Night Games and Sleep: Physiological, Neuroendocrine, and Psychometric Mechanisms

2018 ◽  
Vol 13 (7) ◽  
pp. 867-873 ◽  
Author(s):  
Laura E. Juliff ◽  
Jeremiah J. Peiffer ◽  
Shona L. Halson

Context: Night games are a regular occurrence for team-sport athletes, yet sleep complaints following night competitions are common. The mechanisms responsible for reported sleep difficulty in athletes are not understood. Methods: An observational crossover design investigating a night netball game and a time-matched rest day in 12 netball athletes was conducted to ascertain differences in physiological (core temperature), psychometric (state and trait), and neuroendocrine (adrenaline, noradrenaline, and cortisol) responses. Results: Following the night game, athletes experienced reduced sleep durations, lower sleep efficiency, early awakenings, and poorer subjective sleep ratings compared with the rest day. No differences were found between core temperature, state psychometric measures, and cortisol at bedtime. Adrenaline and noradrenaline concentrations were elevated compared with the time-matched rest day prior to (26.92 [15.88] vs 12.90 [5.71] and 232.6 [148.1] vs 97.83 [36.43] nmol/L, respectively) and following the night game (18.67 [13.26] vs 11.92 [4.56] and 234.1 [137.2] vs 88.58 [54.08] nmol/L, respectively); however, the concentrations did not correlate to the sleep variables (duration, efficiency, and sleep-onset latency). A correlation (rs = −.611) between sleep efficiency and hyperarousal (trait psychometric measure) was found. Conclusions: Athletes experienced poor sleep following a night game. Furthermore, results suggest that athletes who have a tendency toward a high trait arousal may be more susceptible to sleep complaints following a night game. These data expand knowledge and refute frequently hypothesized explanations for poor sleep following night competition. The results may also help support staff and coaches target strategies for individual athletes at a higher risk of sleep complaints.

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A43-A43
Author(s):  
Rocio Barragan ◽  
Faris Zuraikat ◽  
Victoria Tam ◽  
Samantha Scaccia ◽  
Justin Cochran ◽  
...  

Abstract Introduction Poor sleep health is a key determinant of obesity risk, largely explained by overconsumption of energy. Eating behavior characteristics are predictive of energy intake and weight change and may link sleep with risk factors for obesity. However, the relationships between sleep and dimensions of eating behavior, and potential individual differences in these relations, are not well characterized. Elucidating these relations may aid in the development of targeted strategies to mitigate obesity risk. Therefore, we aimed to 1) evaluate whether associations of sleep were related with eating behavior characteristics, 2) explore if these associations differed by sex. Methods This was a cross-sectional analysis of 179 adults aged 20–73 y (68.7% women; 64.8% with BMI≥25 kg/m2; 27.4% minority). Sleep was assessed over 2 wk using wrist actigraphy; eating behavior characteristics (dietary restraint, disinhibition and hunger) were measured with the Three-Factor Eating Questionnaire. Linear regression models were used to evaluate associations of sleep with eating behavior characteristics, adjusting for confounding variables. In separate models, sex was added as an interaction term and analyses were stratified when interactions were significant (p<0.10). Results Variable (sleep midpoint standard deviation >60 min) vs. stable sleep timing was associated with greater tendency towards hunger (β=0.84 ± 0.39, p=0.03). When evaluated on the continuous scale, lower sleep efficiency (β=-0.13 ± 0.05; p=0.01), longer wake after sleep onset (β=0.03 ± 0.01; p=0.01) and higher sleep fragmentation index (β=0.074 ± 0.036; p=0.041) were associated with higher dietary restraint. Sex influenced associations of sleep efficiency, sleep onset latency, and sleep fragmentation index with hunger. In men, but not women, lower sleep efficiency (β=-0.15 ± 0.05; p<0.01), longer sleep onset latency (β=0.17 ± 0.07; p=0.02) and higher sleep fragmentation index (β=0.11 ± 0.04; p<0.01) were associated with greater hunger. Conclusion Objective measures of sleep were associated with eating behaviors previously linked with obesity and its risk factors. Moreover, we provide evidence of sex-specific associations between poor sleep and tendency towards hunger. Our results suggest that, particularly in men, differences in eating behavior traits may underlie susceptibility to overeating in response to poor sleep. Support (if any) Supported by NIH grants R01HL128226 and R01HL142648 and AHA grant 16SFRN27950012 (PI: St-Onge).


SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A389-A390
Author(s):  
F Gu ◽  
C Jungquist ◽  
A Sonia ◽  
L Liu ◽  
E Repasky ◽  
...  

Abstract Introduction Sleep disturbances are reported to be highly prevalent in head and neck cancer (HNC) patients, but no carefully assessed sleep data exists in patients with HNC undergoing concurrent chemoradiotherapy (CRT). Methods To objectively assess sleep patterns in this study population, we conducted a pilot study in 15 patients and 13 non-cancer healthy volunteers. Patients wore the wrist Actiwatch Spectrum (Philips Respironics) at week 1, 3, and 6/7 during the 7-week treatment period. Volunteers wore the Actiwatch for one week. We used the Actiware software to calculate sleep parameters. A sleep log was used as a complement to define participants’ bedtime and rise-up time. Any sleep episode scored by the software during daytime was considered as a nap. Results Compared to healthy volunteers, patients had lower overnight sleep efficiency, longer sleep onset latency and more waking time after sleep onset (WASO), indicating more difficulty falling asleep and maintaining sleep. During CRT, patients’ sleep efficiency decreased whereas latency and WASO increased, indicating possible the decrease of sleep quality. Sleep efficiency of <85% has been used previously as a cut-off for poor sleep; based on this criteria, 45% of HNC patients had poor sleep at treatment baseline, compared to 31% in non-cancer volunteers, and this proportion increased to 51% by the end of treatment. Patients had longer napping time: compared to healthy volunteers, the napping time was on average 2 hours longer at baseline, and 3 hours longer at the end of treatment, indicating unhealthy sleep habits of these patients. Conclusion Our data suggested HNC patients had severe sleep disturbances and unhealthy sleep habits, which were aggravated during CRT treatment. Support This study was supported by UL1TR001412-04, a Clinical and Translational Research Award under SUNY-Buffalo.


Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 852
Author(s):  
Rocío Barragán ◽  
Faris M. Zuraikat ◽  
Victoria Tam ◽  
Samantha Scaccia ◽  
Justin Cochran ◽  
...  

Poor sleep is a determinant of obesity, with overconsumption of energy contributing to this relationship. Eating behavior characteristics are predictive of energy intake and weight change and may underlie observed associations of sleep with weight status and obesity risk factors. However, relationships between sleep and dimensions of eating behavior, as well as possible individual differences in these relations, are not well characterized. Therefore, the aim of this study was to evaluate whether sleep behaviors, including duration, timing, quality, and regularity relate to dietary restraint, disinhibition, and tendency towards hunger and to explore whether these associations differ by sex. This cross-sectional study included 179 adults aged 20–73 years (68.7% women, 64.8% with BMI ≥ 25 kg/m2). Sleep was evaluated by accelerometry over 2 weeks. Eating behavior dimensions were measured with the Three-Factor Eating Questionnaire. Prolonged wake after sleep onset (WASO) (0.029 ± 0.011, p = 0.007), greater sleep fragmentation index (0.074 ± 0.036, p = 0.041), and lower sleep efficiency (−0.133 ± 0.051, p = 0.010) were associated with higher dietary restraint. However, higher restraint attenuated associations of higher WASO and sleep fragmentation with higher BMI (p-interactions < 0.10). In terms of individual differences, sex influenced associations of sleep quality measures with tendency towards hunger (p-interactions < 0.10). Stratified analyses showed that, in men only, higher sleep fragmentation index, longer sleep onset latency, and lower sleep efficiency were associated with greater tendency towards hunger (β = 0.115 ± 0.037, p = 0.003, β = 0.169 ± 0.072, p = 0.023, β = −0.150 ± 0.055, p = 0.009, respectively). Results of this analysis suggest that the association of poor sleep on food intake could be exacerbated in those with eating behavior traits that predispose to overeating, and this sleep-eating behavior relation may be sex-dependent. Strategies to counter overconsumption in the context of poor quality sleep should be evaluated in light of eating behavior traits.


SLEEP ◽  
2020 ◽  
Vol 43 (11) ◽  
Author(s):  
Michael D Wirth ◽  
Angela Jessup ◽  
Gabrielle Turner-McGrievy ◽  
Nitin Shivappa ◽  
Thomas G Hurley ◽  
...  

Abstract Study Objectives Non-pharmacological sleep interventions may improve sleep profiles without the side-effects observed with many pharmacological sleep aids. The objective of this research was to examine the association between sleep and inflammation and to examine how changes in dietary inflammatory potential influence changes in sleep. Methods The Inflammation Management Intervention Study (IMAGINE), which was a dietary intervention designed to lower inflammation, provided access to 24-h dietary recalls (24HR), objectively measured sleep using SensewearTM armbands, and a range of self-reported demographics, health histories, lifestyle behaviors, psychosocial metrics, anthropometric measurements, and inflammatory biomarkers. Dietary Inflammatory Index® (DII®) scores were calculated from three unannounced 24HR-derived estimated intakes of whole foods and micro and macronutrients over a 2-week period at baseline and post-intervention (i.e. month 3). Statistical analyses primarily utilized linear regression. Results At baseline, for every 1-min increase in sleep onset latency, tumor necrosis factor-α increased by 0.015 pg/mL (±0.008, p = 0.05). Every one-percentage increase in sleep efficiency was associated with decreased C-reactive protein (CRP) of −0.088 mg/L (±0.032, p = 0.01). Every 1-min increase in wake-after-sleep-onset (WASO) increased both CRP and interleukin-6. Compared to participants with pro-inflammatory DII changes over 3 months, those with anti-inflammatory changes decreased WASO (0 vs. −25 min, respectively, p &lt; 0.01) and improved sleep efficiency (−2.1% vs. +2.6%, respectively, p = 0.04). Conclusions Non-pharmacological treatments, such as anti-inflammatory diets, may improve sleep in some adults. Future research involving dietary treatments to improve sleep should not only focus on the general population, but also in those commonly experiencing co-morbid sleep complaints. Clinical Trial Information NCT02382458.


2018 ◽  
Vol 8 (3) ◽  
pp. 274-277 ◽  
Author(s):  
Chi-Fu Jeffrey Yang ◽  
Kelli Aibel ◽  
Ryan Meyerhoff ◽  
Frances Wang ◽  
David Harpole ◽  
...  

ObjectivesPatients receiving induction chemotherapy for acute myeloid leukaemia (AML) anecdotally describe poor sleep, but sleep disturbances have not been well-characterised in this population. We aimed to test the feasibility of measuring sleep quality in AML inpatients using a wearable actigraphy device.MethodsUsing the Actigraph GT3X ‘watch’, we assessed the total sleep time, sleep onset latency, wake after sleep onset, number of awakenings after sleep onset and sleep efficiency for inpatients with AML receiving induction chemotherapy. We assessed patient self-reported sleep quality using the Pittsburgh Sleep Quality Index (PSQI).ResultsOf the 12 patients enrolled, 11 completed all actigraphy and PSQI assessments, demonstrating feasibility. Patients wore the Actigraph device for a mean (SD) of 15.92 (8.3) days, and actigraphy measures suggested poor sleep. Patients had a median average awakening length of 6.92 min, a median number of awakenings after sleep onset of 4 and a median sleep onset latency of 10.8 min. Actual median sleep efficiency (0.91) was high, suggesting that patients’ poor sleep was not due to insomnia but perhaps due to interruptions, such as administration of medications, lab draws and vital sign measurements.ConclusionsCollection of sleep quality data among inpatients with AML via a wearable actigraphy device is feasible. AML inpatients appear to have poor sleep quality and quantity, suggesting that sleep issues represent an area of unmet supportive care needs in AML. Further research in this areas is needed to inform the development of interventions to improve sleep duration and quality in hospitalised patients with AML.


2020 ◽  
pp. 1-15
Author(s):  
Allie Peters ◽  
John Reece ◽  
Hailey Meaklim ◽  
Moira Junge ◽  
David Cunnington ◽  
...  

Abstract Insomnia is a common major health concern, which causes significant distress and disruption in a person's life. The objective of this paper was to evaluate a 6-week version of Mindfulness-Based Therapy for Insomnia (MBTI) in a sample of people attending a sleep disorders clinic with insomnia, including those with comorbidities. Thirty participants who met the DSM-IV-TR diagnosis of insomnia participated in a 6-week group intervention. Outcome measures were a daily sleep diary and actigraphy during pre-treatment and follow-up, along with subjective sleep outcomes collected at baseline, end-of-treatment, and 3-month follow-up. Trend analyses showed that MBTI was associated with a large decrease in insomnia severity (p < .001), with indications of maintenance of treatment effect. There were significant improvements in objective sleep parameters, including sleep onset latency (p = .005), sleep efficiency (p = .033), and wake after sleep onset (p = .018). Significant improvements in subjective sleep parameters were also observed for sleep efficiency (p = .005) and wake after sleep onset (p < .001). Overall, this study indicated that MBTI can be successfully delivered in a sleep disorders clinic environment, with evidence of treatment effect for both objective and subjective measures of sleep.


SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A303-A303
Author(s):  
Cagri Yuksel ◽  
Xi Chen ◽  
Lauren Watford ◽  
Margaret Gardner ◽  
Kathryn Lewandowski ◽  
...  

Abstract Introduction Recent studies show that sleep favors oligodendrocyte proliferation and myelination, and sleep loss is associated with alterations in white matter structure and decreased myelination. Psychotic disorders are characterized by disrupted white matter integrity, and abnormal axon and myelin structure. Despite common sleep disturbances in these disorders, little is known about the relationship between sleep quality and white matter findings. A novel in vivo neuroimaging technique that combines diffusion tensor spectroscopy (DTS) and magnetization transfer ratio (MTR) allows separately examining the axon structure and glial function, and myelin content, respectively. Using this method, we examined the association of sleep quality with white matter biology in a sample of patients with psychotic disorders and matched healthy controls. Methods Participants included patients diagnosed with bipolar disorder with psychotic features (euthymic or depressed, n=12) and schizophrenia spectrum disorders (n=9), and age and sex matched healthy controls (n=20). DTS and MTR data was collected from the right prefrontal white matter at 4T. DTS measures included apparent diffusion coefficients of water, NAA, creatine and choline. Sleep quality was measured using Pittsburgh Sleep Quality Index (PSQI). Results PSQI total score was significantly higher in patients. and patient sample included a higher percentage of poor sleepers (PSQI total score&gt;5). In patients, total PSQI score and sleep onset latency were significantly and negatively associated with MTR (F=6.9, p=0.02 and F=9.7, p=0.007, respectively). There was no difference in any DTS measures between groups. Conclusion Our preliminary results show that poor sleep quality is associated with decreased myelin content in the frontal lobe, in patients with psychotic disorders. This finding suggests that sleep loss may be a mediator of white matter alterations in psychosis. Support (if any) This work is supported by National Institute of Mental Health K23MH119322 to Cagri Yuksel


Author(s):  
Aman Gul ◽  
Nassirhadjy Memtily ◽  
Pirdun Mijit ◽  
Palidan Wushuer ◽  
Ainiwaer Talifu ◽  
...  

Objective: To preliminarily investigate the clinical features and PSG in abnormal sewda-type depressive insomnia. Methods: A total of 127 abnormal sewda-type depressive insomnia patients were evaluated with overnight PSG, and 32 normal participants were compared. Results: Patients with abnormal sewda-type depressive insomnia were compared with the control group; the sleep symptoms showed a long incubation period of sleep, low sleep maintenance rate, low sleep efficiency and poor sleep quality as well as daytime dysfunction. At process and continuity of sleep: Total sleep time, sleep efficiency, sleep maintenance rate in abnormal sewda-type depressive insomnia group were shorter than the control group. Wake after sleep onset, and sleep latency were longer than the control group. At sleep structure: N1 ratio and N2 ratio in depressive insomnia group were longer than the control group, N3 ratio and REM sleep ratio shorter than the control group. At REM index: REM latency, REM cycles, and REM sleep time were shorter than the control group. Conclusion: Insomnia symptoms in abnormal sewda-type depression comorbid insomnia patients were similar to the ordinary insomnia patients. The PSG characteristics had significant changes in sleep process, sleep structure and REM indicators. The severity of the abnormal sewda-type depression was closely related to REM indicators. Change of REM sleep characteristics may be the specificity, and these could be taken as reference in diagnosis and identification of abnormal sewda-type depressive insomnia.


Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Vivian Cao ◽  
Nour Makarem ◽  
Moorea Maguire ◽  
Ivan Samayoa ◽  
Huaqing Xi ◽  
...  

Introduction: Poor sleep and history of weight cycling (HWC) are associated with worse cardiovascular health, yet limited research has evaluated the association between HWC and poor sleep patterns. Hypothesis: We hypothesized that HWC would be associated with poor sleep in US women. Methods: The AHA Go Red for Women Strategically Focused Research Network cohort at Columbia University (n=506, mean age 37 ± 15.7y, 61% racial/ethnic minority) was used to evaluate cross-sectional associations of HWC and sleep characteristics at baseline, and prospective associations of HWC from baseline with sleep measures at 1-yr. HWC, defined as losing and gaining ≥ 10 lbs at least once (excluding pregnancy), and number of WC episodes were self-reported. Sleep duration, measures of sleep quality, insomnia severity, and obstructive sleep apnea (OSA) risk were assessed using the validated Pittsburgh Sleep Quality Index, Insomnia Severity Index, and Berlin questionnaire. Linear and logistic regression models, adjusted for age, race/ethnicity, education, health insurance status, pregnancy history, and menopausal status, were used to evaluate the relation of HWC with sleep. Results: Most women reported ≥1episode of weight cycling (72%). In linear models of cross-sectional and prospective data, each additional weight cycling episode was related to shorter sleep duration, poorer sleep quality, longer sleep onset latency, greater insomnia severity, more sleep disturbances and daytime dysfunction, lower sleep efficiency, and higher sleep medication use frequency. In logistic models, HWC (≥1 vs. 0 episodes) was associated with greater odds for short sleep, poor sleep quality, long sleep onset latency ≥26 min, high OSA risk, and sleep efficiency<85% ( Table ). Conclusion: HWC predicted poor sleep among women, suggesting that weight maintenance may represent an important strategy to promote sleep health. Long-term studies are needed to disentangle the complex relations between weight fluctuations and sleep across the life course.


SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A422-A422
Author(s):  
A K Wilkerson ◽  
D J Taylor ◽  
G L Sahlem ◽  
R O Simmons ◽  
A Russell ◽  
...  

Abstract Introduction Previous studies have shown that sleep problems are commonly reported during treatment for substance use disorders (SUDs) and sleep complaints have been linked to subsequent relapse. However, most of these findings were in well-controlled clinical trials and may not generalize to the public. Little is known about the natural progression of sleep complaints during treatment in community clinics, the most common treatment approach for SUDs. The aim of this study is to longitudinally assess prevalence of clinically significant sleep disturbance at baseline and post-treatment in a community-based intensive outpatient (IOP) SUD treatment program using a multi-method approach with well-validated measures of sleep. Methods Adults beginning IOP SUD treatment completed the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Nightmare Disorder index (NDI), and one week of actigraphy and sleep diaries. Measures were repeated following treatment (approximately 5 weeks later). Results Preliminary analyses on 21 adults who have been enrolled thus far revealed 85.6% of participants experienced sleep disturbance (PSQI &gt; 5) at baseline. 28.5% of participants reached cutoff for moderate-to-severe insomnia symptoms (ISI &gt; 15) and 42.9% reported nightmares more than once per week. Sleep parameters taken from actigraphy and sleep diaries revealed mean sleep efficiency was 77.5% (TST M = 6.2 hours; TIB M = 7.9 hours). These variables did not improve from baseline to post-treatment. Further, most measures indicated a worsening of sleep, though this did not reach significance (all ps &gt; .05). Conclusion This preliminary data show a high prevalence of self-reported sleep complaints and objectively measured poor sleep efficiency that do not improve over the course of treatment. Data collection is ongoing and expected to at least double. More robust analyses, including differences between SUD type (e.g., cannabis vs. opioid) and relationship to relapse at post-treatment, will then be completed. Support K12DA031794


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