Delayed sleep timing is associated with low levels of free-living physical activity in normal sleeping adults.
ABSTRACT: We and others have reported that experimentally induced short sleep does not affect resting metabolic rate and leads to increased laboratory-measured 24-h energy expenditure. Here, we aimed to determine if sleep timing and/or quality are related to physical activity (PA) levels.Measures of PA via waist actigraphy, sleep diary, and sleep quality questionnaires were collected over a 7-18-day period in 22 adults (mean age?±?standard deviation (SD): 35.8?±?4.6 years, and mean body mass index?±?SD: 23.8?±?1.1?kg/m(2)) who were on their habitual sleep-wake and activity schedules.During the recording period, mean (±SD) bedtime and wake times were 00:17?±?1:07?h (range: 22:02-02:07?h) and 08:20?±?1:14?h (range: 06:30-10:11?h), respectively. After controlling for sleep duration, later bedtime, wake time, and midpoint of sleep were associated with less time spent in moderate-to-vigorous PA (p?=?0.013, p?=?0.005, and p?=?0.007, respectively), and increased time in sedentary PA (p?=?0.016, p?=?0.013, and p?=?0.013, respectively).Current results suggest that even relatively small alterations in sleep timing may influence PA. However, causality cannot be inferred from this cross-sectional study. Clinical intervention studies should be conducted to assess the relationship between sleep timing and energy balance.
Project description:Variable daily sleep (ie, higher intraindividual variability; IIV) is associated with negative health consequences, but potential physiological mechanisms are poorly understood. This study examined how the IIV of sleep timing, duration, and quality is associated with physiological dysregulation, with diurnal cortisol trajectories as a proximal outcome and allostatic load (AL) as a multisystem distal outcome.Participants are 436 adults (Mage ± standard deviation = 54.1 ± 11.7, 60.3% women) from the Midlife in the United States study. Sleep was objectively assessed using 7-day actigraphy. Diurnal cortisol was measured via saliva samples (four/day for 4 consecutive days). AL was measured using 23 biomarkers from seven systems (inflammatory, hypothalamic-pituitary-adrenal axis, metabolic glucose and lipid, cardiovascular, parasympathetic, sympathetic) using a validated bifactor model. Linear and quadratic effects of sleep IIV were estimated using a validated Bayesian model.Controlling for covariates, more variable sleep timing (p = .04 for risetime, p = .097 for bedtime) and total sleep time (TST; p = .02), but not mean sleep variables, were associated with flatter cortisol diurnal slope. More variable sleep onset latency and wake after sleep onset, later average bedtime, and shorter TST were associated with higher AL adjusting for age and sex (p-values < .05); after controlling for all covariates, however, only later mean bedtime remained significantly associated with higher AL (p = .04).In a community sample of adults, more variable sleep patterns were associated with blunted diurnal cortisol trajectories but not with higher multisystem physiological dysregulation. The associations between sleep IIV and overall health are likely complex, including multiple biopsychosocial determinants and require further investigation.
Project description:Circadian misalignment, as seen in shift workers, can disrupt metabolic processes. Associations between sleep timing in nonshift workers and metabolic health are unknown. We examined sleep timing and indices of metabolic health in a community sample of midlife women.Caucasian (n = 161), African American (n = 121) and Chinese (n = 56) non-shift-working women aged 48-58 y who were not taking insulin-related medications, participated in the Study of Women's Health Across the Nation (SWAN) Sleep Study and were subsequently examined approximately 5.39 (standard deviation = 0.71) y later. Daily diary-reported bedtimes were used to calculate four measures of sleep timing: mean bedtime, bedtime variability, bedtime delay and bedtime advance. Body mass index (BMI) and insulin resistance (homeostatic model assessment-insulin resistance, HOMA-IR) were measured at two time points. Linear regressions evaluated whether sleep timing was associated with BMI and HOMA-IR cross-sectionally and prospectively.In cross-sectional models, greater variability in bedtime and greater bedtime delay were associated with higher HOMA-IR (? = 0.128; P = 0.007, and ? = 0.110; P = 0.013, respectively) and greater bedtime advance was associated with higher BMI (? = 0.095; P = 0.047). Prospectively, greater bedtime delay predicted increased HOMA-IR at Time 2 (? = 0.152; P = 0.003). Results were partially explained by shifted sleep timing on weekends.Frequent shifts in sleep timing may be related to metabolic health among non-shift working midlife women.A commentary on this article appears in this issue on page 269.
Project description:Sleep is modulated by several factors, including sex, age, and chronotype. It has been hypothesised that contemporary urban populations are under pressure towards shorter sleep duration and poorer sleep quality. Baependi is a small town in Brazil that provides a window of opportunity to study the influence of sleep patterns in a highly admixed rural population with a conservative lifestyle. We evaluated sleep characteristics, excessive daytime sleepiness, and chronotype using the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Morningness-Eveningness Questionnaire questionnaires, respectively. The sample consisted of 1,334 subjects from the Baependi Heart study (41.5% male; age: 46.5?±?16.2 y, range: 18-89 years). Average self-reported sleep duration was 07:07?±?01:31 (bedtime 22:32?±?01:27, wake up time: 06:17?±?01:25 hh:min), sleep quality score was 4.9?+?3.2, chronotype was 63.6?±?10.8 and daytime sleepiness was 7.4?±?4.8. Despite a shift towards morningness in the population, chronotype remained associated with reported actual sleep timing. Age and sex modulated the ontogeny of sleep and chronotype, increasing age was associated with earlier sleep time and shorter sleep duration. Women slept longer and later, and reported poorer sleep quality than men (p?<?0.0001). This study provides indirect evidence in support of the hypothesis that sleep timing was earlier prior to full urbanisation.
Project description:BACKGROUND: In our previous studies, we found that the Ile394Thr SNP in the melanopsin gene (OPN4) was functionally associated with the pupillary light reflex. This indicates the possibility that OPN4*Ile394Thr is associated with other non-image forming responses. The aim of this study was therefore to determine whether OPN4*Ile394Thr is associated with sleep/wake timing. METHODS: A total of 348 healthy Japanese university students participated in this study. Scalp hair was used to genotype the Ile394Thr SNP of OPN4. Sleep habits, including bedtime, wake time and sleep duration, were assessed separately for weekdays and weekends. A total of 328 samples, including 223 samples with TT genotype, 91 with TC genotype and 14 with CC genotype, were used for statistical analysis. No significant difference in age or male/female distribution was found among the three genotype groups. RESULTS: There was no significant difference in circadian preference among the genotype groups. During weekdays, bedtime, wake time and midpoint of sleep for CC subjects were significantly later than those for TT and TC subjects. However, there was no difference between TT and TC subjects in any of their sleep habits. During weekends, bedtime of CC subjects was significantly later than those of TT and TC subjects, and the midpoint of sleep of CC subjects was significantly later than that of TC subjects. CONCLUSIONS: Our findings demonstrated that OPN4*Ile394Thr is associated with sleep/wake timing. We also found that the sleep/wake timing of subjects with the CC genotype was later than that of subjects with the TT or TC genotype.
Project description:The current study examined within-family relations between mothers', fathers', and children's objectively assessed sleep. Participants were 163 children (Mage = 10.45 years; SD = 0.62) and their parents. For 7 nights, families wore actigraphs to assess sleep duration (minutes), quality (efficiency, long wake episode, total wake minutes), and schedule (wake time). A sleep log assessed bedtime. Multilevel models indicated that children's sleep minutes, sleep efficiency, wake minutes, and wake time were associated with fluctuations in their mothers', but not fathers', sleep that same night. The duration and quality of mothers' sleep was associated with both fathers' and children's sleep that night, whereas fathers' sleep was positively associated with only mothers' sleep. Findings highlight the importance of examining sleep within a family context.
Project description:BACKGROUND & AIMS:While environmental factors are presumed to be primary drivers of food timing, preliminary evidence suggests that genetics may be an additional determinant. The aim was to explore the relative contribution of genetics and environmental factors to variation in the timing of food intake in a Spanish twin population. Because chronotype, bedtime and wake time are related to food timing, covariance with food timing was further assessed. METHODS:In this observational study, 53 pairs of adult (mean (SD) = 52 (6.03) years) female twins (28 monozygotic; 25 dizygotic) were recruited from the Murcia Twin Register. Zygosity was determined by DNA-testing. Timing of the three main meals of the day was assessed via 7-day dietary records, and the midpoint of food intake was computed by calculating the midpoint between breakfast and dinner times. Chronotype, bedtime and wake time were self-reported. Heritability of food timing and related traits were estimated by comparing monozygotic and dizygotic twin correlations and fitting genetic structural equation models to measured variables. RESULTS:We observed genetic influences for food timing, with highest heritability for the midpoint of food intake (64%) in an overweight/obese population (BMI = 26.01 ± 3.77). Genetic factors contributed to a higher degree to the timing of breakfast (56%) than the timing of lunch (38%) or dinner (n.s.). Similarly, heritability estimates were larger in related behavioral traits earlier on in the day (i.e. wake time, (55%)), than those later on in the day (i.e. bedtime, (38%)). Bivariate analyses revealed a significant genetic overlap between food timing and bedtime and chronotype (rG between 0.78 and 0.91). CONCLUSIONS:Genetic influences appear to account for a significant proportion of the variability in food timing, particularly breakfast. Thus, interventions related to food timing may be more effective when targeting afternoon/evening traits, such as lunch or dinner times. Furthermore, our data suggest shared genetic architecture underlying food timing and phenotypically related traits. CLINICAL TRIAL:NCT03059576. https://clinicaltrials.gov/ct2/show/NCT03059576.
Project description:The use of light-emitting electronic devices before bedtime may contribute to or exacerbate sleep problems. Exposure to blue-wavelength light in particular from these devices may affect sleep by suppressing melatonin and causing neurophysiologic arousal. We aimed to determine if wearing amber-tinted blue light-blocking lenses before bedtime improves sleep in individuals with insomnia. Fourteen individuals (n = 8 females; age ± SD 46.6 ± 11.5 y) with insomnia symptoms wore blue light-blocking amber lenses or clear placebo lenses in lightweight wraparound frames for 2 h immediately preceding bedtime for 7 consecutive nights in a randomized crossover trial (4-wk washout). Ambulatory sleep measures included the Pittsburgh Insomnia Rating Scale (PIRS) completed at the end of each intervention period, and daily post-sleep questionnaire and wrist-actigraphy. PIRS total scores, and Quality of Life, Distress, and Sleep Parameter subscales, were improved in amber vs. clear lenses condition (p-values <0.05). Reported wake-time was significantly delayed, and mean subjective total sleep time (TST), overall quality, and soundness of sleep were significantly higher (p-values <0.05) in amber vs. clear lenses condition over the 7-d intervention period. Actigraphic measures of TST only were significantly higher in amber vs. clear lenses condition (p = 0.035). Wearing amber vs. clear lenses for 2-h preceding bedtime for 1 week improved sleep in individuals with insomnia symptoms. These findings have health relevance given the broad use of light-emitting devices before bedtime and prevalence of insomnia. Amber lenses represent a safe, affordable, and easily implemented therapeutic intervention for insomnia symptoms. CLINICAL TRIALS REGISTRATION:ClinicalTrials.gov Identifier: NCT02698800.
Project description:Background: Understanding variation in physical activity (PA) and sleep is necessary to develop novel intervention strategies targeting adolescents' health behaviors. We examined the extent to which PA and sleep vary by aspects of the physical environment. Participants: We performed a cross-sectional analysis of 669 adolescents in the Project Viva cohort. Methods: We estimated total PA, sleep duration, sleep efficiency, and sleep midpoint timing from wrist accelerometers. We used multivariable linear regression models and generalized estimated equations to assess associations of PA and sleep with season and daily weather conditions obtained from the National Oceanic and Atmospheric Administration archive. Results: Mean age was 12.9 (SD 0.6) years; 51% were female and 68% were white. Mean sleep duration was 466 (SD 42) min per night and total PA was 1,652 (SD 431) counts per min per day. Sleep midpoint time was 41 (95% CI: 27 to 54) min later in summer, 28 (95% CI: -41 to -14) min earlier in spring, and 29 (95% CI: -43 to -15) min earlier in autumn compared to winter. Higher temperature and longer day length both were associated with small reductions of nightly sleep duration. Adolescents were less physically active during winter and on rainy and short sunlight days. There was an inverse U-shaped relationship between PA and mean temperature. Conclusions: Season was associated with large changes in sleep timing, and smaller changes in other sleep and PA measurements. Given the importance of sleep and circadian alignment, future health behavioral interventions may benefit by targeting "season-specific" interventions.
Project description:The aim of this study was to identify socio-demographic and home environmental predictors of shorter sleep in early childhood, and to examine whether effects were mediated by the timing of bedtime or wake time.Participants were from Gemini, a British birth cohort of twins, and included 1702 children; one randomly selected from each twin pair. Parents reported night-time sleep duration at an average age of 15.8 months (range 14-27 months) using a modified version of the Brief Infant Sleep Questionnaire. Multiple logistic regression models were used to identify predictors of shorter sleep for this study.Using a cut-off of <11 h a night, shorter sleep was reported in 14.1% of children. Lower maternal education, non-white ethnic background, being male, low birth weight, living in a home with >1 older child and watching >1 h of TV in the evening were independently associated with shorter sleep. Mediation analyses showed that associations between education, ethnicity, evening TV viewing and sleep were driven predominantly by later bedtimes, while sex differences were driven predominantly by earlier wake times in boys.In this sample, multiple environmental factors were associated with shorter sleep in young children, with several operating predominantly through later bedtime. An emphasis on the importance of an early and consistent bedtime could help promote healthy sleep and reduce inequalities in child health.
Project description:Study Objectives:Having a regular, age-appropriate bedtime and sufficient sleep from early childhood may be important for healthy weight in adolescence. This study aimed to (1) identify heterogeneous groups of children by bedtime and sleep routines and (2) test longitudinal associations of childhood bedtime and sleep routine groups with adolescent body mass index (BMI). Methods:We analyzed longitudinal data from the Fragile Families and Child Wellbeing Study, a national birth cohort from 20 US cities (N = 2196). Childhood bedtime and sleep routines were assessed by mothers' reports of their children's presence and timing of bedtimes, adherence to bedtimes, and habitual sleep duration at ages 5 and 9. At age 15, these adolescents reported their height and weight, which were used to calculate BMI z-score. Results:Latent Class Analysis revealed four groups of childhood bedtime and sleep routines: No Bedtime Routine Age 5 (Group 1), No Bedtime Routine Age 9 (Group 2), Borderline Bedtimes Ages 5 and 9 (Group 3), and Age-Appropriate Bedtime and Sleep Routines Ages 5 and 9 (Group 4, reference). Compared with adolescents in the reference group, those in the No Bedtime Routine Age 9 (Group 2) had +0.38 SD greater BMI (95% CI = [0.13 to 0.63]), above the level for overweight (1.02 SD BMI/85th percentile). Associations persisted after adjusting for age 3 BMI and sociodemographic characteristics. Conclusions:Results demonstrate heterogeneity in childhood bedtime routine groups and their associations with adolescent BMI. Future studies should focus on whether childhood sleep behavior interventions promote healthier sleep and weight in later life course stages.