scholarly journals Too Jittery to Sleep? Temporal Associations of Actigraphic Sleep and Caffeine in Adolescents

Nutrients ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 31
Author(s):  
Gina Marie Mathew ◽  
David A. Reichenberger ◽  
Lindsay Master ◽  
Orfeu M. Buxton ◽  
Anne-Marie Chang ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Sleep Onset ◽  
Poor Sleep ◽  
Caffeine Consumption ◽  
Sleep Health ◽  
Subjective Sleep Quality ◽  
Beverage Consumption ◽  
Wake Time ◽  
Regularity Index ◽  
Social Jetlag

Caffeine consumption has been linked to poor sleep health in adolescents, but it is unknown whether poor sleep predicts caffeine consumption, and/or whether caffeine consumption predicts poor sleep, particularly when sleep is measured objectively. Data were collected from a micro-longitudinal sub-study of the age 15 wave of the Fragile Families and Child Wellbeing Study (n = 589). Adolescents wore an actigraphy device and completed daily surveys for ~1 week. Daily surveys assessed subjective sleep quality and caffeinated beverage consumption (0 = no caffeine, 1 = any caffeine). Separate mixed models assessed whether actigraphy-measured sleep duration, timing, maintenance efficiency, and subjective quality predicted next-day caffeinated beverage consumption within and between adolescents. Variability (standard deviation) of sleep duration and timing, sleep regularity index, and social jetlag were tested as additional between-person predictors. Lagged models tested whether daily caffeinated beverage consumption predicted sleep that night (n = 458). Adolescents with more variable sleep duration and midpoint had higher average odds of consuming caffeinated beverages compared to others. After adolescents consumed ≥1 caffeinated beverage, they had later sleep onset that night and wake time the next morning than usual versus when they did not consume caffeine. Curbing caffeinated beverage consumption may aid in the maintenance of regular sleep schedules and advance sleep timing in adolescents.

Aggression in Young Adults — A Matter of Short Sleep and Social Jetlag?

2013 ◽  
Vol 113 (3) ◽  
pp. 754-765 ◽  
Author(s):  
Christoph Randler ◽  
Christian Vollmer
Keyword(s):  
Sleep Duration ◽  
Physical Aggression ◽  
Sleep Onset ◽  
Onset Time ◽  
Verbal Aggression ◽  
Wake Time ◽  
Adult Men ◽  
Composite Scale ◽  
Social Jetlag ◽  
Aggression Questionnaire

Evening orientation and sleep duration have been linked with aggression and problematic behaviors, but no study has used an explicit aggression questionnaire. The present study used the Buss-Perry Aggression Questionnaire based on physical aggression, verbal aggression, anger, and hostility, as well as questionnaires on the timing of sleep and sleep duration to assess this relationship in young adult men. The Composite Scale of Morningness was used to assess circadian preference; sleep-wake variables (wake time and sleep onset time on weekdays and on weekend days) were used to calculate midpoint of sleep, social jetlag, and sleep duration. Results indicated that sleep duration correlated negatively with verbal aggression, physical aggression, and anger. Short sleepers were more aggressive. Using multivariate analysis of variance, shorter sleep duration was a significant predictor of verbal aggression and anger. Concerning physical aggression, social jetlag also contributed to the model. Morningness-eveningness was associated with the hostility scale with eveningness related to higher hostility. Men scored higher than women in physical and verbal aggression.

181 Sleep health concordance among socioeconomically disadvantaged caregiver-child dyads

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A73-A74
Author(s):  
Lauren Covington ◽  
Benjamin Brewer ◽  
Rachel Blair ◽  
Elissa Hoopes ◽  
Jean-Philippe Laurenceau ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Family System ◽  
Sleep Onset ◽  
Correlation Coefficients ◽  
Sleep Efficiency ◽  
Sleep Health ◽  
Individual Level ◽  
Wake Time ◽  
Modifiable Factors ◽  
Objectively Measured

Abstract Introduction Child and caregiver sleep typically occurs within a family system. Disadvantaged families experience disproportionately poorer sleep health than more advantaged families. The extent to which objectively measured sleep health metrics (e.g. duration, timing, regularity, efficiency) are concordant within disadvantaged family systems, such as caregiver-child dyads, is not clear. To address this gap, this study aimed to: (1) characterize sleep health metrics, and (2) identify levels of sleep health concordance among disadvantaged caregiver-child dyads. Methods 23 disadvantaged dyads were recruited from Philadelphia and Delaware communities. Dyads were eligible if the child was between 6-14 years, slept in the same house as the caregiver at least four nights/week, had no diagnosis of a sleep disorder or use of sleep medication, and qualified for federally funded food assistance programs (e.g., food stamps, WIC or SNAP benefits). Sleep health of the dyads was objectively measured for 7-14 days. Sleep metrics used to characterize the sample were: nighttime sleep duration (hours), time-to-bed, sleep regularity (standard deviation of sleep duration), sleep midpoint (halfway point between sleep onset and wake time) and efficiency (percentage of time spent asleep versus awake). Concordance in sleep health metrics within dyads was calculated using Pearson’s correlation coefficients of the average sleep metrics over the monitoring period. Results Children (46.2% female) slept, on average, 7.96 hours per night, with 1.25 hours of nightly sleep variability, bedtime of 10:47 PM, sleep midpoint of 2:56 AM, and sleep efficiency of 83.55%. Caregivers (mean age = 40.5 years, 85.0% female) slept, on average, 6.92 hours per night, with 1.22 hours of nightly sleep variability, bedtime of 11:24 PM, sleep midpoint of 3:04 AM, and sleep efficiency of 76.29%. Bedtime (r = 0.19, p < 0.001), sleep midpoint (r = 0.39, p < 0.001), and sleep efficiency (r = 0.24, p < 0.001) were significantly concordant among caregiver-child dyads. Conclusion Given their level of concordance, bedtime, sleep midpoint and efficiency are modifiable factors of sleep health in disadvantaged dyads that could be targeted using family versus individual level interventions. Support (if any) University of Delaware General University Research Grant and School of Nursing SEED funding.

scholarly journals Night-to-Night Associations Between Light Exposure and Sleep Health

2021 ◽  
Author(s):  
Michael Mead ◽  
Kathryn Reid ◽  
Kristen Knutson
Keyword(s):  
Sleep Duration ◽  
Light Exposure ◽  
Poor Sleep ◽  
Sleep Health ◽  
Cross Sectional ◽  
Wake Time ◽  
Light Levels ◽  
Fragmentation Index ◽  
Multi Level ◽  
Offset Time

Previous research has demonstrated that exposure to light preceding and during sleep is associated with poor sleep, but most research to date has utilized either experimental or cross-sectional designs. The current study expands upon prior studies by using a microlongitudinal design that examines the night-to-night associations between light and sleep health in a diverse sample of adults (pre-registered at osf.io/k5zgv). U.S. adults aged 18 to 87 from two parent studies (N= 124) wore an actiwatch for up to 10 nights. Light variables estimated from actigraphy include both average exposure and time above light threshold of 10 (TALT10) and 40 (TALT40) lux both during sleep and for the 1-hour preceding sleep. Actigraphy-based sleep variables included sleep offset, duration, percentage, and fragmentation index. Higher average light exposure during sleep was associated with a later sleep offset time, lower sleep percentage, and higher fragmentation index (all p <.01). More minutes of TALT10 during sleep was associated with later sleep timing, lower sleep percentage, and higher fragmentation index (all p < .01) and greater TALT40 during sleep was associated with lower sleep percentage. Light exposure was not related to sleep duration. In summary, greater light exposure during sleep was related to poorer sleep continuity and later wake time. The lack of association between light and sleep duration may be the result of compensating for sleep disruption by delaying wake time. Multi-level interventions to consistently reduce light levels during sleep should be considered.

scholarly journals Sleep Insufficiency, Sleep Health Problems and Performance in High School Students

2011 ◽  
Vol 5 ◽  
pp. CCRPM.S7955 ◽  
Author(s):  
Xue Ming ◽  
Rebecca Koransky ◽  
Victor Kang ◽  
Sarah Buchman ◽  
Christina E. Sarris ◽  
...  
Keyword(s):  
High School Students ◽  
Sleep Duration ◽  
School Performance ◽  
Sleep Onset ◽  
Health Problems ◽  
Poor Sleep ◽  
Sleep Health ◽  
Poor School Performance ◽  
School Start Times ◽  
Poor School

A survey on sleep schedule, sleep health, school performance and school start times was conducted in 1,941 adolescents. A high level of early and circadian-disadvantaged sleep/wake schedules during weekdays was observed. Shorter sleep duration on weekdays was reported, especially in upper classmen. Complaints of inadequate sleep and sleepiness during weekdays, alarm clock use, and napping were prevalent. Night awakening and prolonged sleep onset were common and associated with poor school performance. Students with a sleep length of less than 7 hours on both weekdays and weekends exhibited poorer performance, while those who made up this sleep loss on weekends did not. The total number of poor sleep factors in an individual also correlated with poor school performance. Earlier school start times were associated with a perception of poor sleep quality, shorter sleep duration and more sleep health problems. We conclude that sleep inadequacies and sleep health problems were prevalent in this population, especially in those who started school earlier in the morning, and that these poor sleep factors were associated with school performance.

scholarly journals PERSONALITY AND SELF-REPORTED AND ACTIGRAPHY-MEASURED SLEEP HEALTH IN ADULTHOOD

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S779-S779
Author(s):  
Nasreen A Sadeq ◽  
Nasreen A Sadeq ◽  
Soomi Lee ◽  
Alyssa Gamaldo ◽  
David M Almeida
Keyword(s):  
Personality Traits ◽  
Sleep Duration ◽  
Sleep Latency ◽  
Sleep Onset ◽  
The United States ◽  
Poor Sleep ◽  
Big Five Personality ◽  
Sleep Health ◽  
Linear Regressions ◽  
Insomnia Symptoms

Abstract Personality may be associated with sleep health, however, the majority of existing studies rely on self-reported measures of sleep (often focusing on sleep duration). The purpose of this study is to examine the associations between Big Five personality traits and self-reported and actigraphy measured sleep. This study included 3928 participants and a subsample of 441 participants from the Midlife in the United States study. Linear regressions were used to analyze the relationships between personality traits and sleep. Neuroticism was associated with more frequent actigraphy-measured waking after sleep onset, and several self-reported measures of sleep quality, including shorter sleep duration, longer sleep latency, and a greater number of insomnia symptoms. Agreeableness was associated with shorter actigraphy-measured sleep duration and more self-reported insomnia symptoms. Our findings support an association between Neuroticism and poor sleep, and suggest that Agreeableness may be associated with worse sleep health.

140 Short and Long Sleep Duration, Poor Sleep Quality, and Later Sleep are Associated with Lower Odds of Adolescents Eating Breakfast

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A58-A58
Author(s):  
Gina Mathew ◽  
David Reichenberger ◽  
Orfeu Buxton ◽  
Lauren Hale ◽  
Anne-Marie Chang
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Poor Sleep ◽  
Sleep Health ◽  
Subjective Sleep Quality ◽  
Breakfast Consumption ◽  
Lower Odds ◽  
Subjective Sleep ◽  
Sleep Timing ◽  
Eating Breakfast

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

scholarly journals The Influence of Sleep on Glycated Hemoglobin in Pregnancy With Gestational Diabetes

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A436-A437
Author(s):  
Cristina Sampaio Facanha ◽  
Veralice S De Bruin ◽  
Fernando Henrique A Lopes ◽  
Magno M P Faria ◽  
Paula S Machado ◽  
...  
Keyword(s):  
Gestational Diabetes ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Sleep Disturbances ◽  
Glycated Hemoglobin ◽  
Sleep Onset ◽  
Diabetic Patients ◽  
Poor Sleep ◽  
Wake Time ◽  
Sleep Log

Abstract Background: Sleep disturbances have been associated with poor glycemic control in differential clinical settings. Both short and long sleep duration, influence insulin resistance and blood glucose in diabetic patients. Pregnancy is an additional risk for reduced sleep quality and quantity, and the presence of hyperglycemia, as a complicating factor, has being increasingly frequent. Different measures of sleep evaluation, both objectively and subjectively, can provide additional information about the influence of sleep in metabolic control in Gestational Diabetes Mellitus (GDM). Objective: To investigate the influence of sleep quality and objective sleep measures on glycated hemoglobin (HBA1C) in patients with GDM. Methodology: This is a cross-sectional study examining patients with GDM from 2nd to 3rd trimester of pregnancy. Clinical data and behavior questionnaires were collected by a face-to-face interview. Self-Rated Sleep Quality was evaluated by Pittsburgh Sleep Quality Index- (PSQI). In order to improve the accuracy of the information, a 14-day sleep log was obtained, and objective sleep measurements were registered by actigraphic record (5 to 7 days). Results: Overall, GDM patients (N=311), aged from 20 to 46 y (33.1±5.6) were evaluated. Sleep duration ≤6 hours/night was found in 43.4%, and 63.9% reported poor sleep quality (PSQI>5). Sleep duration measured by actigraphy was correlated with sleep duration registered by sleep log (r=.45, p=.04), and with PSQI (r=-.33, p=.002). Sleep quality and sleep duration registered by either actigraphy or sleep log were not correlated with Hba1c. Amongst all, Hba1c varied from 4.3 to 7.0 mg/dL (5.9 ±.53). Sleep fragmentation, measured by the length of time patient spends awake after sleep onset (WASO) was correlated withHba1c level in patients with GDM (r=.41, p=0.04). Conclusion: Sleep duration obtained from the sleep log was a reliable measure correlating with objective sleep parameters registered by actigraphy and with sleep quality. In GDM patients, increased wake time after sleep onset was correlated with higher Hba1c.

534 Food Insecurity and Sleep Health by Race/Ethnicity and Age Group in the United States

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A211-A211
Author(s):  
Nyree Riley ◽  
Dana Alhasan ◽  
W Braxton Jackson ◽  
Chandra Jackson
Keyword(s):  
Food Security ◽  
Food Insecurity ◽  
Sleep Duration ◽  
Sleep Disturbances ◽  
The United States ◽  
Poor Sleep ◽  
High Food ◽  
Short Sleep Duration ◽  
Sleep Health ◽  
Falling Asleep

Abstract Introduction Food insecurity may influence sleep through poor mental health (e.g., depression) and immune system suppression. Although prior studies have found food insecurity to be associated with poor sleep, few studies have investigated the food security-sleep association among racially/ethnically diverse participants and with multiple sleep dimensions. Methods Using National Health Interview Survey data, we examined overall, age-, sex/gender-, and racial/ethnic-specific associations between food insecurity and sleep health. Food security was categorized as very low, low, marginal, and high. Sleep duration was categorized as very short (<6 hours), short (<7 hours), recommended (7–9 hours), and long (≥9 hours). Sleep disturbances included trouble falling and staying asleep, insomnia symptoms, waking up feeling unrested, and using sleep medication (all ≥3 days/times in the previous week). Adjusting for sociodemographic characteristics and other confounders, we used Poisson regression with robust variance to estimate prevalence ratios (PRs) and 95% confidence intervals (95% CI) for sleep dimensions by very low, low, and marginal vs. high food security. Results The 177,435 participants’ mean age was 47.2±0.1 years, 52.0% were women, 68.4% were Non-Hispanic (NH)-White. Among individuals reporting very low food security, 75.4% had an annual income of <$35,000 and 60.3% were ≥50 years old. After adjustment, very low vs. high food security was associated with a higher prevalence of very short (PR=2.61 [95%CI: 2.44–2.80]) and short (PR=1.66 [95% CI: 1.60–1.72]) sleep duration. Very low vs. high food security was associated with both trouble falling asleep (PR=2.21 [95% CI: 2.12–2.30]) and trouble staying asleep (PR=1.98 [95% CI: 1.91–2.06]). Very low vs. high food security was associated with higher prevalence of very short sleep duration among Asians (PR=3.64 [95% CI: 2.67–4.97]), Whites (PR=2.73 [95% CI: 2.50–2.99]), Blacks (PR=2.03 [95% CI: 1.80–2.31]), and Hispanic/Latinxs (PR=2.65 [95% CI: 2.30–3.07]). Conclusion Food insecurity was associated with poor sleep in a diverse sample of the US population. Support (if any):

142 Prenatal Sleep Quality and Infant Sleep: A Longitudinal Study

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A58-A59
Author(s):  
Rebecca Burdayron ◽  
Marie-Helene Pennestri ◽  
Elizabeth Keys ◽  
Lianne Tomfohr-Madsen ◽  
Gerald Giesbrecht
Keyword(s):  
Sleep Quality ◽  
Sleep Duration ◽  
Gestational Age ◽  
Sleep Onset ◽  
Depression Scale ◽  
Future Research ◽  
Poor Sleep ◽  
Infant Sleep ◽  
Maternal Sleep ◽  
Sleep Parameters

Abstract Introduction Poor sleep quality is common during pregnancy and can increase the risk of adverse obstetric and fetal outcomes. Existing research on the association between prenatal sleep and infant sleep is scarce and has focused on other aspects of prenatal sleep such as sleep duration, chronotype, and insomnia symptoms. To our knowledge, no studies have examined the association between prenatal sleep quality and infant sleep outcomes. Thus, this study aimed to investigate whether maternal sleep quality during pregnancy was prospectively associated with infant sleep dimensions, independent of relevant covariates. Methods Participants were a subset of 272 mother-infant dyads enrolled in an ongoing cohort study. Maternal prenatal sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI) in early to mid- (M gestational age = 15.12 ± 3.56 weeks) and late- (M gestational age = 32.44 ± 0.99 weeks) pregnancy. Mothers completed the Brief Infant Sleep Questionnaire (BISQ) at 3, 6, and 12 months postpartum. The following infant sleep parameters were assessed: sleep duration (day, night, 24-hour), number of night awakenings, and wake after sleep onset. Prenatal depressive symptoms were assessed with the Edinburgh Postnatal Depression Scale (EPDS) at both pregnancy time points. Other covariates included maternal age at enrollment, infant age, parity, and co-sleeping status. Results Generalized estimating equations (GEE) models revealed that poorer maternal sleep quality during early-to-mid pregnancy did not significantly predict infant sleep parameters after adjustment for covariates (p > .05). However, in late pregnancy, poorer maternal sleep quality significantly predicted shorter 24-hour sleep duration and longer wake after sleep onset, but not daytime sleep duration, nighttime sleep duration, and number of night awakenings (p < .05). Conclusion Study findings advance our understanding of the prospective link between maternal prenatal sleep quality and infant sleep. Results indicate that maternal sleep quality during late gestation may play a role in the development of infant sleep patterns. These findings have important implications for intervention efforts targeting maternal sleep quality during pregnancy. Future research should use objective measures of sleep, such as actigraphy, to better elucidate the effects of prenatal sleep quality on infant sleep outcomes. Support (if any) The Canadian Institutes of Health Research (CIHR)

scholarly journals Association of physical activity with sleep health: A systematic review

2019 ◽  
Vol 23 ◽  
pp. 1-26
Author(s):  
Andrea Wendt ◽  
Thaynã Ramos Flores ◽  
Inácio Crochemore Mohnsam Silva ◽  
Fernando César Wehrmeister
Keyword(s):  
Physical Activity ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Undergraduate Students ◽  
Data Extraction ◽  
Activity Measurement ◽  
Poor Sleep ◽  
Long Term Effects ◽  
Sleep Health ◽  
Cross Sectional

The aim of this study was to systematically examine the literature on physical activity and sleep in non-clinical and population-based settings. The inclusion criteria were original studies testing the association between physical activity (as exposure) and sleep (as outcome) in representative samples of the general population, workers, or undergraduate students. Sleep health included sleep duration, sleep quality and insomnia. Studies evaluating samples including only individuals with some disease or a health condition were excluded. A search was performed in the PubMed, Scopus, Lilacs, CINAHL, and SPORTdiscus databases in March 2018. Data extraction was performed using the following items: year, author, country, population, age group, sample size, study design, sleep measurement/definition, physical activity measurement/definition, adjustment and main results. A total of 57 studies were selected, which markedly used heterogeneous instruments to measure physical activity and sleep. The majority were conducted in high-income countries and with cross-sectional design. Physical activity was associated with lower odds of insomnia (observed in 10 of 17 studies), poor sleep quality (observed in 12 of 19 studies) and long sleep duration (observed in 7 of 11 studies). The results about short sleep or continuous sleep duration remain unclear. Physical activity seems to be associated with sleep quality and insomnia, especially among adult and elderly populations in which these outcomes are more usually measured. The short- and long-term effects of physical activity intensities and dose-response on sleep should be better evaluated.

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