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Cumulative display of sleep architecture in all 92 participants. The percentage of participants in each sleep stage is shown for stages W (black), N1 (gray), N2 (light blue), N3 (blue), and R (red). W awake, R rapid eye movement sleep, N non-rapid eye movement sleep. A total of 587 polysomnography data points were clustered in 92 older adults.
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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...
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Citations
... 20 Knowledge about the effects of physical activity on sleep focuses mainly on the direct and indirect mechanisms associated with well-being and metabolic changes. 50 Among the best known of these are the changes that physical activity exerts on the regulation of body temperature, 51 the central nervous system, the control of energy consumption and conservation, 52 and anxiety levels, 53 which have all been shown to be capable of improving objective and subjective sleep parameters. 50 Arakaki et al. (2022) demonstrated that male older adults who were classified as inactive using the Interna-tional Physical Activity Questionnaire (IPAQ), based on the cut-off point established by the World Health Organization (WHO), had worse sleep quality (β ¼ À2.15 (95%CI: À3.91 to -0.39)) than those who were active. ...
... 50 Among the best known of these are the changes that physical activity exerts on the regulation of body temperature, 51 the central nervous system, the control of energy consumption and conservation, 52 and anxiety levels, 53 which have all been shown to be capable of improving objective and subjective sleep parameters. 50 Arakaki et al. (2022) demonstrated that male older adults who were classified as inactive using the Interna-tional Physical Activity Questionnaire (IPAQ), based on the cut-off point established by the World Health Organization (WHO), had worse sleep quality (β ¼ À2.15 (95%CI: À3.91 to -0.39)) than those who were active. 21 This previous study supports the findings of this study that low levels of physical activity are associated with sleep complaints. ...
The worldwide increase in life expectancy has resulted in a significant aging of the population. The physiological and functional changes that result from the aging process, changes in sleep patterns, and the prevalence of chronic diseases affect the health and well-being of individuals aged over 60.
Objective The aim of this study was to investigate the relationship between levels of physical activity (PA) and sleep quality in community-dwelling older adults.
Methods This is a cross-sectional study, with the participants randomly recruited according to the region and street in which they live. The Pittsburgh Sleep Quality Index (PSQI) was applied to assess sleep quality, the Modified Baecke Questionnaire for the Elderly (MBQ-E) to assess PA levels, as well as questionnaires to obtain social, demographic and anthropometric data. Multivariable regression analyses were conducted with PA activity as the independent variable and sleep quality as the dependent variable of interest, while also considering all potential covariates.
Results A total of 503 older adults were analyzed, of whom 377 (75%) were classified as inactive and only 126 (25%) as active. Among the participants, 344 (68.4%) had poor sleep quality, 86 (17.1%) had symptoms of insomnia, and 57 (11.5%) reported complaints of excessive daytime sleepiness. We found that 128 participants (25.4%) consumed alcohol and 41 (8.2%) were current smokers. Multivariate regression results showed an inverse association between PA levels and sleep (Beta coefficient = −0.67 ([95% confidence interval = −1.29 to −0.04]).
Conclusions The results of the study indicate that being physically inactive is associated with poor sleep quality.
... Although have substantial impacts on healthcare costs among adults, it is not yet clear whether the combination of both boosts economic losses. We hypothesize that the coexistence of sleep synergistic effect is particularly relevant considering the association between sleep problems and insufficient PA. 10,11 ...
BACKGROUND
The magnitude of economic losses attributed to sleep problems and insufficient physical activity (PA) remains unclear. This study aimed to investigate the association between insufficient PA, sleep problems, and direct healthcare costs.
OBJECTIVE
To investigate the association between insufficient physical activity (PA), sleep problems, and direct healthcare costs among adults.
DESIGN AND SETTING
Adults aged ≥ 50 years attended by the Brazilian National Health Service were tracked from 2010 to 2014.
METHODS
Direct healthcare costs were assessed using medical records and expressed in US$. Insufficient PA and sleep problems were assessed through face-to-face interviews. Differences were identified using the analysis of covariance and variance for repeated measures.
RESULTS
In total, 454 women and 166 men were enrolled. Sleep problems were reported by 28.9% (95%CI: 25.2% to 32.4%) of the sample, while insufficient PA was reported by 84.8% (95%CI: 82.1% to 87.6%). The combination of sleep problems and insufficient PA explained 2.3% of all healthcare costs spent on these patients from 2010 to 2014, which directly accounts for approximately US$ 4,765.01.
CONCLUSION
The combination of sleep problems and insufficient PA plays an important role in increasing direct healthcare costs in adults. Public health stakeholders, policymakers, and health professionals can use these results to reinforce the need for strategies to improve sleep quality and increase PA, especially in nations that finance their National Health Systems.
KEYWORDS (MeSH terms):
Exercise; Health care cost; Sleep
AUTHOR KEYWORDS:
Public health; Lifestyle; Observational
... Physical activity and exercise may be important for improving poor and/or disordered sleep, such that poor sleep may impair the maintenance of an active 510 lifestyle (Seol et al. 2022). Actigraphy data detected a spontaneous elevation of physical activity, as observed by increases in the number of calories used per day and sedentary breaks between PPod and MMPod conditions. ...
The purpose of this study was to investigate the effects of a novel dietary supplement, including melatonin and magnesium, delivered via coffee pods on sleep quality, resting metabolic rate (RMR), and body composition in individuals with poor sleep quality disturbances. Using a double-blinded, randomized, crossover trial, we recruited 35 participants to a 4-week intervention with both supplements (1.9 mg melatonin + 200 mg elemental magnesium before sleep) and placebo conditions, considering a 7d washout period between treatments. The Pittsburgh Sleep Quality Index (PSQI) questionnaire was applied, RMR (kcal) was measured using indirect calorimetry (canopy ventilated open-circuit system) and body composition was assessed using dual-energy X-ray absorptiometry. Decreases in PSQI and anger - hostility scores, as well as in energy intake and fat mass, were observed (p < 0.05) for both conditions, from baseline to the end of each 4-week intervention. Differences between conditions were also observed for these parameters along with energy spent in activity, number of sedentary breaks, sleep efficiency, latency time, time in bed, total sleep time, awakening time, and movement index (p < 0.05) favouring the supplement condition. However, the final PSQI questionnaire scores still indicated poor sleep quality on average (PSQI > 5), in both conditions, with no changes regarding RMR. A melatonin-magnesium supplement, in a coffee pod format, showed improvements in sleep quality in otherwise healthy individuals with sleep disturbances, however PSQI questionnaire scores still indicated poor quality on average (PSQI > 5).
... These changes in REM and NREM sleep were also observed during the first 180 min of sleep, indicating that they were not attributable to alterations in total sleep time, and were also robust to differences in sleep timing. These findings are consistent with laboratory PSG studies that have evaluated the effects of exercise on REM/NREM sleep architecture, which have found that exercise reduces REM sleep and increases REM-L 14,16,21,25,26 . Our results extend these findings to naturalistic environments and demonstrate that these changes in sleep architecture can be observed over time within individuals. ...
Physical activity has been found to alter sleep architecture, but these effects have been studied predominantly in the laboratory and the generalizability of these findings to naturalistic environments and longer time intervals, as well as their psychological effects, have not been evaluated. Recent technological advancements in wearable devices have made it possible to capture detailed measures of sleep outside the lab, including timing of specific sleep stages. In the current study, we utilized photoplethysmography coupled with accelerometers and smartphone ambulatory assessment to collect daily measurements of sleep, physical activity and mood in a sample of N = 82 over multi-month data collection intervals. We found a robust inverse relationship between sedentary behavior and physical activity and sleep architecture: both low-intensity and moderate-to-vigorous physical activity were associated with increased NREM sleep and decreased REM sleep, as well as a longer REM latency, while higher levels of sedentary behavior showed the opposite pattern. A decreased REM/NREM ratio and increased REM latency were in turn associated with improved wellbeing, including increased energy, reduced stress and enhanced perceived restfulness of sleep. Our results suggest that physical activity and sleep account for unique variance in a person’s mood, suggesting that these effects are at least partially independent.
... blood pressure, HbA1c, and blood lipids), even in the normal range, is warranted to discuss the biological mechanisms connecting sleeping and signs of illness. A portable multichannel electroencephalography recorder (InSomnograf K2; S'UIMIN Inc., Tokyo, Japan) was recently developed to measure EEG-based sleep parameters of healthy and unhealthy people at home (Supplementary Fig. 1) 15 . Using this modality, we aimed to examine the associations between EEG-based sleep characteristics and 50 physical health parameters (including blood pressure and blood and urine parameters), which can be generally measured at private health check clinics in Japan, in the general population of adults aged 30-59 years via a cross-sectional study. ...
... Second, misclassification of the studied parameters is possible. EEG-based parameters were measured by InSomnograf K2, which may be less accurate than those measured with the gold-standard method of polysomnography 15 . Blood samples were measured in the morning, although some parameters (e.g. ...
... Details of the InSomnograf K2 are described in a previous study using this modality for older people 15 . In brief, InSomnograf K2 is a newly developed modality to measure brain waves during sleep, with five soft sticking electrodes placed on the head in the frontal and occipital locations and connected to a portable recording machine ( Supplementary Fig. 1). ...
We examined the associations between electroencephalogram (EEG)-based sleep characteristics and physical health parameters in general adults via a cross-sectional study recruiting 100 volunteers aged 30–59 years. Sleep characteristics were measured at home using a portable multichannel electroencephalography recorder. Using the k-means + + clustering method, according to 10 EEG-based parameters, participants were grouped into better (n = 39), middle (n = 46), and worse (n = 15) sleep groups. Comparing 50 physical health parameters among the groups, we identified four signals of difference (P < 0.05), including systolic (sBP) and diastolic blood pressure (dBP), γ-glutamyl transpeptidase (γ-GTP), and serum creatinine, where sBP reached a Bonferroni-corrected threshold (P < 0.001). The sBP was higher by 7.9 (95% confidence interval 1.9–13.9) and 15.7 (7.3–24.0) mmHg before adjustment and 5.4 (− 0.1–10.9) and 8.7 (1.1–16.3) mmHg after adjustment for age, sex, body mass index, smoking, drinking habits, and 3% oxygen desaturation index in the middle and worse sleep groups, respectively, than in the better group. As another approach, among 500 combinations of EEG-based and physical health parameters, there were 45 signals of correlation, of which 4 (N1% and sBP, dBP, γ-GTP, and triglycerides) reached a Bonferroni-corrected threshold (P < 0.0001). Thus, EEG-based sleep characteristics are associated with several physical health parameters, particularly sBP.
... A questionnaire was administered at bedtime to determine whether there were any behaviors that affected sleep signi icantly, and another (OSA-MA) upon waking to evaluate sleep subjectively. Group X (10 subjects) received 7 days of a placebo edible ilm immediately before bedtime in intervention 1 (days [8][9][10][11][12][13][14], followed by a 7-day washout period (days [15][16][17][18][19][20][21]; an edible ilm containing 7.5 mg crocetin was then administered for 7 days immediately before bedtime in intervention 2 (days [22][23][24][25][26][27][28]. Group Y (10 subjects) received 7 days of an edible ilm containing 7.5 mg crocetin immediately before bedtime in intervention 1 (days [8][9][10][11][12][13][14], followed by a 7-day washout period (days 15-21); a placebo edible ilm was then administered for 7 days immediately before bedtime in intervention 2 (days [22][23][24][25][26][27][28]. ...
... Group X (10 subjects) received 7 days of a placebo edible ilm immediately before bedtime in intervention 1 (days [8][9][10][11][12][13][14], followed by a 7-day washout period (days [15][16][17][18][19][20][21]; an edible ilm containing 7.5 mg crocetin was then administered for 7 days immediately before bedtime in intervention 2 (days [22][23][24][25][26][27][28]. Group Y (10 subjects) received 7 days of an edible ilm containing 7.5 mg crocetin immediately before bedtime in intervention 1 (days [8][9][10][11][12][13][14], followed by a 7-day washout period (days 15-21); a placebo edible ilm was then administered for 7 days immediately before bedtime in intervention 2 (days [22][23][24][25][26][27][28]. Sleep was objectively evaluated by measuring EEG and other bioelectrical potentials from bedtime to waking time for 5 days during the two intake periods (days 10-14 and 24-28 (Monday through Friday)) Age-related changes to sleep patterns are widely known and have been demonstrated to decrease the total sleep time, prolong the sleep latency, fragment sleep (e.g., an increased number of WASO), increase the proportion of non-REM in sleep stages N₁ and N₂, and decrease the proportion of REM and non-REM in sleep stage N₃ [9]. ...
... S'UIMIN's portable EEG device, InSomnograf® is equipment that measures the bioelectrical potentials including EEG, electromyography (EMG), and electrooculography (EOG) with 5 electrodes, and the sleep stage of each 30 seconds (epoch) during sleep is determined according to AASM scoring manual. It has an 86.9% correlation with polysomnography (PSG) [26]. Parameters related to sleep quality and quantity, which were calculated from the results of the sleep staging (hypnogram), were used in the analysis. ...
It has been reported that Japanese people sleep for an average of 7 hours and 22 minutes per night, with those in their 40s and 50s sleeping the least. This is much less than in other developed countries. Aging has also been reported to decrease the total sleep time and sleep latency as well as increase wake after sleep onset (WASO). Crocetin is a carotenoid with antioxidant activity. It has been reported that 14 consecutive days of crocetin intake increases delta power during sleep and decreases WASO. However, the benefits of short-term ingestion have not been clarified. In this double-blind, randomized crossover study, we examined the effects of crocetin-containing edible films consumed for seven consecutive days on the sleep quality of healthy Japanese subjects working in management positions who were aged 45 years or older. The study participants comprised 20 subjects (12 males and 8 females; mean age 50.4 ± 4.8 years; body mass index (BMI) 22.5 ± 2.7). An electroencephalography (EEG) measuring device (InSomnograf®) was used to measure sleep objectively and a questionnaire, OSA Sleep Questionnaire MA version (OSA-MA) was used to assess sleep subjectively upon waking. The crocetin group demonstrated significantly higher values of OSA-MA Factor 3 (frequent dreaming) than the placebo group (placebo: 46.8 ± 6.9; crocetin: 49.5 ± 7.4). No differences were observed for the other four factors. No differences were observed in the sleep parameters determined with InSomnograf®. Our findings suggest a new effect of crocetin on sleep quality of frequent dreaming.
... However, the use of electrodes and other components in existing type II-IV PSGs remains complex, prompting the need for the development of portable electroencephalography (EEG) devices that patients can easily wear to screen for conditions such as OSA [5]. A portable EEG device that integrates electrodes, which is simpler than PSG, has been used in studies involving healthy middle-aged and/or older adults [14,15]. The advantage of this device is that although it has a smaller number of electrodes than the existing PSGs, a variety of channels can be generated by combining montages, and its accuracy improved with less number of electrodes [14] (Supplementary Figure S1). ...
... The total sleep time, sleep e ciency, and arousal index averaged 425.8 ± 69.5 minutes, 85.4 ± 9.4%, and 37.0 ± 15.1, respectively ( Fig. 1 and Table 2). In this study, apnea was categorized using the AHI as mild (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) in 20 patients (25.9%), moderate (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) in 17 patients (22.1%), and severe (> 30) in 34 patients (44.1%). Six patients (7.9%) were suspected of having apnea during screening; however, they had an AHI of < 5. Table 2 presents the sleep variables measured using both the type I PSG and portable EEG devices. ...
... The total sleep time, sleep e ciency, and arousal index averaged 425.8 ± 69.5 minutes, 85.4 ± 9.4%, and 37.0 ± 15.1, respectively ( Fig. 1 and Table 2). In this study, apnea was categorized using the AHI as mild (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15) in 20 patients (25.9%), moderate (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) in 17 patients (22.1%), and severe (> 30) in 34 patients (44.1%). Six patients (7.9%) were suspected of having apnea during screening; however, they had an AHI of < 5. Table 2 presents the sleep variables measured using both the type I PSG and portable EEG devices. ...
Efforts to simplify standard polysomnography (PSG) in laboratories, especially for obstructive sleep apnea (OSA), and to assess its agreement with portable electroencephalogram (EEG) devices are limited. We aimed to evaluate the agreement between a portable EEG device and type I PSG in patients with OSA and examined the EEG-based arousal index's ability to estimate apnea severity. We enrolled 77 Japanese patients with OSA who underwent simultaneous type I PSG and portable EEG monitoring. Combining pulse rate, oxygen saturation (SpO2), and EEG data improved sleep staging accuracy. Bland-Altman plots, paired t-tests, and receiver operating characteristics curves were used to assess agreement and screening accuracy. Significant small biases were observed for total sleep time, sleep latency, awakening after falling asleep, sleep efficiency, N1, N2, and N3 rates, and arousal index. All variables showed > 95% agreement in the Bland-Altman analysis, with interclass correlation coefficients ranging from 0.76–0.982, indicating high inter-instrument validity. The EEG-based arousal index demonstrated sufficient power for screening AHI ≥ 15 and AHI ≥ 30. Portable EEG device showed strong agreement with type I PSG in patients with OSA. Additionally, the EEG-based arousal index yielded promising results in predicting apnea severity. This suggests that patients with OSA may assess their condition at home.
... At the Editor's suggestion, we include a proof of principle analysis investigating the effects of exercise on sleep. A recent daily observational study [77], similar in design to BSETS, found increased REM latency, reduced REM and slightly increased N3 after mild, but not after vigorous exercise in the elderly. A recent meta-analysis [16], following previous similar studies [18,78,79] highlights that current recommendations advise against exercise in sleep, and quantitively synthesizes 23 investigating the effect of evening exercise on sleep. ...
... Our findings do not directly replicate the results of the previous meta-analysis or a recent daily observational study [77], but suggests that exercise may complicate the onset of sleep. The limitations of our analysis include that we did not control for the time of exercise relative to sleep, and thus could not distinguish between exercise any time during the day and specifically in the evening. ...
Sleep is both a neurophysiological state and a biologically necessary behavior that performs a variety of indispensable roles for human health, development, and cognitive functioning. Despite this, comparatively little is known about the relationships between daily experiences and sleep features. Importantly, these relationships are bidirectional in nature, may be differently associated with subjectively and objectively assessed sleep, and may also be modulated by individual differences To address this challenge, we created the Budapest Sleep, Experiences, and Traits Study (BSETS), a multidisciplinary observational sleep study utilizing novel remote EEG devices. BSETS was designed to establish a dataset for future use in investigating the relationships between sleep features and daily experiences. In this paper we describe the protocol of the currently ongoing BSETS, which examines a community-dwelling sample of over 250 healthy participants who are studied in a naturalistic setting using a large questionnaire assessing psychological, demographic, and anthropometric information, as well as evening/morning diaries of sleep and daily experiences, and mobile EEG recordings over a period of 7 days. This dataset will become an accessible resource to the wider scientific community and can be utilized to investigate the complex multidirectional relationships between objectively and subjectively measured sleep, daily experiences, and individual differences, bestowing it with significant value for sleep researchers as well as practitioners working in clinical settings with patients suffering from disordered sleep.
... However, low correlations between objective and subjective assessments of sleep quality have been reported [39,40]. In addition, skilled personnel are needed to install polysomnography electrodes, though it should be noted that polysomnographic recording of sleep at home has become possible [41]. Although beneficial effects of time-restricted eating on sleep were not reported, no adverse effects on sleep were found. ...
There is a physiological link between sleep and eating. Insufficient sleep is a risk factor for overeating and excess body weight gain, and molecules such as orexin and insulin play a role in the control of sleep and energy intake. The effects of dietary timing on sleep and energy metabolism were examined in this review. First, we examined sleep energy metabolism and sleep quality under time-restricted eating, including skipping breakfast or dinner. Second, the mechanisms, benefits, and translational potential of the effects of time-restricted diets on sleep were discussed. Time-restricted eating under controlled conditions, in which daily caloric intake was kept constant, affected the time course of energy metabolism but did not affect total energy expenditure over 24 h. In free-living conditions, time-restricted eating for extended durations (4–16 weeks) decreased energy intake and body weight, and the effects of early time-restricted eating were greater than that of midday time-restricted eating. Although assessment of sleep by polysomnographic recording remains to be performed, no negative effects on the subjective quality of sleep have been observed.
Background
Health-beneficial emergency bedding has become increasingly important for dealing with natural disasters such as the anticipated Nankai Trough earthquake in Japan. When the Great East Japan Earthquake occurred, cardboard beds were provided to evacuees. However, there were concerns about lower back pain and sleep disturbances, as cardboard beds offer insufficient pressure distribution. This study aimed to compare the effects of cardboard beds with those of foldable camp cots on sleep quality.
Methods
A randomized controlled crossover study involving 20 healthy participants aged 18–45 years was conducted between June 2022 and January 2023. Participants were asked to sleep for one night on a camp cot and for another night on a cardboard bed, with a minimum three-day washout period between the two nights. Body pressure distribution and sleep metrics obtained from polysomnography (PSG) and questionnaires were compared between the two-bed types ( P < 0.05).
Results
The camp cot exhibited better body pressure distribution than a cardboard bed, leading to improved sleep satisfaction, bedding comfort, and reduced morning sleepiness. Nevertheless, polysomnography revealed no notable differences in sleep metrics or sleep architecture between the two types of beds.
Conclusions
Our findings indicate that cardboard beds have lower pressure dispersion capabilities than camp cots, leading to an increased number of position changes during sleep. Additionally, subjective sleep quality, such as alertness on waking, sleep comfort, and sleep satisfaction, was lower for cardboard beds, suggesting that camp cots might offer a more comfortable bedding option for evacuees. However, there were no discernible differences between the two-bed types in terms of objective sleep metrics derived from PSG. The potential for sleep disturbances caused by lower back pain from a hard mattress has been noted, and it is possible that a single night’s experience in healthy individuals might not be enough for sleep issues to manifest.
