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Journal articles on the topic 'Sleep timing'
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Yan, Li-Ming, Hai-Jun Li, Qi Fan, Yi-Dong Xue, and Tao Wang. "Chronobiological perspectives: Association between meal timing and sleep quality." PLOS ONE 19, no. 8 (August 1, 2024): e0308172. http://dx.doi.org/10.1371/journal.pone.0308172.
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Background Meal timing has been associated with metabolism and cardiovascular diseases; however, the relationship between meal timing and sleep quality remains inconclusive. Objective This study aims to investigate the relationship between meal timing and sleep quality from a chronobiological perspective. Methods This study utilized data from the NHANES for the years 2005–2008, including a cohort of 7,023 participants after applying exclusion criteria. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Meal timing was analyzed based on two 24-hour dietary recalls from each individual, considering the timing of the initial and final meals, meal duration, and frequency of meal occasions. Multiple linear regression models and hierarchical analyses were employed to examine the relationship between meal timing and PSQI scores, adjusting for various demographic and habitat covariates. Results Statistical analysis revealed a positive correlation between delayed meal timings, increased meal occasions, and elevated PSQI scores, indicating that later meal timing are intricately linked with diminished sleep quality. Both later meal timings and more frequent meal occasions were significantly associated with poorer sleep quality. Compared to the first tertile, the β (95%CI) values of the third tertile were 0.545 (0.226, 0.864) for first meal timing, 0.586 (0.277, 0.896) for midpoint meal timing, 0.385 (0.090, 0.680) for last meal timing, and 0.332 (0.021, 0.642) for meal occasions in the adjusted models. Conclusion These findings suggest that late initial, midpoint, and final meal timing, as well as more frequent meal occasions, are chrono-nutrition patterns associated with poor sleep quality.
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Wescott, D. L., K. D. Dickman, P. L. Franzen, B. P. Hasler, and K. A. Roecklein. "1091 The Effects Of Sleep Duration, Timing, And Depressed Mood On Daily Eating Patterns." Sleep 43, Supplement_1 (April 2020): A415. http://dx.doi.org/10.1093/sleep/zsaa056.1086.
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Abstract Introduction Insufficient sleep, circadian misalignment, and altered eating patterns are linked to depression. Despite the temporal association between the sleep/wake and feed/fast cycles, it is unclear how depression severity influences this relationship. Methods Sixty-eight participants ages 18-65 years across the depression continuum wore an Actiwatch for 5-17 nights and reported daily meal times (730 nights total). Multilevel models tested previous night’s sleep timing and duration as predictors of the length of the next day’s eating window. Within-person sleep duration and timing were entered as Level 1 predictors to account for nightly variation in sleep. Between-person sleep duration and timing were entered as Level 2 predictors. A three-way interaction between depression severity and Level 2 sleep duration/timing was entered. Covariates included age, gender, and day (weeknight/weekend). Results Across participants, average later sleep timing predicted a longer eating window (Β= -.222; p =.005). Earlier sleep timing (Β= -.186; p < .001) and shorter sleep duration(Β= -.103; p < .001) relative to a person’s average each predicted a longer next-day eating window. A three-way interaction was found between sleep duration, timing, and depression (Β= -.159; p = .002). At shorter sleep durations, individuals with higher depression severity had a positive relationship between sleep timing and eating window length, and individuals with low depression had a negative relationship between sleep timing and eating window length. Conclusion At shorter sleep durations (< 6.5 hr), individuals with high depression and later sleep timing or low depression and early sleep timing had the longest eating windows, which have been linked to adverse metabolic health. Future experiments should test short sleep duration, sleep timing, and depression as potential causes of lengthened eating windows to determine if targeting sleep duration and timing could improve adverse metabolic markers in depression. Support NIMH K.A.R. MH103303
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Kelly, Rachael M., John H. McDermott, and Andrew N. Coogan. "Differences in Sleep Offset Timing between Weekdays and Weekends in 79,161 Adult Participants in the UK Biobank." Clocks & Sleep 4, no. 4 (November 22, 2022): 658–74. http://dx.doi.org/10.3390/clockssleep4040050.
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Variability in the timing of daily sleep is increasingly recognized as an important factor in sleep and general physical health. One potential driver of such daily variations in sleep timing is different work and social obligations during the “working week” and weekends. To investigate the nature of weekday/weekend differences in the timing of sleep offset, we examined actigraphy records of 79,161 adult participants in the UK Biobank who wore an actiwatch for 1 week. The time of sleep offset was found to be on average 36 min later on weekends than on weekdays, and when this difference was expressed as an absolute value (i.e., irrespective of sleep offset being either later or earlier on weekends), it was 63 min. Younger age, more socioeconomic disadvantage, currently being in employment, being a smoker, being male, being of non-white ethnicity and later chronotype were associated with greater differences in sleep offset between weekdays and weekend days. Greater differences in sleep offset timing were associated with age-independent small differences in cardiometabolic health indicators of BMI and diastolic blood pressure, but not HbA1c or systolic blood pressure. In a subset of participants with Type 2 Diabetes Mellitus, weekday/weekend sleep offset differences were associated weakly with BMI, systolic blood pressure and physical activity. Overall, this study demonstrates potentially substantive differences in sleep offset timings between weekdays and weekends in a large sample of UK adults, and that such differences may have public health implications.
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von Gall, Charlotte, Leon Holub, Amira A. H. Ali, and Simon Eickhoff. "Timing of Deep and REM Sleep Based on Fitbit Sleep Staging in Young Healthy Adults under Real-Life Conditions." Brain Sciences 14, no. 3 (March 6, 2024): 260. http://dx.doi.org/10.3390/brainsci14030260.
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Sleep timing is controlled by intrinsic homeostatic and circadian components. The circadian component controls the chronotype, which is defined by the propensity to sleep at a particular clock time. However, sleep timing can be significantly affected by external factors such as the morning alarm clock. In this study, we analysed the timing of deep and REM sleep as well as the composition of REM sleep using Fitbit sleep staging in young healthy adults (n = 59) under real-life conditions. Sleep stage percentiles were correlated with the timing of total sleep in time after sleep onset for the homeostatic component and in clock time for the circadian component. Regarding the circadian component, the phase of total sleep is most strongly associated with the phases of early deep sleep and REM sleep. Furthermore, a stronger phase relationship between deep and REM sleep with total sleep is associated with greater consolidation of REM sleep. Chronotype-dependent sleep loss correlates negatively with the strength of the phase relationship between deep sleep and total sleep. In conclusion, the interaction of the circadian component of sleep timing with the timing of sleep stages is associated with REM sleep quality. In particular, the interaction of the circadian component of sleep timing with deep sleep seems to be more vulnerable to external factors.
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Jeon, Bomin, and Eileen Chasens. "661 Chronotype, Mood, and Diabetes-Related Distress in Adults with Type 2 Diabetes." Sleep 44, Supplement_2 (May 1, 2021): A258—A259. http://dx.doi.org/10.1093/sleep/zsab072.659.
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Abstract Introduction Chronotype refers to an individual’s preferred timing of sleep and wakefulness, which can be classified as ‘normal’ or ‘late’ chronotypes. The purpose of this study was to examine whether late sleep timing was associated with impaired mood and diabetes-related distress in persons with type 2 diabetes (T2D). Methods The study is a secondary analysis of pooled cross-sectional baseline data from two studies of treatment of obstructive sleep apnea (R01-DK96028) and insomnia (K24-NR016685) in persons with T2D. Sleep timing was measured by the bedtime from a 7-day sleep diary. “Normal” sleep timing was defined as bedtime between 9PM to 12AM ≥ 85% per week. “Late” sleep timing as bedtime after 12AM with normal sleep timing < 85% per week. Other sleep variables evaluated were sleep duration, daytime sleepiness (Epworth Sleepiness Scale [ESS]), and OSA severity (apnea-hypopnea index [AHI]). The Profiles of Mood States measured Total Mood Disturbance (TMD) and the subscales of Tension-Anxiety (T-A), Depression-Dejection (D-D), Anger-Hostility (A-H), Vigor-Activity (V-A), Fatigue-Inertia (F-I), and Confusion-Bewilderment (C-B). Diabetes-related distress was measured by the Problem Areas in Diabetes (PAID). Hierarchical multiple regression was performed to determine whether sleep timing was associated with mood and diabetes-related distress. Results The sample (N=296) had 61% with late sleep timing (n=181). Persons with normal vs late sleep timing were similar in age, sex, race, and education (p >.05). Persons with late sleep timing were less likely to be partnered, had shorter sleep duration and greater mood impairment (TMD and T-A, D-D, A-H, C-B subscales) than those with normal timing (all p values <.05); there was no significant difference by sleep timing in PAID scores (p=.256). Hierarchical regression analyses adjusting for demographics (age, sex, race, marital status, education level), clinical (HbA1c, BMI), and sleep variables (sleep duration, ESS, AHI) revealed that late sleep timing was not significantly associated with impaired mood (TMD and subscales) or PAID. However, ESS was statistically significant in predicting greater TMD (β=.310, p <.001), mood subscales (all p-values <.05) and PAID (β =.222, p <.001). Conclusion Daytime sleepiness, not late sleep timing, is a significant sleep-related symptom for increased mood impairment and diabetes-related distress in persons with T2D. Support (if any):
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Chaput, Jean-Philippe, Caroline Dutil, Ryan Featherstone, Robert Ross, Lora Giangregorio, Travis J. Saunders, Ian Janssen, et al. "Sleep timing, sleep consistency, and health in adults: a systematic review." Applied Physiology, Nutrition, and Metabolism 45, no. 10 (Suppl. 2) (October 2020): S232—S247. http://dx.doi.org/10.1139/apnm-2020-0032.
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The objective of this systematic review was to examine the associations between sleep timing (e.g., bedtime/wake-up time, midpoint of sleep), sleep consistency/regularity (e.g., intra-individual variability in sleep duration, social jetlag, catch-up sleep), and health outcomes in adults aged 18 years and older. Four electronic databases were searched in December 2018 for articles published in the previous 10 years. Fourteen health outcomes were examined. A total of 41 articles, including 92 340 unique participants from 14 countries, met inclusion criteria. Sleep was assessed objectively in 37% of studies and subjectively in 63% of studies. Findings suggest that later sleep timing and greater sleep variability were generally associated with adverse health outcomes. However, because most studies reported linear associations, it was not possible to identify thresholds for “late sleep timing” or “large sleep variability”. In addition, social jetlag was associated with adverse health outcomes, while weekend catch-up sleep was associated with better health outcomes. The quality of evidence ranged from “very low” to “moderate” across study designs and health outcomes using GRADE. In conclusion, the available evidence supports that earlier sleep timing and regularity in sleep patterns with consistent bedtimes and wake-up times are favourably associated with health. (PROSPERO registration no.: CRD42019119534.) Novelty This is the first systematic review to examine the influence of sleep timing and sleep consistency on health outcomes. Later sleep timing and greater variability in sleep are both associated with adverse health outcomes in adults. Regularity in sleep patterns with consistent bedtimes and wake-up times should be encouraged.
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Duffy, Jeanne F., Jamie M. Zeitzer, David W. Rimmer, Elizabeth B. Klerman, Derk-Jan Dijk, and Charles A. Czeisler. "Peak of circadian melatonin rhythm occurs later within the sleep of older subjects." American Journal of Physiology-Endocrinology and Metabolism 282, no. 2 (February 1, 2002): E297—E303. http://dx.doi.org/10.1152/ajpendo.00268.2001.
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We investigated the relationship between sleep timing and the timing of the circadian rhythm of plasma melatonin secretion in a group of healthy young and older subjects without sleep complaints. The timing of sleep and the phase of the circadian melatonin rhythm were earlier in the older subjects. The relationship between the plasma melatonin rhythm and the timing of sleep was such that the older subjects were sleeping and waking earlier relative to their nightly melatonin secretory episode. Consequently, the older subjects were waking at a time when they had higher relative melatonin levels, in contrast with younger subjects, whose melatonin levels were relatively lower by wake time. Our findings indicate that aging is associated not only with an advance of sleep timing and the timing of circadian rhythms but also with a change in the internal phase relationship between the sleep-wake cycle and the output of the circadian pacemaker. In healthy older subjects, the relative timing of the melatonin rhythm with respect to sleep may not play a causal role in sleep disruption.
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AKERSTEDT, TORBJORRN, KEN HUME, DAVID MINORS, and JIM WATERHOUSE. "Good sleep - its timing and physiological sleep characteristics." Journal of Sleep Research 6, no. 4 (December 1997): 221–29. http://dx.doi.org/10.1111/j.1365-2869.1997.00221.x.
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Randler, Christoph. "Sleep, sleep timing and chronotype in animal behaviour." Animal Behaviour 94 (August 2014): 161–66. http://dx.doi.org/10.1016/j.anbehav.2014.05.001.
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Yoshitake, Rikako, Insung Park, Hitomi Ogata, and Naomi Omi. "Meal Timing and Sleeping Energy Metabolism." Nutrients 15, no. 3 (February 2, 2023): 763. http://dx.doi.org/10.3390/nu15030763.
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There is a physiological link between sleep and eating. Insufficient sleep is a risk factor for overeating and excess body weight gain, and molecules such as orexin and insulin play a role in the control of sleep and energy intake. The effects of dietary timing on sleep and energy metabolism were examined in this review. First, we examined sleep energy metabolism and sleep quality under time-restricted eating, including skipping breakfast or dinner. Second, the mechanisms, benefits, and translational potential of the effects of time-restricted diets on sleep were discussed. Time-restricted eating under controlled conditions, in which daily caloric intake was kept constant, affected the time course of energy metabolism but did not affect total energy expenditure over 24 h. In free-living conditions, time-restricted eating for extended durations (4–16 weeks) decreased energy intake and body weight, and the effects of early time-restricted eating were greater than that of midday time-restricted eating. Although assessment of sleep by polysomnographic recording remains to be performed, no negative effects on the subjective quality of sleep have been observed.
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Cox, Rebecca, Brandon Aylward, Isabella Macarelli, and Michele Okun. "0954 Associations Between Sleep Duration and Timing and Postpartum Anxiety Symptoms." SLEEP 47, Supplement_1 (April 20, 2024): A409. http://dx.doi.org/10.1093/sleep/zsae067.0954.
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Abstract Introduction Postpartum anxiety is understudied and underdiagnosed in postpartum women, despite being more common than postpartum depression. Given associations between postpartum anxiety and adverse maternal and infant outcomes, it is crucial to identify patterns and predictors of postpartum anxiety. We examined the associations between sleep duration and timing and postpartum anxiety over 6 months following delivery. Methods Pregnant women (n=147; 30-39 weeks) with a history of depression completed the Pittsburgh Sleep Quality Index (PSQI), Edinburgh Postnatal Depression Scale, and Generalized Anxiety Disorder Scale-7 monthly following delivery for 6 months. Sleep duration and timing were extracted from the PSQI. Sleep timing was calculated as the midpoint between sleep onset and offset. In a multilevel model, sleep duration and timing were person-mean centered at level 1 (month level) and grand-mean centered at level 2 (participant level). Level 1 included main effects of time, sleep duration and timing, and interactions between time and person-mean centered sleep duration and timing and time and grand-mean centered sleep duration and timing. Level 2 included main effects of sleep duration and timing. Depression symptoms were included as a covariate at both levels. Results The intraclass correlation for anxiety symptoms was .46, supporting the use of a multilevel model. Anxiety symptoms increased over time (p<.001). Months with shorter sleep duration were associated with higher concurrent anxiety symptoms (p<.001). The effect of sleep duration on anxiety symptoms varied over time, such that those with shorter sleep duration reported higher anxiety symptoms than those with longer sleep duration in early postpartum months, whereas anxiety symptoms increased during later postpartum months regardless of sleep duration. Sleep timing was not significantly associated with anxiety symptoms (p>.05). Conclusion Postpartum anxiety increased over time, suggesting such symptoms are not transient features of the immediate postpartum period and highlighting the need to identify predictors. Shorter sleep duration may signal risk for elevated postpartum anxiety on a monthly timescale, particularly during early postpartum months. Treatments aimed at promoting sleep to improve postpartum anxiety may be most effective if targeted at early postpartum months. Future research should replicate these findings with objective sleep measures. Support (if any) Happiest Baby, Inc.; NIH T32 HL149646
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Jansen, Erica C., Ana Baylin, Alejandra Cantoral, Martha María Téllez Rojo, Helen J. Burgess, Louise M. O'Brien, Libni Torres Olascoaga, and Karen E. Peterson. "Dietary Patterns in Relation to Prospective Sleep Duration and Timing among Mexico City Adolescents." Nutrients 12, no. 8 (July 31, 2020): 2305. http://dx.doi.org/10.3390/nu12082305.
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Adult studies show that healthy diet patterns relate to better sleep. However, evidence during adolescence, when sleep may change dramatically, is lacking. Within a cohort of 458 Mexican adolescents, we examined whether consumption of three dietary patterns was associated with sleep duration and timing measured 2 years later, as well as changes in sleep timing and duration. Dietary patterns (identified a posteriori in a prior analysis) were assessed with a baseline food frequency questionnaire, and sleep was measured with wrist actigraphy at baseline and follow-up. Linear regression analyses adjusting for sex, age, screen time, and smoking were conducted. Adolescents with higher consumption of a Plant-Based and Lean Proteins pattern had earlier sleep timing (−0.45 h with 95% Confidence Interval (CI) −0.81, −0.08 in the highest compared to lowest quartiles), less of a phase delay in sleep timing over follow-up (−0.39 h with 95% CI −0.80, 0.02), and shorter weekend sleep duration (0.5 h with 95% CI −0.88, −0.1). Higher consumption of an Eggs, Milk and Refined Grain pattern was associated with earlier sleep timing (−0.40 h with 95% CI −0.77, −0.04), while consumption of a Meat and Starchy pattern was related to higher social jetlag (weekend–weekday sleep timing difference). Healthier diet patterns may promote better sleep in adolescents.
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Kelly, Rachael M., John H. McDermott, and Andrew N. Coogan. "Thematic Daily Sleep Routine Analysis of Adults Not in Employment Living with Type 2 Diabetes Mellitus." Clocks & Sleep 6, no. 1 (December 29, 2023): 11–23. http://dx.doi.org/10.3390/clockssleep6010002.
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Background: Day-to-day variations in sleep timing have been associated with poorer glycemic control in type 2 diabetes mellitus, although the factors that influence this sleep timing variability are poorly understood. Methods: Daily routines of sleep in a sample of seventeen adults with type 2 diabetes mellitus who were either retired or not currently working were examined qualitatively through the application of semi-structured interviews and a thematic analysis of the resulting transcripts. Results: Four themes were identified: “Consistent Sleeping Patterns”, “Fluctuating Sleep Timing”, “Night-Time Disruptions” and “Lasting Effort Needed with Type Two Diabetes Mellitus”. The subthemes reflected that many participants had consistent sleep schedules across the seven-day week, but that a desire to maintain a sense of normality, household routines, television schedules and socializing were associated with different sleep timing on weekends. Active disease monitoring and timed medication taking were not identified as important factors in shaping sleep timing. Nocturia, stress and rumination were identified as important factors linked to disrupted sleep. Sleep was not reported as an issue discussed during routine clinical care. Conclusion: Sleep timing in participants appears to be driven by interacting psychosocial and physiological factors, although active disease management does not emerge as a major influence on sleep schedules.
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Jessen, Elena, Celine Vetter, Till Roenneberg, Klaus-Peter Liesenkötter, Helene Werner, Oskar Jenni, Erwin Lankes, et al. "Sleep Timing in Patients with Precocious and Delayed Pubertal Development." Clocks & Sleep 1, no. 1 (February 16, 2019): 140–50. http://dx.doi.org/10.3390/clockssleep1010013.
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Previous studies have reported a shift in the timing of sleep during adolescence toward a later time. To date, it is unclear whether hormonal changes during puberty might contribute to this change in sleeping behavior. We systematically assessed pubertal development and sleep timing in a cross-sectional case-control study in girls with precocious (n = 42) and boys with delayed pubertal development (n = 19). We used the Munich ChronoType Questionnaire and the Children’s ChronoType Questionnaire to assess sleep timing in patients and age- and sex-matched controls (n = 309) and used the midpoint of sleep on free days, corrected for potential sleep debt accumulated during the school week, as a marker for sleep timing. Compared to the controls, girls with central precocious puberty showed a delay in sleep timing of 54 min, and girls with premature pubarche slept on average 30 min later. Male adolescents with delayed pubertal development showed an average sleep midpoint that was 40 min earlier compared to the control group. The results of this pilot study suggest an association between pubertal onset and shifts in sleep timing, which is a novel finding in human sleep behavior. Prospective studies in larger cohorts will be needed to examine the robustness and generalizability of the findings.
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Kang, Jee eun, Linying Ji, Orfeu Buxton, and Martin Sliwinski. "DAILY ASSOCIATIONS OF SOCIAL INTERACTIONS WITH OBJECTIVE SLEEP MEASURES AMONG OLDER ADULTS." Innovation in Aging 7, Supplement_1 (December 1, 2023): 57. http://dx.doi.org/10.1093/geroni/igad104.0181.
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Abstract Disturbed sleep is a common problem and can have profound effects on older adults. Social relationships are known to be associated with quantity and quality of sleep. To extend prior research, we examined the associations of daily social interactions and sleep, using objective sleep measures and an ecological momentary assessments (EMA) approach. Participants in the Einstein Aging Study (n=285, Mage=77, range=70-90, 68% women, 46% White, 40% Black) reported their recent social interactions and physical contact four times a day for 16 days via EMA on mobile phones. Objective sleep measures (sleep timing, night sleep time, wake after sleep onset (WASO), sleep maintenance efficiency) were calculated from concurrent wrist actigraphy. Multilevel models controlled for demographics, living arrangement, Instrumental Activities of Daily Living, sleep-disordered breathing, and hypoxemia. Results showed that, on days when older adults had more day-time social interactions than their average, they had earlier sleep timing, shorter night sleep time, and less WASO, but no differences in sleep efficiency. On days when older adults had more physical contact than their average, they had earlier sleep timing and shorter night sleep time but no differences in WASO or sleep efficiency. These micro-longitudinal analyses among older adults suggest that daily social interactions are related to subsequent earlier sleep timing and shorter sleep at night, and can be beneficial for sleep quality. Physical contact seemed to be only associated with the timing and quantity of sleep but not sleep quality. Potential benefits of using an EMA approach in sleep research will be discussed.
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Hamilton, J. L., T. R. Goldstein, C. Sewall, J. Zelazny, N. Rode, B. Gibbons, and P. L. Franzen. "1000 Social Media Use And Actigraphic Measures Of Sleep Timing Among High-risk Adolescents." Sleep 43, Supplement_1 (April 2020): A379—A380. http://dx.doi.org/10.1093/sleep/zsaa056.996.
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Abstract Introduction Social media use is a risk factor for poor sleep among adolescents. It remains unclear whether social media use before bed impacts later sleep timing or whether youth turn to social media because of sleep problems, which impacts sleep timing. No study to date has examined this relationship using prospective designs and objective sleep measures among high-risk adolescents, who may be particularly vulnerable to social media use. Methods As a preliminary test of this relationship, 25 adolescents and young adults in an intensive outpatient program for depression and suicidality completed baseline measures of social media use and wore actiwatches for up to three months. Social media use included: 1) minutes of use within 2 hours of going to sleep, and 2) frequency of social media use due to difficulty falling or staying asleep. To examine social media as a predictor of sleep timing over the next month, actigraphic measures of sleep timing (i.e., onset) were used in the first month after baseline. Results Multilevel modeling indicated that higher levels of social media use in the 2 hours before bed (mean = 46.94 minutes) predicted later sleep timing (B = .02; SE = .01; p= .003). Similarly, higher frequency of social media use due to perceived sleep problems predicted later sleep timing (B = .22; SE = .11; p= .04). Models covaried for age, gender, and prior-day depressed mood. When simultaneously entered, only minutes of social media use in the 2 hours before bed significantly predicted later sleep timing. Conclusion Findings suggest that the relationship between social media use and sleep timing among adolescents with depression and suicidality may be driven by both social media use before bed and media use due to sleep problems. Research assessing objective social media use and daily relationships are needed to further disentangle this relationship. Support Jessica L Hamilton is supported by a T32 fellowship from NHLBI (HL082610; PI: Buysse). This research is supported by grants from the American Foundation for Suicide Prevention and University of Pittsburgh Clinical and Translational Science Institute.
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Swaminathan, Krithika, Elizabeth B. Klerman, and Andrew J. K. Phillips. "Are Individual Differences in Sleep and Circadian Timing Amplified by Use of Artificial Light Sources?" Journal of Biological Rhythms 32, no. 2 (April 2017): 165–76. http://dx.doi.org/10.1177/0748730417699310.
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Within the human population, there is large interindividual variability in the timing of sleep and circadian rhythms. This variability has been attributed to individual differences in sleep physiology, circadian physiology, and/or light exposure. Recent experimental evidence suggests that the latter is necessary to evoke large interindividual differences in sleep and circadian timing. We used a validated model of human sleep and circadian physiology to test the hypothesis that intrinsic differences in sleep and circadian timing are amplified by self-selected use of artificial light sources. We tested the model under 2 conditions motivated by an experimental study (Wright et al., 2013): (1) a “natural” light cycle, and (2) a “realistic” light cycle that included attenuation of light due to living indoors when natural light levels are high and use of electric light when natural light levels are low. Within these conditions, we determined the relationship between intrinsic circadian period (within the range of 23.7-24.6 h) and timing of sleep onset, sleep offset, and circadian rhythms. In addition, we simulated a work week, with fixed wake time for 5 days and free sleep times on weekends. Under both conditions, a longer intrinsic period resulted in later sleep and circadian timing. Compared to the natural condition, the realistic condition evoked more than double the variation in sleep timing across the physiological range of intrinsic circadian periods. Model predictions closely matched data from the experimental study. We found that if the intrinsic circadian period was long (>24.2 h) under the realistic condition, there was significant mismatch in sleep timing between weekdays and weekends, which is known as social jetlag. These findings indicate that individual tendencies to have very delayed schedules can be greatly amplified by self-selected modifications to the natural light/dark cycle. This has important implications for therapeutic treatment of advanced or delayed sleep phase disorders.
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Fudge, Jennifer E., Emily T. Peterson, Shae-Lynn M. Koe, and Hans C. Dringenberg. "The Impact of Lunch Timing on Nap Quality." Clocks & Sleep 6, no. 3 (August 5, 2024): 402–16. http://dx.doi.org/10.3390/clockssleep6030027.
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Purpose: Previous research has established that food intake is a biological regulator of the human sleep–wake cycle. As such, the timing of eating relative to sleep may influence the quality of sleep, including daytime naps. Here, we examine whether the timing of lunch (1 h vs. 2 h interval between lunch and a napping opportunity) impacts the quality of an afternoon nap. Methods: Using a randomized within-subject design over two separate experimental sessions (7 days apart), participants (n = 40, mean age = 25.8 years) consumed lunch 1 h and 2 h prior to an afternoon nap opportunity. Polysomnography and subjective self-reports were used to assess sleep architecture, sleepiness levels, and nap quality. Results: Results revealed no significant differences in subjective ratings of sleep quality and sleepiness, or in sleep architecture (total sleep time, sleep efficiency, sleep onset latency, sleep stages) between the 1 h and 2-h lunch conditions. Conclusions: All sleep measures were similar when napping followed eating by either 1 h or 2 h, suggesting that eating closer to nap onset may not negatively impact sleep architecture and quality. Future research should continue to identify conditions that improve nap quality, given the well-documented benefits of naps to reduce sleep pressure and improve human performance.
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Wirz-Justice, A. "S27-01 - Sleep timing and sleep manipulation as antidepressants." European Psychiatry 25 (2010): 91. http://dx.doi.org/10.1016/s0924-9338(10)70091-2.
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MacPherson, A. R., D. Schreiber, J. L. Imel, and N. D. Dautovich. "0728 Sleep Timing, Not Sleep Duration, Predicts Breakfast Intake." Sleep 41, suppl_1 (April 2018): A270. http://dx.doi.org/10.1093/sleep/zsy061.727.
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Chung, Nikola, Yu Sun Bin, Peter A. Cistulli, and Chin Moi Chow. "Does the Proximity of Meals to Bedtime Influence the Sleep of Young Adults? A Cross-Sectional Survey of University Students." International Journal of Environmental Research and Public Health 17, no. 8 (April 14, 2020): 2677. http://dx.doi.org/10.3390/ijerph17082677.
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Avoiding food before bedtime is a widely accepted sleep hygiene practice, yet few studies have assessed meal timing as a risk factor for disrupted sleep. This study examined the relationship between evening meal timing and sleep quality in young adults. A total of N = 793 participants (26% male) aged between 18 and 29 years responded to an online survey, which captured sociodemographic information, lifestyle variables, and sleep characteristics. Meal timing was defined as meals more than 3 h before or within 3 h of bedtime. The outcomes were as follows: one or more nocturnal awakenings, sleep onset latency of >30 min, and sleep duration of ≤6 h. Logistic regression analyses showed that eating within 3 h of bedtime was positively associated with nocturnal awakening (OR = 1.61, 95% CI = 1.15–2.27) but not long sleep onset latency (1.24; 0.89–1.73) or short sleep duration (0.79; 0.49–1.26). The relationship remained significant after adjusting for potential confounders of ethnicity and body mass index (OR = 1.43, 95% CI = 1.00–2.04). Meal timing appears to be a modifiable risk factor for nocturnal awakenings and disrupted sleep. However, this is a preliminary cross-sectional study and highlights the need for additional research on the influence of the timing of food intake on sleep.
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Derby, Carol, Michelle Hood, Martica Hall, Hadine Joffe, Rebecca Thurston, Howard Kravitz, and Leslie Swanson. "SLEEP REGULARITY, SLEEP TIMING, AND COGNITIVE PERFORMANCE AMONG WOMEN ENTERING EARLY OLDER AGE." Innovation in Aging 7, Supplement_1 (December 1, 2023): 623–24. http://dx.doi.org/10.1093/geroni/igad104.2032.
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Abstract Poor sleep health is a modifiable behavior linked to cognitive impairment risk. While prior work has focused primarily on sleep quantity and quality, emerging evidence suggests the importance of sleep timing and regularity. We examined whether sleep timing and regularity were associated with cognitive performance within a diverse cohort of women ages 60.5-72.2 years, and tested whether associations were independent of sleep duration and quality (wake after sleep onset). The sample included 1178 SWAN women who completed 4-7 nights of actigraphy and cognitive testing at the 15th SWAN follow-up in 2015-2016, [Mean age 65.5 (± 2.63 years); 25% Black, 12% Chinese, 6% Hispanic White, 11% Japanese, 46% Non-Hispanic White]. Sleep timing was defined as the midpoint time between sleep onset and waking, averaged across nights and was dichotomized as healthy (2am – 4am) or unhealthy (outside 2am – 4am). Sleep regularity was defined as the standard deviation of the sleep midpoint across nights. Associations of sleep regularity and timing with verbal episodic memory (East Boston Memory immediate (EBMT-I) and delayed (EBMT-D)), and processing speed (Symbol Digit Modalities) were examined using linear regression. Covariates included sleep duration and quality, age, race/ethnicity, education, economic hardship, depression, comorbidities, medications, alcohol use, vasomotor symptoms and testing language. Greater sleep irregularity was associated with worse verbal memory (EBMT-I β= -0.29; p=0.02; EBMT-D β= -0.36; p=0.007). Sleep midpoint outside the healthy range was associated with slower processing speed (β= -1.48; p=0.017). Sleep timing and regularity may be important targets for interventions aimed at preserving cognitive health.
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Hanlon, Erin, Wajdey Nesheiwat, Stephanie Sintetas, Eve Van Cauter, and Kristen Knutson. "019 A Simple, Objective Estimate of Dietary Timing as a Circadian Biomarker." Sleep 44, Supplement_2 (May 1, 2021): A9. http://dx.doi.org/10.1093/sleep/zsab072.018.
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Abstract Introduction The importance of diet for health has been recognized for centuries, yet, the focus has mostly been on what someone eats. Recently, however, focus has expanded to include when someone eats. Experimental studies that manipulated timing of food intake demonstrated effects on metabolic function. Most population-based studies have had to rely on self-reported methods to assess dietary behavior, including food logs or dietary recall, but self-report is subjective, error-prone, and burdensome. The goal of this analysis was to identify an objective estimate of dietary timing in clock time format. Further, we planned to examine whether sleep “chronotype” and this dietary “chronotype” are correlated. Methods We used continuous glucose monitoring (CGM), which involves inserting a small sensor into the back of a participant’s upper arm. It measures interstitial glucose levels every 5 minutes continuously for up to 2 weeks. We had 13 participants wear a CGM device for 2–10 days. We characterized dietary timing by simply identifying the clock time at which glucose levels were the highest. We identified this time point for each day and then calculated the mean clock time for each participant. Participants also wore wrist actigraphy for approximately one week and we calculated mean sleep start, sleep end, and midpoint times. We calculated intervals between highest glucose and sleep timing measures. Results The mean time of highest glucose was 16:57 (SD 3:05) and ranged from 11:16 to 22:27. The mean (SD) intervals were 10.4 (2.9) hours for sleep end to highest glucose, 13.5 (2.8) hours for midpoint to highest glucose, and 5.8 (2.8) hours for highest glucose to sleep start. The correlations between highest glucose and sleep timing were .13 (p=.70) for sleep start, .05 (p=.88) for sleep end, and -.19 (p=.55) for midpoint. Conclusion There was a wide range in the timing of highest glucose values in this sample, Further, the timing of highest glucose does not correlate with sleep timing, which indicates that these two timing measures are not redundant with one another. The timing of highest glucose from CGM may provide an objective, simple circadian biomarker of dietary behavior. Support (if any) P01A1011412-18A1
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Pande, Babita, Meenakshi Sinha, and Ramanjan Sinha. "229 Sleep-wake behavior, meal timings and digital media duration of Indians during COVID-19 Lockdown." Sleep 44, Supplement_2 (May 1, 2021): A91—A92. http://dx.doi.org/10.1093/sleep/zsab072.228.
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Abstract Introduction Lockdown and stay home order has been imposed on people in many countries including India to prevent the community transmission of COVID-19 pandemic. However this social restriction led to disturbed daily routine and lifestyle behaviour that is needed to be attended for proper therapeutic management of overall health during such crisis. The impact of lockdown on the most apparent behavioral changes viz. sleep-wake behaviour, major meal timings, and digital screen duration of Indians were investigated. In addition the effects of gender and age were explored. Methods After seeking permission from Ethical Institution, an online questionnaire based survey was circulated within India in the first week of May, 2020 for which total 1511 male and female (age ≥18 years) subjects participated. The sleep-wake behavior observed were sleep-wake timings, sleep duration, mid sleep time (MST) as function of lockdown, and social (lockdown) jetlag (SJL = MST before lockdown-MST during lockdown). Results The sleep onset-wakeup and meal times were significantly delayed during lockdown, which was more pronounced in younger age group. The sleep duration increased, specifically in young individuals during lockdown. Females showed more delayed sleep onset-waking times and first meal timing with longer sleep duration during lockdown. Increased digital media duration was observed in all age groups, primarily in males. The younger age group and specifically female reported higher SJL and delayed MST. A positive association was obtained between sleep duration & first meal time, and SJL & major meal timings/screen duration, and a significant negative relationship of sleep duration and SJL with age. Conclusion The study shows delayed sleep-wake schedule, meal timings and increased digital media duration among Indians during COVID-19 lockdown compared to before lockdown. Also, gender and age emerged as important mediating factors for this alteration. The pandemic has given opportunity to sleep more and compensate for the sleep. In spite of that, the higher social jetlag in young age group and female showed the compromised sleep and maladaption with societal timing. These findings have applied implications in sleep health during longer social isolation conditions and for proper therapeutic management. Support (if any) No
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von Gall, Charlotte, Leon Holub, Martina Pfeffer, and Simon Eickhoff. "Chronotype-Dependent Sleep Loss Is Associated with a Lower Amplitude in Circadian Rhythm and a Higher Fragmentation of REM Sleep in Young Healthy Adults." Brain Sciences 13, no. 10 (October 19, 2023): 1482. http://dx.doi.org/10.3390/brainsci13101482.
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In modern society, the time and duration of sleep on workdays are primarily determined by external factors, e.g., the alarm clock. This can lead to a misalignment of the intrinsically determined sleep timing, which is dependent on the individual chronotype, resulting in reduced sleep quality. Although this is highly relevant given the high incidence of sleep disorders, little is known about the effect of this misalignment on sleep architecture. Using Fitbit trackers and questionnaire surveys, our study aims to elucidate sleep timing, sleep architecture, and subjective sleep quality in young healthy adults (n = 59) under real-life conditions (average of 82.4 ± 9.7 days). Correlations between variables were calculated to identify the direction of relationships. On workdays, the midpoint of sleep was earlier, the sleep duration was shorter, and tiredness upon waking was higher than on free days. A higher discrepancy between sleep duration on workdays and free days was associated with a lower stability of the circadian rhythm of REM sleep and also with a higher fragmentation of REM sleep. Similarly, a higher tiredness upon waking on free days, thus under intrinsically determined sleep timing conditions, was associated with a lower proportion and a higher fragmentation of REM sleep. This suggests that the misalignment between extrinsically and intrinsically determined sleep timing affects the architecture of sleep stages, particularly REM sleep, which is closely connected to sleep quality.
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Dadzie, Adwoa, Lindsay Master, Emily Hohman, Erika Hernandez, Sara Tauriello, Ian Paul, Jennifer Savage, Stephanie Anzman-Frasca, and Orfeu Buxton. "0105 INSIGHT Study associations between sleep health and child behavior at age 6 years." SLEEP 46, Supplement_1 (May 1, 2023): A47. http://dx.doi.org/10.1093/sleep/zsad077.0105.
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Abstract Introduction Sub-optimal sleep duration, quality and timing are associated with the presence of disruptive behaviors in childhood. Previous studies have largely utilized parent-/teacher-report of children’s behaviors and focused on mean sleep duration and quality measures, ignoring sleep variability. This analysis uses actigraphy and standardized laboratory behavioral tasks to examine the associations of average levels and variability (SD) of sleep duration, timing, and quality with child behavior. Methods The Intervention Nurses Start Infants Growing on Healthy Trajectories (INSIGHT) Study randomized families with firstborn newborns to a responsive parenting intervention or a safety control shortly after delivery. At age 6 years, children wore a wrist actigraphy device (Spectrum Plus) for 7 days to measure sleep and completed frustration (Transparent Box) and parent-child interaction (Picture Frame) tasks. Tasks were recorded and coded using global behavioral coding schemes; inter-rater reliability was sufficient (Transparent Box ICCs=.83-.97; Picture Frame=.83-1). Children with data on sleep (≥3 valid days) and both behavioral tasks were included in this secondary data analysis (n=143). Separate linear regression models examined associations between 10 sleep variables (M/SD of onset, offset, and midpoint of sleep timing, sleep maintenance efficiency, and total sleep time) and 4 behavioral variables (Transparent Box: emotion regulation, impulsivity; Picture Frame: prosocial and antisocial behavior). Models controlled for child sex and age, household income, and study group. Results Children were aged 6.7 ± 0.3 years and predominantly White, non-Hispanic (95%). Sleep onset (timing) variability was positively associated with impulsivity (B=.85, p=.004) and negatively associated with emotion regulation (B=-.65, p=.01). Sleep midpoint (timing) variability was positively associated with impulsivity (B=.80, p=.03). Mean sleep timing, sleep duration, and sleep maintenance efficiency were not associated with any of the behavioral variables. Conclusion The regularity of sleep timing (onset and midpoint) at age 6 had a greater role in behavioral and emotional regulation than duration and quality of sleep. These findings support existing literature that highlight the importance of parents implementing consistent routines (e.g., consistent bedtime) and how such routines play a key role in socioemotional outcomes among children. Support (if any) R01DK088244
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Baron, K., L. Bardsley, K. J. Reid, L. F. Wolfe, M. Buman, M. Toledo, and P. C. Zee. "0060 Role Of Circadian Timing and Alignment In The Timing And Intensity Of Physical Activity." Sleep 41, suppl_1 (April 2018): A24. http://dx.doi.org/10.1093/sleep/zsy061.059.
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Chung, J., M. O. Goodman, T. Huang, M. Wallace, S. Bertisch, D. Johnson, and S. Redline. "0363 Racial/Ethnic Differences in Actigraphy, Questionnaire, and Polysomnography-Measured Indicators of Sleep Health and Sleep Quality: The Multi-Ethnic Study of Atherosclerosis." Sleep 43, Supplement_1 (April 2020): A138—A139. http://dx.doi.org/10.1093/sleep/zsaa056.360.
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Abstract Introduction Paradigm shifts in sleep research suggest the importance of considering multi-dimensional sleep health, compared to single metrics, to promote physical and mental well-being and to understand racial/ethnic disparities in sleep. Methods We used data from the Multi-Ethnic Study of Atherosclerosis (MESA; n = 1,740) to create a Sleep Health Score (SHS), including questionnaire (quality, sleepiness); 7-day actigraphy (total sleep time, sleep continuity [sleep maintenance efficiency], timing consistency [midpoint variability], fragmentation, wake after sleep onset, sleep onset latency); and in-home polysomnography (%N3 sleep, %REM sleep, AHI). Sleep parameters were dichotomized based on prior literature or by healthiest quartile(s), with positive values denoting healthier sleep (e.g. Epworth scores < 10). All 11 dichotomized parameters were summed to calculate the SHS (mean=4.9, sd=1.58). We used modified Poisson and linear regression for individual sleep outcomes and the SHS, respectively, adjusting for age and sex. Results The sample was older (mean age=68.28, sd=9.08) and 54% female. SHSs were associated with Black race (β=-0.60 [-0.78, -0.42]) and Hispanic ethnicity (β=-0.40 [-0.59, -0.21]), but not Chinese ethnicity (β=-0.16 [-0.41, 0.08]). Compared to Whites (n=644), Blacks (n=485) showed lower adjusted probability of obtaining favorable levels of: sleep continuity, fragmentation, timing consistency, alertness/sleepiness, and sleep depth (%N3 sleep). Chinese respondents (n=202) had lower probability of obtaining favorable levels of: sleep continuity and timing consistency, but higher probability of quality. Hispanics (n=409) had lower probability of obtaining healthy levels of: sleep continuity, timing consistency, and fragmentation. Neither healthy total sleep time (middle quartiles) nor AHI (<30) differed by race/ethnicity. Conclusion Among MESA-Sleep participants, summary SHSs were lowest in Blacks, followed by Hispanics. Multiple dimensions of sleep - particularly related to continuity and timing consistency - were less favorable across race/ethnic minority groups. A summary SHS may help monitor sleep health across populations, while measurement of specific sleep components may help identify modifiable targets. Support Joon Chung is supported by a T-32 NIH training grant.
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Ceolin, Chiara, Federica Limongi, Paola Siviero, Caterina Trevisan, Marianna Noale, Filippo Catalani, Silvia Conti, et al. "Changes in Sleep Duration and Sleep Timing in the General Population from before to during the First COVID-19 Lockdown: A Systematic Review and Meta-Analysis." International Journal of Environmental Research and Public Health 21, no. 5 (May 2, 2024): 583. http://dx.doi.org/10.3390/ijerph21050583.
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Background: The COVID-19 lockdown had a profound effect on everyday life, including sleep health. This systematic review and meta-analysis evaluated changes in quantitative sleep parameters during the first lockdown compared with pre-lockdown in the general population. Methods: A search in scientific databases was performed to identify eligible observational studies from inception to 8 February 2023. We performed a random effects meta-analysis of those studies reporting (a) means of sleep duration, time in bed (TIB), and sleep timing (bedtime and wake-up time); (b) the percentages of atypical sleep duration before and during the lockdown; (c) the percentages of change in sleep duration and sleep timing. Results: A total of 154 studies were included. A small increase in sleep duration (0.25 standardized mean difference, 95% CI 0.180–0.315) was found, with 55.0% of the individuals reporting changes, predominantly an increase (35.2%). The pooled relative risk for sleeping more than 8/9 h per night was 3.31 (95% IC 2.60–4.21). There was a moderately significant delay in sleep timing and a surge in napping. Conclusion: An increase in sleep duration and napping, and delayed sleep timing were observed. High-quality studies should evaluate whether these parameters have now become chronic or have returned to pre-lockdown values.
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Van Reen, Eliza, Leila Tarokh, Tracy L. Rupp, Ron Seifer, and Mary A. Carskadon. "Does Timing of Alcohol Administration Affect Sleep?" Sleep 34, no. 2 (February 2011): 195–205. http://dx.doi.org/10.1093/sleep/34.2.195.
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Chen, Bo-chiuan, Dong-Chul Seo, Hsien-Chang Lin, and David Crandall. "Framework for estimating sleep timing from digital footprints." BMJ Innovations 4, no. 4 (August 30, 2018): 172–77. http://dx.doi.org/10.1136/bmjinnov-2018-000274.
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ObjectiveWe propose a method that estimates sleep timing from publicly observable activity on online social network sites. The method has the potential to minimise participant-related biases, does not require specialised equipment and can be applied to a large population.Materials and methodsWe propose a framework that estimates midpoints of habitual sleep time from activity records on a social media—Twitter. We identified sets of before-bedtime and after-wake-up tweets that marked the periods of reduced Twitter activity, which we use as a proxy of sleep. We then estimated the timing of sleep by deriving the median among midpoints of paired before-bedtime and after-wake-up tweets. Visualisations and examples of our estimates comparing sleep timing of users from different countries are provided.DiscussionInitial results suggest that the proposed framework could detect differences in sleep timing among user groups of different countries. The proposed framework may be a cost-efficient complement for future research regarding sleep-related health concerns. Researchers and practitioners may benefit from accessing habitual sleep data. While validation is still required prior to actual applications, the proposed framework may be a first step towards a convenient and cost-efficient complement to currently available methods.
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Griggs, Stephanie, Quiana Howard, Grant Pignatiello, Kingman Strohl, Chiang-Shan R. Li, Margaret Grey, Sybil Crawford, and Ronald Hickman. "0921 Pilot Cognitive Behavioral Sleep Health Randomized Controlled Trial for Young Adults with Type 1 Diabetes." SLEEP 47, Supplement_1 (April 20, 2024): A395. http://dx.doi.org/10.1093/sleep/zsae067.0921.
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Abstract Introduction Short sleep duration and inconsistent timing have been linked to poor glycemic target achievement and greater comorbidities in individuals with type 1 diabetes (T1D), particularly adults aged 18-26 years who achieve glycemic targets at the lowest rates (only 14%). Preliminary evidence supports cognitive behavioral sleep interventions (sleep extension + timing consistency) in improving the achievement of sleep and glycemic targets. The purpose of this pilot randomized controlled trial (RCT) was to determine the preliminary effects of a cognitive behavioral sleep health self-management intervention (CB-Sleep Health - sleep extension + timing consistency) on self-report and objectively derived sleep health dimensions (satisfaction, alertness, timing, efficiency, and duration) in young adults with T1D. Methods Young adults with T1D for at least 6 months with a hemoglobin A1C ≥ 7% or ≤ 80% time in glucose range were randomly assigned 1:1 stratified by sex at birth to a 12-week CB-Sleep Health (n = 21) or time balanced attention control (AC) condition (n = 18). Participants completed the Pittsburgh Sleep Quality Index (sleep satisfaction) and trail making test (daytime alertness) while concurrently wearing continuous glucose monitors and research grade actigraphy (timing, efficiency, and duration) for 14 days at baseline, post-intervention, and a 3-month follow up. Results Thirty-nine young adults (mean age 21, BMI 25.9 kg/m2, A1C 8.5% and 44% time in glucose range, 59% male, 26% Non-White - 18% Black/8% other race) participated. Baseline sleep health dimension values (mean + sd) were 5.4 + 0.7 vs. 5.3 + 0.5 score (satisfaction), 18.4 + 1.4 vs. 20.3 + 1.3 seconds (daytime alertness), 16:07 + 0.4 vs. 15:95 + 0.4 hours (timing), 85.6 + 4.1% vs. 84.7 + 4.5% (efficiency), and 6.4 + 1.0, vs. 6.9 + 1.0 hours (duration) for CB-Sleep Health vs. AC respectively. Sleep duration and alertness improved for CB-Sleep Health compared to AC post intervention (+18 minute vs. -25.8 minutes, p = .01 and -3.92 seconds vs. +0.71, p = .005) and were sustained at the 3-month follow up. Conclusion Preliminary effects of a CB-Sleep Health intervention on sleep duration and alertness without impairing efficiency for young adults with T1D are encouraging. Support (if any) National Institute of Nursing Research (R00NR018886)
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Rogers, Michelle, Alison M. Coates, and Siobhan Banks. "Meal timing, sleep, and cardiometabolic outcomes." Current Opinion in Endocrine and Metabolic Research 18 (June 2021): 128–32. http://dx.doi.org/10.1016/j.coemr.2021.03.006.
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GIRARD, TODD A., and J. ALLAN CHEYNE. "Timing of spontaneous sleep-paralysis episodes." Journal of Sleep Research 15, no. 2 (June 2006): 222–29. http://dx.doi.org/10.1111/j.1365-2869.2006.00512.x.
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Born, Jan, Kirsten Hansen, Lisa Marshall, Matthias Mölle, and Horst L. Fehm. "Timing the end of nocturnal sleep." Nature 397, no. 6714 (January 1999): 29–30. http://dx.doi.org/10.1038/16166.
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Cibella, F., O. Marrone, S. Sanci, V. Bellia, and G. Bonsignore. "Expiratory timing in obstructive sleep apnoeas." European Respiratory Journal 3, no. 3 (March 1, 1990): 293–98. http://dx.doi.org/10.1183/09031936.93.03030293.
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Diaphragmatic electromyogram was recorded during NREM sleep in 4 patients affected by obstructive sleep apnoea (OSA) syndrome in order to evaluate the behaviour of expiratory time (TE) in the course of the obstructive apnoea-ventilation cycle. The two components of TE, i.e. time of post-inspiratory inspiratory activity (TPIIA) and time of expiratory phase 2 (TE2) were separately analysed. TPIIA showed a short duration, with only minor variations, within the apnoea, while its duration was more variable and longer in the interapnoeic periods: the longest TPIIA values were associated with the highest inspiratory volumes in the same breaths. This behaviour seemed regulated according to the need of a more or less effective expiratory flow braking, probably as a result of pulmonary stretch receptors discharge. Conversely TE2 showed a continuous gradual modulation, progressively increasing in the pre-apnoeic period, decreasing during the apnoea and increasing in the post-apnoeic period: these TE2 variations seemed related to oscillations in chemical drive. These data show that TE in the obstructive apnoea-ventilation cycle results from a different modulation in its two components and suggest that both mechanical and chemical influences play a role in its overall duration.
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Meyhöfer, Svenja, Rodrigo Chamorro, Manfred Hallschmid, Denisa Spyra, Nelli Klinsmann, Bernd Schultes, Hendrik Lehnert, Sebastian M. Meyhöfer, and Britta Wilms. "Late, but Not Early, Night Sleep Loss Compromises Neuroendocrine Appetite Regulation and the Desire for Food." Nutrients 15, no. 9 (April 23, 2023): 2035. http://dx.doi.org/10.3390/nu15092035.
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Objective: There is evidence that reduced sleep duration increases hunger, appetite, and food intake, leading to metabolic diseases, such as type 2 diabetes and obesity. However, the impact of sleep timing, irrespective of its duration and on the regulation of hunger and appetite, is less clear. We aimed to evaluate the impact of sleep loss during the late vs. early part of the night on the regulation of hunger, appetite, and desire for food. Methods: Fifteen normal-weight ([mean ± SEM] body-mass index: 23.3 ± 0.4 kg/m2) healthy men were studied in a randomized, balanced, crossover design, including two conditions of sleep loss, i.e., 4 h sleep during the first night-half (‘late-night sleep loss’), 4 h sleep during the second night-half (‘early-night sleep loss’), and a control condition with 8h sleep (‘regular sleep’), respectively. Feelings of hunger and appetite were assessed through visual analogue scales, and plasma ghrelin and leptin were measured from blood samples taken before, during, and after night-time sleep. Results: Ghrelin and feelings of hunger and appetite, as well as the desire for food, were increased after ‘late-night sleep loss’, but not ‘early-night sleep loss’, whereas leptin remained unaffected by the timing of sleep loss. Conclusions: Our data indicate that timing of sleep restriction modulates the effects of acute sleep loss on ghrelin and appetite regulation in healthy men. ‘Late-night sleep loss’ might be a risk factor for metabolic diseases, such as obesity and type 2 diabetes. Thereby, our findings highlight the metabolic relevance of chronobiological sleep timing.
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Dunietz, Liana, Anna Olson, Lucas Tittle, David Kalmbach, D'Angela Pitts, Chia-Lun Yang, Erica Jansen, et al. "0727 Sleep Timing and Depression Risk in Pregnancy." SLEEP 47, Supplement_1 (April 20, 2024): A311. http://dx.doi.org/10.1093/sleep/zsae067.0727.
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Abstract Introduction There is growing evidence that sleep timing is linked to health outcomes. Poorly timed sleep has been associated with metabolic risk factors and mood problems although there is a lack of data in the pregnant population. Emerging data suggest that late sleep timing during pregnancy may be associated with gestational diabetes, gestational hypertension, and preterm birth. However, data on sleep timing and mood during pregnancy are lacking. Methods Pregnant women were recruited from prenatal clinics at a large Midwestern tertiary referral center. Women were eligible if they were at least 18 years old and pregnant in their second or third trimester with a single fetus. There were no other exclusion criteria. Participants were queried about their sleep including questions about the time they went to bed, the time they woke up and their typical nocturnal sleep duration. Sleep mid-point was calculated as the time midway between bedtime and wake time and a delayed midpoint was defined as being after 4:00am. Demographic information was abstracted from medical records. Women were considered to have depression with a score of 13 or more on the Edinburgh Postnatal Depression Scale (EPDS) or a clinical diagnosis of depression. Results A total of 1349 women were included in the analysis, of which 15% were classified as having depression. Mean age was 30.7 years (SD 5.6 years) and mean gestational age was 33.8 weeks (SD 4.3 weeks). Overall, 26% of women had a sleep midpoint after 4:00am. In a regression model, women with a delayed sleep midpoint had a significantly increased odds ratio for depression (OR 1.4, 95%CI 1.1-1.8), which did not appreciably change after controlling for age, race, presence of hypertension or diabetes, first pregnancy, marital status, and sleep duration (aOR 1.5, 95%CI 1.1-2.2). Conclusion We provide initial evidence suggesting a link between self-reported late sleep midpoint and depressive symptoms in pregnancy. Assessment of sleep timing during pregnancy may have potential for identification of women at risk of depression. Support (if any)
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Zerón-Rugerio, María Fernanda, Giovana Longo-Silva, Álvaro Hernáez, Ana Eugenia Ortega-Regules, Trinitat Cambras, and Maria Izquierdo-Pulido. "The Elapsed Time between Dinner and the Midpoint of Sleep Is Associated with Adiposity in Young Women." Nutrients 12, no. 2 (February 5, 2020): 410. http://dx.doi.org/10.3390/nu12020410.
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Meal timing relative to sleep/wake schedules is relevant in the search for obesity risk factors. However, clock time does not accurately characterize the timing of food intake in the context of internal circadian timing. Therefore, we studied elapsed between dinner and the midpoint of sleep (TDM) as a practical approach to evaluate meal timing relative to internal timing, and its implications on obesity. To do so, adiposity, sleep, diet, physical activity, and TDM were measured in 133 women. The participants were grouped into four categories according to their sleep timing behavior (early-bed/early-rise; early-bed/late-rise; late-bed/early-rise; late-bed/late-rise). Differences among the categories were tested using ANOVA, while restricted cubic splines were calculated to study the association between TDM and adiposity. Our results show that, although participants had dinner at about the same time, those that had the shortest TDM (early-bed/early-rise group) were found to have significantly higher BMI and waist circumference values (2.3 kg/m2 and 5.2 cm) than the other groups. In addition, a TDM of 6 h was associated with the lowest values of adiposity. The TDM could be a practical approach to personalizing meal timing based on individual sleep/wake schedules. Thus, according to our findings, dining 6 h before the midpoint of sleep is an important finding and could be vital for future nutritional recommendations and for obesity prevention and treatment.
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Estevan, Ignacio, Natalia Coirolo, Bettina Tassino, and Ana Silva. "The Influence of Light and Physical Activity on the Timing and Duration of Sleep: Insights from a Natural Model of Dance Training in Shifts." Clocks & Sleep 5, no. 1 (January 31, 2023): 47–61. http://dx.doi.org/10.3390/clockssleep5010006.
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Environmental, social, and behavioral variables influence sleep timing and duration. Using wrist-worn accelerometers, we recorded 31 dancers (age = 22.6 ± 3.5) for 17 days and who trained either in the morning (n = 15) or in the late evening (n = 16). We estimated the dancers’ daily sleep pattern: onset, end, and duration. In addition, their minutes of moderate-to-vigorous physical activity (MVPA) and mean light illuminance were also calculated daily and for the morning-shift and late-evening-shift time windows. On training days, the shifts involved differences in sleep timing, alarm-driven waking frequency, and the pattern of light exposure and MVPA duration. Sleep was strongly advanced when dancers trained in the morning and when alarms were used, while morning light had a low influence. Sleep was delayed when dancers were more exposed to light and displayed longer MVPA during the late evening. Sleep duration was strongly reduced on weekends and when alarms were used. A small reduction in sleep duration was also observed when morning illuminance was lower or when late evening MVPA was longer. Training in shifts influenced the timing of environmental and behavioral factors, which added up to shape dancers’ sleep timing and duration.
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Zhu, Liwei, Dexin Meng, Xiaohan Ma, Jing Guo, and Li Mu. "Sleep timing and hygiene practices of high bedtime procrastinators: a direct observational study." Family Practice 37, no. 6 (August 12, 2020): 779–84. http://dx.doi.org/10.1093/fampra/cmaa079.
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Abstract Background Bedtime procrastination (BP) has been proven to be an important indicator of sleep insufficiency from a psychological perspective. However, the effect of BP on sleep patterns related to sleep deficiency remains unknown. Objective This study aimed to investigate the characteristics of self-reported sleep timing and hygiene practices between high and low-moderate bedtime procrastinators. It also aimed to examine the relationship between these characteristics and high level of BP. Methods A total of 391 Chinese college students were recruited for this study. Participants completed questionnaires on demographics, sleep timing variables, the Sleep Hygiene Practice Scale (SHPS) and the Bedtime Procrastination Scale (BPS). Results High bedtime procrastinators were more likely to have higher SHPS global and subdomain scores (Ps < 0.001). They also were more likely to exhibit later sleep onset, sleep offset and rise time on both weekdays and weekends (Ps < 0.01). The significant independent determinant factors of the prevalence of high BP were: SHPS total score [odds ratio (OR) = 1.05, P < 0.001], arousal-related behaviour (OR = 1.07, P = 0.007), sleep schedule and timing (OR = 1.12, P < 0.001) and sleep onset on weekdays (OR = 2.65, P < 0.001). Conclusions High bedtime procrastinators showed maladaptive sleep-related variables, which mainly manifested as changes in arousal-related behaviour and sleep schedule and timing, as well as delays in sleep onset time on weekdays. The findings could help guide the formulation of appropriate interventions in primary health care.
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Prayag, Abhishek, Mirjam Münch, Daniel Aeschbach, Sarah Chellappa, and Claude Gronfier. "Light Modulation of Human Clocks, Wake, and Sleep." Clocks & Sleep 1, no. 1 (March 13, 2019): 193–208. http://dx.doi.org/10.3390/clockssleep1010017.
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Light, through its non-imaging forming effects, plays a dominant role on a myriad of physiological functions, including the human sleep–wake cycle. The non-image forming effects of light heavily rely on specific properties such as intensity, duration, timing, pattern, and wavelengths. Here, we address how specific properties of light influence sleep and wakefulness in humans through acute effects, e.g., on alertness, and/or effects on the circadian timing system. Of critical relevance, we discuss how different characteristics of light exposure across the 24-h day can lead to changes in sleep–wake timing, sleep propensity, sleep architecture, and sleep and wake electroencephalogram (EEG) power spectra. Ultimately, knowledge on how light affects sleep and wakefulness can improve light settings at home and at the workplace to improve health and well-being and optimize treatments of chronobiological disorders.
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Mathew, Gina, David Reichenberger, Orfeu Buxton, Lauren Hale, and Anne-Marie Chang. "140 Short and Long Sleep Duration, Poor Sleep Quality, and Later Sleep are Associated with Lower Odds of Adolescents Eating Breakfast." Sleep 44, Supplement_2 (May 1, 2021): A58. http://dx.doi.org/10.1093/sleep/zsab072.139.
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Abstract Introduction Sleep health is linked to dietary choices, and skipping breakfast is associated with risk of negative health outcomes in adolescents. However, there is a lack of research on whether dimensions of sleep at night predict adolescents eating breakfast the next day. We investigated within- and between-person associations of multiple aspects of sleep with adolescent breakfast consumption. Methods Data were collected from a subset of the age 15 wave of the Fragile Families and Child Wellbeing Study (n=590). Teens wore an actigraphy device and completed daily surveys for ~1 week (mean=5.9 days). Surveys assessed subjective sleep quality (low–high) and consumption of breakfast (no/yes). Mixed models assessed whether actigraphy-measured sleep timing (onset, midpoint, and offset) and subjective sleep quality predicted odds of breakfast consumption in both within- and between-person models. A curvilinear association between sleep duration and breakfast consumption was also assessed. Irregularity of sleep duration and timing were tested as additional predictors, calculated as SD per person (in between-person models only). Analyses included random intercepts for participants and covariates: school day, boredom, loneliness, happiness, depressive symptoms, sex, race/ethnicity, body mass index, and household income. Results Within-person analyses revealed a significant curvilinear association between sleep duration and breakfast consumption, such that on nights when teens slept shorter or longer than their average, they had lower odds of eating breakfast the next day (p=.005). Additionally, on nights when teens had a later sleep midpoint or offset than their usual, they tended to skip breakfast the next day (both p<.05). Between-person models showed that teens who on average had later sleep timing (onset, midpoint, and offset) and who reported lower sleep quality had lower odds of eating breakfast (all p<.04). Lastly, teens with greater irregularity of sleep duration and sleep timing (midpoint and offset) had lower odds of eating breakfast (all p<.009). Conclusion Findings indicate that multiple dimensions of adolescent sleep health, including long and short sleep duration, later sleep timing, and poorer sleep quality, are associated with lower odds of eating breakfast. These sleep and dietary behaviors in adolescence may consequently impact future metabolic health. Support (if any) R01HD073352
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Chang, Anne-Marie, Kathryn J. Reid, Ramadevi Gourineni, and Phyllis C. Zee. "Sleep Timing and Circadian Phase in Delayed Sleep Phase Syndrome." Journal of Biological Rhythms 24, no. 4 (July 22, 2009): 313–21. http://dx.doi.org/10.1177/0748730409339611.
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Reis, Cátia, Luísa K. Pilz, Lena Katharina Keller, Teresa Paiva, and Till Roenneberg. "Social timing influences sleep quality in patients with sleep disorders." Sleep Medicine 71 (July 2020): 8–17. http://dx.doi.org/10.1016/j.sleep.2020.02.019.
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Thomas, Matthew, Philip Kern, Dorothy Sears, and Julie Pendergast. "0097 Sleep and Eating Rhythms are Associated with Metabolic Risk in Postmenopausal Women." SLEEP 46, Supplement_1 (May 1, 2023): A43—A44. http://dx.doi.org/10.1093/sleep/zsad077.0097.
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Abstract Introduction Postmenopausal women are particularly vulnerable to metabolic dysfunction. Compelling evidence suggests that this is due to their lacking the protective effect of estrogens. We have shown that circulating estrogens regulate daily eating and sleep-activity rhythms in female mice and protect them from obesity and diabetes. However, few studies have investigated whether postmenopausal women have disrupted eating and sleep-activity rhythms that could contribute to their metabolic dysfunction. The purpose of this study was to investigate the relationship between eating rhythms, sleep, and metabolic risk in postmenopausal women. Methods During 7 days, we studied sedentary, postmenopausal women who were not taking hormones (estrogens ± progestin) and were metabolically unhealthy, defined as prediabetic or normal glucose tolerance with at least 1 feature of the metabolic syndrome. Women taking medications affecting sleep or eating were excluded. Sleep timing and quality were assessed by actigraphy and sleep logs. Times of first and last meals were collected from participants with a texting system. Body composition (DXA), body mass index (BMI), and waist circumference were collected as markers of obesity. Lipid metabolism and glycemic control were assessed by fasting lipid panel and HbA1c as well as oral glucose tolerance test. Results Eighteen postmenopausal women (mean ± SEM; 57.2 ± 1.1 years) participated in the study. Both sleep timing and quality were associated with metabolic risk in postmenopausal women. Specifically, later timing of sleep onset was associated with later meal timing and greater BMI and body fat percentage. Increased sleep fragmentation was associated with reduced HDL. In addition, both the timing and duration of eating were associated with worse metabolic measures. Longer eating duration was associated with larger waist circumference. Later eating time was associated with greater waist circumference and BMI. Conclusion We found that late timing and poor quality of sleep, as well as long eating duration, are associated with markers of metabolic risk in postmenopausal women. These data suggest that interventions that reduce eating duration and advance the timing of last meal and sleep onset may improve metabolic risk in postmenopausal women. Support (if any) This study is supported by NIH awards R01DK124774, T32 AG078110, and UL1TR001998.
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Hehr, Aneesh, Hilary A. Marusak, Edward D. Huntley, and Christine A. Rabinak. "Effects of Duration and Midpoint of Sleep on Corticolimbic Circuitry in Youth." Chronic Stress 3 (January 2019): 247054701985633. http://dx.doi.org/10.1177/2470547019856332.
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Introduction Adequate sleep is essential for cognitive and emotion-related functioning, and 9 to 12 hr of sleep is recommended for children ages 6 to 12 years and 8 to 10 hr for children ages 13 to 18 years. However, national survey data indicate that older youth sleep for fewer hours and fall asleep later than younger youth. This shift in sleep duration and timing corresponds with a sharp increase in onset of emotion-related problems (e.g., anxiety, depression) during adolescence. Given that both sleep duration and timing have been linked to emotion-related outcomes, the present study tests the effects of sleep duration and timing, and their interaction, on resting-state functional connectivity (RS-FC) of corticolimbic emotion-related neural circuitry in children and adolescents. Methods A total of 63 children and adolescents (6–17 years, 34 females) completed a weekend overnight sleep journal and a 10-min resting-state functional magnetic resonance imaging scan the next day (Sunday). Whole-brain RS-FC of the amygdala was computed, and the effects of sleep duration, timing (i.e., midpoint of sleep), and their interaction were explored using regression analyses. Results Overall, we found that older youth tended to sleep later and for fewer hours than younger youth. Controlling for age, shorter sleep duration was associated with lower RS-FC between the amygdala and regions implicated in emotion regulation, including ventral anterior cingulate cortex, precentral gyrus, and superior temporal gyrus. Interestingly, midpoint of sleep was associated with altered connectivity in a distinct set of brain regions involved in interoception and sensory processing, including insula, supramarginal gyrus, and postcentral gyrus. Our data also indicate widespread interactive effects of sleep duration and midpoint on brain regions implicated in emotion regulation, sensory processing, and motor control. Conclusion These results suggest that both sleep duration and midpoint of sleep are associated with next-day RS-FC within corticolimbic emotion-related neural circuitry in children and adolescents. The observed interactive effects of sleep duration and timing on RS-FC may reflect how homeostatic and circadian process interact in the brain and explain the complex patterns observed with respect to emotional health when considering sleep duration and timing. Sleep-related changes in corticolimbic circuitry may contribute to the onset of emotion-related problems during adolescence.
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Verma, Sumedha, Donna Pinnington, Rachel Manber, and Bei Bei. "225 Sleep Timing and Chronotype in Mothers: Longitudinal Changes and Associations with Wellbeing from Pregnancy to 2 Years Postpartum." Sleep 44, Supplement_2 (May 1, 2021): A90. http://dx.doi.org/10.1093/sleep/zsab072.224.
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Abstract Introduction Women experience significant changes to sleep during perinatal periods. Existing research focuses on sleep duration and quality, but not sleep timing or chronotype (i.e., preferred timing for activity and sleep). This study investigated change trajectories of sleep timing and chronotype from late pregnancy to two years postpartum, and examined longitudinal associations between chronotype and insomnia, sleep-related daytime impairment, and mood. Methods Data were from a 2-arm randomized controlled trial testing behavioral sleep and diet interventions. A community sample of nulliparous women without severe sleep/mental health conditions participated. Women self-reported bedtime, risetime, chronotype (reduced Morningness-Eveningness Questionnaire), Insomnia Severity Index, and PROMIS Depression, Anxiety, and Sleep-Related Impairment over 7 time points: 30 and 35 weeks’ gestation, and postpartum months 1.5, 3, 6, 12 and 24. Results 163 women (mean age 33.35 ± 3.42 years) took part. Mixed effects models controlling for age and group allocation showed that both bed- and risetimes became progressively earlier over time by approximately 20-30 minutes on average (p < .001); chronotype also shifted progressively towards morningness (p < .01). After controlling for covariates (sleep duration and efficiency, mental health history, social support, age, group allocation), greater morningness was significantly associated with lower symptoms of insomnia and sleep-related impairment over time (p-values < .001); longitudinal associations between chronotype and symptoms of depression and anxiety were non-significant (p-values > .65). Conclusion This is one of the first studies to examine longitudinal changes in sleep timing and chronotype from pregnancy to two years postpartum. Sleep timing and chronotype became progressively earlier over the first two postpartum years. The magnitude of changes is beyond what is expected with increasing age. Greater morningness was associated with lower sleep complaints and sleep-related daytime impairment during the postpartum period. The mechanisms underlying these associations require further research. Support (if any) Australasian Sleep Association, Monash University, Australian Government RTP Scholarship and National Health and Medical Research Council.
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Dutil, Caroline, Irina Podinic, Christin M. Sadler, Bruno G. da Costa, Ian Janssen, Amanda Ross-White, Travis J. Saunders, Jennifer R. Tomasone, and Jean-Philippe Chaput. "Sleep timing and health indicators in children and adolescents: a systematic review." Health Promotion and Chronic Disease Prevention in Canada 42, no. 4 (April 2022): 150–69. http://dx.doi.org/10.24095/hpcdp.42.4.04.
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Introduction To continue to inform sleep health guidelines and the development of evidence-based healthy sleep interventions for children and adolescents, it is important to better understand the associations between sleep timing (bedtime, wake-up time, midpoint of sleep) and various health indicators. The objective of this systematic review was to examine the associations between sleep timing and 9 health indicators in apparently healthy children and adolescents 5 to 18 years old. Methods Studies published in the 10 years preceding January 2021 were identified from searches in four electronic databases. This systematic review followed the guidelines prescribed in PRISMA 2020, the methodological quality and risk of bias were scored, and the summary of results used a best-evidence approach for accurate and reliable reporting. Results Forty-six observational studies from 21 countries with 208 992 unique participants were included. Sleep timing was assessed objectively using actigraphy in 24 studies and subjectively in 22 studies. The lack of studies in some of the health outcomes and heterogeneity in others necessitated using a narrative synthesis rather than a metaanalysis. Findings suggest that later sleep timing is associated with poorer emotional regulation, lower cognitive function/academic achievement, shorter sleep duration/ poorer sleep quality, poorer eating behaviours, lower physical activity levels and more sedentary behaviours, but few studies demonstrated associations between sleep timing and adiposity, quality of life/well-being, accidents/injuries, and biomarkers of cardiometabolic risk. The quality of evidence was rated as “very low” across health outcomes using GRADE. Conclusion The available evidence, which relies on cross-sectional findings, suggests that earlier sleep timing is beneficial for the health of school-aged children and adolescents. Longitudinal studies and randomized controlled trials are needed to better advance this field of research. (PROSPERO registration no.: CRD42020173585)The pandemic has negatively impacted a substantial portion of the Defence Team. When responding to future crises, it is recommended that leaders of organizations provide additional supports to higher-risk groups and to supervisors who are ideally positioned to support employees during challenging times.
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Hisler, G., S. Pedersen, D. Clark, S. Rothenberger, and B. Hasler. "0216 Is There a Daily Rhythm in Alcohol Craving and Does It Vary by Circadian Timing?" Sleep 43, Supplement_1 (April 2020): A84. http://dx.doi.org/10.1093/sleep/zsaa056.214.
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Abstract Introduction People with later circadian timing tend to consume more alcohol, potentially due to altered rhythms in when and how much they crave alcohol throughout the day. However, whether circadian factors play a role in alcohol craving has received scant attention. Here, we investigated if the daily rhythm of alcohol craving varied by circadian timing in two independent studies of late adolescent and young adult drinkers. Methods In Study 1, 32 participants (18–22 years of age; 61% female; 69% White) completed momentary reports of alcohol craving five times a day for 14 days. Participants wore wrist actigraphs and completed two in-lab assessments of dim light melatonin onset (DLMO). Average actigraphically-assessed midpoint of sleep on weekends and average DLMO were used as indicators of circadian timing. In Study 2, 231 participants (21–35 years of age; 28% female; 71% White) completed momentary reports of alcohol craving six times a day for 10 days. Average midpoint of self-reported time-in-bed on weekends was used to estimate circadian timing. Results Multilevel cosinor analysis revealed a 24-hour daily rhythm in alcohol craving which was moderated by circadian timing in both studies (p’s<0.05). In both Study 1 and 2, people with later circadian timing had a later timed peak of craving. In Study 1, but not Study 2, later circadian timing predicted a blunted amplitude in craving. Conclusion Findings support a daily rhythm in craving that varies by individual differences in circadian timing. Because craving is an important predictor of future alcohol use, the findings implicate circadian factors as a useful area to advance alcohol research and potentially improve interventions. Support R21AA023209; R01DA044143; K01AA021135; ABMRF/The Foundation for Alcohol Research.