scholarly journals ARE THERE DIFFERENCES BETWEEN MALE AND FEMALE BADMINTON ATHLETES IN SLEEP, PHYSICAL ACTIVITY AND SEDENTARY TIME?

2021 ◽  
Vol 27 (2) ◽  
pp. 174-178
Author(s):  
Arilene Maria da Silva Santos ◽  
Sérgio Luiz Galan Ribeiro ◽  
Antônio Valdeci Marreiro de Sousa Junior ◽  
Dionis de Castro Dutra Machado ◽  
Paula Alves Monteiro ◽  
...  
Keyword(s):  
Physical Activity ◽  
Female Athletes ◽  
Sedentary Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Control Group ◽  
Vigorous Activity ◽  
Sleep Quantity ◽  
Time In Bed ◽  
Or Groups

ABSTRACT Introduction: High-performance athletes often undergo periods of exhaustive training and insufficient recovery, which can lead to decreased performance, but it is not clear whether there are any differences between the sexes in the level of habitual physical activity, sedentary time or sleep quantity and quality in young highly trained badminton athletes. Objectives: The aim of this study was to compare the habitual physical activity (PA), sedentary time and sleep quantity and quality of highly trained young male and female badminton athletes and non-athletes. Methods: Twenty-seven young badminton athletes and twenty-one non-athletes (control group) were recruited. Sleep duration and quality (total time in bed, total sleep time, wake after sleep onset, sleep efficiency and latency), total counts, vigorous activity time and sedentary time were measured using a tri-axial accelerometer. Results: Male athletes spent less sedentary time (p=0.028), more time in vigorous activity (p=0.016) and had higher total counts (p<0.001) than the male control group. There were no significant differences in sedentary time (p=0.702) or vigorous activity time (p=0.205) between the female athletes and non-athletes, but the female athletes accumulated higher total counts than the female control group (p=0.003). There were no significant differences between the sexes or groups for time in bed, total sleep time, sleep efficiency, wake after sleep onset and latency (p> 0.05). Conclusion: Among males but not females, young highly trained badminton athletes had less sedentary time and more time in vigorous activity than the non-athletes, however, there were no significant differences between the sexes or groups in sleep quantity and quality. Level of evidence III; Case-control study .

scholarly journals Tossing and turning: association of sleep quantity–quality with physical activity in COPD

2020 ◽  
Vol 6 (4) ◽  
pp. 00370-2020
Author(s):  
Raquel Pastrello Hirata ◽  
Daniele Caroline Dala Pola ◽  
Lorena Paltanin Schneider ◽  
Mariana Pereira Bertoche ◽  
Karina Couto Furlanetto ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Sleep Onset ◽  
Physically Active ◽  
Walking Test ◽  
Sleep Quantity ◽  
Time In Bed ◽  
Vigorous Intensity ◽  
Active Patients ◽  
Physically Inactive

The association between characteristics of sleep and physical activity in daily life (PADL) has not yet been investigated in depth in subjects with COPD. This study evaluated whether time spent per day in physical activity (PA) and sedentary behaviour are associated with sleep quantity and quality in this population.Sleep and PADL were objectively assessed by an activity monitor for 7 days and analysed on a minute-by-minute basis. Subjects also underwent spirometry and 6-min walking test (6MWT).Fifty-five subjects with moderate-to-severe COPD (28 male, 67±8 years) were studied. Subjects with total time in bed (TIB) per night ≥9 h had higher wake-after-sleep onset than TIB 7–9 h and TIB ≤7 h (195 (147–218) versus 117 (75–167) and 106 (84–156) min) and more fragmented sleep than TIB ≤7 h (8.2 (6.7–14.3) versus 6.3 (5.6–6.9) sleeping bouts; p<0.05 for all). Subjects with TIB ≥9 h also spent more time per day in sedentary behaviour and less time per day in PA of light and moderate-to-vigorous intensity than those with TIB 7–9 h and ≤7 h. In multiple linear regression, TIB ≥9 h was the only significant predictor of physical inactivity (β=−3.3 (−5.1, −1.6), p≤0.0001), accounting for 20% of its variation. Sleep fragmentation was frequent and more pronounced in physically inactive than active patients (7.5 (6.3–9.6) versus 6.4 (5.5–7.3) sleeping bouts; p=0.027).In summary, subjects with COPD with TIB ≥9 h·night−1 have more fragmented sleep, are more sedentary and less physically active than those with <9 h·night−1, independently of the awake time. Sleep quality is frequently poor and even worse in patients classified as physically inactive.

scholarly journals Reliability of GENEActiv accelerometers to estimate sleep, physical activity, and sedentary time in children

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Devan Antczak ◽  
Chris Lonsdale ◽  
Borja del Pozo Cruz ◽  
Philip Parker ◽  
Taren Sanders
Keyword(s):  
Physical Activity ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Sleep Onset ◽  
Reliable Estimate ◽  
Moderate Physical Activity ◽  
Accelerometer Data ◽  
Wake Time ◽  
Time In Bed ◽  
Minimum Criteria

Abstract Background Reliable estimates of habitual sleep, physical activity, and sedentary time are essential to investigate the associations between these behaviours and health outcomes. While the number of days needed and hours/day for estimates of physical activity and sedentary time are generally known, the criteria for sleep estimates are more uncertain. The objective of this study was to identify the number of nights needed to obtain reliable estimates of habitual sleep behaviour using the GENEActiv wrist worn accelerometer. The number of days to obtain reliable estimate of physical activity was also examined. Methods Data was used from a two-year longitudinal study. Children wore an accelerometer for up to 8 days 24 h/day across three timepoints. The sample included 2,745 children (51 % girls) between the ages of 7-12-years-old (mean = 9.8 years, SD = 1.1 year) with valid accelerometer data from any timepoint. Reliability estimates were calculated for sleep duration, sleep efficiency, sleep onset, wake time, time in bed, light physical activity, moderate physical activity, moderate-to-vigorous physical activity, vigorous physical activity, and sedentary time. Results Intraclass correlations and the Spearman Brown prophecy formula were used to determine the nights and days needed for reliable estimates. We found that between 3 and 5 nights were needed to achieve acceptable reliability (ICC = 0.7) in sleep outcomes, while physical activity and sedentary time outcomes required between 3 and 4 days. Conclusions To obtain reliable estimates, researchers should consider these minimum criteria when designing their studies and prepare strategies to ensure sufficient wear time compliance.

scholarly journals Descriptive epidemiology of objectively-measured, free-living sleep parameters in a rural African setting.

2020 ◽  
Author(s):  
Ian Cook ◽  
Matlawa Mohlabe ◽  
Marianne Alberts
Keyword(s):  
Physical Activity ◽  
Body Mass ◽  
Sleep Onset ◽  
Sleep Time ◽  
Free Living ◽  
Sleep Quantity ◽  
Sleep Parameters ◽  
Reported Data ◽  
Objectively Measured ◽  
African Setting

Abstract Objectives To investigate the descriptive nature of objectively-measured, free-living sleep quantity and quality, and the relationship to adiposity, in a rural African setting in 145 adults (≥40 years, female: n=104, male: n=41). Wrist-mounted, tri-axial accelerometry data was collected over nine days. Measures of sleep quantity and quality, and physical activity were extracted from valid minute-by-minute data. From stature, body mass and waist circumference, body-mass-index and conicity index were calculated. Self-reported data included behavioural, health and socio-demographic variables. Community consultation followed the quantitative data analyses, for validation and interpretation of findings. Results Females had more nocturnal sleep than males (7.2 vs. 6.8 hours/night, p=0.0464) while males recorded more diurnal sleep time (p=0.0290). Wake after sleep onset and number of awakenings were higher in females, and sleep efficiency was higher in males (p≤0.0225). Sleep indices were generally similar between weekdays and weekends, except for sleep fragmentation index (p=0.0458). Sleep quantity, but not sleep quality was independently and inversely associated with adiposity (p=0.0453). Physical activity and morbidity measures were significantly and consistently associated with sleep and adiposity measures (p<0.0458). The qualitative data explained some of the unexpected associational directions of the independent variables correlated with sleep variables.

scholarly journals Descriptive epidemiology of objectively-measured, free-living sleep parameters in a rural African setting.

2020 ◽  
Author(s):  
Ian Cook ◽  
Matlawa Mohlabe ◽  
Marianne Alberts
Keyword(s):  
Physical Activity ◽  
Sleep Onset ◽  
Sleep Time ◽  
Free Living ◽  
Cultural Economic ◽  
Sleep Quantity ◽  
Sleep Parameters ◽  
Reported Data ◽  
Objectively Measured ◽  
African Setting

Abstract Objectives: To investigate the descriptive nature of objectively-measured, free-living sleep quantity and quality, and the relationship to adiposity, in a rural African setting in 145 adults (≥40 years, female: n=104, male: n=41). Wrist-mounted, triaxial accelerometry data was collected over nine days. Measures of sleep quantity and quality, and physical activity were extracted from valid minute-by-minute data. Adiposity indices were body-mass-index, waist circumference and conicity index. Self-reported data included behavioural, health and socio-demographic variables. Community consultation followed the quantitative data analyses, for validation and interpretation of findings. Results: Females had more nocturnal sleep than males (7.2 vs. 6.8 hours/night, p=0.0464) while males recorded more diurnal sleep time (p=0.0290). Wake after sleep onset and number of awakenings were higher in females, and sleep efficiency was higher in males (p≤0.0225). Sleep indices were generally similar between weekdays and weekends, except for sleep fragmentation index (p=0.0458). Sleep quantity, but not sleep quality was independently and inversely associated with adiposity (p=0.0453). Physical activity and morbidity measures were significantly and consistently associated with sleep and adiposity measures (p<0.0458). The preliminary qualitative data suggests that future studies should include more detailed data around contextual issues of sleep (social, cultural, economic, environment).

507 Clinical Impression of Excessive Daytime Sleepiness (EDS) at initial Sleep Medicine (SM) consultation and its clinical correlates

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A199-A200
Author(s):  
Leon Rosenthal ◽  
Raúl Aguilar Roblero
Keyword(s):  
Lower Energy ◽  
Energy Levels ◽  
Sleep Onset ◽  
Sleep Time ◽  
Clinical Impression ◽  
Sleep Onset Latency ◽  
Convenience Sample ◽  
Time In Bed ◽  
Number Of Patients ◽  
Cardinal Symptom

Abstract Introduction EDS represents a cardinal symptom in SM. Use of subjective scales are prevalent, which have a modest correlation with the MSLT. While the Clinical Global Impression has been used in research, reports of clinical impression (CI) in medical practice are lacking. We report on the CI of EDS in a convenience sample of patients undergoing initial consultation. Methods Patients reported primary, secondary symptoms and completed the Sleep Wake Activity Inventory (SWAI) prior to Tele-Medicine consultation. A SM physician completed the assessment which included ascertainment of CI of EDS (presence S+ / absence S-). Results There were 39 ♂and 13 ♀. The CI identified 26 patients in each group (S+/S-). Age (52 [14]), BMI (33 [7]), reported time in bed, sleep time, sleep onset latency and # of awakenings did not differ. All identified a primary symptom (S-: 21, S+: 19 reported snoring or a previous Dx of OSA). Sleepiness as a 1ry or 2ry symptom was identified by 0 in the S- and by 13 in the S+ groups. Refreshing quality of sleep differed (χ2 &lt;0.05): un-refreshing sleep was reported by 7 (S-) and by 13 (S+). Naps/week: 0.7 [1.5] and 1.57 [1.5] for the S-, S+ groups respectively (p&lt;0.05). A main effect (p&lt;0.01) was documented on the SWAI. We report on the Sleepiness [SS] and Energy Level [EL] scales (lower scores on the SS reflect higher sleepiness while lower scores on EL denote higher energy). Higher sleepiness (p&lt;0.01) 43 [12] and lower energy levels 24 [6] (p&lt;0.05) were documented on the S+ group (S- 61 [17], and 18 [6] respectively). Available spouse’s Epworth score on 29 patients: S- patients 5.8 [4] and S+ 10.2 [6] (p&lt;0.05). Dx of OSA was identified among all but 1 in the S+ group. Also, Insomnia was diagnosed among 11 (S-) and 19 (S+) patients (p&lt;0.05) despite only 3 and 7 (respectively) identifying it as a presenting symptom. Conclusion While snoring or previous Dx of OSA were prevalent motivations for consultation, sleepiness and insomnia were clinically relevant among a substantial number of patients. Unrefreshing sleep, daytime naps, lower energy, and higher sleepiness were ubiquitous among S+ patients. Support (if any):

scholarly journals P091 The impact of cognitive fitness and gender on sleep quantity and timing and mental health of competitive athletes

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A50-A51
Author(s):  
L Mascaro ◽  
S Drummond ◽  
J Leota ◽  
J Boardman ◽  
D Hoffman ◽  
...  
Keyword(s):  
Mental Health ◽  
Gender Differences ◽  
Female Athletes ◽  
Intolerance Of Uncertainty ◽  
Well Being ◽  
Sleep Time ◽  
Self Control ◽  
Sleep Quantity ◽  
Competitive Athletes ◽  
The Impact

Abstract Introduction Mental fitness is increasingly considered key to an athlete’s competitive arsenal. Its active ingredients include cognitive fitness factors, such as impulse control, and recovery factors, such as sleep, which may differ between male and female athletes. Our study investigated: 1) gender differences in cognitive fitness; and 2) the associations of gender and cognitive fitness with sleep and mental health in competitive athletes during the COVID-19 lockdown. Methods 84 athletes competing at levels from regional/state to international (42F, mean age=23.2) completed a questionnaire battery containing validated measures of: a) depression, anxiety, and stress; b) sleep (Total Sleep Time, Sleep Latency, mid-sleep time on training- and competition-free days); and c) self-control, intolerance of uncertainty, and impulsivity (representing cognitive fitness constructs). Results Female athletes reported significantly higher depression, anxiety, and stress, a later mid-sleep time on free days, lower self-control, higher intolerance of uncertainty, and higher positive urgency impulsivity compared with male athletes. Self-control was negatively associated, and intolerance of uncertainty was positively associated, with depression, anxiety, and mid-sleep time on free days. Discussion Female athletes in our sample reported poorer mental health and cognitive fitness, and later sleeping times on free days. Greater cognitive fitness was associated with better mental health, independent of gender. Overall, these findings are consistent with prior work in community samples. Future work should examine the source(s) of these gender differences. If replicated, our findings would suggest a need to develop interventions aimed at improving athlete well-being, potentially with a particular focus on female athletes.

scholarly journals Proteomic Profiling Reveals the Molecular Changes of Insomnia Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Guanying Wang ◽  
Xiaojuan Ren ◽  
Xingping Zhang ◽  
Qingquan Wang ◽  
Tao Liu ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Cholesterol Metabolism ◽  
Sleep Onset ◽  
Public Health Problem ◽  
Sleep Time ◽  
Control Group ◽  
Proteomic Profiling ◽  
Ppi Network ◽  
Metabolic Systems ◽  
Hub Proteins

Background. Insomnia is an economic burden and public health problem. This study is aimed at exploring potential biological pathways and protein networks for insomnia characterized by wakefulness after sleep. Method. Proteomics analysis was performed in the insomnia group with wakefulness and the control group. The differentially expressed proteins (DEPs) were enriched; then, hub proteins were identified by protein-protein interaction (PPI) network and verified by parallel reaction monitoring (PRM). Results. Compared with the control group, the sleep time and efficiency of insomnia patients were decreased, and awakening time and numbers after sleep onset were significantly increased ( P < 0.001 ). The results of proteomic sequencing found 68 DEPs in serum under 1.2-fold changed standard. These DEPs were significantly enriched in humoral immune response, complement and coagulation cascades, and cholesterol metabolism. Through the PPI network, we identified 10 proteins with the highest connectivity as hub proteins. Among them, the differential expression of 9 proteins was verified by PRM. Conclusion. We identified the hub proteins and molecular mechanisms of insomnia patients characterized by wakefulness after sleep. It provided potential molecular targets for the clinical diagnosis and treatment of these patients and indicated that the immune and metabolic systems may be closely related to insomnia characterized by wakefulness after sleep.

scholarly journals A study on sleep apnea in patients with abnormal sewda type of depression

2020 ◽  
pp. 1-8
Author(s):  
Aman Gul ◽  
Nassirhadjy Memtily ◽  
Pirdun Mijit ◽  
Palidan Wushuer ◽  
Ainiwaer Talifu ◽  
...  
Keyword(s):  
Rem Sleep ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Control Group ◽  
Poor Sleep ◽  
Sleep Structure ◽  
Maintenance Rate ◽  
Sleep Maintenance ◽  
Insomnia Symptoms

Objective: To preliminarily investigate the clinical features and PSG in abnormal sewda-type depressive insomnia. Methods: A total of 127 abnormal sewda-type depressive insomnia patients were evaluated with overnight PSG, and 32 normal participants were compared. Results: Patients with abnormal sewda-type depressive insomnia were compared with the control group; the sleep symptoms showed a long incubation period of sleep, low sleep maintenance rate, low sleep efficiency and poor sleep quality as well as daytime dysfunction. At process and continuity of sleep: Total sleep time, sleep efficiency, sleep maintenance rate in abnormal sewda-type depressive insomnia group were shorter than the control group. Wake after sleep onset, and sleep latency were longer than the control group. At sleep structure: N1 ratio and N2 ratio in depressive insomnia group were longer than the control group, N3 ratio and REM sleep ratio shorter than the control group. At REM index: REM latency, REM cycles, and REM sleep time were shorter than the control group. Conclusion: Insomnia symptoms in abnormal sewda-type depression comorbid insomnia patients were similar to the ordinary insomnia patients. The PSG characteristics had significant changes in sleep process, sleep structure and REM indicators. The severity of the abnormal sewda-type depression was closely related to REM indicators. Change of REM sleep characteristics may be the specificity, and these could be taken as reference in diagnosis and identification of abnormal sewda-type depressive insomnia.

Exploring Preschoolers’ Physical Activity and Sedentary Time During Outdoor Play at Childcare: A Cross-Sectional Analysis of the Supporting Physical Activity in the Childcare Environment Study

2021 ◽  
pp. 1-8
Author(s):  
Brianne A. Bruijns ◽  
Leigh M. Vanderloo ◽  
Brian W. Timmons ◽  
Patricia Tucker
Keyword(s):  
Physical Activity ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Outdoor Play ◽  
Control Group ◽  
Activity Levels ◽  
Cross Sectional ◽  
Environment Study ◽  
Sectional Analysis ◽  
Experimental Group

Background: Moderate-to-vigorous physical activity (MVPA) offers many health benefits for preschoolers (2.5–5 y). In childcare, MVPA is predominantly accumulated outdoors, with higher rates purported among children within the first few minutes outside. The Supporting Physical Activity in the Childcare Environment intervention included shorter, more frequent outdoor play sessions; this study sought to explore children’s activity levels during various outdoor play schedules. Methods: During the final week of the Supporting Physical Activity in the Childcare Environment intervention, preschoolers wore an Actical™ accelerometer for 5 days during childcare and staff logged outdoor times. Separate linear mixed effects models were run to explore the effect of the intervention on preschoolers’ physical activity (total and MVPA) and sedentary time during outdoor play. Sex was entered as an interaction effect. Results: Preschoolers (n = 292) were significantly more active in the first 10 minutes outdoors compared with remaining time (P < .0083). For total outdoor time, children in the experimental group engaged in significantly less sedentary time than those in the control group (P < .017), and experimental group boys and girls engaged in higher MVPA than boys and girls in the control group (P < .017). Conclusions: Findings support scheduling more frequent outdoor play sessions in childcare to increase physical activity participation among young children.

Classification and Processing of 24-Hour Wrist Accelerometer Data

2018 ◽  
Vol 1 (2) ◽  
pp. 51-59 ◽  
Author(s):  
Anna Pulakka ◽  
Eric J. Shiroma ◽  
Tamara B. Harris ◽  
Jaana Pentti ◽  
Jussi Vahtera ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Time ◽  
Total Activity ◽  
Sleep Time ◽  
Accelerometer Data ◽  
Classification Methods ◽  
Wake Time ◽  
Wear Time ◽  
Aging Study ◽  
Activity Measures

Background: An important step in accelerometer data analysis is the classification of continuous, 24-hour data into sleep, wake, and non-wear time. We compared classification times and physical activity metrics across different data processing and classification methods.Methods: Participants (n = 576) from the Finnish Retirement and Aging Study (FIREA) wore an accelerometer on their non-dominant wrist for seven days and nights and filled in daily logs with sleep and waking times. Accelerometer data were first classified as sleep or wake time by log, and Tudor-Locke, Tracy, and ActiGraph algorithms. Then, wake periods were classified as wear or non-wear by log, Choi algorithm, and wear sensor. We compared time classification (sleep, wake, and wake wear time) as well as physical activity measures (total activity volume and sedentary time) across these classification methods.Results:M(SD) nightly sleep time was 467 (49) minutes by log and 419 (88), 522 (86), and 453 (74) minutes by Tudor-Locke, Tracy, and ActiGraph algorithms, respectively. Wake wear time did not differ substantially when comparing Choi algorithm and the log. The wear sensor did not work properly in about 29% of the participants. Daily sedentary time varied by 8–81 minutes after excluding sleep by different methods and by 1–18 minutes after excluding non-wear time by different methods. Total activity volume did not substantially differ across the methods.Conclusion: The differences in wear and sedentary time were larger than differences in total activity volume. Methods for defining sleep periods had larger impact on outcomes than methods for defining wear time.

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