How much does sleep vary from night-to-night? A quantitative summary of intraindividual variability in sleep by age, gender, and racial/ethnic identity across eight-pooled datasets

Methods for Characterization of Day-to-Day Intra-Individual Variation in 24-Hour Physical Behaviors

OCCUPATIONAL APPLICATIONSWe present methods to characterize individual day-to-day variation in physical behaviors, either by assessing variation in one behavior in isolation or multiple behaviors simultaneously. These methods could be used in future studies to evaluate the health implications of variation in occupational exposures. For example, the method presented for characterizing variation in a single behavior can be used to investigate how day-to-day variation in time spent standing relates to risks of developing musculoskeletal pain. However, it may be that the health risks associated with variation in one occupational exposure (e.g., standing) depend on the variation in other occupational exposures (e.g., sitting). The method presented for assessing variation in multiple behaviors could facilitate the exploration of such research questions. This method could also be used by practitioners to evaluate the effectiveness of interventions aimed to enhance variation in workplaces.

Exploratory analyses of sleep intraindividual variability and fatigue in parents of children on the autism spectrum

Fatigue is associated with numerous harmful physical and mental health outcomes. Despite the established relationship between sleep and fatigue, research examining sleep variability within a person (i.e. intraindividual variability; IIV) and fatigue is limited. In addition, the associations between child and parent sleep regarding parent fatigue have not been explicitly explored, which could be relevant for parents of autistic children with increased sleep disturbance likelihood. The current study used two weeks of objective sleep (actigraphy) and subjective fatigue data from 81 parents and their children to explore associations among child sleep IIV, parent sleep IIV, and parent average daily fatigue, including evaluating evidence for mediation. Sleep IIV was estimated using a validated Bayesian model. Linear regression analyses indicated that greater parent total sleep time IIV predicted significantly higher fatigue levels. Child sleep IIV was unrelated to parent sleep IIV and fatigue, unsupportive of hypothesized mediation. Similarly, post hoc analyses examining child sleep averages, parent total sleep time IIV, and average parent fatigue were insignificant. Findings cautiously support the uniqueness of total sleep time IIV within parental sleep's relationship with fatigue, independent of child sleep. Objective sleep IIV should continue to be examined in addition to average levels.Lay abstractFatigue is associated with numerous harmful physical and mental health outcomes. Despite research indicating a relationship between fatigue and sleep, there has been a limited focus on how the variability of a person's sleep may be associated with fatigue. In addition, previous studies have not explicitly explored relationships among child sleep, parent sleep, and parent fatigue. Increasing knowledge about this area of research could be particularly relevant for families with autistic children with an increased likelihood of sleep disturbances. The current study used two weeks of objective sleep (actigraphy) data and subjective ratings of parent fatigue from 81 parents and their autistic children to examine associations among child and parent within-person sleep variability regarding average parent fatigue levels. Evidence was assessed for the role of parent sleep variability in hypothesized connections between child sleep variability and parent fatigue. We found that only greater variability in parents' total sleep time was associated with higher levels of parents' average daily fatigue rating over the two weeks. Child sleep variability was not significantly associated with parent sleep variability or average daily fatigue. In addition, average levels of child sleep were unrelated to parent total sleep time variability and fatigue. Although cautious interpretation is required, findings support the idea that variability in total sleep time may be a unique aspect of parental sleep's association with fatigue, independent of child sleep. In addition, sleep variability could be important to consider when examining sleep in addition to average levels of parameters like total sleep time.

A replicate crossover trial on the interindividual variability of sleep indices in response to acute exercise undertaken by healthy men

STUDY OBJECTIVES

Using the necessary replicate-crossover design, we investigated whether there is interindividual variability in home-assessed sleep in response to acute exercise.

METHODS

Eighteen healthy men (mean [SD]: 26[6] years) completed two identical control (8 hour laboratory rest, 08:45-16:45) and two identical exercise (7 hour laboratory rest; 1 hour laboratory treadmill run [62(7)% peak oxygen uptake], 15:15-16:15) trials in randomized sequences. Wrist-worn actigraphy (MotionWatch 8) measured home-based sleep (total sleep time, actual wake time, sleep latency, and sleep efficiency) two nights before (nights 1 and 2) and three nights after (nights 3-5) the exercise/control day. Pearson's correlation coefficients quantified the consistency of individual differences between the replicates of control-adjusted exercise responses to explore: (1) immediate (night 3 minus night 2); (2) delayed (night 5 minus night 2); and (3) overall (average post-intervention minus average pre-intervention) exercise-related effects. Within-participant linear mixed models and a random-effects between-participant meta-analysis estimated participant-by-trial response heterogeneity.

RESULTS

For all comparisons and sleep outcomes, the between-replicate correlations were nonsignificant, ranging from trivial to moderate (r range = -0.44 to 0.41, p ≥ .065). Participant-by-trial interactions were trivial. Individual differences SDs were small, prone to uncertainty around the estimates indicated by wide 95% confidence intervals, and did not provide support for true individual response heterogeneity. Meta-analyses of the between-participant, replicate-averaged condition effect revealed that, again, heterogeneity (τ) was negligible for most sleep outcomes.

CONCLUSIONS

Control-adjusted sleep in response to acute exercise was inconsistent when measured on repeated occasions. Interindividual differences in sleep in response to exercise were small compared with the natural (trial-to-trial) within-subject variability in sleep outcomes.

CLINICAL TRIALS INFORMATION

https://clinicaltrials.gov/study/NCT05022498. Registration number: NCT05022498.

Sleep disturbances across 2 weeks predict future mental healthcare utilization

STUDY OBJECTIVES

Insufficient sleep costs the US economy over $411 billion per year. However, most studies investigating the economic costs of sleep rely on one-time measures of sleep, which may be prone to recall bias and cannot capture variability in sleep. To address these gaps, we examined how sleep metrics captured from daily sleep diaries predicted medical expenditures.

METHODS

Participants were 391 World Trade Center (WTC) responders enrolled in the WTC Health Program (mean age = 54.97 years, 89% men). At baseline, participants completed 14 days of self-reported sleep and stress measures. Mean sleep, variability in sleep, and a novel measure of sleep reactivity (i.e. how much people's sleep changes in response to daily stress) were used to predict the subsequent year's medical expenditures, covarying for age, race/ethnicity, sex, medical diagnoses, and body mass index.

RESULTS

Mean sleep efficiency did not predict mental healthcare utilization. However, greater sleep efficiency reactivity to stress (b = $191.75, p = .027), sleep duration reactivity to stress (b = $206.33, p = .040), variability in sleep efficiency (b = $339.33, p = .002), variability in sleep duration (b = $260.87, p = .004), and quadratic mean sleep duration (b = $182.37, p = .001) all predicted greater mental healthcare expenditures. Together, these sleep variables explained 12% of the unique variance in mental healthcare expenditures. No sleep variables were significantly associated with physical healthcare expenditures.

CONCLUSIONS

People with more irregular sleep, more sleep reactivity, and either short or long sleep engage in more mental healthcare utilization. It may be important to address these individuals' sleep problems to improve mental health and reduce healthcare costs.

The stability of slow-wave sleep and EEG oscillations across two consecutive nights of laboratory polysomnography in cognitively normal older adults

Laboratory polysomnography provides gold-standard measures of sleep physiology, but multi-night investigations are resource intensive. We assessed the night-to-night stability via reproducibility metrics for sleep macrostructure and electroencephalography oscillations in a group of cognitively normal adults attending two consecutive polysomnographies. Electroencephalographies were analysed using an automatic algorithm for detection of slow-wave activity, spindle and K-complex densities. Average differences between nights for sleep macrostructure, electroencephalography oscillations and sleep apnea severity were assessed, and test-retest reliability was determined using two-way intraclass correlations. Agreement was calculated using the smallest real differences between nights for all measures. Night 2 polysomnographies showed significantly greater time in bed, total sleep time (6.3 hr versus 6.8 hr, p < 0.001) and percentage of rapid eye movement sleep (17.5 versus 19.7, p < 0.001). Intraclass correlations were low for total sleep time, percentage of rapid eye movement sleep and sleep efficiency, moderate for percentage of slow-wave sleep and percentage of non-rapid eye movement 2 sleep, good for slow-wave activity and K-complex densities, and excellent for spindles and apnea-hypopnea index with hypopneas defined according to 4% oxygen desaturation criteria only. The smallest real difference values were proportionally high for most sleep macrostructure measures, indicating moderate agreement, and proportionally lower for most electroencephalography microstructure variables. Slow waves, K-complexes, spindles and apnea severity indices are highly reproducible across two consecutive nights of polysomnography. In contrast, sleep macrostructure measures all demonstrated poor reproducibility as indicated by low intraclass correlation values and moderate agreement. Although there were average differences in percentage of rapid eye movement sleep and total sleep time, these were numerically small and perhaps functionally or clinically less significant. One night of in-laboratory polysomnography is enough to provide stable, reproducible estimates of an individual's sleep concerning measures of slow-wave activity, spindles, K-complex densities and apnea severity.

Sleep Characteristics During the First Year Postpartum in a Cohort of Black and White Women

Study Objectives

The postpartum period is a unique time when sleep deficiency often occurs. Black and White adults are reported to have differences in sleep characteristics, but little is known if these differences exist in the postpartum period. Therefore, the purpose of this study was to examine sleep characteristics in a cohort of Black and White women from 6-8 weeks to 12 months postpartum.

Methods

Participants were 49 Black and 85 White women who gave birth to an infant at ≥37 weeks gestation. Participants were instructed to wear an Actiwatch for 7 days at 6-8 weeks, 4, 6, 9, and 12 months postpartum. Mixed-effects linear models with a race by time interaction were used to examine if characteristics differed between races over time.

Results

Only bedtime varied by race. White women had a later bedtime at 6-8 weeks compared to 6 months, but no significant change occurred for Black women. For the entire sample, average nighttime sleep duration increased from 385 minutes at 6-8 weeks to 404 minutes at 4 months postpartum. Percent sleep during the sleep interval and wake after sleep onset (WASO) improved by 6 and 9 months, respectively. However, average WASO remained >45 minutes and sleep efficiency <85% at all timepoints for both Black and White women. Compared to White women, Black women had significantly shorter sleep duration (range: 40.6-59.9 minutes shorter across all timepoints, p<0.0001) and time in bed (range: 17.5-67.6 minutes shorter, p=0.0046), and lower percent sleep (range: 0.7%-1.2% lower, p=0.0407) and sleep efficiency (range: 2.6%-5.7% lower, p=0.0005). Sociodemographic factors were associated with sleep outcomes in Black and White women while behavioral factors were associated with sleep outcomes in White women only.

Conclusion

While there were improvements in nighttime sleep duration and quality, sleep duration remained suboptimal, and quality remained poor throughout the first year postpartum. In this sample, differences existed in factors associated with sleep outcomes between Black and White women.

Correlates of sleep variability in a mobile EEG-based volunteer study

Variable sleep patterns are a risk factor for disease, but the reasons some people express greater within-individual variability of sleep characteristics remains poorly understood. In our study, we leverage BSETS, a novel mobile EEG-based dataset in which 1901 nights in total were recorded from 267 extensively phenotyped participants to identify factors related to demographics, mental health, personality, chronotype and sleep characteristics which predict variability in sleep, including detailed sleep macrostructure metrics. Young age, late chronotype, and napping emerged as robust correlates of increased sleep variability. Correlations with other characteristics (such as student status, personality, mental health and co-sleeping) generally disappeared after controlling for age. We critically examine the utility of controlling the correlates of sleep variability for the means of sleep variables. Our research shows that age and sleep habits affecting the amount of sleep pressure at night are the most important factors underlying sleep variability, with a smaller role of other psychosocial variables. The avoidance of daytime naps emerges as the most promising modifiable behavior associated with increased sleep regularity.

Irregular sleep is linked to poorer mental health: A pooled analysis of eight studies

OBJECTIVES

Greater sleep disturbances on average are a risk factor for impaired mental health. Recent research has shown that more intraindividual variability (i.e., inconsistency) in sleep (hereafter called "sleep intraindividual variability") may also be uniquely related to mental health, even above the influence of mean sleep patterns averaged across days. The current study examined associations between sleep intraindividual variability and symptoms of anxiety, depression, and insomnia across different facets of sleep intraindividual variability (sleep duration, efficiency, and timing) and sleep measurement types (sleep diary and actigraphy).

METHODS

We pooled eight datasets (N = 3053 participants) that assessed repeated measures of sleep diary- and/or actigraphy-determined sleep across multiple days, as well as one-time measures of mental health or sleep disorder symptoms (i.e., anxiety, depression, and insomnia). Multilevel regression analyses were conducted to examine associations between sleep intraindividual variability and mental health or sleep disorder symptoms.

RESULTS

Greater diary- and actigraphy-determined sleep duration intraindividual variability was associated with more depression symptoms (diary: b=0.02, p < .001; actigraphy: b=0.03, p = .006) and more insomnia symptoms (diary: b=0.02, p < .001; actigraphy: b=0.02, p < .001). Greater diary-determined sleep efficiency intraindividual variability was associated with fewer anxiety symptoms (b=-0.23, p = .019) and fewer insomnia symptoms (b=-0.15, p < .001). Greater diary- and actigraphy-determined sleep midpoint intraindividual variability was associated with more insomnia symptoms (diary: b=0.41, p = .044; actigraphy: b=0.66, p = .021).

CONCLUSIONS

More inconsistent sleep duration and sleep timing may be a correlate of poorer mental health. Future experimental work should examine whether stabilizing sleep patterns can improve mental health outcomes.

Night-to-night variability of objective sleep outcomes in youth Middle Eastern football players

OBJECTIVE

To describe components of night-to-night variation in objective measures of sleep.

METHODS

We conducted a secondary data analysis of consecutive and chronologically ordered actigraphy-based measurements for time in bed (min), time asleep (min), and wake-after-sleep onset (min). This investigation examined 575 individual night-based measures available for a sub-sample of fifty-two, male youth Middle Eastern football players tracked over a 14-day surveillance period (chronological age range: 12.1 to 16 years). Distinct multivariable-adjusted generalized additive models included each objective sleep outcome measure as dependent variable and disaggregated components of variation for night measurement-by-sleep period interaction, week part (weekday or weekend), and study participant random effects from within-subject night-to-night sleep variation.

RESULTS

The within-subject standard deviation (SD) of ±98 min (95% confidence interval [CI], 92 to 104 min) for time in bed, ±87 min (95%CI, 82 to 93 min) for time asleep, and ±23 min (95%CI, 22 to 25 min) for wake-after-sleep-onset overwhelmed other sources of variability and accounted for ∼44% to 53% of the overall night-to-night variation. The night measurement-by-fragmented sleep period interaction SD was ±83 min (95%CI, 44 to 156 min) for time in bed, ±67 min (95%CI, 34 to 131 min) for time asleep, and ±15 min (95%CI, 7 to 32 min) for wake-after-sleep-onset that accounted for ∼22% to 32% of each sleep outcome measure overall variability.

CONCLUSIONS

Substantial random night-to-night within-subject variability poses additional challenges for strategies aiming to mitigate problems of insufficient and inconsistent sleep that are detrimental to school learning and youth athlete development processes.

Objective and Subjective Intraindividual Variability in Sleep: Predisposing Factors and Health Consequences

OBJECTIVE

We investigated the factors that predispose or precipitate greater intraindividual variability (IIV) in sleep. We further examined the potential consequences of IIV on overall sleep quality and health outcomes, including whether these relationships were found in both self-reported and actigraphy-measured sleep IIV.

METHODS

In Study 1, 699 US adults completed a Sleep Intra-Individual Variability Questionnaire and self-reported psychosocial, sleep quality, and health outcomes. In Study 2, 100 university students wore actigraphy and completed psychosocial, sleep, and health surveys at multiple timepoints.

RESULTS

In cross-sectional analyses that controlled for mean sleep duration, predisposing/precipitating factors to greater IIV were being an underrepresented racial/ethnic minority (Study 1: F = 13.95, p < .001; Study 2: F = 7.03, p = .009), having greater stress (Study 2: r values ≥ 0.32, p values ≤ .002) or trait vulnerability to stress (Study 1: r values ≥ 0.15, p values < .001), and showing poorer time management (Study 1: r values ≤ -0.12, p values ≤ .004; Study 2: r values ≤ -0.23, p values ≤ .028). In addition, both studies showed that greater sleep IIV was associated with decreased overall sleep quality, independent of mean sleep duration (Study 1: r values ≥ 0.20, p values < .001; Study 2: r values ≥ 0.33, p values ≤ .001). Concordance across subjective and objective IIV measures was modest ( r values = 0.09-0.35) and similar to concordance observed for subjective-objective mean sleep duration measures.

CONCLUSION

Risk for irregular sleep patterns is increased in specific demographic groups and may be precipitated by, or contribute to, higher stress and time management inefficiencies. Irregular sleep may lead to poor sleep quality and adverse health outcomes, independent of mean sleep duration, underscoring the importance of addressing sleep consistency.

Short-term stability and night-to-night variability of sleep parameters in nightmares comorbid with chronic insomnia Disorder across multiple nights of polysomnography

STUDY OBJECTIVES

The purpose of this study was to examine the degree of short-term stability of polysomnographic (PSG) measured sleep parameters and the overall differences between individuals with comorbid nightmares and insomnia compared to those with chronic insomnia disorder alone or good sleeping controls across four nights in the sleep lab.

METHODS

A total of 142 good sleeping controls, 126 chronic insomnia alone, and 24 comorbid insomnia/nightmare participants underwent four consecutive nights of 8-hour PSG recordings. Outcomes included sleep continuity, architecture, and REM-related parameters across nights one through four. Intraclass correlation coefficients with mixed-effect variances and repeated-measure analysis of covariance were used, respectively, to determine short-term stability as well as between-participants and time-by-group interaction effects.

RESULTS

Wake after sleep onset and stage 1 showed "poor stability" in the comorbid insomnia/nightmare group compared to "moderate stability" in the good sleeping controls and chronic insomnia alone group. Significant between-group effects (all ps < .05) showed that the comorbid insomnia/nightmare group took longer to fall asleep and had a greater first-night-effect in stage 1 compared to good sleeping controls and chronic insomnia alone group; in addition, the comorbid insomnia/nightmare and insomnia alone groups slept shorter, with fewer awakenings and REM periods, compared to the good sleeping controls.

CONCLUSIONS

Nightmares are associated with abnormal sleep above and beyond REM disruption, as sleep continuity was the primary aspect in which poor stability and group differences emerged. The greater inability to fall asleep and instability of sleep fragmentation in those with comorbid insomnia/nightmares compared to chronic insomnia alone may be attributed to the impact of presleep anticipatory anxiety and nightmare-related distress itself.

CLINICAL TRIAL INFORMATION

The data analyzed in this study does not come from any current or previous clinical trials. Therefore, there is no clinical trial information to report.

Day-to-day sleep variability with Alzheimer's biomarkers in at-risk elderly

INTRODUCTION

Measuring day-to-day sleep variability might reveal unstable sleep-wake cycles reflecting neurodegenerative processes. We evaluated the association between Alzheimer's disease (AD) fluid biomarkers with day-to-day sleep variability.

METHODS

In the PREVENT-AD cohort, 203 dementia-free participants (age: 68.3 ± 5.4; 78 males) with a parental history of sporadic AD were tested with actigraphy and fluid biomarkers. Day-to-day variability (standard deviations over a week) was assessed for sleep midpoint, duration, efficiency, and nighttime activity count.

RESULTS

Lower cerebrospinal fluid (CSF) ApoE, higher CSF p-tau181/amyloid-β (Aβ)42, and higher plasma p-tau231/Aβ42 were associated with higher variability of sleep midpoint, sleep duration, and/or activity count. The associations between fluid biomarkers with greater sleep duration variability were especially observed in those that carried the APOE4 allele, mild cognitive impairment converters, or those with gray matter atrophy.

DISCUSSION

Day-to-day sleep variability were associated with biomarkers of AD in at-risk individuals, suggesting that unstable sleep promotes neurodegeneration or, conversely, that AD neuropathology disrupts sleep-wake cycles.

Age, sex and race distribution of accelerometer-derived sleep variability in US school-aged children and adults

Sleep variability (e.g. intra-individual variabilities in sleep duration or sleep timing, social jetlag, and catch-up sleep) is an important factor impacting health and mortality. However, limited information is available on the distribution of these sleep parameters across the human life span. We aimed to provide distribution of sleep variability related parameters across lifespan by sex and race in a national representative sample from the U.S. population. The study included 9981 participants 6 years and older from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, who had 4-7 days of valid 24-h accelerometer recording with at least one day obtained during weekend (Friday or Saturday night). Of the study participants, 43% showed ≥ 60 min sleep duration standard deviation (SD), 51% experienced ≥ 60 min catch-up sleep, 20% showed ≥ 60 min sleep midpoint SD, and 43% experienced ≥ 60 min social jetlag. American youth and young adults averaged greater sleep variability compared to other age groups. Non-Hispanic Blacks showed greater sleep variability in all parameters compared to other racial groups. There was a main effect of sex on sleep midpoint SD and social jetlag with males averaging slightly more than females. Our study provides important observations on sleep variability parameters of residents of the United States by using objectively measured sleep patterns and will provide unique insights for personalized advice on sleep hygiene.

Day-to-day deviations in sleep parameters and biological aging: Findings from the NHANES 2011-2014

OBJECTIVES

The majority of the previous research has focused on the impact of average sleep parameters on longevity. In this study, we aimed to investigate the associations of day-to-day deviations in sleep parameters with biological ages among 6052 adults participating in the 2011-2014 waves of the US National Health and Nutrition Examination Survey.

METHODS

Sleep parameters, including sleep duration, efficiency, midpoint, and day-to-day deviations in sleep parameters, including standard deviation of sleep duration (sleep variability), standard deviation of sleep midpoint (sleep irregularity), catch-up sleep, and social jetlag, were obtained from 4 to 7 days of 24-h accelerometer recording. We used physiological data to compute measurements of biological aging according to 3 published algorithms: PhenoAge, Klemera-Doubal method Biological Age, and homeostatic dysregulation.

RESULTS

After adjustment of multiple covariates, we observed that all parameters of day-to-day deviations in sleep were significantly associated with biological aging with larger sleep variability, larger sleep irregularity, more catch-up sleep, and more social jetlag linked with more advanced biological aging. The significant associations of sleep irregularity, catch-up sleep, and social jetlag with biological aging indices remained even after adjustment for sleep duration, efficiency, and midpoint.

CONCLUSION

In this study, we found that day-to-day deviations in sleep parameters are independently associated with biological aging in US general population. Since day-to-day deviation in sleep is a modifiable behavioral factor, our finding suggests that intervention aiming at increasing regularity in sleep patterns may be a novel approach for extending a healthy life span.

Sleep Variability, Eating Timing Variability, and Carotid Intima-Media Thickness in Early Adulthood

Background Day-to-day variability in sleep patterns and eating timing may disrupt circadian rhythms and has been linked with various adverse cardiometabolic outcomes. However, the extent to which variability in sleep patterns and eating timing relate to atherosclerotic development in subclinical stages remains unclear. Methods and Results Generally healthy adults (N=62, 29.3±7.3 years, 66% female) completed 14 days of sleep and dietary assessments via wrist accelerometry and photo-assisted diet records, respectively. Variability in sleep duration, sleep onset, eating onset (time of first caloric consumption), eating offset (time of last caloric consumption), and caloric midpoint (time at which 50% of total daily calories are consumed) were operationalized as the SD across 14 days for each variable. Separate regression models evaluated the cross-sectional associations between sleep and eating variability metrics with end-diastolic carotid intima-media thickness (CIMT) measured via ultrasonography. Models adjusted for age, sex, systolic blood pressure, sleep duration, and total energy intake. Each 60-minute increase in sleep duration SD and sleep onset SD were associated with a 0.049±0.016 mm (P=0.003) and 0.048±0.017 mm (P=0.007) greater CIMT, respectively. Variability in eating onset and offset were not associated with CIMT; however, each 60-minute increase in caloric midpoint SD was associated with a 0.033±0.015 mm greater CIMT (P=0.029). Exploratory post hoc analyses suggested that sleep duration SD and sleep onset SD were stronger correlates of CIMT than caloric midpoint SD. Conclusions Variability in sleep patterns and eating timing are positively associated with clinically relevant increases in CIMT, a biomarker of subclinical atherosclerosis, in early adulthood.

Age, sex and race distribution of accelerometer-derived sleep variability in US school-aged children and adults

Background

Sleep variability (e.g. intra-individual variabilities in sleep duration or sleep timing, social jetlag, and catch-up sleep) is an important factor impacting health and mortality. However, limited information is available on the distribution of these sleep parameters across the human life span. We aimed to provide distribution of sleep variability related parameters across lifespan by sex and race in a national representative sample from the U.S. population.

Methods

The study included 9,799 participants 6 years and older from the National Health and Nutrition Examination Survey (NHANES) 2011-2014, who had at least 3 days of valid sleep parameters with at least one day obtained during weekend (Friday or Saturday night). These were calculated from 7-day 24-h accelerometer recordings.

Results

Of the study participants, 43% showed ≥ 60 minutes sleep duration standard deviation (SD), 51% experienced ≥ 60 minutes catch-up sleep, 20% showed ≥ 60 minutes midpoint of sleep SD, and 43% experienced ≥ 60 minutes social jetlag. American youth and young adults averaged greater sleep variability compared to other age groups. Non-Hispanic Blacks showed greater sleep variability in all parameters compared to other racial groups. There was a main effect of sex on sleep midpoint SD and social jetlag with males averaging slightly more than females.

Conclusion

Our study provides important observations on sleep irregularity parameters of residents of the United States by using objectively measured sleep patterns and will provide unique insights for personalized advice on sleep hygiene.