Analysis of dynamic, bidirectional associations in older adult physical activity and sleep quality

Age and gender disparities in joint associations of physical activity and sleep duration with depressive symptoms trajectories: a longitudinal analysis of Chinese middle-aged and older adults

OBJECTIVES

The combined effects of physical activity and sleep duration on depressive symptoms trajectories, and age and gender disparities remain inadequately understood. The objective of this study was to identify the joint relationship of physical activity and sleep duration with depressive symptoms trajectories in Chinese middle-aged and older adults, and explored disparities in the joint associations.

METHOD

This longitudinal analysis draws upon data from the China Health and Retirement Longitudinal Study. The analysis comprised 35063 observations. Linear mixed-effect models were employed to discern independent and joint correlation of physical activity and sleep duration with depressive symptoms trajectories.

RESULTS

Chinese middle-aged and older adults showed increasing depressive symptoms trajectory. Physical activity and sleep duration interplayed to impact depressive symptoms trajectory in different ways. Compared to participants engaged in lower physical activity and short sleep, depressive symptom trajectories of those with higher physical activity and optimal sleep, and higher physical activity and short sleep increased less rapidly among group aged 60-70 years, as well as in women group.

CONCLUSION

This study emphasized the importance of combining interventions targeting habits of physical activity and sleep for middle-aged and older adults to improve their mental health, especially for women and those aged 60-70 years.

Engagement in moderate-intensity physical activity supports overnight memory retention in older adults

Preserving the ability to vividly recall emotionally rich experiences contributes to quality of life in older adulthood. While prior works suggest that moderate-intensity physical activity (MPA) may bolster memory, it is unclear whether this extends to emotionally salient memories consolidated during sleep. In the current study, older adults (mean age = 72.3 ± 5.8) completed an overnight polysomnography assessment with emotional memory tested before and after sleep and a self-report questionnaire assessing habitual PA. Results show that better negative emotional memory consolidation was associated with the frequency and duration of MPA. Statistically replacing 30 min of lower-intensity activity with MPA was associated with better negative emotional memory consolidation. MPA may enhance sleep-dependent consolidation of negative memories in older adults, with modest increases in MPA yielding significant consolidation benefits. Findings may guide interventions and inform public health recommendations by demonstrating that substituting even short durations of low-intensity activity for MPA could produce significant cognitive gains in older adulthood.

Association Between Physical Activity and Sleep Health Among Community-Dwelling Adults Aged ≥50 in Ghana: The Mediating Role of Psychosomatic Factors

OBJECTIVES

Data on the direct and indirect associations between physical activity (PA) and sleep quality in old age via psychosomatic mechanisms (e.g. mobility, pain, loneliness, depression, and anxiety) remain scarce in low- and middle-income countries (LMICs). We explored the association of PA with poor sleep quality (PSQ) among individuals aged ≥ 50 in Ghana and explored the potential mediating factors in this association.

METHODS

We analyzed community-based data from the Aging, Health, Psychological Well-being, and Health-seeking Behavior Study. We assessed PA using the International Physical Activity Questionnaire (IPAQ). Two items on nighttime and daytime sleep problems in the last 30 days were used to measure PSQ. Multivariable ordinary least square (OLS) regressions and bootstrapping models were performed to evaluate the associations.

RESULTS

Overall, 1,201 participants (Mage = 66.15 ± 11.58 years; 63.3% female) were included in the analysis. PA was independently associated with decreased PSQ in the overall sample (B = -0.181, 95%I = -0.271 to -0.092) and in women (B = -0.195, 95%I = -0.305 to -0.084). The association was stronger in the ≥ 65 (B = -0.138) than in the 50-64 age group (B = -0.213). Mobility (37.06%), pain (23.66%), loneliness (6.71%), and comorbid anxiety and depression (8.95%) mediated the PA-PSQ association.

CONCLUSIONS

PA was associated with decreased PSQ levels, which was particularly explained by psychosomatic factors.

CLINICAL IMPLICATIONS

Clinicians encourage older adults to engage in regular PA and manage psychosomatic problems may improve their sleep health.

Associations of accelerometer-measured physical activity, sedentary behaviour, and sleep with next-day cognitive performance in older adults: a micro-longitudinal study

BACKGROUND

Previous studies suggest short-term cognitive benefits of physical activity occurring minutes to hours after exercise. Whether these benefits persist the following day and the role of sleep is unclear. We examined associations of accelerometer-assessed physical activity, sedentary behaviour, and sleep with next-day cognitive performance in older adults.

METHODS

British adults aged 50-83 years (N = 76) without evidence of cognitive impairment or dementia wore accelerometers for eight days, and took daily cognitive tests of attention, memory, psychomotor speed, executive function, and processing speed. Physical behaviour (time spent in moderate-to-vigorous physical activity [MVPA], light physical activity [LPA], and sedentary behaviour [SB]) and sleep characteristics (overnight sleep duration, time spent in rapid eye movement [REM] sleep and slow wave sleep [SWS]) were extracted from accelerometers, with sleep stages derived using a novel polysomnography-validated machine learning algorithm. We used linear mixed models to examine associations of physical activity and sleep with next-day cognitive performance, after accounting for habitual physical activity and sleep patterns during the study period and other temporal and contextual factors.

RESULTS

An additional 30 min of MVPA on the previous day was associated with episodic memory scores 0.15 standard deviations (SD; 95% confidence interval = 0.01 to 0.29; p = 0.03) higher and working memory scores 0.16 SD (0.03 to 0.28; p = 0.01) higher. Each 30-min increase in SB was associated with working memory scores 0.05 SD (0.00 to 0.09) lower (p = 0.03); adjustment for sleep characteristics on the previous night did not substantively change these results. Independent of MVPA on the previous day, sleep duration ≥ 6 h (compared with < 6 h) on the previous night was associated with episodic memory scores 0.60 SD (0.16 to 1.03) higher (p = 0.008) and psychomotor speed 0.34 SD (0.04 to 0.65) faster (p = 0.03). Each 30-min increase in REM sleep on the previous night was associated with 0.13 SD (0.00 to 0.25) higher attention scores (p = 0.04); a 30-min increase in SWS was associated with 0.17 SD (0.05 to 0.29) higher episodic memory scores (p = 0.008).

CONCLUSIONS

Memory benefits of MVPA may persist for 24 h; longer sleep duration, particularly more time spent in SWS, could independently contribute to these benefits.

The relationship between physical activity level and timing and sleep quality and hygiene in healthy individuals: a cross-sectional study

The current study focused on investigating the relationship between level and timing of physical activity and sleep quality and hygiene in healthy individuals. This cross-sectional study design recruited 175 participants (male: 98, 56%, female: 77, 44%, and BMI: 23.87 ± 3.92) aged between 18 and 65, 157 of whom were physically active and 18 of whom were physically inactive. The study recruited healthy participants from various sports facilities, fitness centers, and walking parks to ensure a diverse sample of physically active individuals in a metropolitan city. The study excluded people with sleep disorders, rheumatoid arthritis, heart or neurological problems, and those who had shift work. The study employed the Demographic Information Form, International Physical Activity Questionnaire (Short Form), Pittsburgh Sleep Quality Scale, and Sleep Hygiene Questionnaire. A one-way MANOVA was employed to compare sleep quality and hygiene in different physical activity levels. A second MANOVA compared sleep quality and hygiene in different physical activity timing, including only the minimally active and very active participants. One-way MANOVA showed a significant difference F (4, 171) = 7.532, Pillai's trace = 0.161, partial eta squared = 0.081 between sleep quality and hygiene scores among inactive, minimally active, and very active participants. A post hoc analysis showed sleep quality was significantly better in minimal active (6.42 ± 2.55, p = 0.002, Cohen's d = 0.867) and very active participants (5.99 ± 2.29, p < 0.001, Cohen's d = 1.092) than inactive (8.61 ± 2.50) participants. Also, sleep hygiene was significantly better in minimal active (28.50 ± 6.74, p = 0.001, Cohen's d = 0.867) and very active participants (29.52 ± 6.56, p < 0.001, Cohen's d = 0.992) than inactive (36.05 ± 8.39) participants. The one-way MANOVA revealed no statistically significant differences in sleep quality and hygiene scores based on physical activity time. Our study showed that physically active individuals had significantly better sleep quality and hygiene scores, while there was no difference based on the timing of physical activity. Healthy individuals may be encouraged to participate in physical activity in the morning, afternoon, or evening to improve sleep parameters.

Exploring the effects of multi-dimensional geographic environment on daily sleep and physical activity based on the Actigraph data

Understanding the interplay between people's daily sleep and physical activity and how geographic environment influences them are important for developing healthy cities. However, such research has been limited. This study aims to explore the bidirectional and nonlinear relationship between daily sleep and physical activity, and further investigate the comprehensive influences of multi-dimensional geographic environment on these health behaviors. Based on the objective data on sleep and physical activity over seven consecutive days using wrist-based accelerometers in Beijing, China, we developed a series of models to analyze the mutual influences between people's daily sleep and physical activity, and employed the generalized additive model (GAM) to examine their potential nonlinear relationships and how geographic environment - including meteorological conditions, built environment, and social environment - influences them. The results show that sleep and physical activity exhibit notable bidirectional relationship. Moderate-to-vigorous physical activity (MVPA) is observed to improve sleep quality, but it decreases sleep duration. In contrast, total sleep time (TST) exhibits an inverted U-shaped pattern with both MVPA and total step counts, with the optimal sleep duration at 5 h. Furthermore, meteorological factors, built environment characteristics, and social environment have significant linear or nonlinear effects on people's daily sleep and physical activity. The outcomes of this study offer valuable insights for enhancing residents' health and developing healthy cities.

Diurnal patterns of accelerometer-measured physical activity and sleep and risk of all-cause mortality: a follow-up of the National Health and Nutrition Examination Surveys (NHANES)

BACKGROUND

Physical activity and sleep are established modifiable lifestyle factors, but the optimal time of the day of these behaviours for health is unknown. This study examined the independent and joint associations of diurnal patterns of physical activity and sleep with all-cause mortality.

METHODS

This prospective cohort study included 6,673 participants who have attended the accelerometer assessment in the 2011-2014 National Health and Nutrition Examination Surveys (NHANES). Diurnal patterns of accelerometer-measured physical activity and sleep were identified using K-means clustering analysis. All-cause mortality was ascertained from the accelerometer measurement to December 31, 2019 (median follow-up 6.8 years). Survey-weighted Cox proportional hazard models were performed to estimate the independent and joint associations of diurnal patterns of physical activity and sleep with all-cause mortality.

RESULTS

Diurnal patterns identified were: early-morning (32.4%), midday (42.5%), and late-afternoon (25.1%) for physical activity; and irregular sleep (37.4%), morning lark (33.6%), and night owl (29.0%) for sleep. After adjusting for volume of physical activity, sleep duration and other potential covariates, the early-morning physical activity pattern (hazard ratio 1.36, 95% confidence interval 1.13-1.64) and irregular sleep pattern (1.42, 1.01-1.99) were independently associated with higher risk of all-cause mortality, compared with midday physical activity and morning lark sleep patterns, respectively. In addition, participants with the combined pattern of early-morning physical activity and irregular sleep had higher risk of all-cause mortality compared to those with midday physical activity combined with a morning lark sleep pattern (1.92, 1.33-2.78). Several sociodemographic differences were observed in the strength of these associations.

CONCLUSIONS

Wearable activity-rest monitoring data showed that peak physical activity in the early morning and irregular sleep diurnal patterns are associated with increased mortality risk, and the combination of these patterns further exaggerated the risk. Public health program should acknowledge that the diurnal patterns of physical activity and sleep, in addition to their duration and frequency, may play a crucial role in lifestyle-based health promotion and management strategies.

24-H movement behaviours research in Chinese population: A scoping review

Background

Numerous studies examining 24-h movement behaviours have been exponentially published globally. However, no comprehensive reviews summarized and synthesized the evidence on the Chinese population. This review aimed to map the most recent research state and fill the gaps related to 24-h movement behaviours in the Chinese population.

Methods

Five electronic databases (Web of Science, PubMed, Scopus, EBSCOhost, and CNKI (Chinese database)) were searched from their inceptions through October 2023. Quantitative studies published in English and/or Chinese were included if they were related to 24-h movement behaviours in the Chinese population.

Results

From 9431 documents screened, 53 met the inclusion criteria. All the included studies were published between 2019 and 2023, showing a notable increasing trend over the years. Most studies used cross-sectional designs (96.2 %) and self-reported measures (56.6 %). Nearly all the studies targeted general healthy population (96.2 %), especially children and adolescents (64.2 %). The main three research topics observed were health outcomes (81.1 %), prevalence (66.0 %), and correlates (15.1 %) of 24-h movement behaviours.

Conclusion

24-h movement behaviours in the Chinese population has been an increasingly important research topic in the literature, with predominant focus on children and adolescents (study population), self-report measure (measurement), cross-sectional design (study design), guidelines adherence (study topic), and health outcomes examination (study topic). These findings delineate a research landscape in the Chinese population, and highlight the research gaps needed to be addressed. Future studies are suggested to target these research gaps, expanding evidence base for the Chinese populations. For instance, more studies using device-based measures, longitudinal or interventional designs, as well as qualitative and mixed-methods approaches are required.

Factors associated with the fragmentation and stability of the rest-activity rhythm in adults and older adults

This cross-sectional study aimed to identify factors related to the fragmentation and stability of the rest-activity rhythm (RAR) in adults and older adults. It is part of a larger research project investigating aspects concerning sleep duration, quality, and disorders in a representative subsample of the population. Sociodemographic data, lifestyle, health habits and subjective sleep variables were obtained; RAR records were collected by means of actigraphy and analyzed using non-parametric variables (IS, IV, M10, L5, RA, sL5, and sM10). Study participants were 313 individuals with complete actigraphy records. There was a prevalence of older adults (50.2%) and females (51.1%). Females, individuals with 4-8 y of education, and those who used alcohol abusively exhibited lower RAR fragmentation. Higher fragmentation was observed in individuals who napped and those reporting poor sleep quality. Greater rhythm stability was evident in females, older adults, those with 4-8 y of education, and those who had a partner. Smokers demonstrated lower RAR stability. These findings may contribute valuable insights for decision-making aimed at preventing and treating issues related to fragmentation and instability of the rhythm and its possible consequences to health.

Joint associations of physical activity and sleep duration with cognitive ageing: longitudinal analysis of an English cohort study

BACKGROUND

Physical activity and sleep duration are key factors associated with cognitive function and dementia risk. How physical activity and sleep interact to influence cognitive ageing is not well explored. We aimed to examine the associations of combinations of physical activity and sleep duration with 10-year cognitive trajectories.

METHODS

In this longitudinal study, we analysed data from the English Longitudinal Study of Ageing collected between Jan 1, 2008, and July 31, 2019, with follow-up interviews every 2 years. Participants were cognitively healthy adults aged at least 50 years at baseline. Participants were asked about physical activity and nightly sleep duration at baseline. At each interview, episodic memory was assessed using immediate and delayed recall tasks and verbal fluency using an animal naming task; scores were standardised and averaged to produce a composite cognitive score. We used linear mixed models to examine independent and joint associations of physical activity (lower physical activity or higher physical activity, based on a score taking into account frequency and intensity of physical activity) and sleep duration (short [<6 h], optimal [6-8 h], or long [>8 h]) with cognitive performance at baseline, after 10 years of follow-up, and the rate of cognitive decline.

FINDINGS

We included 8958 respondents aged 50-95 years at baseline (median follow-up 10 years [IQR 2-10]). Lower physical activity and suboptimal sleep were independently associated with worse cognitive performance; short sleep was also associated with faster cognitive decline. At baseline, participants with higher physical activity and optimal sleep had higher cognitive scores than all combinations of lower physical activity and sleep categories (eg, difference between those with higher physical activity and optimal sleep vs those with lower physical activity and short sleep at baseline age 50 years was 0·14 SDs [95% CI 0·05-0·24]). We found no difference in baseline cognitive performance between sleep categories within the higher physical activity category. Those with higher physical activity and short sleep had faster rates of cognitive decline than those with higher physical activity and optimal sleep, such that their scores at 10 years were commensurate with those who reported low physical activity, regardless of sleep duration (eg, difference in cognitive performance after 10 years of follow-up between those with higher physical and optimal sleep and those with lower physical activity and short sleep was 0·20 SDs [0·08-0·33]; difference between those with higher physical activity and optimal sleep and those with lower physical activity and short sleep was 0·22 SDs [0·11-0·34]).

INTERPRETATION

The baseline cognitive benefit associated with more frequent, higher intensity physical activity was insufficient to ameliorate the more rapid cognitive decline associated with short sleep. Physical activity interventions should also consider sleep habits to maximise benefis of physical activity for long-term cognitive health.

FUNDING

UK Economic and Social Research Council.

Association of physical activity, sedentary behaviour, and daylight exposure with sleep in an ageing population: findings from the Whitehall accelerometer sub-study

BACKGROUND

Ageing is accompanied by changes in sleep, while poor sleep is suggested as a risk factor for several health outcomes. Non-pharmacological approaches have been proposed to improve sleep in elderly; their impact remains to be investigated. The aim of this study was to examine the independent day-to-day associations of physical behaviours and daylight exposure with sleep characteristics among older adults.

METHODS

Data were drawn from 3942 participants (age range: 60-83 years; 27% women) from the Whitehall II accelerometer sub-study. Day-to-day associations of objectively-assessed daytime physical behaviours (sedentary behaviour, light-intensity physical activity (LIPA), moderate-to-vigorous physical activity (MVPA), mean acceleration, physical activity chronotype) and daylight exposure (proportion of waking window with light exposure > 1000 lx and light chronotype) with sleep characteristics were examined using mixed models.

RESULTS

A 10%-increase in proportion of the waking period spent sedentary was associated with 5.12-minute (4.31, 5.92) later sleep onset and 1.76-minute shorter sleep duration (95%confidence interval: 0.86, 2.66). Similar increases in LIPA and MVPA were associated with 6.69 (5.67, 7.71) and 4.15 (2.49, 5.81) earlier sleep onset respectively and around 2-minute longer sleep duration (2.02 (0.87, 3.17) and 2.23 (0.36, 4.11), respectively), although the association was attenuated for MVPA after adjustment for daylight exposure (1.11 (- 0.84, 3.06)). A 3-hour later physical activity chronotype was associated with a 4.79-minute later sleep onset (4.15, 5.43) and 2.73-minute shorter sleep duration (1.99, 3.47). A 10%-increase in proportion of waking period exposed to light> 1000 lx was associated with 1.36-minute longer sleep (0.69, 2.03), independently from mean acceleration. Associations found for sleep duration were also evident for duration of the sleep windows with slightly larger effect size (for example, 3.60 (2.37, 4.82) minutes for 10%-increase in LIPA), resulting in associations with sleep efficiency in the opposite direction (for example, - 0.29% (- 0.42, - 0.16) for 10%-increase in LIPA). Overall, associations were stronger for women than for men.

CONCLUSIONS

In this study, higher levels of physical activity and daylight exposure were associated with slightly longer sleep in older adults. Given the small effect sizes of the associations, increased physical activity and daylight exposure might not be enough to improve sleep.

Association of Sleep and Physical Activity Among Older Adults and the Moderation of Chronotype

This study aimed to examine the associations of both subjectively and objectively measured sleep with physical activity among older adults and to explore the possible moderating role of chronotype in these associations. We included baseline data of 116 community-dwelling older adults without dementia from three prior studies. Pittsburgh Sleep Quality Index and Actigraphy were used as subjective and objective sleep measures, respectively. Physical activity was assessed by the Physical Activity Scale for the Elderly. The Morningness-Eveningness Questionnaire was used to measure chronotype, which was further dichotomized into morning type and non-morning type. Multiple linear regressions were performed to examine the associations, controlling for demographic and health characteristics. We found that better subjective sleep quality, shorter actigraphy sleep duration, and higher actigraphy sleep efficiency were uniquely associated with greater physical activity. Being a morning type might alleviate the adverse association between poor subjective sleep quality and physical activity among older adults.

Bidirectional associations between physical activity and sleep in older adults: a multilevel analysis using polysomnography

Although recent studies have examined the bidirectional associations between physical activity and sleep parameters, few have focused on older adults utilizing objective assessments, such as polysomnography. This micro-longitudinal observational study included 92 Japanese older adults (aged 65–86 years) who underwent objective evaluations of sleep quality using polysomnography and completed subjective sleep-related questionnaires. Activity levels were assessed using an accelerometer. Polysomnography, subjective sleep-related questionnaires, and accelerometer were administered for 7 consecutive days. Multilevel models (participant-, day-level) were used to examine the temporal associations of objective and subjective sleep parameters with sedentary behavior and physical activity. In the day-level analysis, higher levels of sedentary behavior during daytime were associated with longer rapid eye movement (REM) sleep, shorter REM latency, lower levels of non-REM sleep (stage N3), and reduced delta power during daytime. Higher levels of low-intensity physical activity during daytime were associated with lower levels of REM sleep, longer REM latency, and increased stage N3 sleep in the day-level analysis. Higher levels of moderate-to-vigorous physical activity were associated with increased REM latency. Longer subjective sleep time was associated with increased next-day moderate-to-vigorous physical activity. Thus, low-intensity physical activity may provide objective benefits related to deep sleep parameters in older adults.

The association between sleep deficits and sedentary behavior in people with mild Parkinson disease

Purpose: Sleep deficits are a common nonmotor symptom of Parkinson disease (PD). People with mild PD also achieve less physical activity (PA) than healthy older adults (HOA), but the relationship between sleep and PA in PD is unclear. This study examined associations between sleep and PA in participants with PD and HOA.Materials and Methods: Secondary analysis of a prospective observational study. Participants wore a commercially available activity monitor for two weeks. Wilcoxon Rank-Sum tests compared nighttime sleep, wakenings after sleep onset, number of wakenings, naps, step count, and PA intensity between PD and HOA groups. Age-adjusted regression models calculated associations between nighttime sleep and PA.Results: Per day, participants with PD slept 75 fewer minutes (p < 0.01), took 5,792 fewer steps (p < 0.001), achieved less PA at all intensities, and had 32% more sedentary time (p < 0.001) compared to HOA. Thirty minutes more sleep was associated with 26 fewer sedentary minutes for HOA (p = 0.01) and 25 fewer sedentary minutes for the PD group (p < 0.001).Conclusions: Sleep and PA are reduced in mild PD compared to HOA. Both groups demonstrated similar associations between reduced sleep and increased sedentary behavior. Results may encourage providers to screen for sleep deficits when promoting PA.IMPLICATIONS FOR REHABILITATIONThe use of a wrist-worn commercial activity and sleep monitor was well tolerated by both healthy older adults and people with mild Parkinson Disease in this study.People with mild Parkinson Disease slept less and were less active than a group of healthy older adults.Less sleep was associated with more sedentary behavior in both groups.The relationship between poor sleep and sedentary behavior in mild Parkinson Disease suggests that rehabilitation interventions may be optimized by targeting both physical activity and sleep deficits.

How are combinations of physical activity, sedentary behaviour and sleep related to cognitive function in older adults? A systematic review

The relationships between cognitive function and each of physical activity, sleep and sedentary behaviour in older adults are well documented. However, these three "time use" behaviours are co-dependent parts of the 24-hour day (spending time in one leaves less time for the others), and their best balance for cognitive function in older adults is still largely unknown. This systematic review summarises the existing evidence on the associations between combinations of two or more time-use behaviours and cognitive function in older adults. Embase, Pubmed, PsycInfo, Medline and Emcare databases were searched in March 2020 and updated in May 2021, returning a total of 25,289 papers for screening. A total of 23 studies were included in the synthesis, spanning >23,000 participants (mean age 71 years). Findings support previous evidence that spending more time in physical activity and limiting sedentary behaviour is broadly associated with better cognitive outcomes in older adults. Higher proportions of moderate-vigorous physical activity in the day were most frequently associated with better cognitive function. Some evidence suggests that certain types of sedentary behaviour may be positively associated with cognitive function, such as reading or computer use. Sleep duration appears to share an inverted U-shaped relationship with cognition, as too much or too little sleep is negatively associated with cognitive function. This review highlights considerable heterogeneity in methodological and statistical approaches, and encourages a more standardised, transparent approach to capturing important daily behaviours in older adults. Investigating all three time-use behaviours together against cognitive function using suitable statistical methodology is strongly recommended to further our understanding of optimal 24-hour time-use for brain function in aging.

Bi-Directional, Day-to-Day Associations between Objectively-Measured Physical Activity, Sedentary Behavior, and Sleep among Office Workers

The bi-directional, day-to-day associations between daytime physical activity and sedentary behavior, and nocturnal sleep, in office workers are unknown. This study investigated these associations and whether they varied by weekday or weekend day. Among 324 Swedish office workers (mean age 42.4 years; 33.3% men), moderate-to-vigorous physical activity (MVPA), and sedentary behaviors and sleep (total sleep time (TST) and sleep efficiency (SE)) were ascertained by using accelerometers (Actigraph GT3X) over 8 days. Multilevel linear mixed models were used to assess the bi-directional, day-to-day, within-person associations. Additional analyses stratified by weekend/weekday were performed. On average, participants spent 6% (57 min) of their day in MVPA and 59% (9.5 h) sedentary, and during the night, TST was 7 h, and SE was 91%. More daytime sedentary behavior was associated with less TST that night, and reciprocally, more TST at night was associated with less sedentary behavior on the following weekday. Greater TST during the night was also associated with less MVPA the next day, only on weekdays. However, daytime MVPA was not associated with TST that night. Higher nighttime SE was associated with greater time spent sedentary and in MVPA on the following day, regardless if weekday or weekend day. Sleep may be more crucial for being physically active the following day than vice versa, especially on weekdays. Nevertheless, sedentary behavior's relation with sleep time may be bi-directional. Office workers may struggle with balancing sleep and physical activity time.

Associations Among Sleep and Cancer Risk Behaviors: a Scoping Review of Experimental Studies in Healthy Adult Populations

BACKGROUND

Links among poor sleep and cancer risk behaviors have been largely overlooked in the context of cancer prevention and behavioral medicine. The goal of this scoping review was to determine the extent and nature of experimental studies conducted with healthy adult populations that tested the associations among poor sleep and cancer risk behaviors.

METHOD

Electronic databases and major sleep journals were searched to identify experimental studies in healthy adult samples published through January 2018. Studies examined associations among eight pairings of manipulated behaviors and outcomes ("independent variable (IV)-outcome pairs"): the impact of sleep manipulations on physical activity (PA), diet, alcohol consumption, and tobacco use outcomes; and the impact of PA, diet, alcohol consumption, and tobacco use manipulations on sleep outcomes. Studies were characterized in terms of sample characteristics; study design; IV type, dose, and duration; and outcome measurement and duration.

RESULTS

Abstracts of 5697 papers and 345 full texts were screened. Eighty-eight studies describing 125 comparisons met inclusion criteria. Only two studies tested the association between tobacco use and sleep; none tested whether sleep influenced alcohol consumption. Sample sizes were typically small, most studies used crossover designs, and studies tended to include younger and more male participants. Within each IV-outcome pair, there was substantial heterogeneity in how behaviors were manipulated, outcome measurement, and type of control group. Few studies assessed mechanisms.

CONCLUSION

There is a need for larger experimental studies with more representative samples. Overall, heterogeneity and limitations in study designs make it difficult to synthesize evidence across studies.

Bidirectional relationship between sleep and sedentary behavior in adults with overweight or obesity: A secondary analysis

Study Objectives

The relationships between daytime sedentary behavior and that night’s sleep and sleep and next day’s sedentary behavior are unknown. The purpose of this analysis was to examine these potentially bidirectional associations.

Methods

This study was a secondary analysis of baseline data from an ecological momentary assessment study to determine the triggers for dietary lapses during a weight loss intervention. Sedentary behavior, physical activity, and sleep were objectively measured using accelerometers. Linear mixed modeling was used to examine the bidirectional multivariate associations between activity and sleep characteristics for each outcome examined separately. The models included sex, age, body mass index (BMI), education, and day of the week (weekday vs. weekend).

Results

Participants were predominantly white (81.5%) and female (88.9%) with a mean age of 51.2 ± 10.6 years. Longer previous night’s total sleep time (TST) (b = −0.320, standard error [SE] = 0.060; p < .001) and being a weekend (b = −63.845, SE = 9.406; p < .001) were associated with less sedentary time the next day. More daytime sedentary time was associated with less wake after sleep onset (b = −0.018, SE = 0.008; p = .016), fewer awakenings (b = −0.010, SE = 0.004; p = .016), and less TST (b = −0.060, SE = 0.028; p = .029) that night.

Conclusions

The bidirectional relationships between sedentary time and sleep characteristics are complex and may vary depending on participant characteristics and duration of sedentary and sleep time. Interventions to decrease sedentary behavior may benefit by targeting sleep duration and weekday activity.

The bidirectional relationship between sleep and physical activity following traumatic brain injury

Sleep and physical activity are both modifiable behavioural factors that are associated with better health and are potentially related. Following traumatic brain injury, damage to the brain caused by an external force, sleep disturbances are common. Exploring bidirectional relationships between sleep and physical activity might provide insight into whether increasing physical activity could decrease these sleep disturbances. The current study, therefore, examined inter- and intra-individual temporal associations between sleep and daytime physical activity in 64 people with traumatic brain injury reporting sleep problems or fatigue (47 males; mean age, 40 years). Sleep and physical activity were measured using actigraphy with corroborating sleep diaries over 14 consecutive days. Multilevel models were used to examine inter- and intra-individual associations between physical activity and sleep. Inter-individual variations showed that earlier bedtimes, earlier wake-up times and lower sleep efficiency were associated with more physical activity. Intra-individual temporal variations showed no significant association of daytime physical activity with sleep duration or continuity. However, shorter sleep time and less wake after sleep onset than usual were associated with more time spent in light-intensity activity the next day. Therefore, sleep may have more of an influence on physical activity than physical activity has on sleep in people with traumatic brain injury. In conclusion, the results do not confirm a potential beneficial effect of physical activity on sleep but suggest that improving sleep quality might be relevant to support of a physically active lifestyle in people with traumatic brain injury. Further research is necessary to confirm these results.

Accelerometer-measured physical activity and its impact on sleep quality in patients suffering from restless legs syndrome

BACKGROUND

The primary symptoms of restless legs syndrome (RLS) are sleep onset insomnia and difficulty to maintain sleep. Previous studies have shown that regular physical activity can reduce the risk of developing RLS. However, the relationship between physical activity and sleep quality parameters in individuals suffering from RLS has not yet been investigated by applying accelerometry. Thus, the present study investigates the impact of physical activity (measuring both intensity levels and duration of physical activity) during the day (7-12 h, 12-18 h, 18-23 h) on sleep quality in patients suffering from idiopathic RLS by applying a real-time approach.

METHODS

In a sample of 47 participants suffering from idiopathic RLS, physical activity and sleep quality were measured over one week using accelerometers. For data analysis, physical activity levels and step counts during three periods of the day (morning, afternoon, evening) were correlated with sleep quality parameters of the subsequent night.

RESULTS

This observational study revealed that in most instances physical activity was not correlated with sleep parameters (two exceptions exist: steps taken in the morning were negatively correlated with periodic leg movements during sleep, and physical activity in the evening was negatively correlated with total sleep time). The physical activity levels of the participants in this study, however, were unexpectedly high compared to population-level data and variance in physical activity was low. The average activity was 13,817 (SD = 4086) steps and 347 (SD = 117) minutes of moderate physical activity per day in females, and 10,636 (SD = 3748) steps and 269 (SD = 69) minutes of moderate physical activity in males, respectively. Participants did not engage in any vigorous physical activity.

CONCLUSIONS

Further interventional studies are needed to investigate the daily effects of different intensities of physical activity on RLS symptoms.

Effect of exercise on sleep and bi-directional associations with accelerometer-assessed physical activity in men with obesity

This study examined the effect of exercise training on sleep duration and quality and bidirectional day-to-day relationships between physical activity (PA) and sleep. Fourteen inactive men with obesity (age: 49.2 ± 7.9 years, body mass index: 34.9 ± 2.8 kg/m²) completed a baseline visit, 8-week aerobic exercise intervention, and 1-month post-intervention follow-up. PA and sleep were assessed continuously throughout the study duration using wrist-worn accelerometry. Generalised estimating equations were used to examine associations between PA and sleep. Sleep duration increased from 5.2 h at baseline to 6.6 h during the intervention period and 6.5 h at 1-month post-intervention follow-up (p < 0.001). Bi-directional associations showed that higher overall activity volume and moderate-to-vigorous physical activity (MVPA) were associated with earlier sleep onset time (p < 0.05). Later timing of sleep onset was associated with lower overall volume of activity, most active continuous 30 min (M30_CONT), and MVPA (p < 0.05). Higher overall activity volume, M30_CONT, and MVPA predicted more wake after sleep onset (WASO) (p < 0.001), whereas greater WASO was associated with higher overall volume of activity, M30_CONT, and MVPA (p < 0.001). An aerobic exercise intervention increased usual sleep duration. Day-to-day, more PA predicted earlier sleep onset, but worse sleep quality and vice versa. Novelty: Greater levels of physical activity in the day were associated with an earlier sleep onset time that night, whereas a later timing of sleep onset was associated with lower physical activity the next day in men with obesity. Higher physical activity levels were associated with worse sleep quality, and vice versa.

The association between physical activity and a composite measure of sleep health

PURPOSE

Physical activity has been associated with several individual dimensions of sleep. However, the association between physical activity and sleep health, a construct that emphasizes the multidimensional nature of sleep, has not been explored. This analysis examined the relationship between physical activity and a composite measure of sleep health.

METHODS

A total of 114 adults (66% female, 60.3 ± 9.2 years) were included in the analyses. Participants reported daily light-intensity physical activity (LPA) and moderate- and vigorous-intensity physical activity (MVPA) via diary, while wearing a pedometer (Omron HJ-720ITC) to measure daily steps. Sleep health was measured using the RU_SATED questionnaire, which addresses regularity of sleep patterns, satisfaction with sleep, daytime alertness, and sleep timing, efficiency, and duration. Multiple linear regression, binary logistic regression, and analysis of covariance (ANCOVA) were utilized for analyses.

RESULTS

Mean sleep health score was 9.6 ± 2.4 (0 [poor]-12 [good]). Participants reported 62.9 ± 66.0 and 51.2 ± 51.2 min/day of LPA and MVPA, respectively, and took 5585.5 ± 2806.7 steps/day. Greater MVPA was associated with better sleep health (β = 0.27, P = 0.005) and sleep health scores differed between those reporting < 30 min/day and ≥ 60 min/day of MVPA (P = 0.004). Greater MVPA was associated with higher odds of having good sleep satisfaction (OR = 1.58 [1.14-2.20], P < 0.01), timing (OR = 2.07 [1.24-3.46], P < 0.01), and duration (OR = 1.48 [1.02-2.18], P = 0.04). Pedometer-based physical activity and LPA were not related to sleep health or its individual dimensions.

CONCLUSIONS

In middle- to older-aged adults, higher-intensity activity, but not lower-intensity or volume of activity, was associated with greater sleep health. These data suggest that physical activity intensity may be important for sleep health.