of developing CVD (odds ratio (OR) = 1.76; 95% confidence interval (CI) = 1.26-2.45, P < 0.05), while an inverse association was found between OBS and CVD risk (quartile (Q) 4 vs Q1: OR = 0.67; 95% CI = 0.47-0.94, P = 0.02, P for trend <0.05). There was an interaction between sleep patterns and OBS (P for interaction = 0.03). Participants with unhealthy (intermediate and poor) sleep patterns and pro-oxidant OBS (Q1 and Q2) were significantly associated with increased risk of total CVD (OR = 2.31; 95% CI = 1.42-3.74, P < 0.05), as well as angina and congestive heart failure, but not coronary heart disease (CHD). Stratified analysis showed that among individuals without hyperlipidaemia, participants with both unhealthy sleep patterns and pro-oxidant OBS exhibited a higher risk of CHD compared to those with healthy sleep patterns and antioxidative OBS.
CONCLUSIONS
Unhealthy sleep patterns and reduced oxidative balance are positively associated with an increased risk of overall and specific CVD. Interventions that target healthy sleep habits and antioxidant-rich diets and lifestyles may be important for reducing the risk of CVD.
Topics: Adult; Humans; Nutrition Surveys; Cardiovascular Diseases; Antioxidants; Reactive Oxygen Species; Risk Factors; Sleepiness; Oxidative Stress; Sleep
PubMed: 38085249
DOI: 10.7189/jogh.14.04170 -
Sleep Medicine Clinics Sep 2022Undesirable side effects of insomnia and/or sleepiness may occur with many prescribed drugs, psychotropics as well as non-psychotropics. These central nervous system... (Review)
Review
Undesirable side effects of insomnia and/or sleepiness may occur with many prescribed drugs, psychotropics as well as non-psychotropics. These central nervous system effects can be explained by the interactions of the drug with any of the numerous neurotransmitters and receptors that are involved in sleep and wakefulness. Also a close - sometimes bidirectional - relationship between disease and (disturbed) sleep/wakefulness is often present e.g. in chronic pain; drug effects may lead this vicious circle in both ways. Besides the importance for health and quality of life, effects on sleep or waking function can be a potential source of non-compliance.
Topics: Disorders of Excessive Somnolence; Humans; Quality of Life; Sleep; Sleep Initiation and Maintenance Disorders; Sleepiness; Wakefulness
PubMed: 36150808
DOI: 10.1016/j.jsmc.2022.06.011 -
Traffic Injury Prevention 2023Driver monitoring systems are growing in importance as well as capability. This paper reports drowsy driving detection models that use vehicular, behavioral, and...
OBJECTIVE
Driver monitoring systems are growing in importance as well as capability. This paper reports drowsy driving detection models that use vehicular, behavioral, and physiological data. The objectives were to augment camera-based system with vehicle-based and heart rate variability measures from a wearable device and compare the performance of drowsiness detection models that use these data sources. Timeliness of the models in predicting drowsiness is analyzed. Timeliness refers to how quickly a model can identify drowsiness and, by extension, how far in advance of an adverse event a classification can be given.
METHODS
Behavioral data were provided by a production-type Driver Monitoring System manufactured by Aisin Technical Center of America. Vehicular data were recorded from the National Advanced Driving Simulator's large-excursion motion-base driving simulator. Physiological data were collected from an Empatica E4 wristband. Forty participants drove the simulator for up to three hours after being awake for at least 16 hours. Periodic measurements of drowsiness were recorded every ten minutes using both observational rating of drowsiness by an external rater and the self-reported Karolinska Sleepiness Scale. Nine binary random forest models were created, using different combinations of data sources and ground truths.
RESULTS
The classification accuracy of the nine models ranged from 0.77 to 0.92 on a scale from 0 to 1, with 1 indicating a perfect model. The best-performing model included physiological data and used a reduced dataset that eliminated missing data segments after heartrate variability measures were computed. The most timely model was able to detect the presence of drowsiness 6.7 minutes before a drowsy lane departure.
CONCLUSIONS
The addition of physiological measures added a small amount of accuracy to the model performance. Models trained on observational ratings of drowsiness detected drowsiness earlier than those based only on Karolinska Sleepiness Scale, making them more timely in detecting the onset of drowsiness.
Topics: Humans; Wakefulness; Automobile Driving; Sleepiness; Accidents, Traffic; Monitoring, Physiologic; Sleep Stages
PubMed: 37267009
DOI: 10.1080/15389588.2023.2164839 -
Journal of Sleep Research Dec 2019
Topics: Emotions; Humans; Quality of Life; Sleep; Sleep Wake Disorders; Sleepiness
PubMed: 31691456
DOI: 10.1111/jsr.12942 -
Continuum (Minneapolis, Minn.) Aug 2020This article explains the clinical approach to patients presenting with sleepiness or sleeplessness in a neurologic practice setting. Addressing the patient's sleep... (Review)
Review
PURPOSE OF REVIEW
This article explains the clinical approach to patients presenting with sleepiness or sleeplessness in a neurologic practice setting. Addressing the patient's sleep symptoms may help improve symptoms of their other underlying primarily neurologic disorder.
RECENT FINDINGS
New diagnostic modalities at home such as home sleep apnea testing have improved access and diagnosis of sleep apnea. Consumer health tracking devices have also helped patients focus on their sleep duration and quality, prompting them to bring their concerns to their neurologist.
SUMMARY
Like many neurologic disorders, a detailed history and physical examination are critical in the evaluation of patients with sleepiness or sleeplessness. Patients who have neurologic disorders are more likely to have poor-quality sleep. Questions about the patient's sleep schedule or screening patients for common sleep disorders such as sleep apnea and restless legs syndrome (RLS) are useful to add to a typical neurologic evaluation to better recognize sleep disorders in this population. Polysomnography, home sleep apnea testing, multiple sleep latency tests, and actigraphy can be used with the available history and examination to determine the proper diagnosis and management plan for these patients.
Topics: Actigraphy; Humans; Nervous System Diseases; Neurologic Examination; Polysomnography; Sleep Initiation and Maintenance Disorders; Sleepiness
PubMed: 32756226
DOI: 10.1212/CON.0000000000000880