scholarly journals Actigraphy-Derived Sleep Is Associated with Eating Behavior Characteristics

Nutrients ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 852
Author(s):  
Rocío Barragán ◽  
Faris M. Zuraikat ◽  
Victoria Tam ◽  
Samantha Scaccia ◽  
Justin Cochran ◽  
...  
Keyword(s):  
Individual Differences ◽  
Eating Behavior ◽  
Dietary Restraint ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Fragmentation ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Fragmentation Index ◽  
Behavior Characteristics

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.

105 Sleep Behaviors Are Differentially Associated with Eating Behavior Characteristics Based on Sex

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A43-A43
Author(s):  
Rocio Barragan ◽  
Faris Zuraikat ◽  
Victoria Tam ◽  
Samantha Scaccia ◽  
Justin Cochran ◽  
...  
Keyword(s):  
Eating Behavior ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Sleep Fragmentation ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Obesity Risk ◽  
Fragmentation Index ◽  
Behavior Characteristics

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&lt;0.10). Results Variable (sleep midpoint standard deviation &gt;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&lt;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&lt;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).

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
Keyword(s):  
Core Temperature ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Sleep Difficulty ◽  
Sleep Complaints ◽  
Temperature State ◽  
Psychometric Measures ◽  
Cortisol Responses

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.

scholarly journals 1025 Sleep Patterns In Head Neck Cancer Patients During Radiotherapy

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A389-A390
Author(s):  
F Gu ◽  
C Jungquist ◽  
A Sonia ◽  
L Liu ◽  
E Repasky ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Neck Cancer ◽  
Sleep Disturbances ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Sleep Patterns ◽  
Sleep Habits ◽  
End Of Treatment

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 &lt;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.

scholarly journals Sleep Fragmentation and Biomarkers in Juvenile Idiopathic Arthritis

2015 ◽  
Vol 18 (3) ◽  
pp. 299-306 ◽  
Author(s):  
Teresa M. Ward ◽  
Weichao Yuwen ◽  
Joachim Voss ◽  
Dirk Foell ◽  
Faekah Gohar ◽  
...  
Keyword(s):  
Juvenile Idiopathic Arthritis ◽  
Sleep Duration ◽  
Sleep Efficiency ◽  
Sleep Fragmentation ◽  
Cutoff Score ◽  
Poor Sleep ◽  
Protein Biomarkers ◽  
Sleep Habits ◽  
Fragmentation Index ◽  
Nighttime Sleep

Objectives: (1) To compare sleep (nighttime sleep duration and sleep efficiency) and sleep fragmentation (movement and fragmentation index), as measured by actigraphy, and symptoms (pain and fatigue) in 8- to 14-year-old children with polyarticular and extended oligoarticular juvenile idiopathic arthritis (JIA) and (2) to examine the associations between sleep fragmentation (movement and fragmentation index) and the calcium-binding protein biomarkers S100A12 and myeloid-related protein (MRP8/14). Method: Participants included 40 children with extended oligoarticular ( n = 15) or polyarticular ( n = 25) JIA and their parents. Serum protein samples were obtained during routine rheumatology clinic visits. Children completed the PedsQL Multidimensional Fatigue Scale and daily pain and sleep diaries and wore actigraphy monitors for 9 consecutive days. Parents completed the Children’s Sleep Habits Questionnaire (CSHQ). Results: Of the 40 children, 68% scored above the CSHQ clinical cutoff score for sleep disturbances. Mean nighttime sleep duration was 7.5 hr, and mean sleep efficiency was 85.3%. Group differences were not found for nighttime sleep duration, sleep efficiency, movement and fragmentation index, or S100A12 and MRP8/14 protein concentrations. In a stepwise regression, medications, joint count, and movement and fragmentation index explained 21% of the variance in MRP8/14 concentration. Conclusion: Decreased nighttime sleep duration, poor sleep efficiency, and fragmented sleep were observed in our sample, regardless of JIA category. Sleep fragmentation was a significant predictor of MRP8/14 protein concentration. Additional research is needed to understand the interrelations among sleep fragmentation, effects of medication, and S100A12 and MRP8/14 protein biomarkers in JIA.

Actigraphy assessment of sleep quality among patients with acute myeloid leukaemia during induction chemotherapy

2018 ◽  
Vol 8 (3) ◽  
pp. 274-277 ◽  
Author(s):  
Chi-Fu Jeffrey Yang ◽  
Kelli Aibel ◽  
Ryan Meyerhoff ◽  
Frances Wang ◽  
David Harpole ◽  
...  
Keyword(s):  
Acute Myeloid Leukaemia ◽  
Sleep Quality ◽  
Myeloid Leukaemia ◽  
Induction Chemotherapy ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Acute Myeloid

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.

Mindfulness and Behaviour Therapy for Insomnia: An Assessment of Treatment Effect in a Sleep Disorders Clinic Population with Insomnia

2020 ◽  
pp. 1-15
Author(s):  
Allie Peters ◽  
John Reece ◽  
Hailey Meaklim ◽  
Moira Junge ◽  
David Cunnington ◽  
...  
Keyword(s):  
Sleep Disorders ◽  
Treatment Effect ◽  
Sleep Onset ◽  
Sleep Efficiency ◽  
Health Concern ◽  
Sleep Diary ◽  
Sleep Onset Latency ◽  
Subjective Sleep ◽  
Sleep Parameters

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.

778 Poor Sleep Quality is Associated with Reduced Myelination in Patients with Psychotic Disorders

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A303-A303
Author(s):  
Cagri Yuksel ◽  
Xi Chen ◽  
Lauren Watford ◽  
Margaret Gardner ◽  
Kathryn Lewandowski ◽  
...  
Keyword(s):  
White Matter ◽  
Sleep Quality ◽  
Psychotic Disorders ◽  
Sleep Onset ◽  
Sleep Loss ◽  
Magnetization Transfer Ratio ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Healthy Controls ◽  
Poor Sleep Quality

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

scholarly journals A study on sleep apnea in patients with abnormal sewda type of depression

2020 ◽  
pp. 1-8
Author(s):  
Aman Gul ◽  
Nassirhadjy Memtily ◽  
Pirdun Mijit ◽  
Palidan Wushuer ◽  
Ainiwaer Talifu ◽  
...  
Keyword(s):  
Rem Sleep ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Control Group ◽  
Poor Sleep ◽  
Sleep Structure ◽  
Maintenance Rate ◽  
Sleep Maintenance ◽  
Insomnia Symptoms

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.

Abstract 037: History Of Weight Cycling Is Prospectively Associated With Shorter And Poorer Quality Sleep, And Higher Sleep Apnea Risk In Diverse Us Women: Results From The AHA Go Red For Women Strategically Focused Research Network

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Vivian Cao ◽  
Nour Makarem ◽  
Moorea Maguire ◽  
Ivan Samayoa ◽  
Huaqing Xi ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Onset ◽  
Research Network ◽  
Poor Sleep ◽  
Sleep Onset Latency ◽  
Weight Cycling ◽  
Onset Latency ◽  
Cross Sectional ◽  
History Of ◽  
Insomnia Severity

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.

scholarly journals 0127 Relationship Between Sleep Metrics with Free-Living Glucose Concentrations and Glycemic Variability in Non-Diabetic Adults

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A50-A50
Author(s):  
J R Sparks ◽  
E E Kishman ◽  
X Wang
Keyword(s):  
South Carolina ◽  
Glucose Metabolism ◽  
Sleep Onset ◽  
Glycemic Variability ◽  
Sleep Efficiency ◽  
Sleep Diary ◽  
Poor Sleep ◽  
Free Living ◽  
Experimental Conditions ◽  
Time In Bed

Abstract Introduction Insufficient sleep and poor sleep quality have been associated with impaired glucose metabolism at fasting and under experimental conditions. Continuous glucose monitoring (CGM) measures glucose concentrations over an extended, free-living period that can be used to assess glycemic health. Relationships between CGM-assessed glucose concentrations and glycemic variability, an emerging glycemic health marker, with sleep metrics have yet to be elucidated. The purpose of this study was to examine the relationships between sleep metrics with glucose concentrations and glycemic variability in non-diabetic adults. Methods Twenty-four non-diabetic adults (age=46.0±5.8 years; BMI=32.2±5.7 kg/m2) completed actigraphy, sleep diary, and CGM over 7 consecutive days. Time-in-bed (TIB), total sleep time (TST), wake duration after sleep onset, and sleep efficiency [(TST÷TIB)×100%] were determined using actigraphy assisted with sleep diary input. Nightly variability of each sleep metric was calculated as standard deviation (SD) across all nights. Glucose concentrations at waking in the morning, and 1, 2, and 3 hours prior to waking, and diurnal, nocturnal, and 24-hour means were determined. Intra-day glycemic variability, including mean amplitude of glycemic excursions and continuous overlapping of net glycemic action of 1, 2, and 4 hours, and inter-day glycemic variability, mean of daily differences, were calculated. Pearson product correlations between sleep metrics with glucose concentrations and glycemic variability were performed. Results Average TIB and TST were 462.6±61.7 minutes and 403.3±59.7 minutes, respectively. TIB negatively correlated with glucose concentrations at 2 and 3 hours prior to waking (r=-0.42, p=0.04 and r=-0.42, p=0.04, respectively). Nightly variability in sleep efficiency positively correlated with waking, and 1, 2, and 3 hours prior to waking glucose concentrations (0.44≤r≤0.48, p≤0.03 for all). No sleep metrics correlated with glycemic variability measures (p≥0.10 for all). Conclusion Findings suggest a longer amount of sleep opportunity and more consistent sleep efficiency relate to better glucose metabolism in non-diabetic adults. Support American Heart Association 14BGIA20380706 and University of South Carolina Support to Promote Advancement of Research and Creativity Grant #11530-17-43917.

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