Differences In Sleep Behavior Research Articles

Sleep fragmentation after traumatic brain injury impairs behavior and conveys long-lasting impacts on neuroinflammation

Traumatic brain injury (TBI) causes a prolonged inflammatory response in the central nervous system (CNS) driven by microglia. Microglial reactivity is exacerbated by stress, which often provokes sleep disturbances. We have previously shown that sleep fragmentation (SF) stress after experimental TBI increases microglial reactivity and impairs hippocampal function 30 days post-injury (DPI). The neuroimmune response is highly dynamic the first few weeks after TBI, which is also when injury induced sleep-wake deficits are detected. Therefore, we hypothesized that even a few weeks of TBI SF stress would synergize with injury induced sleep-wake deficits to promote neuroinflammation and impair outcome. Here, we investigated the effects of environmental SF in a lateral fluid percussion model of mouse TBI. Half of the mice were undisturbed, and half were exposed to 5 h of SF around the onset of the light cycle, daily, for 14 days. All mice were then undisturbed 15–30 DPI, providing a period for SF stress recovery (SF-R). Mice exposed to SF stress slept more than those in control housing 7–14 DPI and engaged in more total daily sleep bouts during the dark period. However, SF stress did not exacerbate post-TBI sleep deficits. Testing in the Morris water maze revealed sex dependent differences in spatial reference memory 9–14 DPI with males performing worse than females. Post-TBI SF stress suppressed neurogenesis-related gene expression and increased inflammatory signaling in the cortex at 14 DPI. No differences in sleep behavior were detected between groups during the SF stress recovery period 15–30 DPI. Microscopy revealed cortical and hippocampal IBA1 and CD68 percent-area increased in TBI SF-R mice 30 DPI. Additionally, neuroinflammatory gene expression was increased, and synaptogenesis-related gene expression was suppressed in TBI-SF mice 30 DPI. Finally, IPA canonical pathway analysis showed post-TBI SF impaired and delayed activation of synapse-related pathways between 14 and 30 DPI. These data show that transient SF stress after TBI impairs recovery and conveys long-lasting impacts on neuroimmune function independent of continuous sleep deficits. Together, these finding support that even limited exposure to post-TBI SF stress can have lasting impacts on cognitive recovery and regulation of the immune response to trauma.

Towards data‐driven video analysis for quantification of nocturnal sleep disturbance in dementia

AbstractBackgroundSleep disturbance is common among people living with dementia as well as their caregivers. Non‐contact video technology can be used to characterise such disturbances as well as quantifying sleep quality by measuring the number of sleep body positions (poses). Such an approach may be beneficial for home‐based longitudinal clinical monitoring of sleep pattern changes and disturbances at all stages of dementia. Here we present our pilot results of a personalised data‐driven method applied to video data for quantification of sleep disturbance comparing older and younger participants.MethodData were collected in two separate studies which included an overnight 10‐12 hour laboratory sleep recording from thirteen older (65‐80 years, 9 male:4 female) and eleven younger (18‐34 years, 7 male:4 female) participants in a dedicated sleep facility. A data‐driven analysis using Principal Component Analysis and k‐means clustering was applied to infrared video data extracted from a clinical polysomnography (PSG) system. The data‐driven analysis automatically determined statistically significant groupings or clusters of unique body poses for each individual. Pose number, number of pose transitions, pose duration, and pose transition duration were computed for each participant.ResultThe number of data‐driven poses in older and younger participants was remarkably similar with 15.2±3.9 and 15.8±1.8 (mean±SD) poses per participant, respectively. However, the older group had a higher number of pose transitions (33.0±8.82) compared to the younger group (23.9±6.83) (p = 0.03). A significant 20% difference (p = 0.03) in the average duration of each body position was observed, with 62.3±7.1 minutes and 78.9±15.9 minutes for the older and younger groups, respectively (see Figure 1 and Figure 2). Pose transition duration was 19.2±7.25 seconds and 14.6±4.32 seconds for the older and younger groups, respectively where they were not significantly different.ConclusionAlthough the number of body positions did not vary significantly between the two cohorts, the older group changed body position more frequently and it took them longer to do so. Data‐driven automated analysis of video‐based sleep monitoring holds significant promise for quantifying age‐related and inter‐individual differences in sleep behavior.

Characterization of differences in sleep behaviors between academy, semi-professional and professional levels of competition in rugby union athletes

Athletes display differing sleep habits to non-athletic populations; similarly, differences occur in sleep habits between athletes from different sports. There is currently limited research investigating the differences in sleep habits and behaviors between different levels of competition within the same sport. A total of 224 rugby union athletes (109 academy, 38 semi-professional, 84 professional) completed the Athlete Sleep Behavior Questionnaire and the Pittsburgh Sleep Quality Index. Professional athletes displayed a significantly longer self-reported sleep duration compared to semi-professional and academy athletes (7 h 52 min ± 51 min vs. 7 h 16 min ± 1 h 15 min vs. 7 h 19 min ± 1 h 12 min, p < 0.01). Pittsburgh Sleep Quality Index global scores revealed a significantly lower ( p = 0.04, d = 0.3) score for professional athletes (5.2 ± 2.5 AU) than academy athletes (6.0 ± 2.7 AU). Individual components of the Pittsburgh Sleep Quality Index revealed significant differences ( p < 0.05) between groups for sleep duration and daytime dysfunction. No significant differences ( p > 0.05) were observed between levels of competition for the Athlete Sleep Behavior Questionnaire global score; however, significant differences ( p < 0.05) were observed for 6 of the 18 items. This study was the first to investigate sleep behaviors across multiple levels of competition in rugby union athletes. Professional athletes displayed longer sleep duration compared to semi-professional and academy level athletes. Additionally, results highlighted that differences exist between levels of competition for specific sleep behaviors. This study identified that sleep behaviors could be improved for all levels of rugby union athletes.

Sleep Behavior Among Student Athletes

This study was conducted to identify the sleep behavior of student athletes. The study involved 116 student athletes in Perak State Sports School as a sample study to identify sleep behavior by making comparisons based on gender, training frequency, level of involvement and age. The researcher used the Athlete Sleep Behavior Questionnaire (ASBQ) which consists of 18 items and is divided into 3 subscales namely routine factors (6 items), behavioral factors (7 items) and sports -related factors (5 items). Inferential analysis t test and One -way ANOVA were used for the purpose of data analysis. The findings of the study showed that there was no significant difference in sleep behavior between male and female student athletes of the Perak State Sports School. In addition, the findings also showed that there were no significant differences in sleep behavior based on the highest level of involvement, training frequency and age among student athletes. In summary, good sleep behavior in sports students is due to an optimal sleep time of at least 7 hours a day.

Trait-like nocturnal sleep behavior identified by combining wearable, phone-use, and self-report data

Using polysomnography over multiple weeks to characterize an individual’s habitual sleep behavior while accurate, is difficult to upscale. As an alternative, we integrated sleep measurements from a consumer sleep-tracker, smartphone-based ecological momentary assessment, and user-phone interactions in 198 participants for 2 months. User retention averaged >80% for all three modalities. Agreement in bed and wake time estimates across modalities was high (rho = 0.81–0.92) and were adrift of one another for an average of 4 min, providing redundant sleep measurement. On the ~23% of nights where discrepancies between modalities exceeded 1 h, k-means clustering revealed three patterns, each consistently expressed within a given individual. The three corresponding groups that emerged differed systematically in age, sleep timing, time in bed, and peri-sleep phone usage. Hence, contrary to being problematic, discrepant data across measurement modalities facilitated the identification of stable interindividual differences in sleep behavior, underscoring its utility to characterizing population sleep and peri-sleep behavior.

687 Changes in adolescent sleep habits during the COVID-19 pandemic

IntroductionDuring the COVID-19 pandemic, adolescents have experienced significant lifestyle changes. With an increase in technological dependency and changes in school formats, sleep behaviors may be altered. As individuals with overweight or obesity (OWOB) already report higher rates of sleep issues, they may be particularly at risk during this time. However, to date, there are no data on changes in sleep behavior in adolescents with OWOB during the COVID-19 pandemic.MethodsParticipants included 10 adolescents with BMI ≥85th percentile (Mage=16.30 years, SDage=1.06; 60% male; 70% African American). Prior to the COVID-19 pandemic, participants completed sleep diaries twice per day for one week, noting caffeine intake, bedtime, naps, perceived sleep quality, and media use in bed. Participants then completed sleep diaries again during the COVID-19 pandemic. Five separate paired-samples t-tests assessed differences in sleep behaviors and quality.ResultsA paired-samples t-test demonstrated significantly earlier average bedtime before (M=11:20 PM, SD=55.16 minutes) than during (M=12:29 AM, SD=71.27 minutes) COVID-19 (t(9)=-3.0, p=0.015). A second paired-samples t-test demonstrated lower average media use in bed before (M=11.67, SD=10.97 minutes) than during (M=32.13, SD=27.28 minutes) the COVID-19 pandemic (t(9)=-2.3, p=0.050). No other significant differences were found.ConclusionAdolescents engaged in later bedtimes and increased media use in bed during the COVID-19 pandemic. This suggests adolescents’ sleep schedules have shifted later during the COVID-19 school year, due to either later wake times associated with virtual schooling or disruption in typical daily schedule as a result of the pandemic. However, no differences were found regarding caffeine intake, number of naps, and sleep quality. The significant findings regarding later adolescent bedtimes may reflect delayed sleep phase or possibly improved circadian alignment due to delayed school start times and at-home classes. The null findings regarding naps and caffeine intake may be reflective of the stability of daytime sleepiness. While we would expect daytime sleepiness to improve with increased circadian alignment, the effects may be diminished by increased media use in bed and decreased energy expenditure during the day. Given the observed relationships, current sleep hygiene interventions may require a focus on stimulus control and reducing time with media in bed.Support (if any):

218 BIDEN WON, BUT SLEEP LOST IN THE 2020 US ELECTION

IntroductionThe 2020 US Presidential Election captivated the US public resulting in record turnout. In the months preceding the elections COVID-19, racial injustice and the economic downturn had a daily impact on the lives of voters. In this research, we analyze the sleep behavior of Americans in the lead up to the Presidential Elections. We examine specifically the nights of the Presidential and Vice-Presidential Debates and Election Night.MethodsWe examined sleep data from the PSG-validated SleepScore Mobile Application, which uses a non-contact sonar-based method to objectively capture sleep-related metrics and self-reported lifestyle data. The data set included 123,723 nights (5,967 users residing in the US, aged 18-85, mean age: 46.6 +/- 16.7 years, 52.3% female). Data from September 1st until November 3rd were included. This covered the nights of the Presidential Debates (Tuesday 09/29/2020 and Thursday 10/22/2020) and the Vice-Presidential Debate (Wednesday 10/07/2020). Election night was Tuesday, November 3, 2020. Self-reported stress level (0-24 scale) and alcohol consumption (0-9 drinks) were measured using digital slider scales. Mixed Effect Modelling was used for analysis.ResultsThe night of the 1st Presidential debate saw a change in sleep-related behavior with users going to bed 9.5 minutes later, as compared to a regular Tuesday Night. This resulted in a decrease in both TST (11.5 mins, p<0.001) and TIB (11.8 mins, p<0.001). Interestingly, neither the the 2nd Presidential Debate, nor the Vice Presidential Debate resulted in significant differences in sleep behavior. On election night users went to bed 14.5 (p<0.001) min later on average, as compared to a normal Tuesday Night. This resulted in a decrease in both TIB (24.3 mins, p<0.001) and TST (19.2 mins, p<0.001). Self-report data showed a 13.3% (p<0.001) increase in stress level on election night and 34.4% (p<0.001) increase alcohol consumption Importantly, election night was two nights after the end of Daylight Savings Time (DST), Sunday, November 1st.ConclusionThis analysis shows the 2020 US Presidential election negatively impacted US population sleep. The impact was most pronounced on election night, but also observed following the first Presidential debate. The effect of DST on these findings is unknown but surmised to be meaningful.Support (if any):

Sex differences in deterioration of sleep properties associated with aging: a 12-year longitudinal cohort study.

The sleep patterns of humans are greatly influenced by age and sex and have various effects on overall health as they change continuously during the lifespan. We investigated age-dependent changes in sleep properties and their relation to sex in middle-aged individuals. We analyzed data from 2,640 participants (mean age of 49.8 ± 6.8 years at baseline, 50.6% women) in the Korean Genome and Epidemiology Study, which assessed sleep habits using the Pittsburgh Sleep Quality Index and other clinical characteristics. We analyzed the sleep habit changes that occurred between baseline and a follow-up point (mean interval: 12.00 ± 0.16 years). Associations of age and sex with 9 sleep characteristics were evaluated. Age was associated with most of the sleep characteristics cross-sectionally and longitudinally (P < .05), except for the time in bed at baseline (P = .455) and change in sleep duration (P = .561). Compared with men, women had higher Pittsburgh Sleep Quality Index scores, shorter time in bed, shorter sleep duration, and longer latency at baseline (P ≤ .001). Longitudinal deterioration in Pittsburgh Sleep Quality Index score, habitual sleep efficiency, duration, and latency was more prominent in women (P < .001). The sex differences in these longitudinal sleep changes were mainly noticeable before age 60 years (P < .05). Worsening of Pittsburgh Sleep Quality Index scores, habitual sleep efficiency, and latency was most evident in perimenopausal women. Men presented with greater advancement of chronotype (P = .006), with the peak sex-related difference occurring when they were in their late 40s (P = .048). Aging is associated with substantial deterioration in sleep quantity and quality as well as chronotype advancement, with the degree and timing of these changes differing by sex.

An Exploration of Sleep and Family Factors in Young Children at Familial Risk for ADHD

ABSTRACT Objective: The aim of the current study was to examine relations between sleep problems and family factors and early markers of ADHD in young children with and without a familial risk for ADHD. Methods: Differences in sleep behavior and family functioning in children under 6 years with (n = 72) and without (n = 139) a familial risk for ADHD were investigated. The influence of family and sleep factors on the development of early temperament markers of ADHD (effortful control and negative affect) was explored. Parents/caregivers completed questionnaires on family functioning, child sleep behavior, and general regulatory behaviors. Results: A significant difference was observed between high-risk and low-risk groups for family functioning in the infant/toddler (<3 years) and preschool (>3 years) cohorts. Parents of infants/toddlers in the high-risk group reported poorer infant sleep. However, there were no sleep differences reported for the preschool cohort. Family functioning was found to predict effortful control, while sleep quality predicted negative affect. Conclusion: The results of this study highlight potential family and sleep issues for young children with a familial history of ADHD and the potential influence of these factors on early temperament markers of ADHD. Future research should explore these relations further in order to better establish whether early sleep and family interventions could mitigate later ADHD symptomatology.

Sleep/Wake Behavior and EEG Signatures of the TgF344-AD Rat Model at the Prodromal Stage.

Transgenic modification of the two most common genes (APPsw, PS1ΔE9) related to familial Alzheimer’s disease (AD) in rats has produced a rodent model that develops pathognomonic signs of AD without genetic tau-protein modification. We used 17-month-old AD rats (n = 8) and age-matched controls (AC, n = 7) to evaluate differences in sleep behavior and EEG features during wakefulness (WAKE), non-rapid eye movement sleep (NREM), and rapid eye movement sleep (REM) over 24-h EEG recording (12:12h dark–light cycle). We discovered that AD rats had more sleep–wake transitions and an increased probability of shorter REM and NREM bouts. AD rats also expressed a more uniform distribution of the relative spectral power. Through analysis of information content in the EEG using entropy of difference, AD animals demonstrated less EEG information during WAKE, but more information during NREM. This seems to indicate a limited range of changes in EEG activity that could be caused by an AD-induced change in inhibitory network function as reflected by increased GABAAR-β2 expression but no increase in GAD-67 in AD animals. In conclusion, this transgenic rat model of Alzheimer’s disease demonstrates less obvious EEG features of WAKE during wakefulness and less canonical features of sleep during sleep.

Live fast, die young and sleep later: Life history strategy and human sleep behavior.

Background and objectivesLife History Theory (LHT) describes trade-offs that organisms make with regard to three investment pathways: growth, maintenance and reproduction. In light of the reparative functions of sleep, we examine sleep behaviors and corresponding attitudes as proximate manifestations of an individual’s underlying relative prioritization of short-term reproduction versus long-term maintenance.MethodologyWe collected survey data from 568 participants across two online studies having different participant pools. We use a mixture of segmented and hierarchical regression models, structural equation modeling and machine learning to infer relationships between sleep duration/quality, attitudes about sleep and biodemographic/psychometric measures of life history strategy (LHS).ResultsAn age-mediated U- or V-shaped relationship appears when LHS is plotted against habitual sleep duration, with the fastest strategies occupying the sections of the curve with the highest mortality risk: < 6.5 hr (short sleep) and > 8.5 hr (long sleep). LH ‘fastness’ is associated with increased sleepiness and worse overall sleep quality: delayed sleep onset latency, more wakefulness after sleep onset, higher sleep–wake instability and greater sleep duration variability. Hedonic valuations of sleep may mediate the effects of LHS on certain sleep parameters.Conclusions and implicationsThe costs of deprioritizing maintenance can be parameterized in the domain of sleep, where ‘life history fastness’ corresponds with sleep patterns associated with greater senescence and mortality. Individual differences in sleep having significant health implications can thus be understood as components of lifelong trajectories likely stemming from calibration to developmental circumstances. Relatedly, hedonic valuations of sleep may constitute useful avenues for non-pharmacological management of chronic sleep disorders.Lay Summary: Sleep is essential because it allows the body to repair and maintain itself. But time spent sleeping is time that cannot be spent doing other things. People differ in how much they prioritize immediate rewards, including sociosexual opportunities, versus long-term goals. In this research, we show that individual differences in sleep behaviors, and attitudes toward sleep, correspond with psychological and behavioral differences reflecting such differing priorities. Orientation toward sleep can thus be understood as part of the overall lifetime strategies that people pursue.

Migration gives sleepless nights to the birds: a study on a Palaearctic–Indian migrant, Emberiza bruniceps

Migration is a seasonal phenomenon, wherein the birds swap between their breeding and overwintering grounds to avoid harsh climatic conditions and maximally utilize the geographical resources available. The annual cycle of a migratory bird broadly comprises non-breeding and breeding phases. The non-breeding phase corresponds to non-migratory life history state (LHS), whereas the breeding phase can be bifurcated into migratory (spring/autumn migration) and reproductive stages. Since most of the migratory birds are nocturnal migrants, this results either in shift or compromised sleep in these organisms for the sake of their reproduction and survival. Thus, an obvious question arises regarding the prevalence and distribution of sleep in these night migrants. Therefore, the present study focuses on the life history state-dependent as well as daily (with reference to night) differences in sleep behavior with special mention of different sleep postures in a migratory bunting, Emberiza bruniceps. For this purpose, male redheaded buntings were procured from the wild, and after acclimation in laboratory condition, were subjected to short (8L:16D) and long (13L:11D) photoperiodic schedules. Short photoperiod corresponds to non-migratory, whereas long photoperiod leads to pre-migratory and migratory LHSs. The results reveal that sleep behavior varied with different life history states of the bird. Non-migratory and pre-migratory states were dominated by front and back sleep postures, whereas migratory phase was dominated by active wakefulness. Not only life history state, even the night itself showed gradation in occurrence of different sleep behaviors. As the study was conducted in different phases of night, phasic distribution of different sleep behaviors was also observed. Thus, the bird under study, redheaded bunting, clearly demonstrated life history state, as well as daily differences in distribution of different sleep behaviors.

Children's Sleep Habits Questionnaire in Two Subpopulations from Cape Verde and Mozambique: Exploratory and Regression Analysis.

Children's sleep habits are profoundly affected by socio-economic, cultural, and environmental factors. We aim to describe the sleep habits of pediatric sub-populations from Cape Verde and Mozambique using the Children's Sleep Habits Questionnaire, and to ascertain the determinants of the questionnaire's score. We conducted cross-sectional surveys in surveillance appointments in Cape Verde and in a school in Maputo (Mozambique). The Cape Verde sample included 206 children (mean age: 6.5) and the Mozambique sample 454 children (mean age: 8). The Portuguese version of the Children's Sleep Habits Questionnaire was used to evaluate the children's sleep habits. The distributions of the questionnaire's scores across different levels of the demographic variables were compared using the Mann-Whitney and the Kruskal-Wallis tests. We used regression models to quantify the relationship between the demographic variables and the questionnaire's scores. Cape Verde sample: Questionnaire median score: 50 (range 36 - 81). Prevalence of sleep problems: 29.9% (cut-off = 56). Prevalence of parent-reported sleep problems: 22.8%. Co-sleeping: 63%. Bedtime television: 30%. Daytime nap: 63%. Questionnaire scores are associated with the mother's educational level, the children's age group, and with the frequency of daytime napping. Mozambique Sample: Median Questionnaire score: 48 (range 35 - 77). Prevalence of sleep problems: 28.4% (cut-off: 52). Percentage of parent-reported sleep problems: 6.9%. Co-sleeping: 29%. Bedtime television: 33%. Daytime nap: 23%. Questionnaire scores are associated with the mother's nationality, the father educational level, and with the frequency of bedtime television. Parents tend to overestimate the quality of their children's sleep. The prevalence of sleep disturbances and the cut-off values are higher than observed in previous studies, which may be due to the existence of different standards and cultural expectations across populations. Bedtime television, typically associated with more disturbed sleep, is frequent in both samples. Co-sleeping and daytime napping are frequent in the Cape Verde sample; wetting the bed is common and more prevalent than in previous studies. Bed-sharing increases the parents' awareness of their children's sleep quality, contributing to the high prevalence of parent-reported sleep problems. Parent-reported sleep problems underestimate the Children's Sleep Habits Questionnaire results. This is not necessarily indicative of more disturbed sleep and might reflect differences in sleep behavior, childcare practice, and cognitions and attitudes towards the concept of 'normal' sleep.

Sleep-related behaviors in zoo-housed giraffes (Giraffa camelopardalis reticulata): Basic characteristics and effects of season and parturition.

Despite increasing interest in the behavior of zoo animals, studies of nocturnal behavior of zoo animals are limited. In this study, we investigated the relationship between parturition, season, and the sleep-related behaviors in captive reticulated giraffes to better understand the nocturnal life in giraffes. The subjects were two adult reticulated giraffes living in Kyoto City Zoo, Japan. Observations were made via an infrared camera that was mounted in the indoor enclosure between June 2007 and August 2009. We analyzed video clips that were recorded between 16:30 and 09:00 the next morning, over a total of 199 days. Sleep-related behaviors were classified into two categories based on the posture of the giraffes; recumbent posture and paradoxical sleep. We also recorded the laterality of recumbent posture, which was coded based on the direction of the legs against the torso (right or left). Seasonal differences in sleep behaviors between summer and winter were observed in both individuals. They tended to start to lie down earlier in the winter than in the summer. Parturition also affected the behaviors as both individuals decreased the behaviors before and after the parturition of the female. Additionally, the female lay on her left side less frequently than her right when resuming a recumbent posture in the pre-parturition period, while such laterality was not observed in the baseline and post-parturition period. These results suggested that season and parturition are important factors for determining the sleep-related behaviors in giraffes. Further studies are needed to understand how these changes in sleep affect other welfare parameters.

A survey on social jetlag in Japan: a nationwide, cross-sectional internet survey

Misalignment between an individual’s circadian phase and his/her environment due to social imposition is called social jetlag (SJL). SJL has emerged as a public health concern, as it contributes to an unhealthy lifestyle and adverse health outcomes. This study aimed to elucidate the percentage of SJL in a large Japanese population using the Japanese version of the Munich ChronoType Questionnaire (MCTQ). A total of 10,000 participants responded to a web-based cross-sectional survey, and the final sample comprised 3708 participants (60.1% male; average age 45.1 [SD 13.4] years). SJL was measured by subtracting each participant’s midpoint of sleep on workdays from their midpoint of sleep on free days. The average [SD] absolute SJL (SJLabs) value was 0.91 [0.89] hours, and the percentage of participants with SLJabs of more than 1 h was 40.1%. Our data also showed that SJLabs becomes progressively smaller with advancing age. A considerable number of participants of our Japanese population showed differences in sleep behavior between workdays and free days. Young people in particular commonly oversleep on free days to compensate for the sleep debt accumulated over the workweek because of their late chronotype.

Sexual dimorphism in the physiological response of the Apoe −/− atherosclerosis model to sleep fragmentation

Abstract Sleep fragmentation (SF) is tightly correlated with the development of chronic low grade inflammatory diseases such as, type 2 diabetes and atherosclerosis; however, the exact relationship between SF and atherogenesis is unknown. Little evidence exists regarding the origin of sex differences in sleep behavior. While the role of gender has been studied in atherosclerosis, the impact of gender in SF-associated atherogenesis is not known. Recently, we have shown that high fat diet (HFD) fed male Apolipoprotein E-deficient (Apoe−/−)mice on SF unexpectedly experienced premature death, with 80% of males not surviving past week 2 of SF, while 80% of females survived past week 8 under the same conditions. To investigate the gender effects, male and female Apoe−/− mice were fed a HFD and SF for 10 days. Following HFD and SF, male mice, but not female Apoe−/− mice had enlarged hearts and lymph nodes, as well as peritoneal bleeding. Further, SF resulted in a significantly higher amount of circulating LPS and alterations in the immune composition of bone marrow (BM), blood, and lymph nodes (LN) in male HFD fed Apoe−/− mice vs SF female Apoe−/− mice. We detected a significant decrease in myeloid cells in the BM and blood, as well as a decrease in the percentage of T and B cells in the LN of HFD fed-SF males’ vs diet matched SF females. Interestingly, when male Apoe−/− mice were administered 17b-estradiol orally, in supplement with HFD feeding and SF, they survived past the 14 day death window. Altogether, SF alters the immune response in male atherosclerotic Apoe−/− mice resulting in early death. Our data suggests that the hormonal landscape in female Apoe−/− mice protects against SF-induced premature death via estrogen-dependent mechanisms.

Sleep behaviors in children with different frequencies of parental-reported sleep bruxism

ObjectiveKnowledge on the relationship between sleep bruxism (SB) and sleep behaviors in children is still fragmental, especially when socioeconomic factors are concerned. To assess sleep behaviors in children with different frequencies of proxy-reported SB. MethodsParents of 1475 Colombian children, aged 9.8±1.6years, belonging to 3 different social layers, filled out a questionnaire on their childreńs sleep (Childreńs Sleep Habits Questionnaire [CSHQ]). Differences in sleep behaviors were assessed for the total sample and the three socioeconomic layers, using one-way ANOVA and Bonferroni post-hoc tests or Kruskal-Wallis and Dunn’s post-hoc tests, based on the normality of outcome variables. ResultsMost sleep patterns and daytime sleepiness were similar for children with different frequencies of proxy-reported SB, without differences among socioeconomic layers, whilst sleep disorders and parasomnias increased with the frequency of proxy-reported SB, independently on the socioeconomic layer (Bonferroni post-hoc<0.001). The association between sleep-related habits and the frequency of proxy-reported SB was different for each socioeconomic layer. ConclusionAmong the various sleep behaviors under investigation, some sleep disorders and parasomnias seem to be associated with parental-reported SB in children. The influence of socioeconomic conditions on sleep behaviors seems not relevant. Based on these results, more specific studies on the association between different sleep behaviors are needed. Clinical significanceSleep behaviors, sociodemographic and socioeconomic features are correlated with SB in adults. However, in children, good evidence about this topic is lacking. This article give information to help clinicians evaluating sleep behaviors, sociodemographic and socioeconomic characteristics, when assessing sleep bruxism, based on evidence.

Sibling sleep—What can it tell us about parental sleep reports in the context of autism?

Sleep problems are common in families raising children with Autism Spectrum Disorder (ASD). Clinicians often depend on parent reports of child sleep but minimal research exists to address the accuracy or biases in these reports. To isolate parent-report accuracy (from differences in sleep behaviors), the sleep of younger siblings were assessed within a two-group design. The present study compared parent diary reports of infant sibling sleep to videosomnography and actigraphy. In the high-risk group, families had at least one child with ASD and a younger sibling (n = 33). The low-risk comparison group had no family history of ASD (n = 42). We confirmed comparable sleep behaviors between the groups and used paired t tests, two-one-sided-tests (TOST), and Bland-Altman plots to assess parent report accuracy. The parameters of sleep onset, nighttime sleep duration, awakenings, morning rise time, and daytime sleep duration were evaluated. Diary and videosomnography estimates were comparable for nighttime sleep duration, morning rise time, and awakenings for both groups. Diary and actigraph estimates were less comparable for both groups. Daytime sleep duration estimates had the largest discrepancy with both groups reporting (on average) 40 additional minutes of sleep when compared to actigraphy estimates. In the present study, families raising children with ASD were just as accurate as other families when reporting infant sleep behaviors. Our findings have direct clinical implications and support the use of parent nighttime sleep reports.

Genetic Correlates of Individual Differences in Sleep Behavior of Free-Living Great Tits (Parus major).

Within populations, free-living birds display considerable variation in observable sleep behaviors, reflecting dynamic interactions between individuals and their environment. Genes are expected to contribute to repeatable between-individual differences in sleep behaviors, which may be associated with individual fitness. We identified and genotyped polymorphisms in nine candidate genes for sleep, and measured five repeatable sleep behaviors in free-living great tits (Parus major), partly replicating a previous study in blue tits (Cyanistes caeruleus). Microsatellites in the CLOCK and NPAS2 clock genes exhibited an association with sleep duration relative to night length, and morning latency to exit the nest box, respectively. Furthermore, microsatellites in the NPSR1 and PCSK2 genes associated with relative sleep duration and proportion of time spent awake at night, respectively. Given the detection rate of associations in the same models run with random markers instead of candidate genes, we expected two associations to arise by chance. The detection of four associations between candidate genes and sleep, however, suggests that clock genes, a clock-related gene, or a gene involved in the melanocortin system, could play key roles in maintaining phenotypic variation in sleep behavior in avian populations. Knowledge of the genetic architecture underlying sleep behavior in the wild is important because it will enable ecologists to assess the evolution of sleep in response to selection.

Exploring Sex and Gender Differences in Sleep Health: A Society for Women's Health Research Report

Previous attempts have been made to address sleep disorders in women; however, significant knowledge gaps in research and a lack of awareness among the research community continue to exist. There is a great need for scientists and clinicians to consider sex and gender differences in their sleep research to account for the unique biology of women. To understand the role of sex differences in sleep and the state of women's sleep health research, the Society for Women's Health Research convened an interdisciplinary expert panel of well-established sleep researchers and clinicians for a roundtable meeting. Focused discussions on basic and clinical research along with a focus on specific challenges facing women with sleep-related problems and effective therapies led to the identification of knowledge gaps and the development of research-related recommendations. Additionally, sex differences in sleep disorders were noted and discussed in the context of underlying hormonal differences. Differences in sleep behavior and sleep disorders may not only be driven by biological factors but also by gender differences in the way women and men report symptoms. Progress has been made in identifying sex and gender differences in many areas of sleep, but major research gaps in the areas of epidemiology, sleep regulation, sleep quality, diagnosis, and treatment need to be addressed. Identifying the underlying nature of sex and gender differences in sleep research has potential to accelerate improved care for both men and women facilitating better diagnosis, treatment, and ultimately prevention of sleep disorders and related comorbid conditions.