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Effects of acute sleep loss on leptin, ghrelin, and adiponectin in adults with healthy weight and obesity: A laboratory study.
van Egmond, LT, Meth, EMS, Engström, J, Ilemosoglou, M, Keller, JA, Vogel, H, Benedict, C
Obesity (Silver Spring, Md.). 2023;31(3):635-641
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A lack of sleep may be a risk factor for weight gain. Leptin is an adipocyte-derived hormone that activates satiety networks within the brain. Ghrelin, as opposed to leptin, is mainly produced by the stomach and it acts as a hunger hormone, signalling fuel status to the central nervous system. Some studies have found either no alterations or higher leptin and lower ghrelin blood levels following experimental sleep deprivation. The aim of this study was to investigate whether blood concentrations of leptin, ghrelin, and adiponectin are affected by acute total sleep deprivation in a sex- and weight-specific manner. This study is a laboratory study based on blood samples from 44 participants, mainly university students. Results show that: - acute total sleep deprivation is linked to lower serum levels of the adipokine leptin and higher blood levels of ghrelin. - following sleep deprivation, serum adiponectin levels were elevated. - the drop in serum leptin was larger in women after total sleep deprivation; however, there wasn’t a significant association between biological sex and experimental condition. - the increase in blood levels of adiponectin was slightly more pronounced among women, whereas there weren’t any differences in the effects of sleep loss on plasma ghrelin. Authors conclude that acute total sleep deprivation shifts the endocrine balance from the satiety hormone leptin toward the hunger-promoting hormone ghrelin. However, further investigation in larger samples focusing on their findings linked to sex- and weight-specific differences in leptin, ghrelin, and adiponectin are needed.
Expert Review
Conflicts of interest:
None
Take Home Message:
Sleep deprivation may shift the balance of appetite controlling hormones causing an increase in hunger and decreased satiety and therefore resulting in increased food intake. These changes may be more pronounced in biological females.
Evidence Category:
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X
A: Meta-analyses, position-stands, randomized-controlled trials (RCTs)
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B: Systematic reviews including RCTs of limited number
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C: Non-randomized trials, observational studies, narrative reviews
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D: Case-reports, evidence-based clinical findings
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E: Opinion piece, other
Summary Review:
Introduction
Sleep deprivation may contribute to weight gain and obesity through its effect on the hormonal pathways promoting hunger and satiety. Research has also linked chronic sleep loss with an increase in the brain reward response to food, thus driving an increase in daily food intake. Leptin and ghrelin are hormones involved in the control of food intake. Some research has associated alterations in these hormones following sleep loss, whilst others have not.
This study aimed to investigate whether biological sex and weight status affect fasting serum levels of leptin, ghrelin and adiponectin following chronic sleep deprivation in a supervised laboratory setting.
Methods
This randomised crossover design study included n=44 mixed sex participants with a mean age of 24.9 years. A total of 19 of the participants were classed as obese, with the remaining n= 25 participants were considered normal weight. Participants completed 2 nights in experimental sessions under continuously supervised conditions in a laboratory. One night was spent awake and the other asleep. Fasting blood samples were taken the morning after each session to measure levels of leptin, ghrelin and adiponectin.
Results
Serum levels of leptin after one night’s sleep loss were around 7% lower than those measured after sleep (17.3 = +/-2.6 vs 18.6 +/- 2.8 ng/mL, p = 0.037). Adjustments using sex-stratified analysis showed significantly lower levels of serum leptin in women (25.8 +/_4.3 vs 28.1 +/_ 4.7 ng/mL, p = 0.030) but not for men (10.1 +/_ 2.4 vs 10.6 +/_ 2.3 ng/mL, p = 0.458). However, when comparing individual participant differences between sleep and wake sessions, the results were not significant. Additionally, no significant differences were found between normal weight and obese participants.
Higher levels of ghrelin were found following sleep deprivation in both sexes and weight sub-groups (839.4 +/-77.5 vs 741.4+/-63.2 pg/mL, p= 0.003). Adiponectin was also found to be elevated in all participants regardless of biological sex or weight status (7.5 +/- 0.6 vs 6.8 +/- 0.6ug/mL, p= 0.003). However, ghrelin was observed to increase slightly more in participants with obesity, whereas elevations in adiponectin were slightly greater in those of normal weight.
Conclusion
In this study, sleep loss was associated with lowered levels of leptin and higher levels of ghrelin. Analysis between biological sexes indicated that there may be a greater decrease in leptin in females. Serum levels of adiponectin were also found to be elevated after sleep deprivation for both sexes with a slightly larger increase in women. These changes may result in increased hunger and food intake and decreased satiety. No significant differences were found between normal weight and obese participants.
Notes: The authors reported no conflicts of interest.
Clinical practice applications:
Sleep deprivation may lead to lower levels of leptin in both sexes with a greater decrease for females. Ghrelin and adiponectin levels may be increased in both men and women after sleep loss with a slightly larger increase in adiponectin for women. This could lead to an increase in appetite, food consumption and therefore weight gain, particularly in women.
Considerations for future research:
- Larger studies are needed to investigate sex and weight status related differences in serum levels of ghrelin, leptin and adiponectin.
- It may be beneficial for blood samples to be taken at different points during the day to allow for fluctuations in hormone levels.
- Food intake should be measured to monitor any increases in food intake.
Abstract
OBJECTIVE This study investigated whether blood concentrations of leptin, ghrelin, and adiponectin are affected by acute total sleep deprivation in a sex- and weight-specific manner. METHODS A total of 44 participants (mean age 24.9 years; 20 women; 19 with obesity) participated in a crossover design, including one night of sleep deprivation and one night of sleep in the laboratory. After each night, fasting blood was collected. RESULTS After sleep deprivation, fasting levels of leptin were lower (mean [SE], vs. sleep: 17.3 [2.6] vs. 18.6 [2.8] ng/mL), whereas those of ghrelin and adiponectin were higher (839.4 [77.5] vs. 741.4 [63.2] pg/mL and 7.5 [0.6] vs. 6.8 [0.6] μg/mL, respectively; all p < 0.05). The changes in leptin and adiponectin following sleep loss were more pronounced among women. Furthermore, the ghrelin increase was stronger among those with obesity after sleep loss. Finally, the sleep loss-induced increase in adiponectin was more marked among normal-weight participants. CONCLUSIONS Acute sleep deprivation reduces blood concentrations of the satiety hormone leptin. With increased blood concentrations of ghrelin and adiponectin, such endocrine changes may facilitate weight gain if persisting over extended periods of sleep loss. The observed sex- and weight-specific differences in leptin, ghrelin, and adiponectin call for further investigation.
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Improving stress management, anxiety, and mental well-being in medical students through an online Mindfulness-Based Intervention: a randomized study.
Fazia, T, Bubbico, F, Nova, A, Buizza, C, Cela, H, Iozzi, D, Calgan, B, Maggi, F, Floris, V, Sutti, I, et al
Scientific reports. 2023;13(1):8214
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Medical students commonly experience anxiety, depression, burnout and emotional discomfort due to the pressures of medical school. This randomised, controlled study of 362 medical students at Italian Universities evaluated the effectiveness of a 5-week online mindfulness-based intervention (MBI), consisting of an introductory session, 8 sessions of 35 min integral meditation and 10 min yoga, and one dietary advice/question and answer session with a nutritionist. The control group received no intervention. Effectiveness was measured through a variety of validated questionnaires for perceived stress, anxiety, wellbeing, emotional health, resilience and cognition. Overall, at baseline, participants of this study fared worse for stress than other studies had shown for general populations. The MBI was effective in improving perceived stress, mental wellbeing, emotional regulation, resilience, tendency to mind-wandering, ability to maintain attention and overall distress, although effect sizes for all outcomes were small. No statistically significant effect was seen for the anxiety rating. Interestingly, two cohorts were included in this study and whilst one benefitted from the programme, the other did not, one explanation of which may be that they were done during different phases of the COVID pandemic. The authors conclude that adopting MBI may help improve students’ wellbeing.
Abstract
Pressures and responsibilities of medical school put a strain on medical student's personal wellbeing, leading among all to high rates of anxiety, emotional discomfort and stress. In this work we evaluated the effectiveness of a comprehensive Mindfulness-Based Intervention (MBI) in reducing this load. The intervention comprised 10 twice-a-week Integral Meditation classes, dietary advice, and brief yoga sessions. We performed a randomized trial on two cohort of medical students from Italian universities: 239 in cohort 1 (106 treated and 133 controls), and 123 in cohort 2 (68 treated and 55 control) for a total sample of 362 students. Nine questionnaires for evaluating the effectiveness of our intervention on stress (PSS), state anxiety (STAIX-1), well-being (WEMWBS), mind-wandering (MW-S), overall distress (PANAS), emotion regulation (DERS), resilience (RS-14), and attentional control (ACS-C and ACS-D) were collected both pre and post intervention. Linear mixed effect models were run on the whole sample showing that, after multiple testing correction, our intervention was effective in reducing perceived stress (β = - 2.57 [- 4.02; - 1.12], p = 0.004), improving mental well-being (β = 2.82 [1.02; 4.63], p = 0.008) and emotional regulation (β = - 8.24 [- 12.98; - 3.51], p = 0.004), resilience (β = 3.79 [1.32; 6.26], p = 0.008), reducing the tendency to wander with the mind (β = - 0.70 [- 0.99; - 0.39], p = 0.0001), ameliorating the ability to maintain attention (AC-S (β = - 0.23 [- 0.44; - 0.02], p = 0.04) and AC-D (β = - 0.19 [- 0.36; - 0.01], p = 0.04)), and the overall distress (β = 1.84 [0.45; 3.23], p = 0.02).
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Psychobiotic Lactobacillus plantarum JYLP-326 relieves anxiety, depression, and insomnia symptoms in test anxious college via modulating the gut microbiota and its metabolism.
Zhu, R, Fang, Y, Li, H, Liu, Y, Wei, J, Zhang, S, Wang, L, Fan, R, Wang, L, Li, S, et al
Frontiers in immunology. 2023;14:1158137
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Test anxiety, characterised by feelings of failure, tension, and worrying when an individual faces a vital test for promoting, occurs prevalently among college students. Lactobacillus plantarum, has become increasingly popular in reducing the severity of anxiety and depression in stressed animal models. The main aim of this study was to evaluate the psychological effects of Lactobacillus plantarum JYLP-326 (JYLP-326) on exam stress-induced behaviours like anxiety, depression, and insomnia. This study enrolled 60 anxious and 30 un-anxious undergraduates preparing for the approaching exams. Out of the 60 anxious participants, 30 were selected randomly to receive the probiotic product and the other 30 received a placebo product. The 30 un-anxious students were assigned as the healthy control group. Results demonstrated that the intervention of JYLP-326 is effective in alleviating exam stress-induced symptoms in college students. Furthermore, it also protected against exam stress-induced dysbiosis of the gut microbiota and the disturbances of faecal metabolomic. Authors conclude that the changed gut microbiota genera and faecal metabolites were closely associated with stress-related symptoms like anxiety/depression and insomnia, indicating that they might be regarded as biomarkers for diagnosing and treating stress and anxiety disorders.
Abstract
INTRODUCTION Test anxiety is a common issue among college students, which can affect their physical and psychological health. However, effective interventions or therapeutic strategies are still lacking. This study aims to evaluate the potential effects of Lactobacillus plantarum JYLP-326 on test anxious college students. METHODS Sixty anxious students were enrolled and randomly allocated to the placebo group and the probiotic group. Both groups were instructed to take placebo and JYLP-326 products twice per day for three weeks, respectively. Thirty unanxious students with no treatments were assigned to a regular control group. The anxiety, depression, and insomnia questionnaires were used to measure students' mental states at the baseline and the end of this study. 16S rRNA sequencing and untargeted metabolomics were performed to analyze the changes in the gut microbiota and fecal metabolism. RESULTS The questionnaire results suggested that JYLP-326 administration could relieve the symptoms of anxiety, depression, and insomnia in test anxious students. The gut microbiomes of the placebo group showed a significantly greater diversity index than the control group (p < 0.05). An increased abundance of Bacteroides and Roseburia at the genus level was observed in the placebo group, and the relative abundance of Prevotella and Bifidobacterium decreased. Whereas, JYLP-326 administration could partly restore the disturbed gut microbiota. Additionally, test anxiety was correlated with disordered fecal metabolomics such as a higher Ethyl sulfate and a lower Cyclohexylamine, which could be reversed after taking JYLP-326. Furthermore, the changed microbiota and fecal metabolites were significantly associated with anxiety-related symptoms. CONCLUSION The results indicate that the intervention of L. plantarum JYLP-326 could be an effective strategy to alleviate anxiety, depression, and insomnia in test anxious college students. The potential mechanism underlying this effect could be related to the regulation of gut microbiota and fecal metabolites.
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Causal relationship between nonalcoholic fatty liver disease and different sleep traits: a bidirectional Mendelian randomized study.
Sun, Z, Ji, J, Zuo, L, Hu, Y, Wang, K, Xu, T, Wang, Q, Cheng, F
Frontiers in endocrinology. 2023;14:1159258
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Non-alcoholic fatty liver disease (NAFLD) is caused by a build up of fat in the liver. NAFLD is becoming more common, with the rise in rates of obesity. There are no specific medications available for NAFLD and patients are advised to manage their diets and lifestyle following diagnosis. The aim of this study was to assess and evaluate the causal relationship between sleep and NAFLD. The study was a two-way Mendelian randomised clinical trial. Results showed that different sleep traits can be the cause of the onset and exacerbation of NAFLD. NAFLD does not change sleep traits and the causal relationship between them is unidirectional. Authors conclude that sleep characteristics are associated with an elevated risk of NAFLD. Thus, enhancing sleep should be considered by healthcare practitioners as part of prevention and management NAFLD.
Abstract
BACKGROUND AND AIMS Non-alcoholic fatty liver disease(NAFLD) is common worldwide and has previously been reported to be associated with sleep traits. However, it is not clear whether NAFLD changes sleep traits or whether the changes in sleep traits lead to the onset of NAFLD. The purpose of this study was to investigate the causal relationship between NAFLD and changes in sleep traits using Mendelian randomization. METHODS We proposed a bidirectional Mendelian randomization (MR) analysis and performed validation analyses to dissect the association between NAFLD and sleep traits. Genetic instruments were used as proxies for NAFLD and sleep. Data of genome-wide association study(GWAS) were obtained from the center for neurogenomics and cognitive research database, Open GWAS database and GWAS catalog. Three MR methods were performed, including inverse variance weighted method(IVW), MR-Egger, weighted median. RESULTS In total,7 traits associated with sleep and 4 traits associated with NAFLD are used in this study. A total of six results showed significant differences. Insomnia was associated with NAFLD (OR(95% CI)= 2.25(1.18,4.27), P = 0.01), Alanine transaminase levels (OR(95% CI)= 2.79(1.70, 4.56), P =4.71×10-5) and percent liver fat(OR(95% CI)= 1.31(1.03,1.69), P = 0.03). Snoring was associated with percent liver fat (1.15(1.05,1.26), P =2×10-3), alanine transaminase levels (OR(95% CI)= 1.27(1.08,1.50), P =0.04).And dozing was associated with percent liver fat(1.14(1.02,1.26), P =0.02).For the remaining 50 outcomes, no significant or definitive association was yielded in MR analysis. CONCLUSION Genetic evidence suggests putative causal relationships between NAFLD and a set of sleep traits, indicating that sleep traits deserves high priority in clinical practice. Not only the confirmed sleep apnea syndrome, but also the sleep duration and sleep state (such as insomnia) deserve clinical attention. Our study proves that the causal relationship between sleep characteristics and NAFLD is the cause of the change of sleep characteristics, while the onset of non-NAFLD is the cause of the change of sleep characteristics, and the causal relationship is one-way.
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Sleep loss disrupts the neural signature of successful learning.
Guttesen, AÁV, Gaskell, MG, Madden, EV, Appleby, G, Cross, ZR, Cairney, SA
Cerebral cortex (New York, N.Y. : 1991). 2023;33(5):1610-1625
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Understanding how sleep disturbances impair learning and memory is increasingly important in modern society, where many people fail to regularly obtain an adequate amount of sleep. The aim of this study was to investigate the relationship between sleep-associated consolidation and next-day learning and how suppressing slow-wave activity (SWA) [during slow-wave sleep, electrical activity in the brain changes while the body relaxes into deep and restorative rest] contributes to this relationship. This study was a within-subjects (n = 30), crossover design which showed that sleep improved both memory retention and next-day learning however, there was no evidence of a relationship between these measures or with SWA. Furthermore, an absence of sleep disrupts the neural operations underpinning memory encoding, leading to suboptimal performance. Authors conclude that an extended lack of sleep might disrupt the ability to draw upon semantic knowledge when encoding novel associations, necessitating the use of more surface-based and ultimately suboptimal routes to learning.
Abstract
Sleep supports memory consolidation as well as next-day learning. The influential "Active Systems" account of offline consolidation suggests that sleep-associated memory processing paves the way for new learning, but empirical evidence in support of this idea is scarce. Using a within-subjects (n = 30), crossover design, we assessed behavioral and electrophysiological indices of episodic encoding after a night of sleep or total sleep deprivation in healthy adults (aged 18-25 years) and investigated whether behavioral performance was predicted by the overnight consolidation of episodic associations from the previous day. Sleep supported memory consolidation and next-day learning as compared to sleep deprivation. However, the magnitude of this sleep-associated consolidation benefit did not significantly predict the ability to form novel memories after sleep. Interestingly, sleep deprivation prompted a qualitative change in the neural signature of encoding: Whereas 12-20 Hz beta desynchronization-an established marker of successful encoding-was observed after sleep, sleep deprivation disrupted beta desynchrony during successful learning. Taken together, these findings suggest that effective learning depends on sleep but not necessarily on sleep-associated consolidation.
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Sleep disruption and activation of cellular inflammation mediate heightened pain sensitivity: a randomized clinical trial.
Irwin, MR, Olmstead, R, Bjurstrom, MF, Finan, PH, Smith, MT
Pain. 2023;164(5):1128-1137
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Sleep disturbance is associated with elevated levels of inflammation. Experimental studies have found that even a modest amount of sleep loss activates inflammatory processes. Experimental sleep disruption also induces alterations in sleep architecture including loss of slow wave or N3 sleep and loss of rapid eye movement sleep. The aim of this study was to clarify whether changes in the amount of N3 sleep and cellular inflammation mediate thermal pain sensitivity (i.e., heat pain threshold) in response to experimental sleep disruption. This study was a secondary analysis (assessor-blind) of a randomised controlled trial. The enrolled participants were randomised to 1 of 2 groups: 2 nights of undisturbed sleep (US) and 2 nights of sleep disruption or forced awakening (FA). Participants underwent 2 consecutive nights of US (or FA), followed by a 2-week washout interval in their home environment, and then completed 2 consecutive nights of the opposing sleep condition FA (or US). Results showed that in healthy adults, experimental disruption of sleep due to the administration of FA induced a significant decrease in heat pain threshold, as compared with responses after US. Experimental manipulation of sleep with FA also led to disturbance in sleep continuity and changes in sleep architecture, including loss of N3 sleep. Moreover, in the morning after FA, there was a robust activation of cellular inflammation Authors conclude that the differential loss of N3 sleep and increases in cellular inflammation may be important drivers of pain sensitivity in response to sleep disruption.
Abstract
Sleep loss heightens pain sensitivity, but the pathways underlying this association are not known. Given that experimental sleep disruption induces increases in cellular inflammation as well as selective loss of slow wave, N3 sleep, this study examined whether these mechanisms contribute to pain sensitivity following sleep loss in healthy adults. This assessor-blinded, cross-over sleep condition, single-site, randomized clinical trial enrolled 95 healthy adults (mean [SD] age, 27.8 [6.4]; female, 44 [53.7%]). The 2 sleep conditions were 2 nights of undisturbed sleep (US) and 2 nights of sleep disruption or forced awakening (FA, 8 pseudorandomly distributed awakenings and 200 minutes wake time during the 8-hour sleep opportunity), administered in a cross-over design after 2 weeks of washout and in a random order (FA-US; US-FA). Primary outcome was heat pain threshold (hPTH). Sleep architecture was assessed by polysomnography, and morning levels of cellular inflammation were evaluated by Toll-like receptor-4 stimulated monocyte intracellular proinflammatory cytokine production. As compared with US, FA was associated with decreases in the amount of slow wave or N3 sleep ( P < 0.001), increases in Toll-like receptor-4 stimulated production of interleukin-6 and tumor necrosis factor-α ( P = 0.03), and decreases in hPTH ( P = 0.02). A comprehensive causal mediation analysis found that FA had an indirect effect on hPTH by decreases in N3 sleep and subsequent increases in inflammation (estimate=-0.15; 95% confidence interval, -0.30 to -0.03; P < 0.05) with the proportion mediated 34.9%. Differential loss of slow wave, N3 sleep, and increases in cellular inflammation are important drivers of pain sensitivity after sleep disruption.Clinical Trials Registration: NCT01794689.
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Sleep-Opt-In: A Randomized Controlled Pilot Study to Improve Sleep and Glycemic Variability in Adults With Type 1 Diabetes.
Martyn-Nemeth, P, Duffecy, J, Quinn, L, Steffen, A, Baron, K, Chapagai, S, Burke, L, Reutrakul, S
The science of diabetes self-management and care. 2023;49(1):11-22
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Insufficient sleep (insufficient total sleep time) and irregular sleep timing (variability in the occurrence of sleep within a 24-hour period) are increasingly recognized as important contributors to glycaemic control and variability in type 1 diabetes (T1D). The aims of this study were to evaluate the feasibility and acceptability of a sleep intervention (Sleep-Opt-In) targeted for adults with type 1 diabetes with short or irregular sleep and to examine the effects of Sleep-Opt-In on sleep duration and regularity, glucose indices, and patient-reported outcomes. This study was a randomised controlled parallel trial design. Participants (n=14) were randomly assigned to either the Sleep-Opt-In intervention or a Healthy Living attention control group. Results showed that: - Sleep-Opt-In was feasible and acceptable to the target population. - participants with objectively confirmed short or irregular sleep, sleep irregularity improved by 25 minutes on average, whereas sleep duration improved only negligibly (8 minutes). - the control group experienced an increase in sleep duration but no change in sleep regularity. Authors conclude that Sleep-Opt-In is feasible, acceptable, and promising for further evaluation to improve sleep duration or regularity, glucose parameters and important patient reported outcomes of diabetes distress, daytime sleepiness, fatigue and depressive mood in the T1D population.
Abstract
PURPOSE The purpose of this study was to evaluate the feasibility and acceptability of a technology-assisted behavioral sleep intervention (Sleep-Opt-In) and to examine the effects of Sleep-Opt-In on sleep duration and regularity, glucose indices, and patient-reported outcomes. Short sleep duration and irregular sleep schedules are associated with reduced glycemic control and greater glycemic variability. METHODS A randomized controlled parallel-arm pilot study was employed. Adults with type 1 diabetes (n = 14) were recruited from the Midwest and randomized 3:2 to the sleep-optimization (Sleep-Opt-In) or Healthy Living attention control group. Sleep-Opt-In was an 8-week, remotely delivered intervention consisting of digital lessons, sleep tracker, and weekly coaching phone calls by a trained sleep coach. Assessments of sleep (actigraphy), glucose (A1C, continuous glucose monitoring), and patient-reported outcomes (questionnaires for daytime sleepiness, fatigue, diabetes distress, and depressive mood) were completed at baseline and at completion of the intervention. RESULTS Sleep-Opt-In was feasible and acceptable. Those in Sleep-Opt-In with objectively confirmed short or irregular sleep demonstrated an improvement in sleep regularity (25 minutes), reduced glycemic variability (3.2%), and improved time in range (6.9%) compared to the Healthy Living attention control group. Patient-reported outcomes improved only for the Sleep-Opt-In group. Fatigue and depressive mood improved compared to the control. CONCLUSIONS Sleep-Opt-In is feasible, acceptable, and promising for further evaluation as a means to improve sleep duration or regularity in the population of people with type 1 diabetes.
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Effects of mental contrasting on sleep and associations with stress: A randomized controlled trial.
Schmidt, LI, Neubauer, AB, Stoffel, M, Ditzen, B, Schirmaier, J, Farrenkopf, C, Sieverding, M
Journal of health psychology. 2023;28(11):1057-1071
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Insufficient sleep is a widespread problem. For adults between 18 and 64 years, the National Sleep Foundation generally recommends a range of nightly sleep duration from 7 to 9 hours. The aim of this study was to test a self-regulatory intervention based on mental contrasting with implementation intentions (MCII) against the effects of sleep hygiene information only. This study was a single-blinded, randomised controlled trial with daily/nightly assessments in a baseline-week and analog daily/nightly assessments in a post-intervention week. Participants were randomly assigned to one of the two groups. Results indicated an increase in sleep quality and subjective (but not objective) sleep duration from baseline to post-intervention period. Additionally, regarding subjective stress, associations with daily sleep parameters were largely confirmed. Authors conclude that future research should include booster sessions and evaluate MCII effects in the longer run. Furthermore, a better understanding of the causes regarding insufficient sleep among specific target groups and their degree of controllability is required to develop individually targeted interventions.
Abstract
Mental contrasting with implementation intentions (MCII) has been successfully applied to improve health-related behaviors (e.g. exercise). We explored its effectiveness to improve sleep outcomes beyond effects of sleep hygiene (SH) information, and investigated associations with stress. Eighty university employees (mean age: 29.6, SD = 4.5) were randomized to either a MCII + SH or a SH-only condition. During a baseline-week and a post-intervention week, sleep duration (Fitbit Alta and self-report), sleep quality, and stress were assessed daily and saliva was collected to assess the cortisol awakening response (CAR). In total, self-reported sleep quality and duration increased, but there was no meaningful condition*week interaction for sleep parameters or CAR. Higher average stress was associated with shorter sleep duration and lower sleep quality. Within-person, days with higher stress were followed by nights with lower sleep quality. Despite overall improvements, effects of MCII were not confirmed. MCII might be less effective to improve behaviors which are less controllable.
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Effect of Sleep Changes on Health-Related Quality of Life in Healthy Children: A Secondary Analysis of the DREAM Crossover Trial.
Taylor, RW, Haszard, JJ, Jackson, R, Morrison, S, Beebe, DW, Meredith-Jones, KA, Elder, DE, Galland, BC
JAMA network open. 2023;6(3):e233005
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While inadequate or poor-quality sleep has been associated with a wide range of adverse physical and psychological health outcomes in infants, children and adolescents, interest is growing regarding the association of sleep with more global indices of health, such as health-related quality of life (HRQOL). The aim of this study was to determine the effect of mild sleep deprivation on HRQOL in children without major sleep issues. This study was a secondary analysis based on the DREAM randomised crossover trial. Children were randomised to one of two groups (sleep restriction or sleep extension) with a 1-week washout in between. Bedtimes were manipulated to be 1 hour later (sleep restriction) and 1 hour earlier (sleep extension) than usual for 1 week each. Wake times were unchanged. Results showed that after only 1 week of receiving 39 minutes less sleep per night between sleep conditions, children reported significantly lower HRQOL in terms of their physical and overall well-being and ability to cope well at school. Authors conclude that ensuring children receive sufficient good-quality sleep is an important child health issue.
Abstract
IMPORTANCE Little is known regarding the effect of poor sleep on health-related quality of life (HRQOL) in healthy children. OBJECTIVE To determine the effect of induced mild sleep deprivation on HRQOL in children without major sleep issues. DESIGN, SETTING, AND PARTICIPANTS This prespecified secondary analysis focused on HRQOL, a secondary outcome of the Daily Rest, Eating, and Activity Monitoring (DREAM) randomized crossover trial of children who underwent alternating weeks of sleep restriction and sleep extension and a 1-week washout in between. The DREAM trial intervention was administered at participants' homes between October 2018 and March 2020. Participants were 100 children aged 8 to 12 years who lived in Dunedin, New Zealand; had no underlying medical conditions; and had parent- or guardian-reported normal sleep (8-11 hours/night). Data were analyzed between July 4 and September 1, 2022. INTERVENTIONS Bedtimes were manipulated to be 1 hour later (sleep restriction) and 1 hour earlier (sleep extension) than usual for 1 week each. Wake times were unchanged. MAIN OUTCOMES AND MEASURES All outcome measures were assessed during both intervention weeks. Sleep timing and duration were assessed using 7-night actigraphy. Children and parents rated the child's sleep disturbances (night) and impairment (day) using the 8-item Pediatric Sleep Disturbance and 8-item Sleep-Related Impairment scales of the Patient-Reported Outcomes Measurement Information System questionnaire. Child-reported HRQOL was assessed using the 27-item KIDSCREEN questionnaire with 5 subscale scores and a total score. Both questionnaires assessed the past 7 days at the end of each intervention week. Data were presented as mean differences and 95% CIs between the sleep restriction and extension weeks and were analyzed using intention to treat and an a priori difference in sleep of at least 30 minutes per night. RESULTS The final sample comprised 100 children (52 girls [52%]; mean [SD] age, 10.3 [1.4] years). During the sleep restriction week, children went to sleep 64 (95% CI, 58-70) minutes later, and sleep offset (wake time) was 18 (95% CI, 13-24) minutes later, meaning that children received 39 (95% CI, 32-46) minutes less of total sleep per night compared with the sleep extension week in which the total sleep time was 71 (95% CI, 64-78) minutes less in the per-protocol sample analysis. Both parents and children reported significantly less sleep disturbance at night but greater sleep impairment during the day with sleep restriction. Significant standardized reductions in physical well-being (standardized mean difference [SMD], -0.28; 95% CI, -0.49 to -0.08), coping in a school environment (SMD, -0.26; 95% CI, -0.42 to -0.09), and total HRQOL score (SMD, -0.21; 95% CI, -0.34 to -0.08) were reported by children during sleep restriction, with an additional reduction in social and peer support (SMD, -0.24; 95% CI, -0.47 to -0.01) in the per-protocol sample analysis. CONCLUSIONS AND RELEVANCE Results of this secondary analysis of the DREAM trial indicated that even 39 minutes less of sleep per night for 1 week significantly reduced several facets of HRQOL in children. This finding shows that ensuring children receive sufficient good-quality sleep is an important child health issue. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry: ACTRN12618001671257.
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Does providing feedback and guidance on sleep perceptions using sleep wearables improve insomnia? Findings from "Novel Insomnia Treatment Experiment": a randomized controlled trial.
Spina, MA, Andrillon, T, Quin, N, Wiley, JF, Rajaratnam, SMW, Bei, B
Sleep. 2023;46(9)
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Insomnia involves difficulties with initiating sleep, maintaining sleep and early morning awakenings. Sleep–wake state discrepancy is a common phenomenon observed in 9%–50% of individuals with insomnia. In fact, sleep–wake state discrepancy is important to explore as it is linked to daytime functioning, self-reported happiness, social support and self-reported sleep. The primary aim of this study was to examine whether providing individuals with insomnia feedback about sleep using wearable devices, along with support for appropriate interpretation of sleep–wake state discrepancy, improves symptoms of insomnia as the primary outcome. This study was a two-arm, parallel-group, single-blind, superiority randomised controlled trial. Eligible participants were randomised 1:1 to intervention or control groups. Results showed that the intervention group had lower insomnia symptom severity and sleep disturbance and lower rates of insomnia disorder. However, the two groups did not meaningfully differ on all other secondary and exploratory outcomes at post-intervention. Authors conclude that addressing sleep–wake state discrepancy by providing education and guidance on wearable measured sleep data could reduce symptoms of insomnia. Additionally, future studies need to examine how sleep–wake state discrepancy guidance using wearable devices could supplement cognitive behavioural therapy for insomnia (CBT-I), and whether this addition could enhance the benefits of CBT-I.
Abstract
STUDY OBJECTIVES Insomnia is a disorder diagnosed based on self-reported sleep complaints. Differences between self-reported and sensor-based sleep parameters (sleep-wake state discrepancy) are common but not well-understood in individuals with insomnia. This two-arm, parallel-group, single-blind, superiority randomized-controlled trial examined whether monitoring sleep using wearable devices and providing support for interpretation of sensor-based sleep data improved insomnia symptoms or impacted sleep-wake state discrepancy. METHODS A total of 113 (age M = 47.53; SD = 14.37, 64.9% female) individuals with significant insomnia symptoms (Insomnia Severity Index(ISI) ≥10) from the community were randomized 1:1 (permuted block randomization) to receive 5 weeks (1) Intervention (n = 57): feedback about sensor-based sleep (Fitbit and EEG headband) with guidance for data interpretation and ongoing monitoring, and (2) Control (n = 56): sleep education and hygiene. Both groups received one individual session and two check-in calls. The ISI (primary outcome), sleep disturbance (SDis), sleep-related impairment (SRI), depression, and anxiety were assessed at baseline and post-intervention. RESULTS In total, 103 (91.2%) participants completed the study. Intention-to-treat multiple regression with multiple imputations showed that after controlling for baseline values, compared to the Control group (n = 51), the Intervention group (n = 52) had lower ISI (p = .011, d = 0.51) and SDis (p = .036, d = 0.42) post-intervention, but differences in SRI, depression, anxiety, and sleep-wake state discrepancy parameters (total sleep time, sleep onset latency, and wake after sleep onset) were not meaningful (P-values >.40). CONCLUSIONS Providing feedback and guidance about sensor-based sleep parameters reduced insomnia severity and sleep disturbance but did not alter sleep-wake state discrepancy in individuals with insomnia more than sleep hygiene and education. The role of sleep wearable devices among individuals with insomnia requires further research. CLINICAL TRIAL REGISTRATION The Novel Insomnia Treatment Experiment (NITE): the effectiveness of incorporating appropriate guidance for sleep wearables in users with insomnia. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378452, Australia New Zealand Clinical Trials Registry: ACTRN12619001636145.