Temporal relationships between physical activity and sleep in older women

Assessing the level of device-measured physical activity according to insomnia symptoms in 1,354 individuals with diabetes: the HUNT Study, Norway

Background

Insomnia symptoms that influence daytime functioning are common among adults with type 2 diabetes. However, no previous study has examined if levels of physical activity differ among adults with diabetes with and without insomnia symptoms. Thus, the aim of this study was to assess the difference in total physical activity (TPA) and moderate-to-vigorous physical activity (MVPA) levels in individuals with diabetes with and without insomnia symptoms.

Methods

This cross-sectional study included 1,354 participants with any type of diabetes who participated in the Norwegian HUNT4 Study, 2017-19. Participants were defined to have 'insomnia symptoms' if they reported difficulty initiating and/or maintaining sleep ≥ 3 nights/week during the last 3 months. MVPA (defined as moderate/brisk walking [> 4.0 km/h], running, and cycling), and TPA (MVPA including slow walking [≤ 4.0 km/h]) were determined from two accelerometers worn on the thigh and lower back. Analyses were stratified by age and sex.

Results

The median age was 67 years and 491 (36%) had insomnia symptoms and 37 (3%) had insomnia disorder. Among women, 28% with one or more insomnia symptoms fulfilled the recommended minimum level of physical activity, as compared to 34% in women without insomnia symptoms. The corresponding proportions in men were 48% and 45%. Women above 65 years with insomnia symptoms performed less TPA (-73 min/week, 95% CI -122 to -24) and MVPA (-33 min/week, 95% CI -50 to -15), compared to women without insomnia symptoms in the same age group. There was no clear difference in physical activity levels according to insomnia symptoms in men or women below 65 years. Women and men with insomnia disorder had substantially lower TPA (women: -192 min/week, 95% CI -278 to -106; men: -276 min/week, 95% CI -369 to -193) and MVPA (women: -37 min/week, 95% CI -63 to -11; men: -67 min/week, 95% CI -83 to -50) than those without insomnia symptoms.

Conclusions

This study showed that women above 65 years with insomnia symptoms and individuals with insomnia disorder performed less physical activity, suggesting that these subgroups may suffer from additional challenges that prevent them from engaging in regular physical activity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44167-024-00066-4.

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.

Association Between Physical Activity Amount and Cardiorespiratory Fitness, Sleep Quality, and Health-Related Quality of Life in Patients With Long COVID: A Cross-sectional Study

OBJECTIVE

To investigate the association between physical activity (PA) amount and gender differences on cardiorespiratory fitness (CRF), sleep quality, and health-related quality of life (HRQoL) in individuals with long COVID.

DESIGN

Cross-sectional study.

SETTING

An integrated outpatient clinic for post-COVID-19 at a medical center.

PARTICIPANTS

Convenience sample of patients (N=264) diagnosed with long COVID.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

PA amounts, sleep quality, and HRQoL were measured by the International Physical Activity Questionnaire, Pittsburgh Sleep Quality Index, and the World Health Organization Questionnaire on Quality of Life: Short Form, respectively. CRF was evaluated through graded exercise testing.

RESULTS

The participants had a mean age of 42.5±13.5 years and a mean duration of post-COVID-19 symptoms of 12.7±6.8 weeks. More than half (n=149, 56.5%) were female patients. Female participants had significantly lower CRF than male participants (P<.05). Older age and higher body mass index were associated with worse CRF and HRQoL (P<.05). Less sitting behavior and greater amounts of vigorous-intensity PA (VPA) or total PA were associated with better CRF (P<.05). In addition, greater total PA and moderate-intensity PA (MPA) were associated with better sleep quality and HRQoL (P<.05), respectively.

CONCLUSIONS

Gender differences were found in CRF among patients with long COVID. Greater self-reported VPA or total PA was associated with better CRF, whereas greater total PA and MPA were associated with better sleep quality and HRQoL, respectively, in patients with long COVID. Further research is needed to explore these associations in longitudinal studies.

The 24-h activity cycle and cardiovascular outcomes: establishing biological plausibility using arterial stiffness as an intermediate outcome

This review proposes a biologically plausible working model for the relationship between the 24-h activity cycle (24-HAC) and cardiovascular disease. The 24-HAC encompasses moderate-to-vigorous physical activity (MVPA), light physical activity, sedentary behavior (SB), and sleep. MVPA confers the greatest relative cardioprotective effect, when considering MVPA represents just 2% of the day if physical activity guidelines (30 min/day) are met. While we have well-established guidelines for MVPA, those for the remaining activity behaviors are vague. The vague guidelines are attributable to our limited mechanistic understanding of the independent and additive effects of these behaviors on the cardiovascular system. Our proposed biological model places arterial stiffness, a measure of vascular aging, as the key intermediate outcome. Starting with prolonged exposure to SB or static standing, we propose that the reported transient increases in arterial stiffness are driven by a cascade of negative hemodynamic effects following venous pooling. The subsequent autonomic, metabolic, and hormonal changes further impair vascular function. Vascular dysfunction can be offset by using mechanistic-informed interruption strategies and by engaging in protective behaviors throughout the day. Physical activity, especially MVPA, can confer protection by chronically improving endothelial function and associated protective mechanisms. Conversely, poor sleep, especially in duration and quality, negatively affects hormonal, metabolic, autonomic, and hemodynamic variables that can confound the physiological responses to next-day activity behaviors. Our hope is that the proposed biologically plausible working model will assist in furthering our understanding of the effects of these complex, interrelated activity behaviors on the cardiovascular system.

Poor Sleep Quality and Working From Home Influence the Prevalence of Leisure Time Physical Inactivity During the COVID-19 Pandemic: COVID-Inconfidentes Study

OBJECTIVE

The aim of the study is to explore possible associations according to quality of sleep and work from home (WFH) with physical inactivity (PI) during the COVID-19 pandemic.

METHODS

This is a cross-sectional study in two Brazilian cities (>18 years), by probability sampling. Leisure-time physical activity was self-reported and classified according to guidelines. Sleep was by applying the Pittsburgh Sleep Quality Index. Work from home was classified as: total WFH or no WFH.

RESULTS

A total of 1750 adults were analyzed, 69.1% were physically inactive, 51.9% had poor sleep quality, and 79.8% were not in WFH. PI was associated with poor sleep quality and non-WFH. Compared with those who reported WFH and good sleep quality, those who reported non-WFH and poor sleep quality had 4 times the prevalence of PI.

CONCLUSIONS

Poor sleep quality, and not WFH, is associated with leisure PI. These factors combined increase the probability of PI.

Sleep characteristics modify the associations of physical activity during pregnancy and gestational weight gain

OBJECTIVE

Excessive gestational weight gain (eGWG) is associated with adverse long-term maternal outcomes. Most lifestyle interventions that incorporate physical activity have been ineffective at reducing eGWG. The purpose of this study was to determine if sleep modified the relationships between physical activity change from the 2nd to 3rd trimester and the odds of excessive gestational weight gain (eGWG).

METHODS

This was a secondary data analysis of a prospective cohort study of pregnant birthing people with overweight or obesity (n = 105). We estimated physical activity energy expenditure (PAEE) in the 2nd and 3rd trimesters of pregnancy and sleep characteristics (i.e., sleep quality, daytime dysfunction, sleep efficiency, sleep duration) in the 2nd trimester of pregnancy with validated measures. We used regression models with sleep and PAEE change (increase/stable vs. decrease) interaction terms to examine the impact of sleep on PAEE change and eGWG.

RESULTS

Mean GWG was 37.02 ± 16.76 lbs. and 80% of participants experienced eGWG. Eighteen percent of participants increased their PAEE from the 2nd to the 3rd trimester. Increasing (vs. decreasing) PAEE was associated with lower log-odds of eGWG only among participants that slept at least 8 h/night (p = 0.06), had at least 85% sleep efficiency (p = 0.03), or reported less daytime dysfunction (p = 0.08). Sleep quality did not moderate the association between PAEE change and eGWG.

CONCLUSIONS

Weight management interventions in pregnancy should consider screening for and addressing poor sleep in the second trimester.

Sleep-wake patterns are altered with age, Prdm13 signaling in the DMH, and diet restriction in mice

Old animals display significant alterations in sleep-wake patterns such as increases in sleep fragmentation and sleep propensity. Here, we demonstrated that PR-domain containing protein 13 (Prdm13)+ neurons in the dorsomedial hypothalamus (DMH) are activated during sleep deprivation (SD) in young mice but not in old mice. Chemogenetic inhibition of Prdm13+ neurons in the DMH in young mice promotes increase in sleep attempts during SD, suggesting its involvement in sleep control. Furthermore, DMH-specific Prdm13-knockout (DMH-Prdm13-KO) mice recapitulated age-associated sleep alterations such as sleep fragmentation and increased sleep attempts during SD. These phenotypes were further exacerbated during aging, with increased adiposity and decreased physical activity, resulting in shortened lifespan. Dietary restriction (DR), a well-known anti-aging intervention in diverse organisms, ameliorated age-associated sleep fragmentation and increased sleep attempts during SD, whereas these effects of DR were abrogated in DMH-Prdm13-KO mice. Moreover, overexpression of Prdm13 in the DMH ameliorated increased sleep attempts during SD in old mice. Therefore, maintaining Prdm13 signaling in the DMH might play an important role to control sleep-wake patterns during aging.

Altered motivation states for physical activity and 'appetite' for movement as compensatory mechanisms limiting the efficacy of exercise training for weight loss

Weight loss is a major motive for engaging in exercise, despite substantial evidence that exercise training results in compensatory responses that inhibit significant weight loss. According to the Laws of Thermodynamics and the CICO (Calories in, Calories out) model, increased exercise-induced energy expenditure (EE), in the absence of any compensatory increase in energy intake, should result in an energy deficit leading to reductions of body mass. However, the expected negative energy balance is met with both volitional and non-volitional (metabolic and behavioral) compensatory responses. A commonly reported compensatory response to exercise is increased food intake (i.e., Calories in) due to increased hunger, increased desire for certain foods, and/or changes in health beliefs. On the other side of the CICO model, exercise training can instigate compensatory reductions in EE that resist the maintenance of an energy deficit. This may be due to decreases in non-exercise activity thermogenesis (NEAT), increases in sedentary behavior, or alterations in sleep. Related to this EE compensation, the motivational states associated with the desire to be active tend to be overlooked when considering compensatory changes in non-exercise activity. For example, exercise-induced alterations in the wanting of physical activity could be a mechanism promoting compensatory reductions in EE. Thus, one's desires, urges or cravings for movement-also known as "motivation states" or "appetence for activity"-are thought to be proximal instigators of movement. Motivation states for activity may be influenced by genetic, metabolic, and psychological drives for activity (and inactivity), and such states are susceptible to fatigue-or reward-induced responses, which may account for reductions in NEAT in response to exercise training. Further, although the current data are limited, recent investigations have demonstrated that motivation states for physical activity are dampened by exercise and increase after periods of sedentarism. Collectively, this evidence points to additional compensatory mechanisms, associated with motivational states, by which impositions in exercise-induced changes in energy balance may be met with resistance, thus resulting in attenuated weight loss.

The association between multidimensional sleep health and gestational weight gain: nuMoM2b Sleep Duration and Continuity Study

Background

Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep-health framework is needed. This study examined associations among mid-pregnancy sleep health indicators, multidimensional sleep health, and gestational weight gain (GWG).

Methods

We conducted a secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n=745). Indicators of individual sleep domains (i.e., regularity, nap duration, timing, efficiency, and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined "healthy" sleep in each domain based on empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD), and high (>+1 SD).

Results

Nearly 50% of the participants had a healthy sleep profile (i.e., healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of poor health in each domain. While indicators of individual sleep domains were not associated with GWG, multidimensional sleep health was related to low and high GWG. Participants with a sleep profile characterized as having low efficiency, late timing, and long sleep duration (vs. healthy sleep profile) had a higher risk (RR 1.7; 95% CI 1.0, 3.1) of low GWG a lower risk of high GWG (RR 0.5 95% CI 0.2, 1.1) (vs. moderate GWG).

Conclusions

Multidimensional sleep health was more strongly associated with GWG than individual sleep domains. Future research should determine whether sleep health is a valuable intervention target for optimizing GWG.

Synopsis

Study question: What is the association between mid-pregnancy multidimensional sleep health and gestational weight gain?What's already known?: Sleep is associated with weight and weight gain outside of pregnancyWhat does this study add?: We identified patterns of sleep behaviors associated with an increased risk of low gestational weight gain.

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.

[The relationship between physical activity and sleep status among older adults requiring nursing care in the community]

AIM

We investigated the relationship between physical activity and sleep status among older adults requiring nursing care in the community.

METHOD

We included 45 participants ≥65 years old (33 females; mean age, 83.2±4.4 years old) requiring nursing care. Physical activity was evaluated using the Life Space Assessment (LSA), and sleep status was measured by the Pittsburg Sleep Quality Index (PSQI) to determine the total sleep time, sleep efficiency, and PSQI total score. The physical function was measured by the timed up and go test (TUG) and grip strength. We performed a multiple regression analysis with the LSA as the dependent variable and sleep indicators (total sleep time, sleep efficiency, PSQI total score) and TUG as independent variables (demonstrating significant correlations with the LSA), and gender and age as adjusted variables. The analysis was divided into sleep time (Model 1), sleep efficiency (Model 2), and PSQI total score (Model 3). We used R commander, and < 0.05 was considered statistically significant.

RESULTS

TUG (β=-0.375) and sleep time (β=0.383) in Model 1, TUG (β=-0.368) and sleep efficiency (β=0.570) in Model 2, and TUG (β=-0.392) and PSQI total score (β=-0.590) in Model 3 were independently selected as significant variables.

CONCLUSION

In addition to TUG, sleep status, such as the sleep duration and sleep quality, was shown to be related to physical activity in older adults who require nursing care. To improve physical activity, it is necessary to consider not only the physical function but also quantitative and qualitative assessments of 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.

Exploring the Effects of Perceived Stress on the Within-Person Relationships Between Daily Activity Levels and Sleep in Women: An Ecological Momentary Assessment Study

BACKGROUND

Many studies show positive bidirectional associations between physical activity (PA) and sleep at the between-person level. There is an increased interest in investigating these associations at the within-person level. Few studies examined the effects of time-varying moderators on the within-person bidirectional associations between PA and sleep. This study aimed to examine the bidirectional within-person day-level associations between activity levels and self-reported sleep duration and explore the moderating effects of perceived stress on these day-level associations.

METHOD

Data from 158 women that included 7-day free-living monitoring over 4 measurement periods was analyzed using multilevel modeling to explore the moderating effects of daily stress on the bidirectional, within-person associations between activity levels and self-reported sleep duration. Moderate-to-vigorous PA (MVPA) and sedentary behavior (SB) were estimated from a waist-worn accelerometer. Self-reported sleep duration and perceived stress were collected by ecological momentary assessment.

RESULTS

No significant within-person associations between MVPA minutes and self-reported sleep duration were found in either direction. However, engaging in more MVPA than one's usual level was associated with longer sleep later that night when perceived stress was higher than usual (p = .04). Bidirectional negative within-person association between SB minutes and self-reported sleep duration was found (ps < .01). The negative association between SB and sleep duration later that night was stronger when perceived stress was lower than usual (p = .01).

CONCLUSION

Daily stress played an important role in the day-to-day associations between activity levels and sleep.

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.

Short-term effect of physical activity on sleep health: A population-based study using accelerometry

BACKGROUND

Regular physical activity (PA) is an important behavior in improving sleep health. However, the short-term effects of PA on sleep are still controversial. This study aimed to verify the effect of different intensities of PA practiced in different periods of the day on the subsequent sleep night in a population-based cohort of young adults.

METHODS

Prospective analyses were conducted for PA performed during the day and its effect on the following sleep night using data from the 22-year follow-up of the 1993 Pelotas Birth Cohort in Brazil (mean age of participants = 22.6 years). Wrist-worn accelerometry was used to measure both PA and sleep parameters. Regarding intensity, we analyzed the sleep effect of light PA (LPA), moderate PA, and vigorous PA, stratified by sex. Sleep variables were sleep time window (STW; the difference between sleep onset and sleep end), total sleep time (TST; the sum of minutes classified as sleep in STW), and sleep percent (SP; SP = (TST/STW); expressed in percentage). We performed generalized estimating equations using Stata software.

RESULTS

The means of STW, TST, and SP were 443.6 min/day, 371.1 min/day, and 84%, respectively. Time spent in moderate PA and vigorous PA in the morning and afternoon was not associated with sleep variables. Among men, 10 min/day of morning LPA increased TST by 2.56 min/day. Among women, 10 min/day of morning LPA increased SP by 0.15 percentage points. Afternoon LPA also increased SP by 0.09 percentage points for women. Night PA seems to have an inverse effect on sleep variables for any intensity and both sexes.

CONCLUSION

The effect of PA on sleep health is intrinsically related to the period of the day in which it is performed. The effect magnitude is different between sexes. For better sleep health, it is preferable that PA be performed during the day.

Associations of environmental and lifestyle factors with spatial navigation in younger and older adults

OBJECTIVE

Advanced age is associated with prominent impairment in allocentric navigation dependent on the hippocampus. This study examined whether age-related impairment in allocentric navigation and strategy selection was associated with sleep disruption or circadian rest-activity fragmentation. Further, we examined whether associations with navigation were moderated by perceived stress and physical activity.

METHOD

Sleep fragmentation and total sleep time over the course of 1 week were assayed in younger (n = 42) and older (n = 37) adults via wrist actigraphy. Subsequently, participants completed cognitive mapping and route learning tasks, as well a measure of spontaneous navigation strategy selection. Measurements of perceived stress and an actigraphy-based index of physical activity were also obtained. Circadian rest-activity fragmentation was estimated via actigraphy post-hoc.

RESULTS

Age was associated with reduced cognitive mapping, route learning, allocentric strategy use, and total sleep time (ps < .01), replicating prior findings. Novel findings included that sleep fragmentation increased with advancing age (p = .009) and was associated with lower cognitive mapping (p = .022) within the older adult cohort. Total sleep time was not linearly associated with the navigation tasks (ps > .087). Post-hoc analyses revealed that circadian rest-activity fragmentation increased with advancing age within the older adults (p = .026) and was associated with lower cognitive mapping across the lifespan (p = .001) and within older adults (p = .005). Neither stress nor physical activity were robust moderators of sleep fragmentation associations with the navigation tasks (ps > .113).

CONCLUSION

Sleep fragmentation and circadian rest-activity fragmentation are potential contributing factors to age effects on cognitive mapping within older adults.

Evaluation of the sleep hygiene index and physical activity states of the elderly living in nursing homes

The aim: the sleep quality and physical performance play a vital role in older adults’ well-being to maintain good overall health. Therefore, the parameters that have a role in sleep and physical capacity are crucial to achieve a healthy aging outcome. In this study, we aimed at comparing the quality of sleep and physical activity state of the elderly living in 5 nursing homes. Methods: the 181 elderly individuals living in 5 nursing homes were included in this cross-sectional study. Physical activity, sleep hygiene index and demographics were analysed using SPPS 23.0. Results: overall, 68.5 % of the participants were male, and 31.5 % were female. There was no significant correlation between the sleep hygiene scores and physical activity states (p >0.05). Those who were divorced, those who were on at least one type of medication, those who smoked and those with poor perception of health had statistically significant difference in terms of the Sleep Hygiene Index (p<0.05). Conclusion: other than findings of the presented study that influence sleep and physical activity, the many other factors in different geographical areas or cultures could be a reason that is interrelated with sleep quality and physical performance of older adults. In this study, for primary care and family physicians to boost the sleep quality of the elderly, we recommend improving their health perception, quitting smoking, discontinuing unnecessary medications, and increasing their social interactions

Productive engagement, sleep-wake disturbances, and loneliness: SEM analysis of depressive symptoms of community-dwelling Chinese elders

OBJECTIVES

This study set out to examine the bidirectional relationship between loneliness and productive engagement, delineate the association between different dimensions of productive engagement and depression, and explore the potential mediating effect of sleep-wake disturbances in the relationship between loneliness and/or productive engagement and depression.

METHOD

Data from a total of 4427 older adults in China were included in the analysis. Factor analysis was conducted to explore a set of discrete dimensions of productive engagement (recreational activities, group artistic and learning activities, sportive activities, paid work, volunteering, and family caregiving). Structural equation modeling was used to assess the potential relationships between loneliness, multidimensional productive engagement, sleep-wake disturbances, and depression.

RESULTS

All dimensions of productive engagement were found to be negatively associated with loneliness, except for paid work which was associated with elevated level of self-reported loneliness. Sleep-wake disturbances mediated the relationship between leisure activities and depression but this was not significantly related to other forms of productive engagement. The direct effect of productive engagement on depression varied, in that leisure activities and family caregiving were negatively associated with depressive symptoms, while doing paid work was positively associated with depressive symptoms. Volunteering was not significantly related to depressive symptoms.

DISCUSSION

This study makes an important contribution to the research on the relationship between loneliness, productive engagement, sleep-wake disturbances, and depression, by distinguishing the different effects of different dimensions of productive engagement. The findings provide a robust stimulus for intervention programs and other forms of social work practice seeking to mitigate depressive symptoms in older adults.

A Systematic Review of the Relationships Between Physical Activity and Sleep in Early Childhood

The aim of this systematic review was to examine the associations between physical activity and sleep in children aged less than 6 years. Articles were included if participants were primarily aged less than 6 years and study designs were observational or experimental. Study characteristics were extracted, and the Grading Recommendations Assessment, Development and Evaluation framework was used to assess study quality. Thirty-six studies (16 sleep, 16 physical activity, and three fitness outcomes) from 18 countries reported in 29 articles were included. The majority of sleep and physical activity outcome studies reported mixed effects with very low to low quality of evidence. Fitness outcome studies were limited, and therefore, evidence was insufficient. The high prevalence of mixed and null results could be related to study limitations. Importantly, this review points to the critical need for higher quality studies of sleep and physical activity in young children, which would support health recommendations and intervention strategies for healthier child development.

Sleep Health Characteristics among Adults Who Attempted Weight Loss in the Past Year: NHANES 2017-2018

Background: The purpose of this study was to characterize sleep health in adults who attempted weight loss in the prior year. Methods: We analyzed data from the National Health and Nutrition Examination Survey 2017–2018 exam cycle. We included 4837 US adults who did (n = 1919) or did not (n = 2918) attempt weight loss in the past year. Participants self-reported their sleep regularity, satisfaction, sleepiness, timing, and duration, which we defined as “good” based on the prior literature. We characterized sleep health by weight loss attempts status, current BMI and weight change among participants who attempted weight loss. Results: On average, participants reported good sleep health in 3.21 ± 1.14 out of the five sleep domains. A total of 13% of participants had good sleep health in all five domains. The prevalence of sleep regularity (52%) was lowest, and the prevalence of infrequent sleepiness was highest (72%), relative to other sleep domains. In models adjusting for BMI, sleep health was similar in participants who did and did not attempt weight loss. Among adults who attempted weight loss, good sleep health was inversely associated with current BMI and self-reported weight change. Discussion: This study’s findings highlight the importance of considering sleep health when engaging with adults attempting weight loss.

Investigating the within-person relationships between activity levels and sleep duration using Fitbit data

The advancement of wearable technologies provides opportunities to continuously track individuals' daily activity levels and sleep patterns over extended periods of time. These data are useful in examining the reciprocal relationships between physical activity and sleep at the intrapersonal level. The purpose of this study is to test the bidirectional relationships between daily activity levels and sleep duration. The current study analyzed activity and sleep data collected from a Fitbit device as part of a 6 month employer-sponsored weight loss program. A total of 105 overweight/obese adults were included (92% female, 70% obese, and 44% Hispanic). Multilevel models were used to examine (a) whether daily active and sedentary minutes predicted that night's sleep duration and (b) whether sleep duration predicted active and sedentary minutes the following day. Potential extended effects were explored by using a 2 day average of the activity minutes/sleep duration as the predictor. No significant relationships between active minutes and sleep duration were found on a daily basis. However, having less sleep over two nights than one's usual level was associated with an increased likelihood of engaging in some physical activity the following day. There was a significant bidirectional negative association between sedentary minutes and sleep duration for both the daily and 2 day models. Data from wearable trackers, such as Fitbit, can be used to investigate the daily within-person relationship between activity levels and sleep duration. Future studies should investigate other sleep metrics that may be obtained from wearable trackers, as well as potential moderators and mediators of daily activity levels and sleep.

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.

Fluctuations in Self-Reported Symptoms Predict Objective Physical Activity in Adults With Type 2 Diabetes

PURPOSE

The purpose of this study was to examine the association between self-reported symptoms including fatigue and sleep disturbance with moderate-intensity physical activity among adults with type 2 diabetes.

METHODS

This report was a secondary analysis of a cross-sectional study. Data from 53 participants with at least 6 days of repeated measures were used. Daytime physical activity and energy expenditure were assessed using a wrist-worn accelerometer at the free-living setting. Fatigue upon awakening was measured using a 0 to 10 scale. Sleep (eg, restorative sleep, sleep duration, and sleep efficiency) was measured using the Consensus Sleep Diary for Morning. Data were analyzed using linear mixed models by including within- and between-person effects.

RESULTS

Participants were predominantly females (54.7%) with a mean age of 60.3 years. Controlling for the covariates, at the individual level (within-person), fluctuations in restorative sleep and fatigue upon awakening predicted moderate-intensity PA. Similarly, at the individual level, fluctuations in restorative sleep and fatigue upon awakening predicted average hourly energy expenditure. However, at the group level (between-person), no significant associations were found between fatigue and restorative sleep with moderate-intensity physical activity.

CONCLUSIONS

The study findings suggest that within-person fluctuations in fatigue and restorative sleep upon awakening predict daytime moderate-intensity physical activity. At the individual level, reducing fluctuations in fatigue and restorative sleep might encourage participation in physical activity. More research is warranted to uncover the underlying causes of fluctuations in fatigue and restorative sleep. Meanwhile, diabetes care and education specialists should pay attention to the within-person fluctuations of fatigue and sleep.

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.

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.

Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring

In the midst of the COVID-19 pandemic, Remote Patient Monitoring technologies are highly important for clinicians and researchers. These connected-health technologies enable monitoring of patients and facilitate remote clinical trial research while reducing the potential for the spread of the novel coronavirus. There is a growing requirement for monitoring of the full 24 h spectrum of behaviours with a single research-grade sensor. This research describes a free-living and supervised protocol comparison study of the Verisense inertial measurement unit to assess physical activity and sleep parameters and compares it with the Actiwatch 2 actigraph. Fifteen adults (11 males, 23.4 ± 3.4 years and 4 females, 29 ± 12.6 years) wore both monitors for 2 consecutive days and nights in the free-living study while twelve adults (11 males, 23.4 ± 3.4 years and 1 female, 22 ± 0 years) wore both monitors for the duration of a gym-based supervised protocol study. Agreement of physical activity epoch-by-epoch data with activity classification of sedentary, light and moderate-to-vigorous activity and sleep metrics were evaluated using Spearman's rank-order correlation coefficients and Bland-Altman plots. For all activity, Verisense showed high agreement for both free-living and supervised protocol of r = 0.85 and r = 0.78, respectively. For physical activity classification, Verisense showed high agreement of sedentary activity of r = 0.72 for free-living but low agreement of r = 0.36 for supervised protocol; low agreement of light activity of r = 0.42 for free-living and negligible agreement of r = -0.04 for supervised protocol; and moderate agreement of moderate-to-vigorous activity of r = 0.52 for free-living with low agreement of r = 0.49 for supervised protocol. For sleep metrics, Verisense showed moderate agreement for sleep time and total sleep time of r = 0.66 and 0.54, respectively, but demonstrated high agreement for determination of wake time of r = 0.83. Overall, our results showed moderate-high agreement of Verisense with Actiwatch 2 for assessing epoch-by-epoch physical activity and sleep, but a lack of agreement for activity classifications. Future validation work of Verisense for activity cut-point potentially holds promise for 24 h continuous remote patient monitoring.

Associations of Sleep With Sedentary Behavior and Physical Activity Patterns Across Pregnancy Trimesters

INTRODUCTION

Sleep, sedentary behavior, and moderate-to-vigorous physical activity (MVPA) are altered in pregnancy and may affect pregnancy health; however, how these behaviors are associated with each other is unclear.

METHODS

Pregnant women (N = 120) completed the Pittsburgh Sleep Quality Index and wore an activPAL3 micro and ActiGraph GT3X for 7 days in each trimester to assess sleep, sedentary behavior, and MVPA, respectively. Latent trajectories described patterns of sleep duration, efficiency, and quality as well as sedentary behavior and MVPA. Multinomial logistic regression examined associations of sleep patterns with sedentary behavior and MVPA patterns and, in exploratory analyses, with adverse pregnancy outcomes.

RESULTS

Trajectories were identified for sleep duration (consistently short, 20.7% of sample; consistently adequate, 79.3%), efficiency (consistently low, 17.5%; consistently high, 82.5%), and quality (consistently poor, 15.1%; worsening, 23.5%; and consistently good, 61.5%). Compared with those in more optimal sleep groups, women in the short duration, low efficiency, and worsening quality groups had lower odds of being in the moderate and/or high sedentary behavior group (odds ratio range, 0.21-0.31; 95% confidence interval range, 0.09-0.65). Women in the worsening quality group had greater odds of being in the low MVPA group (odds ratio, 2.51; 95% confidence interval, 1.18-5.38). Trends were observed with women in less optimal sleep groups having greater odds of adverse pregnancy outcomes and lower odds of excessive gestational weight gain.

CONCLUSIONS

Less optimal sleep patterns in pregnancy are associated with less sedentary behavior and MVPA; additional research is needed to confirm associations between sleep and pregnancy outcomes.

Benefits and promotion of physical activity in rheumatoid arthritis

PURPOSE OF REVIEW

The aim of this article is to describe the benefits of physical activity and exercise on rheumatoid arthritis disease activity, functioning, and symptoms; and offer recommendations for promotion of physical activity and exercise among people with rheumatoid arthritis.

RECENT FINDINGS

In addition to well-known benefits of exercise such as improving cardiovascular health and metabolic syndrome and reducing obesity, exercise has consistently shown rheumatoid arthritis-specific benefits. Exercise and increases in physical activity improve clinically measured disease activity, reduce symptoms such as fatigue and pain, and improve function and mental health. In spite of these benefits, most people with rheumatoid arthritis are inactive. Patient barriers to engaging in physical activity may include fears of joint damage, rheumatoid arthritis symptoms, and lack of understanding that physical activity improves the symptoms that may be barriers. However, the greatest barrier to healthy levels of physical activity among individuals with rheumatoid arthritis appears to be the lack of direction from healthcare providers.

SUMMARY

Exercise is safe and highly beneficial for people with rheumatoid arthritis. Because receiving recommendations from healthcare providers may be the factor most strongly associated with engaging in physical activity or exercise, providers are encouraged to give patients positive messages about the benefits of physical activity and the extremely low risks of harm.

Daily associations between sleep and physical activity: A systematic review and meta-analysis

The day-to-day variations of sleep and physical activity are associated with various health outcomes in adults, and previous studies suggested a bidirectional association between these behaviors. The daily associations between sleep and physical activity have been examined in observational or interventional contexts. The primary goal of the current systematic review and meta-analysis was to summarize existing evidence about daily associations between sleep and physical activity outcomes at inter- and intra-individual level in adults. A systematic search of records in eight databases from inception to July 2019 identified 33 peer-reviewed empirical publications that examined daily sleep-physical activity association in adults. The qualitative and quantitative analyses of included studies did not support a bidirectional daily association between sleep outcomes and physical activity. Multilevel meta-analyses showed that three sleep parameters were associated with physical activity the following day: sleep quality, sleep efficiency, and wake after sleep onset. However, the associations were small, and varied in terms of direction and level of variability (e.g., inter- or intra-individual). Daytime physical activity was associated with lower total sleep time the following night at an inter-person level with a small effect size. From a clinical perspective, care providers should monitor the effects of better sleep promotion on physical activity behaviors in their patients. Future studies should examine sleep and physical activity during a longer period and perform additional sophisticated statistical analyses. SYSTEMATIC REVIEW REGISTRATION: https://osf.io/w6uy5/.

Day-to-day Relationships between Physical Activity and Sleep Characteristics among People with Heart Failure and Insomnia

OBJECTIVE

Examine the bidirectional relationships between within-person day-to-day fluctuations in physical activity (PA) and sleep characteristics among people with heart failure (HF) and insomnia.

PARTICIPANTS

Ninety-seven community-dwelling adults [median age 61.9 (interquartile range 55.3,70.9) years, female 41%] with stable HF and insomnia (insomnia severity index >7).

METHODS

This sub-study longitudinally analyzed 15 consecutive days and nights of wrist actigraphy recordings, that were collected for baseline data prior to participation in a randomized controlled trial of cognitive behavioral therapy for insomnia. We used two-level mixed models of within- (daily) and between-participants variation to predict daytime PA counts/minutes from sleep variables (total sleep time, sleep efficiency) and predict sleep variables from PA.

RESULTS

PA counts/minutes were low compared to prior cohorts that did not have HF (209 (166,259)) and negatively associated with NYHA class (standardized coefficient β_s = -0.14, p < .01), age (β_s = -0.13, p = .01), comorbidities (β_s = -0.19, p < .01), and body mass index (β_s = -0.12, p = .04). After adjustment for all significant covariates, the within-participant association of total sleep time with next-day PA was estimated to be positive among participants with NYHA class II-IV HF (β_s = 0.09, p = .01), while the within-participant association of PA with same-night total sleep time was estimated to be positive among participants aged ≥60 years (β_s = 0.10, p = .03).

CONCLUSIONS

Depending upon age and HF class, daytime PA was associated with longer same-night sleep and/or longer sleep was associated with greater next-day PA. Among those with more advanced HF, realistic sleep improvements were associated with clinically meaningful PA gains the next day.

Association between objectively measured walking steps and sleep in community-dwelling older adults: A prospective cohort study

Physical inactivity and sleep disturbances are major problems in an ageing society. There is increasing evidence that physical activity is associated with sleep quality. However, the association between daily walking steps and sleep remain unclear. This prospective study examined the relationship between objectively measured daily walking steps and sleep parameters in Japanese community-dwelling older adults. In total, 855 community-dwelling individuals aged 65 and above, with an uninterrupted follow-up from August 2015 to March 2016, were enrolled. The participants wore a wristband sensor for an average of 7.8 days every three months. Multiple linear regression analysis was performed to examine the relationship between daily walking steps and sleep parameters, including the total sleep time, sleep efficiency, time awake after sleep onset (WASO), awakening time count during the night, and naptime. The median (interquartile range, IQR) age of the participants was 73 (69–78) years, with 317 (37.1%) men and 538 (62.9%) women. The median (IQR) educational level was 12 (11–12) years, and the median (IQR) Mini-Mental State Examination score was 29 (27–30) points. The number of daily walking steps showed a positive correlation with sleep efficiency and an inverse correlation with WASO, awakening time count, and naptime, after adjusting for covariates and correcting for the false discovery rate (β = 0.098, 95% confidence interval [CI]: 0.034 to 0.162, p = 0.003; β = −0.107, 95% CI: −0.172 to −0.043, p = 0.001; β = −0.105, 95% CI: −0.17 to −0.04, p = 0.002; and β = −0.31, 95% CI: −0.371 to −0.249, p < 0.001, respectively). Our results can help promote walking as an intervention for preventing sleep disturbances in community-dwelling older adults.

Bidirectional Day-to-Day Associations of Reported Sleep Duration With Accelerometer Measured Physical Activity and Sedentary Time Among Dutch Adolescents: An Observational Study

Objectives

To examine the bidirectional association of sleep duration with proportions of time spent in physical behaviors among Dutch adolescents.

Methods

Adolescents (n = 294, 11-15 years) completed sleep diaries and wore an accelerometer (ActiGraph) over 1 week. With linear mixed-effects models, the authors estimated the association of sleep categories (short, optimal, and long) with the following day's proportion in physical behaviors. With generalized linear mixed models with binomial distribution, the authors estimated the association of physical behavior proportions on sleep categories. Physical behavior proportions were operationalized using percentages of wearing time and by applying a compositional approach. All analyses were stratified by gender accounting for differing developmental stages.

Results

For males (number of observed days: 345, n = 83), short as compared with optimal sleep was associated with the following day's proportion spent in sedentary (-2.57%, p = .03, 95% confidence interval [CI] [-4.95, -0.19]) and light-intensity activities (1.96%, p = .02, 95% CI [0.27, 3.65]), which was not significant in the compositional approach models. Among females (number of observed days: 427, n = 104), long sleep was associated with the proportions spent in moderate- to vigorous-intensity physical activity (1.69%, p < .001, 95% CI [0.75, 2.64]) and in sedentary behavior (-3.02%, p < .01, 95% CI [-5.09, -0.96]), which was replicated by the compositional approach models. None of the associations between daytime activity and sleep were significant (number of obs.: 844, n = 204).

Conclusions

Results indicate partial associations between sleep and the following day's physical behaviors, and no associations between physical behaviors and the following night's sleep.

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.

Sleep disturbance and next-day physical activity in COPD patients

Physical inactivity and sleep disturbance are more problematic in patients with chronic obstructive pulmonary disease (COPD) than in healthy individuals. The purpose of the study was to identify impacts of nighttime sleep on next-day physical activity in COPD patients. The study included 52 COPD patients reporting disturbed sleep. Sleep and physical activity were measured using an accelerometer for 5 days. Increased sleep latency was associated with less next-day physical activity during the afternoon (4-6 p.m.). Greater waking duration/times were associated with less next-morning (6-8 a.m.) physical activity. Greater total sleep time was associated with less next-morning (12-9 a.m.) physical activity, and greater sleep efficiency was associated with less next-morning (1-3 a.m.) and more next-evening (6-7 p.m.) physical activity. Results suggest that sleep disturbance had varying influences on next-day hourly physical activity. These results support the potential value of sleep management in promoting physical activity in COPD patients.

Associations of physical activity and sleep with cardiometabolic risk in older women

In this study, we investigate the associations of objectively measured waking (sedentary, light physical activity [LPA] and moderate-to-vigorous physical activity [MVPA]) and sleep duration and quality characteristics with cardiometabolic risk among older women. Participants from the Healthy Women Study 2010–11 follow-up visit (n = 136, age = 73 ± 2 years, white = 91.9%) concurrently wore an ActiGraph GT1M accelerometer and Actiwatch-2 for seven days. A composite cardiometabolic risk score was calculated by transforming metabolic syndrome (MetS) components and summing z-scores. Multivariable regression models were fitted to relate waking and sleep estimates with the MetS z-score after adjustment for covariates. Compositional data analysis was used to predict the MetS z-score when fixed durations of time were reallocated from one characteristic to another. MVPA (per 10 min/day increase; β = −7.80, P < 0.01), LPA (per 30 min/day increase; β = −0.29, P = 0.04), and sleep efficiency (β = −0.10, P = 0.04) were inversely associated with MetS z-score, while sedentary time (per 30 min/day increase; β = 0.34, P = 0.01) was positively associated with MetS z-score. Reallocation of 5 min from MVPA to sleep, sedentary, or LPA resulted in the greatest predicted change in MetS z-score. On average, the reallocation of 5 min from MVPA to other characteristics predicted an 11% increase in triglycerides, 6% decrease in HDL-C, and 5% increase in waist circumference. Lastly, reallocating 30 min of sedentary time to LPA was associated with a modestly lower predicted MetS z-score. This study suggests that MVPA is the most important contributor of MetS and that maintaining MVPA and increasing LPA may be beneficial for reducing cardiometabolic risk among older women.

Active-to-Sedentary Behavior Transitions, Fatigability, and Physical Functioning in Older Adults

BACKGROUND

With aging, daily physical activity (PA) becomes less frequent and more fragmented. Accumulation patterns of daily PA-including transitions from active-to-sedentary behaviors-may provide important insights into functional status in older, less active populations.

METHODS

Participants of the Baltimore Longitudinal Study of Aging (n = 680, 50% male, aged 27-94 years) completed a clinical assessment and wore an Actiheart accelerometer. Transitions between active and sedentary states were modeled as a probability (Active-to-Sedentary Transition Probability [ASTP]) defined as the reciprocal of the average PA bout duration. Cross-sectional associations between ASTP and gait speed (m/s), fatigability (rating-of-perceived-exertion [RPE]), 400 m time (seconds), and expanded short physical performance battery score were modeled using linear and logistic regression, adjusted for chronic conditions. Further analyses explored the utility of ASTP over-and-above total daily PA.

RESULTS

In continuous models, each 0.10-unit higher ASTP was associated slower gait (β = -0.06 m/s, SE = 0.01), higher fatigability (β = 0.60 RPE, SE = 0.12), slower 400 m time (β = 16.31 s, SE = 2.70), and lower functioning (β = -0.13 expanded short physical performance battery score, SE = 0.03; p < .001). In categorical analyses, those in the highest tertile of ASTP were >2 times more likely to have high fatigability (rating of perceived exertion ≥10), slow 400 m time (>300 seconds) and reduced functional performance (expanded short physical performance battery score < 3.07) than those in the lowest tertile (p < .01). Further analyses demonstrated ASTP provided additional insight into functional outcomes beyond total daily PA.

CONCLUSION

Fragmented daily PA-as measured by ASTP-is strongly linked with measures of health and functional status and may identify those at risk of high fatigability and reduced functional performance over and above traditional PA metrics.

The bidirectional association between physical activity and sleep in middle-aged and older adults: a prospective study based on polysomnography

Study Objectives

To examine the bidirectional association between physical activity (PA) and polysomnographically (PSG)-assessed sleep parameters characterized by total sleep time (TST), sleep onset latency (SOL), wake time after sleep onset (WASO), sleep efficiency and percentage of TST in N1, N2, and N3 stages and rapid eye movement (REM) sleep in middle-aged and older adults.

Methods

Longitudinal study based on a subsample of the Wisconsin Sleep Cohort. Self-reported PA information was used to estimate the metabolic equivalents of task (MET-minutes/week) activity and in-laboratory PSG exams provided information on sleep parameters at baseline and after 3-11 years of follow-up between 2004 and 2015. Poisson and linear regression models controlling for confounders estimated associations of sleep outcomes with changes in PA.

Results

A total of 424 participants (45.8% female; mean ± SD age 60.1 ± 7.5 years) were followed over an average of 5.0 ± 1.6 years. Compared to baseline PA of <500 MET-minutes/week (reference category), 500 to 1500 MET-minutes/week of PA was associated with lower incidences of TST <6 hours (relative risk, RR: 0.49; 95% confidence interval, CI: 0.27; 0.88), WASO >60 minutes (RR: 0.58; 95% CI: 0.41; 0.82) and sleep efficiency <80% (RR: 0.61; 95% CI: 0.39; 0.94), adjusting for sociodemographic, health behaviors and medical conditions. No significant associations were observed between baseline sleep characteristics and changes in PA through the follow-up.

Conclusion

In this prospective study, an intermediate level of PA at baseline predicted lower risk of incident short sleep time, higher WASO and lower sleep efficiency measured with PSG.

Sedentary Time, Physical Activity, Fitness, and Physical Function in Older Adults: What Best Predicts Sleep Quality?

The aim of this study was to identify the best predictor of sleep quality (SQ) among physical behavior or capacity-related variables, namely physical activity, sedentary time, fitness, and physical function (activities of daily living) of independent elders using a representative sample of Portuguese aged 65 years and older (N = 437). SQ and activities of daily living were evaluated by a questionnaire, sedentary time, and physical activity through accelerometry, and physical fitness by means of the Senior Fitness Test. The logistic regression analysis revealed that activities of daily living measured by the Composite Physical Function was the only explanatory variable discriminating between poor SQ and good SQ. Receiver operating characteristic analysis showed that the best trade-off between sensitivity and specificity to discriminate older adults with poor SQ and good SQ was 20 points in the Composite Physical Function (sensitivity = 57.9%; specificity = 60.9%; area under the curve = 0.600, 95% confidence interval [0.536, 0.665], p = .003). Better physical function seems to be associated with better SQ in independent elders.

The Effect of Structured Exercise on Sleep During the Corresponding Night Among Older Women in an Exercise Program

This study investigated the acute effect of exercise on sleep outcomes among healthy older women by comparing days with structured exercise versus days without structured exercise during 4 months of exercise training. Participants (n = 51) in this study had wrist-worn actigraphic sleep data available following at least 3 days with structured exercise and 3 days without structured exercise at mid-intervention and at the end of intervention. The exercise intervention was treadmill walking. Multilevel models were used to examine whether structured exercise impacted sleep outcomes during the corresponding night. Overall, 1,362 nights of data were included in the analyses. In unadjusted and adjusted models, bedtimes were significantly earlier on evenings following an acute bout of structured exercise than on evenings without structured exercise. No other sleep parameters differed between exercise and nonexercise days. Understanding the effects of exercise on sleep in this understudied population may help to improve their overall sleep quality.

The 24-Hour Activity Cycle: A New Paradigm for Physical Activity

The physiologic mechanisms by which the four activities of sleep, sedentary behavior, light-intensity physical activity, and moderate-to-vigorous physical activity (MVPA) affect health are related, but these relationships have not been well explored in adults. Research studies have commonly evaluated how time spent in one activity affects health. Because one can only increase time in one activity by decreasing time in another, such studies cannot determine the extent that a health benefit is due to one activity versus due to reallocating time among the other activities. For example, interventions to improve sleep possibly also increase time spent in MVPA. If so, the overall effect of such interventions on risk of premature mortality is due to both more MVPA and better sleep. Further, the potential for interaction between activities to affect health outcomes is largely unexplored. For example, is there a threshold of MVPA minutes per day, above which adverse health effects of sedentary behavior are eliminated? This article considers the 24-h Activity Cycle (24-HAC) model as a paradigm for exploring inter-relatedness of health effects of the four activities. It discusses how to measure time spent in each of the four activities, as well as the analytical and statistical challenges in analyzing data based on the model, including the inevitable challenge of confounding among activities. The potential usefulness of this model is described by reviewing selected research findings that aided in the creation of the model and discussing future applications of the 24-HAC model.

Calibration of wrist-worn ActiWatch 2 and ActiGraph wGT3X for assessment of physical activity in young adults

BACKGROUND

The validity of Actiwatch 2 in assessing sleep was evident, but its validity in assessing physical activity (PA) level was unknown.

RESEARCH QUESTION

The objective of this study was to validate the wrist-worn Actiwatch 2 and ActiGraph wGT3X as a measurement of PA level against energy expenditure measured by indirect calorimetry.

METHODS

Twenty-seven university students aged 18-26 were recruited from July 2016 to May 2017. They were instructed to run at different speeds (4, 6, 8, 10, and 12 km/h) on a treadmill, each speed for 10 min. Oxygen consumption and carbon dioxide production of the subjects was measured by indirect calorimetry using the Cosmed K4b² gas analyzer. Each subjects wore a single pair of accelerometers (Actiwatch 2 and ActiGraph wGT3X) on both wrists.

RESULTS

All the accelerometers were strongly correlated (ρ=0.83-0.94, all p-values <0.001), and all four accelerometers were strongly correlated with the METs obtained from the Cosmed K4b² (ρ=0.72-0.74, all p-values <0.001). Regression analysis showed that the non-dominant wrist-worn Actiwatch 2 cutoff cpm for moderate and vigorous PA were 399 and 1,404, respectively; for the ActiGraph wGT3X-BT the corresponding cutoffs were 4,514 and 15,044, respectively. The goodness-of-fit of the MET prediction equations were all >75%. When classifying the activities as either sedentary, light activity, moderate-intensity activity, or vigorous-intensity activity using the MET prediction equations, the agreements between the four accelerometers and that by the Cosmed K4b² were high, all AUCs were above 80% except those of the Actiwatch worn on the left (non-dominant) wrist. The Bland-Altman plots show that, for all four accelerometers, the biases were close to zero and error variances were largest when the mean measurements were around 6 METs.

SIGNIFICANCE

We showed that wrist-worn Actiwatch 2 and ActiGraph wGT3X-BT were strongly correlated in PA assessment.

The Relationship Between Sleep Characteristics and Unmet Physical Activity Need in Older Women

Objective: We examined among older women the association of sleep quality, daytime tiredness, and sleep duration with unmet physical activity need, that is, wishing to be more physically active but perceiving no opportunity for it. Method: Cross-sectional logistic regression analyses among women aged 74 to 86 years (Finnish Twin Study on Aging, third wave, n = 302). Results: Thirty-one participants reported unmet physical activity need. Short sleepers had fivefold and long sleepers threefold odds for unmet physical activity need compared with normative sleepers, while for daytime tiredness the odds were double. Presence of daytime tiredness and unmet physical activity coincided with higher prevalence of chronic diseases, depressive symptoms and walking difficulties, which partly explains the observed associations. Poor sleep quality was not associated with unmet physical activity need. Discussion: Older women with nonoptimal sleep characteristics who perceive unmet physical activity need may benefit from solutions that improve their perceived opportunities for physical activity.

Physical Activity and Cognition: A Mediating Role of Efficient Sleep

OBJECTIVE

Physical activity benefits executive control, but the mechanism through which this benefit occurs is unclear. Sleep is a candidate mechanism given that it improves with exercise and has restorative effects on the prefrontal cortex. The present cross-sectional study examined the mediating role of sleep in the relationship between physical activity and executive control in young and older adults.

PARTICIPANTS

Young (n = 59) and older (n = 53) community-dwelling adults ages 21-30 and 55-80.

METHODS

Participants wore an accelerometer for one week to assess sleep efficiency, total sleep time, and physical activity, operationalized as metabolic equivalent of task (METs) during time spent awake. Cognition was assessed in the laboratory across multiple measures of executive control, memory recall, and processing speed. Mediation analyses tested the role of sleep efficiency in the cross-sectional relationship between METs and cognitive performance accounting for age, sex, and education.

RESULTS

METs were significantly associated with performance before, but not after accounting for covariates. METs were associated with sleep efficiency but not total sleep time. Sleep efficiency, but not total sleep time, mediated the relationship between METs and working memory, switching, verbal ability and fluency, and recall. Age group did not moderate the mediating role of sleep efficiency in the relationship between METs and performance.

CONCLUSION

Sleep efficiency is one pathway by which physical activity may be associated with executive control across young and older adults.

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

Sleep quality and physical activity (PA) appear to be interrelated; thus, by promoting one behaviour, it may be possible to improve the other in older adults. Examination of the within-person day-to-day variation in PA and sleep quality could potentially elucidate the directionality of the association of these behaviours. We measured sleep quality (i.e. fragmentation, efficiency, duration and latency) and moderate-to-vigorous PA using the MotionWatch8© over 14 consecutive days and nights in community-dwelling adults (n = 152; age range 53-101 years). Multilevel modelling estimated within-subject autoregressive and cross-lagged effects and between-subject associations between PA and sleep quality. On days when individuals engaged in a high amount of PA on one day (relative to their averages), they were more likely to engage in a high amount of PA on the next day (estimate, 0.19; 95% CI, 0.14, 0.24). Nights in which individuals had a long sleep latency were followed by nights in which they also had a long sleep latency (estimate, 0.09; 95% CI, 0.03, 0.14). In contrast, nights in which individuals slept for a long period of time were followed by nights in which they slept relatively less than their averages (estimate, -0.09; 95% CI, -0.13, -0.04). When individuals engaged in a large amount of PA during the day, they tended to sleep longer that following night (estimate, 0.01; 95% CI, 0.001, 0.02). All other associations between PA and sleep quality were not significant. Increasing PA therefore might increase sleep duration in older adults.

Efficacy of Exercise Intervention for Weight Loss in Overweight and Obese Adolescents: Meta-Analysis and Implications

BACKGROUND

The global rise in obesity prevalence among children and adolescents has been linked to modifiable lifestyle factors, including lack of physical activity. However, no known meta-analysis has been conducted on the effects of exercise intervention on body composition and cardiometabolic risk factors in overweight and obese adolescents.

OBJECTIVES

The aim of this study was to (1) estimate whether exercise intervention meaningfully improves body composition and cardiometabolic risk factors in overweight and obese adolescents; and (2) discuss the implications of the findings in terms of primary healthcare provision and public health policy, using New Zealand as an exemplar context.

DATA SOURCES

Electronic databases (PubMed, Web of Science, SPORTDiscus, Google Scholar) from inception to May 2015. The reference lists of eligible articles and relevant reviews were also checked.

STUDY SELECTION

Inclusion criteria were (1) randomized controlled trial; (2) structured exercise intervention, alone or combined with any other kind of intervention; (3) control group received no structured exercise or behavioural modification designed to increase physical activity; (4) participants overweight or obese (body mass index [BMI] ≥85th percentile); and (5) participants aged between 10 and 19 years.

APPRAISAL AND SYNTHESIS METHODS

Initially, 1667 articles were identified. After evaluation of study characteristics, quality and validity, data from 13 articles (15 trials) involving 556 participants (176 male, 193 female, 187 unknown) were extracted for meta-analysis. Meta-analyses were completed on five body composition parameters and ten cardiometabolic parameters. Effect sizes (ESs) were calculated as mean differences, as well as standardized mean differences in order to determine effect magnitude.

RESULTS

Exercise intervention reduced BMI (mean 2.0 kg/m², 95 % CI 1.5-2.5; ES moderate), body weight (mean 3.7 kg, 95 % CI 1.7-5.8; ES small), body fat percentage (3.1 %, 95 % CI 2.2-4.1; ES small), waist circumference (3.0 cm, 95 % CI 1.3-4.8; ES small), but the increase (improvement) in lean mass was trivial (mean 1.6 kg, 95 % CI 0.5-2.6). The response to an oral glucose tolerance test following exercise intervention was for a decrease in the area under the curve for insulin (mean 162 μU/μl, 95 % CI 93-231; ES large) and blood glucose (mean 39 mg/dl, 95 % CI 9.4-69; ES moderate). Improvements in the homeostatic model assessment were also noted (mean 1.0, 95 % CI 0.7-1.4; ES moderate) and systolic blood pressure (mean 7.1 mmHg, 95 % CI 3.5-10.7; ES moderate). The effects of exercise on total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, fasting insulin and fasting blood glucose were inconclusive.

LIMITATIONS

Most of the included trials were short term (6-36 weeks) and 13 had methodological limitations. Additionally, the meta-analyses for some of the secondary outcomes had a small number of participants or substantial statistical heterogeneity.

CONCLUSIONS

The current evidence suggests that exercise intervention in overweight and obese adolescents improves body composition, particularly by lowering body fat. The limited available evidence further indicates that exercise intervention may improve some cardiometabolic risk factors.

The Temporal Order of Changes in Physical Activity and Subjective Sleep in Depressed Versus Nondepressed Individuals: Findings From the MOOVD Study

Epidemiological studies have shown an association between physical activity and sleep, but it is unclear what the temporal order of this association is and whether it differs for depressed patients and healthy controls. Using a multiple repeated observations design, 27 depressed and 27 pair-matched nondepressed participants completed daily measurements of subjective sleep quality and duration during 30 consecutive days while an accelerometer continuously registered their physical activity. Changes in sleep duration, not quality, predicted next-day changes in physical activity (B = -0.21, p < .001), but not the other way around. Significant heterogeneity between individuals was observed, but the effect was not different for depressed and nondepressed participants. The findings underline the strength of a multiple repeated observations design in observational sleep research.