Sleep and meal-time misalignment alters functional connectivity: a pilot resting-state study.
ABSTRACT: Delayed sleep and meal times promote metabolic dysregulation and obesity. Altered coordination of sleeping and eating times may impact food-reward valuation and interoception in the brain, yet the independent and collective contributions of sleep and meal times are unknown. This randomized, in-patient crossover study experimentally manipulates sleep and meal times while preserving sleep duration (7.05±0.44?h for 5 nights). Resting-state functional magnetic resonance imaging scans (2 × 5-minute runs) were obtained for four participants (three males; 25.3±4.6 years), each completing all study phases (normal sleep/normal meal; late sleep/normal meal; normal sleep/late meal; and late sleep/late meal). Normal mealtimes were 1, 5, 11 and 12.5?h after awakening; late mealtimes were 4.5, 8.5, 14.5 and 16?h after awakening. Seed-based resting-state functional connectivity (RSFC) was computed for a priori regions-of-interest (seeds) and contrasted across conditions. Statistically significant (P<0.05, whole-brain corrected) regionally specific effects were found for multiple seeds. The strongest effects were linked to the amygdala: increased RSFC for late versus normal mealtimes (equivalent to skipping breakfast). A main effect of sleep and interaction with meal time were also observed. Preliminary findings support the feasibility of examining the effects of sleep and meal-time misalignment, independent of sleep duration, on RSFC in regions relevant to food reward and interoception.
Project description:This pilot study tested the independent and interactive effects of sleep and meal times, under identical sleep duration and feeding conditions, on insulin sensitivity (Si) in overweight adults. Participants underwent a 4-phase randomized crossover inpatient study differing in sleep times: normal (Ns: 0000-0800 hours) or late (Ls: 0330-1130 hours); and in meal times: normal (Nm: 1, 5, 11, and 12.5 hours after awakening) or late (Lm: 4.5, 8.5, 14.5, and 16 hours after awakening). An insulin-modified frequently sampled intravenous glucose tolerance test, at scheduled breakfast time, and a meal tolerance test, at scheduled lunch time, were performed to assess Si after 3 days in each condition. Six participants were enrolled (4 men, 2 women; mean age 25.1±[SD] 3.9 years, body mass index 29.2±2.7 kg/m2); only 1 failed to complete her last study phase. There were no effects of sleep and meal times or sleep × meal time interaction on Si (all P>.35), acute insulin response to intravenous glucose (all P>.20), and disposition index (all P>.60) after adjusting for sex and body mass index. Meal tolerance test glucose and insulin areas under the curve were lower during Nm (glucose P=.11; insulin P=.0088). There were a sleep × meal interaction and an effect of meal times on overnight glucose (P=.0040 and .012, respectively) and insulin (P=.0075 and .067, respectively). Sleep timing, without concomitant sleep restriction, does not adversely affect Si and glucose tolerance, but meal times may be relevant for health. Our results should be confirmed in a larger sample.
Project description:BACKGROUND:Studies associate sleeping and eating late in the day with poor dietary quality and higher obesity risk but differences in sleep duration confound this association. We aimed to determine whether sleep and meal timing, independent of sleep duration, influenced food intake in healthy adults. METHODS:This was a controlled, 2?×?2 inpatient crossover study with normal (0000-0800?h) or late (0330-1130?h) sleep and normal (1, 5, 11, and 12.5?h after awakening) or late (4.5, 8.5, 14.5, and 16?h after awakening) meals. Food intake was controlled while blood samples were obtained for determination of appetite-regulating hormones on days 3-4. Self-selected food intake was assessed on day 5. Data were analyzed using linear mixed model analysis with sleep, meal, and sleep x meal interaction as dependent variables. RESULTS:Five participants completed all phases (mean age 25.1?±?[SD] 3.9?y, body mass index 29.2?±?2.7?kg/m2). There was a significant sleep x meal interaction on energy intake (P?=?0.035) and trends on fat and sodium intakes (P?<?0.10). Overnight ghrelin concentrations were higher under normal sleep and meal conditions relative to late (P?<?0.005) but lower when both were combined (P?<?0.001). Overnight leptin concentrations were higher under normal meal conditions (P?=?0.012). There was a significant sleep x meal interaction on ghrelin (P?=?0.032) and glucagon-like peptide 1 (P?=?0.041) concentrations, but not leptin (P?=?0.83), in response to a test meal. CONCLUSIONS:Our results suggest that alignment of sleep and meals may influence food choice and energy balance. Additional research is necessary to expand and confirm our findings.
Project description:OBJECTIVES:This study examines associations between social media use and multiple sleep parameters in a large representative adolescent sample, controlling for a wide range of covariates. DESIGN:The authors used cross-sectional data from the Millennium Cohort Study, a large nationally representative UK birth cohort study. PARTICIPANTS:Data from 11?872 adolescents (aged 13-15 years) were used in analyses. METHODS:Six self-reported sleep parameters captured sleep timing and quality: sleep onset and wake times (on school days and free days), sleep onset latency (time taken to fall asleep) and trouble falling back asleep after nighttime awakening. Binomial logistic regressions investigated associations between daily social media use and each sleep parameter, controlling for a range of relevant covariates. RESULTS:Average social media use was 1 to <3?hours per day (31.6%, n=3720). 33.7% were classed as low users (<1?hour; n=3986); 13.9% were high users (3 to <5?hours; n=1602) and 20.8% were very high users (5+ hours; n=2203). Girls reported spending more time on social media than boys. Overall, heavier social media use was associated with poorer sleep patterns, controlling for covariates. For example, very high social media users were more likely than comparable average users to report late sleep onset (OR 2.14, 95%?CI 1.83 to 2.50) and wake times (OR 1.97, 95%?CI 1.32 to 2.93) on school days and trouble falling back asleep after nighttime awakening (OR 1.36, 95%?CI 1.10 to 1.66). CONCLUSIONS:This study provides a normative profile of UK adolescent social media use and sleep. Results indicate statistically and practically significant associations between social media use and sleep patterns, particularly late sleep onset. Sleep education and interventions can focus on supporting young people to balance online interactions with an appropriate sleep schedule that allows sufficient sleep on school nights.
Project description:Sleep inertia is affected by circadian phase, with worse performance upon awakening from sleep during the biological night than biological day. Visual search/selective visual attention performance is known to be sensitive to sleep inertia and circadian phase. Individual differences exist in the circadian timing of habitual wake time, which may contribute to individual differences in sleep inertia. Because later chronotypes awaken at an earlier circadian phase, we hypothesized that later chronotypes would have worse visual search performance during sleep inertia than earlier chronotypes if awakened at habitual wake time. We analysed performance from 18 healthy participants [five females (22.1 ± 3.7 years; mean ± SD)] at ~1, 10, 20, 30, 40 and 60 min following electroencephalogram-verified awakening from an 8 h in-laboratory sleep opportunity. Cognitive throughput and reaction times of correct responses were impaired by sleep inertia and took ~10-30 min to improve after awakening. Regardless whether chronotype was defined by dim light melatonin onset or mid-sleep clock hour on free days, derived from the Munich ChronoType Questionnaire, the duration of sleep inertia for cognitive throughput and reaction times was longer for later chronotypes (n = 7) compared with earlier chronotypes (n = 7). Specifically, performance for earlier chronotypes showed significant improvement within ~10-20 min after awakening, whereas performance for later chronotypes took ~30 min or longer to show significant improvement (P < 0.05). Findings have implications for decision making immediately upon awakening from sleep, and are consistent with circadian theory suggesting that sleep inertia contributes to longer-lasting impairments in morning performance in later chronotypes.
Project description: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.
Project description:Background:Individuals complaining of a delayed sleep schedule are expected to have shorter sleep duration and lower sleep quality when they must comply with morning obligations. The changes in the sleep schedule imposed by morning obligations may in turn decrease the stability and amplitude of their rest-activity cycle. These expectations were only partially supported in previous studies, possibly due to poor differentiation between days with mandatory or free wake times. Participants:Fourteen college/university students (8 women) with a complaint of a late sleep schedule and a bedtime after midnight were compared to fourteen controls with an earlier sleep schedule and no complaint. Methods:During a week of 24-h activity recording, participants specified in their sleep diary whether their wake time was free or determined by an obligation. Results:The number of nights with mandatory wake times was similar in the two groups. Groups were also similar for sleep duration and sleep quality over the 7 days of recording. Actigraphic sleep efficiency was the same in the two groups for both free and mandatory wake times, but subjective sleep quality decreased on the nights with mandatory wake time in both groups. On the nights with mandatory wake time, delayed participants had shorter sleep episodes and less total sleep time than controls. Rest-activity cycle amplitude was lower in the delayed group whether wake time was free or mandatory. Conclusion:Sleep duration and total sleep time differed between the two groups only when wake time was mandatory. Prior to mandatory wake times, delayed participants kept the same bedtime and shortened their sleep; sleep latency and sleep efficiency were preserved but subjective sleep quality and alertness on awakening decreased compared to nights with free wake time. Lower amplitude of the rest-activity cycle in delayed subjects may reflect lifestyle differences compared to control participants.
Project description:The insula has been implicated in salience processing, craving, and interoception, all of which are critical to the clinical manifestations of drug and behavioral addiction. In this functional magnetic resonance imaging (fMRI) study, we examined resting-state functional connectivity (rsFC) of the insula and its association with Internet gaming characteristics in 74 young adults with Internet gaming disorder (IGD) and 41 age- and gender-matched healthy control subjects (HCs). In comparison with HCs, IGD subjects (IGDs) exhibited enhanced rsFC between the anterior insula and a network of regions including anterior cingulate cortex (ACC), putamen, angular gyrus, and precuneous, which are involved in salience, craving, self-monitoring, and attention. IGDs also demonstrated significantly stronger rsFC between the posterior insula and postcentral gyrus, precentral gyrus, supplemental motor area, and superior temporal gyrus (STG), which are involved in interoception, movement control, and auditory processing. Furthermore, IGD severity was positively associated with connectivity between the anterior insula and angular gyrus, and STG, and with connectivity between the posterior insula and STG. Duration of Internet gaming was positively associated with connectivity between the anterior insula and ACC. These findings highlight a key role of the insula in manifestation of the core symptoms of IGD and the importance to examine functional abnormalities of the anterior and posterior insula separately in IGDs.
Project description:A common complaint of older persons is disturbed sleep, typically characterized as an inability to return to sleep after waking. As every sleep episode (i.e., time in bed) includes multiple transitions between wakefulness and sleep (which can be subdivided into rapid eye movement [REM] sleep and non-REM [NREM] sleep), we applied survival analysis to sleep data to determine whether changes in the "hazard" (duration-dependent probability) of awakening from sleep and/or returning to sleep underlie age-related sleep disturbances. The hazard of awakening from sleep--specifically NREM sleep--was much greater in older than in young adults. We found, however, that when an individual had spontaneously awakened, the probability of falling back asleep was not greater in young persons. Independent of bout length, the number of transitions between NREM and REM sleep stages relative to number of transitions to wake was approximately 6 times higher in young than older persons, highlighting the difficulty in maintaining sleep in older persons. Interventions to improve age-related sleep complaints should thus target this change in awakenings.
Project description:High dream recallers (HR) show a larger brain reactivity to auditory stimuli during wakefulness and sleep as compared to low dream recallers (LR) and also more intra-sleep wakefulness (ISW), but no other modification of the sleep macrostructure. To further understand the possible causal link between brain responses, ISW and dream recall, we investigated the sleep microstructure of HR and LR, and tested whether the amplitude of auditory evoked potentials (AEPs) was predictive of arousing reactions during sleep. Participants (18 HR, 18 LR) were presented with sounds during a whole night of sleep in the lab and polysomnographic data were recorded. Sleep microstructure (arousals, rapid eye movements (REMs), muscle twitches (MTs), spindles, KCs) was assessed using visual, semi-automatic and automatic validated methods. AEPs to arousing (awakenings or arousals) and non-arousing stimuli were subsequently computed. No between-group difference in the microstructure of sleep was found. In N2 sleep, auditory arousing stimuli elicited a larger parieto-occipital positivity and an increased late frontal negativity as compared to non-arousing stimuli. As compared to LR, HR showed more arousing stimuli and more long awakenings, regardless of the sleep stage but did not show more numerous or longer arousals. These results suggest that the amplitude of the brain response to stimuli during sleep determine subsequent awakening and that awakening duration (and not arousal) is the critical parameter for dream recall. Notably, our results led us to propose that the minimum necessary duration of an awakening during sleep for a successful encoding of dreams into long-term memory is approximately 2 min.
Project description:Whether non-nutritive sweetener (NNS) consumption impacts food intake behavior in humans is still unclear. Discrepant sensory and metabolic signals are proposed to mislead brain regulatory centers, in turn promoting maladaptive food choices favoring weight gain. We aimed to assess whether ingestion of sucrose- and NNS-sweetened drinks would differently alter brain responses to food viewing and food intake. Eighteen normal-weight men were studied in a fasted condition and after consumption of a standardized meal accompanied by either a NNS-sweetened (NNS), or a sucrose-sweetened (SUC) drink, or water (WAT). Their brain responses to visual food cues were assessed by means of electroencephalography (EEG) before and 45 min after meal ingestion. Four hours after meal ingestion, spontaneous food intake was monitored during an ad libitum buffet. With WAT, meal intake led to increased neural activity in the dorsal prefrontal cortex and the insula, areas linked to cognitive control and interoception. With SUC, neural activity in the insula increased as well, but decreased in temporal regions linked to food categorization, and remained unchanged in dorsal prefrontal areas. The latter modulations were associated with a significantly lower total energy intake at buffet (mean kcal ± SEM; 791 ± 62) as compared to WAT (942 ± 71) and NNS (917 ± 70). In contrast to WAT and SUC, NNS consumption did not impact activity in the insula, but led to increased neural activity in ventrolateral prefrontal regions linked to the inhibition of reward. Total energy intake at the buffet was not significantly different between WAT and NNS. Our findings highlight the differential impact of caloric and non-caloric sweeteners on subsequent brain responses to visual food cues and energy intake. These variations may reflect an initial stage of adaptation to taste-calorie uncoupling, and could be indicative of longer-term consequences of repeated NNS consumption on food intake behavior.