Sleep and physiological systems: a functional perspective

Manzar, Dilshad; Zannat, Wassilatul; Hussain, M. Ejaz

doi:10.1080/09291016.2014.966504

Cited by 17 publications

(10 citation statements)

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“…Polysubstance use involving the concurrent use of khat is associated with poor sleep. Sleep is intricately related to the function of various physiological systems[ 26 ] and fluctuations in the physical microenvironment. [ 27 ] The health-care systems of the developing societies, which are already under pressure from enormous levels of infectious diseases, may be better placed to strategize prevention and awareness programs to decrease unwarranted sleep problems from polysubstance use.…”

Section: Discussionmentioning

confidence: 99%

Poor sleep in concurrent users of alcohol, khat, and tobacco smoking in community-dwelling Ethiopian adults

et al. 2018

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BACKGROUND:Polysubstance dependence, stress, and sleep disturbances are inter-related by shared physiological pathways. No study has investigated the relationship between sleep and concurrent use of alcohol and khat.OBJECTIVES:The aim of the study was to assess the effect of the concurrent use of alcohol and khat as well as concurrent alcohol, khat, and tobacco smoking on sleep patterns.METHODS:A sample of community-dwelling adults (n = 339, age = 25.5 ± 5.7 years, body mass index = 22.0 ± 2.2 kg/m2) from Mizan-Aman, Ethiopia, participated in a cross-sectional study. Semi-structured tool for sociodemographics, substance use habit, and the Pittsburgh Sleep Quality Index (PSQI) were used. The difference in sleep patterns among substance use groups, i.e., nonusers, alcohol use only, concurrent alcohol and khat use, and concurrent alcohol, khat and tobacco smoking was assessed.RESULTS:The poorest sleep quality was found among concurrent users of alcohol, khat, and tobacco smoking (PSQI global score = 8.2 ± 2.4), followed by concurrent users of alcohol and khat (PSQI global score = 7.3 ± 2.9) (F (3.335) = 23.64, P < 0.001). There were significant differences in the PSQI component score of sleep quality χ2(3) =159.09, P < 0.001, the PSQI component score of sleep latency χ2(3) = 128.09, P < 0.001, and the PSQI component score of sleep disturbances χ2(3) = 37.69, P < 0.001 between substance use groups.CONCLUSION:Concurrent use of alcohol, khat as well as alcohol, khat, and tobacco smoking was associated with poor sleep. Sleep disturbances in this group need management to avoid the prospective development of psychosocial disturbances in polysubstance users.

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Section: Discussionmentioning

confidence: 99%

Poor sleep in concurrent users of alcohol, khat, and tobacco smoking in community-dwelling Ethiopian adults

et al. 2018

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“…The ever-increasing list of problems known to be caused by sleep dysfunction has led to recognition that poor sleep has a complex relationship with overall health. It is now appreciated that disturbed sleep interacts bi-directionally with numerous neurological, physiological, psychological, and behavioral factors [ 4 , 12 – 14 ]. The central role of sleep in overall health has thus underscored the need for both reliable, validated subjective tools and objective polysomnographic (PSG) assessment in modern medical practice.…”

Section: Introductionmentioning

confidence: 99%

Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review

Manzar

BaHammam

Hameed³

et al. 2018

Health Qual Life Outcomes

148

145

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BackgroundThe Pittsburgh Sleep Quality Index (PSQI) dimensionality is much debated, with the greatest number of reported factor structures. Therefore, this review appraised the methodologies of studies investigating the factor structure of the PSQI.Material and methodsMEDLINE, PsycInfo, AJOL, BASE, Cochrane Library, Directory of Open Access Journals (Lund University), CINAHL, and Embase were searched systematically to include articles published till 23rd March, 2018. The articles with the objective of factor analysis of the PSQI (20 articles) or with a major section on the same subject (25 articles) were included. There was no limitation about participant characteristics. Descriptive analysis of articles for measures of the suitability of the data for factor analysis, details of the exploratory factor analysis (EFA) and details of the confirmatory factor analysis (CFA) was performed.ResultsThe analysis used by the majority did not employ the simplest scheme for interpreting the observed data: the parsimony principle. Other shortcomings included under- or non-reporting of sample adequacy measures (11 out of 45 articles), non-use of EFA (20 out of 45 articles), use of EFA without relevant details, non-use of CFA (11 out of 45 articles), and use of CFA without relevant details. Overall, 31 out of 45 articles did not use either EFA or CFA.ConclusionWe conclude that the various PSQI factor structures for standard sleep assessment in research and clinical settings may need further validation.Trial registrationNot applicable because this was a review of existing literature.

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“…During sleep, learning and memory processes consolidate and strengthen retrieval of factual information and facilitate procedural motor skills, which contribute to athletic performance ( Walker and Stickgold, 2004 ). Sleep is also important for energy reestablishment ( Jung et al, 2011 ); emotional regulation ( Palmer and Alfano, 2017 ); and the functioning of immune, cardiovascular, endocrine, and metabolic systems ( Manzar et al, 2015 ). In athletic populations, sleep has, consequently, been recognized as an essential aspect of recovery ( O’Donnell et al, 2018 ), enabling athletic progression and performance improvement ( Kellmann et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Reciprocal Associations Between Sleep, Mental Strain, and Training Load in Junior Endurance Athletes and the Role of Poor Subjective Sleep Quality

et al. 2020

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The importance of adequate sleep for athletic functioning is well established. Still, the literature shows that many athletes report sleep of suboptimal quality or quantity. To date, no research has investigated how bidirectional variations in mental and physiological states influence sleep patterns. The present study, therefore, investigates reciprocal associations between sleep, mental strain, and training load by utilizing a prospective, observational design. In all, 56 junior endurance athletes were followed over 61 consecutive days. Unobtrusive, objective measurements of sleep with novel radar technology were obtained, and subjective daily reports of mental strain and training load were collected. The role of subjective sleep quality was investigated to identify whether the reciprocal associations between sleep, mental strain, and training load depended on being a good versus poor sleeper. Multilevel modeling with Bayesian estimation was used to investigate the relationships. The results show that increases in mental strain are associated with decreased total sleep time (TST, 95% CI = −0.12 to −0.03), light sleep (95% CI = −0.08 to −0.00), and sleep efficiency (95% CI = −0.95 to −0.09). Further, both mental strain and training load are associated with subsequent deceased rapid eye movement (REM, respectively, 95% CI = −0.05 to −0.00 and 95% CI = −0.06 to −0.00) sleep. Increases in TST, light, deep, and REM sleep are all associated with subsequent decreased training load (respectively, 95% CI = −0.09 to −0.03; 95% CI = −0.10 to −0.01; 95% CI = −0.22 to −0.02; 95% CI = −0.18 to −0.03). Finally, among poor sleepers, increases in sleep onset latency are associated with increases in subsequent mental strain (95% CI = 0.09–0.46), and increases in deep sleep are associated with decreases in subsequent training load (95% CI = −67.65 to 11.43). These results offer novel insight into the bidirectional associations between sleep, mental strain, and training load in athletes and demonstrate the detrimental effects of mental strain on sleep, likely caused by mental activation incompatible with sleep. An increased need for recovery, suggested by increased TST and time in different sleep stages, is associated with subsequent self-regulatory reduction of training loads by the athletes. In poor sleepers, increases in deep sleep may suggest an elevated need for physiological recovery.

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Sleep and physiological systems: a functional perspective

Cited by 17 publications

References 100 publications

Poor sleep in concurrent users of alcohol, khat, and tobacco smoking in community-dwelling Ethiopian adults

Poor sleep in concurrent users of alcohol, khat, and tobacco smoking in community-dwelling Ethiopian adults

Dimensionality of the Pittsburgh Sleep Quality Index: a systematic review

Reciprocal Associations Between Sleep, Mental Strain, and Training Load in Junior Endurance Athletes and the Role of Poor Subjective Sleep Quality

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