scholarly journals Sleep Parameters in Short Daily versus Conventional Dialysis: An Actigraphic Study

2017 ◽  
Vol 2017 ◽  
pp. 1-6
Author(s):  
Ludimila D’Avila e Silva Allemand ◽  
Otávio Toledo Nóbrega ◽  
Juliane Pena Lauar ◽  
Joel Paulo Russomano Veiga ◽  
Einstein Francisco Camargos
Keyword(s):  
Total Sleep Time ◽  
Linear Regression Analysis ◽  
Sleep Onset ◽  
Objective Measure ◽  
Sleep Time ◽  
Cross Sectional ◽  
Convenience Sample ◽  
Wake Time ◽  
Daily Dialysis ◽  
Sleep Parameters

Previous studies have observed worse sleep quality in patients undergoing conventional dialysis as compared to daily dialysis. Our aim was to compare the sleep parameters of patients undergoing daily or conventional dialysis using an objective measure (actigraphy). This cross-sectional study was performed in three dialysis centers, including a convenience sample (nonprobability sampling) of 73 patients (36 patients on daily hemodialysis and 37 patients on conventional hemodialysis). The following parameters were evaluated: nocturnal total sleep time (NTST), expressed in minutes; wake time after sleep onset (WASO), expressed in minutes; number of nighttime awakenings; daytime total sleep time (DTST), expressed in minutes; number of daytime naps; and nighttime percentage of sleep (% sleep). The Mini-Mental State Examination and the Beck Depression Inventory were also administered. The mean age was 53.4  ±  17.0 years. After adjustment of confounding factors using multiple linear regression analysis, no difference in actigraphy parameters was detected between the groups: NTST (p=0.468), WASO (p=0.88), % sleep (p=0.754), awakenings (p=0.648), naps (p=0.414), and DTST (p=0.805). Different from previous studies employing qualitative analysis, the present assessment did not observe an influence of hemodialysis modality on objective sleep parameters in chronic renal patients.

scholarly journals Quantitative associations between objective sleep measures and early-morning mobility in Parkinson’s disease: cross-sectional analysis of the PHASE study

SLEEP ◽  
2019 ◽  
Vol 43 (1) ◽  
Author(s):  
Hiroshi Kataoka ◽  
Keigo Saeki ◽  
Yuki Yamagami ◽  
Kazuma Sugie ◽  
Kenji Obayashi
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Linear Regression Analysis ◽  
Sleep Onset ◽  
Sleep Time ◽  
Early Morning ◽  
Cross Sectional ◽  
Objective Evidence ◽  
Sleep Parameters ◽  
The Mean

Abstract Study Objectives Previous studies have suggested associations between sleep measures and early-morning akinesia; however, objective evidence is limited. The purpose of this study was to evaluate the associations between objective sleep measures and morning mobility among patients with Parkinson’s disease (PD). Methods In this cross-sectional study, we measured objective sleep parameters and morning mobility in 157 patients with PD (mean age, 71.4 years) for six consecutive days using an actigraph placed on the nondominant wrist. Low morning mobility was defined as less than 100 counts/min within the first 2 hours after rising. Results The mean duration of low morning mobility was 55.7 minutes (SD, 23.8), and the mean sleep parameters were as follows: sleep efficiency (SE), 72.1% (13.6); wake after sleep onset (WASO), 104.7 minutes (57.9); total sleep time (TST), 343.6 minutes (104.0); and fragmentation index (FI), 3.5 (3.4). Multivariable linear regression analysis adjusted for potential confounders demonstrated significant associations between better objective sleep measures and shorter low morning mobility (SE per %: β, −0.419; 95% CI = −0.635 to −0.204; p < 0.001; WASO per min: β, 0.056; 95% CI = 0.003 to 0.109; p = 0.039; and FI per unit; β, 1.161; 95% CI = 0.300 to 2.023; p = 0.009) but not TST (p = 0.78). These findings were not altered by different cutoff values of mobility (50 counts/min) or duration (1 h after rising). Conclusions In patients with PD, better objective sleep measures are significantly associated with shorter low morning mobility. Future studies investigating whether improved sleep reduces symptoms of low morning mobility are required.

scholarly journals Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Yu Fang ◽  
Daniel B. Forger ◽  
Elena Frank ◽  
Srijan Sen ◽  
Cathy Goldstein
Keyword(s):  
Mental Health ◽  
Smartphone Application ◽  
Sleep Time ◽  
Self Report ◽  
First Year ◽  
Cross Sectional ◽  
Wake Time ◽  
Mood Variability ◽  
Patient Health ◽  
Sleep Parameters

AbstractWhile 24-h total sleep time (TST) is established as a critical driver of major depression, the relationships between sleep timing and regularity and mental health remain poorly characterized because most studies have relied on either self-report assessments or traditional objective sleep measurements restricted to cross-sectional time frames and small cohorts. To address this gap, we assessed sleep with a wearable device, daily mood with a smartphone application and depression through the 9-item Patient Health Questionnaire (PHQ-9) over the demanding first year of physician training (internship). In 2115 interns, reduced TST (b = −0.11, p < 0.001), later bedtime (b = 0.068, p = 0.015), along with increased variability in TST (b = 0.4, p = 0.0012) and in wake time (b = 0.081, p = 0.005) were associated with more depressive symptoms. Overall, the aggregated impact of sleep variability parameters and of mean sleep parameters on PHQ-9 were similar in magnitude (both r2 = 0.01). Within individuals, increased TST (b = 0.06, p < 0.001), later wake time (b = 0.09, p < 0.001), earlier bedtime (b = − 0.07, p < 0.001), as well as lower day-to-day shifts in TST (b = −0.011, p < 0.001) and in wake time (b = −0.004, p < 0.001) were associated with improved next-day mood. Variability in sleep parameters substantially impacted mood and depression, similar in magnitude to the mean levels of sleep parameters. Interventions that target sleep consistency, along with sleep duration, hold promise to improve mental health.

scholarly journals Study of correlation between perceived sleep disturbances in depressed patients with objective changes in sleep architecture using polysomnography before and after antidepressant therapy

2020 ◽  
Vol 8 (7) ◽  
pp. 2551
Author(s):  
Ganesh Ingole ◽  
Harpreet S. Dhillon ◽  
Bhupendra Yadav
Keyword(s):  
Sleep Disturbances ◽  
Total Sleep Time ◽  
Antidepressant Treatment ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Sleep Architecture ◽  
Wake Time ◽  
Depressed Patients ◽  
Before And After

Background: A prospective cohort study to correlate perceived sleep disturbances in depressed patients with objective changes in sleep architecture using polysomnography (PSG) before and after antidepressant therapy.Methods: Patients were recruited into the study after applying strict inclusion and exclusion criterion to rule out other comorbidities which could influence sleep. A diagnosis of Depressive episode was made based on ICD-10 DCR. Psychometry, in the form of Beck Depressive inventory (BDI) and HAMD (Hamilton depression rating scale) insomnia subscale was applied on Day 1 of admission. Patients were subjected to sleep study on Day 03 of admission with Polysomnography. Patients were started on antidepressant treatment post Polysomnography. An adequate trial of antidepressants for 08 weeks was administered and BDI score ≤09 was taken as remission. Polysomnography was repeated post remission. Statistical analysis was performed using Kruskal Wallis test and Pearson correlation coefficient.Results: The results showed positive (improvement) polysomnographic findings in terms of total sleep time, sleep efficiency, wake after sleep onset, percentage wake time and these findings were statistically significant. HAM-D Insomnia subscale was found to correlate with total sleep time, sleep efficiency, wake after sleep onset, total wake time and N2 Stage percentage.Conclusions: Antidepressant treatment effectively improves sleep architecture in Depressive disorder and HAM-D Insomnia subscale correlates with objective findings of total sleep time, sleep efficiency, wake after sleep onset, total wake time and duration of N2 stage of NREM.

scholarly journals 1059 Sleep Parameters In People With Type 2 Diabetes With And Without Insomnia Symptoms

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A402-A403
Author(s):  
M Alshehri ◽  
A Alkathiry ◽  
A Alenazi ◽  
S Alothman ◽  
J Rucker ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Circular Data ◽  
Objective Measures ◽  
Subjective Measures ◽  
Sleep Parameters ◽  
Insomnia Symptoms

Abstract Introduction There is an increasing awareness of the high prevalence of insomnia symptoms in people with type 2 diabetes (T2D). Past studies have demonstrated the importance of measuring sleep parameters in both averages and variabilities using subjective and objective methods. Thus, we aimed to compare the averages and variability of sleep parameters in people with T2D with and without insomnia symptoms. Methods Actigraph measurements and sleep diaries were used in 59 participants to assess sleep parameters, including sleep efficiency (SE), sleep latency, total sleep time, and wake after sleep onset over seven nights. Validated instruments were used to assess the symptoms of depression, anxiety, and pain. Circular data were used to describe the distribution of bed distribution with SE as a magnitude for both groups. Mann Whitney U test was utilized to compare averages and variability of sleep parameters between the two groups. Multivariable general linear model to control for demographic and clinical variables. For the secondary aim, multiple linear regression tests were utilized to assess the association between averages and variability values for both groups. Results SE was found to be lower in average and higher in variability for participants with T2D and insomnia symptoms, than those with T2D only subjectively and objectively. SE variability was also the only sleep parameter higher in people with T2D and insomnia symptoms, with psychological symptoms potentially playing a role in this difference. We observed that people in T2D+Insomnia tend to go to bed earlier compared to the T2D only group based on objective measures, but no difference was observed between groups in subjective measures. The only significant relationship in both objective and subjective measures was between the averages and variability of SE. Conclusion Our findings suggest a discrepancy between subjective and objective measures in only average of total sleep time, as well as agreement in measures of variability in sleep parameters. Also, the relationship between averages and variabilities suggested the importance of improving SE to minimize its variability. Further research is warranted to investigate the complex relationship between sleep parameters and psychological factors in people with T2D and insomnia symptoms. Support None

Links between sleep and body mass index in bipolar disorders: An exploratory study

2015 ◽  
Vol 30 (1) ◽  
pp. 89-93 ◽  
Author(s):  
C. Boudebesse ◽  
P.-A. Geoffroy ◽  
C. Henry ◽  
A. Germain ◽  
J. Scott ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Sleep Disturbances ◽  
Sleep Onset ◽  
Bipolar Disorders ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Cross Sectional ◽  
Sleep Parameters

AbstractStudy objectives:Obesity and excess bodyweight are highly prevalent in individuals with bipolar disorders (BD) and are associated with adverse consequences. Multiple factors may explain increased bodyweight in BD including side effects of psychotropic medications, and reduced physical activity. Research in the general population demonstrates that sleep disturbances may also contribute to metabolic burden. We present a cross-sectional study of the associations between body mass index (BMI) and sleep parameters in patients with BD as compared with healthy controls (HC).Methods:Twenty-six French outpatients with remitted BD and 29 HC with a similar BMI completed a 21-day study of sleep parameters using objective (actigraphy) and subjective (PSQI: Pittsburgh Sleep Quality Index) assessments.Results:In BD cases, but not in HC, higher BMI was significantly correlated with lower sleep efficiency (P = 0.009) and with several other sleep parameters: shorter total sleep time (P = 0.01), longer sleep onset latency (P = 0.05), higher fragmentation index (P = 0.008), higher inter-day variability (P = 0.05) and higher PSQI total score (P = 0.004).Conclusions:The findings suggest a link between a high BMI and several sleep disturbances in BD, including lower sleep efficiency. Physiological mechanisms in BD cases may include an exaggeration of phenomena observed in non-clinical populations. However, larger scale studies are required to clarify the links between metabolic and sleep-wake cycle disturbances in BD.

scholarly journals Seasonal Sleep Variations and Their Association With Meteorological Factors: A Japanese Population Study Using Large-Scale Body Acceleration Data

2021 ◽  
Vol 3 ◽  
Author(s):  
Li Li ◽  
Toru Nakamura ◽  
Junichiro Hayano ◽  
Yoshiharu Yamamoto
Keyword(s):  
Sleep Quality ◽  
Seasonal Variations ◽  
Japanese Population ◽  
Large Scale ◽  
Meteorological Factors ◽  
Sleep Onset ◽  
Sleep Time ◽  
Population Based ◽  
Wake Time ◽  
Sleep Parameters

Seasonal changes in meteorological factors [e.g., ambient temperature (Ta), humidity, and sunlight] could significantly influence a person's sleep, possibly resulting in the seasonality of sleep properties (timing and quality). However, population-based studies on sleep seasonality or its association with meteorological factors remain limited, especially those using objective sleep data. Japan has clear seasonality with distinctive changes in meteorological variables among seasons, thereby suitable for examining sleep seasonality and the effects of meteorological factors. This study aimed to investigate seasonal variations in sleep properties in a Japanese population (68,604 individuals) and further identify meteorological factors contributing to sleep seasonality. Here we used large-scale objective sleep data estimated from body accelerations by machine learning. Sleep parameters such as total sleep time, sleep latency, sleep efficiency, and wake time after sleep onset demonstrated significant seasonal variations, showing that sleep quality in summer was worse than that in other seasons. While bedtime did not show clear seasonality, get-up time varied seasonally, with a nadir during summer, and positively correlated with the sunrise time. Estimated by the abovementioned sleep parameters, Ta had a practically meaningful association with sleep quality, indicating that sleep quality worsened with the increase of Ta. This association would partly explain seasonal variations in sleep quality among seasons. In conclusion, Ta had a principal role for seasonality in sleep quality, and the sunrise time chiefly determined the get-up time.

scholarly journals P129 A substantial percentage of patients with Chronic Insomnia do not appreciably increase Total Sleep Time after Cognitive Behavioural Therapy for Insomnia

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A63-A63
Author(s):  
H Scott ◽  
J Cheung ◽  
A Muench ◽  
H Ivers ◽  
M Grandner ◽  
...  
Keyword(s):  
Total Sleep Time ◽  
Sleep Onset ◽  
Severity Index ◽  
Randomised Clinical Trial ◽  
Sleep Time ◽  
Early Morning ◽  
Behavioural Therapy ◽  
Sleep Diary ◽  
Wake Time ◽  
Sleep Continuity

Abstract Introduction Total sleep time (TST) does not exceed baseline for the majority of patients after CBT-I. However by follow-up, TST increases by almost 1 hour on average. The current study investigated the extent to which this TST improvement is common and assessed for baseline predictors of increased TST after CBT-I. Methods This study is an archival analysis of data from a randomised clinical trial comparing acute CBT-I to acute CBT-I plus maintenance therapy (N = 80). The percent of patients that exceeded baseline TST by ≥30 minutes was assessed at post treatment and 3, 6, 12, and 24 months following treatment. Linear mixed models were conducted to assess the effect of patient demographics (age, sex, ethnicity, marital status), and baseline Sleep Diary-reported sleep continuity and Insomnia Severity Index (ISI) scores on changes in TST. Results 17% of patients achieved an appreciable increase in TST by treatment end, and this proportion only increased to 58% over time. Sleep Diary-reported sleep latency, wake after sleep onset, early morning awakenings, total wake time, TST, and sleep efficiency at baseline were associated with greater increases in TST after CBT-I (interaction ps &lt; .03). Demographics and ISI scores were not significant predictors (interaction ps &gt; .07). Conclusion A substantial proportion of patients do not appreciably increase TST after CBT-I, but patients with more severe sleep continuity disturbances at baseline exhibited the largest improvements. Whether all patients could increase their TST even further after CBT-I is a topic for further investigation.

scholarly journals Sleep and its Association With Pain and Depression in Nursing Home Patients With Advanced Dementia – a Cross-Sectional Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Kjersti Marie Blytt ◽  
Elisabeth Flo-Groeneboom ◽  
Ane Erdal ◽  
Bjørn Bjorvatn ◽  
Bettina S. Husebo
Keyword(s):  
Nursing Home ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Severe Depression ◽  
Sleep Time ◽  
Cross Sectional Study ◽  
Sleep Efficiency ◽  
Sectional Study ◽  
Severe Dementia ◽  
Cross Sectional

Objective: Previous research suggests a positive association between pain, depression and sleep. In this study, we investigate how sleep correlates with varying levels of pain and depression in nursing home (NH) patients with dementia.Materials and methods: Cross-sectional study (n = 141) with sleep-related data, derived from two multicenter studies conducted in Norway. We included NH patients with dementia according to the Mini-Mental State Examination (MMSE ≤ 20) from the COSMOS trial (n = 46) and the DEP.PAIN.DEM trial (n = 95) whose sleep was objectively measured with actigraphy. In the COSMOS trial, NH patients were included if they were ≥65 years of age and with life expectancy &gt;6 months. In the DEP.PAIN.DEM trial, patients were included if they were ≥60 years and if they had depression according to the Cornell Scale for Depression in Dementia (CSDD ≥ 8). In both studies, pain was assessed with the Mobilization-Observation-Behavior-Intensity-Dementia-2 Pain Scale (MOBID-2), and depression with CSDD. Sleep parameters were total sleep time (TST), sleep efficiency (SE), sleep onset latency (SOL), wake after sleep onset (WASO), early morning awakening (EMA), daytime total sleep time (DTS) and time in bed (TiB). We registered use of sedatives, analgesics, opioids and antidepressants from patient health records and adjusted for these medications in the analyses.Results: Mean age was 86.2 years and 76.3% were female. Hierarchical regressions showed that pain was associated with higher TST and SE (p &lt; 0.05), less WASO (p &lt; 0.01) and more DTS (p &lt; 0.01). More severe dementia was associated with more WASO (p &lt; 0.05) and TiB (p &lt; 0.01). More severe depression was associated with less TST (p &lt; 0.05), less DTS (p &lt; 0.01) and less TiB (p &lt; 0.01). Use of sedative medications was associated with less TiB (p &lt; 0.05).Conclusion: When sleep was measured with actigraphy, NH patients with dementia and pain slept more than patients without pain, in terms of higher total sleep time. Furthermore, their sleep efficiency was higher, indicating that the patients had more sleep within the time they spent in bed. Patients with more severe dementia spent more time awake during the time spent in bed. Furthermore, people with more severe depression slept less at daytime and had less total sleep time Controlling for concomitant medication use did not affect the obtained results.

scholarly journals 0260 Association Between Free-Living Physical Activity and Sleep in Icelandic Adolescents

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A99-A99
Author(s):  
V Rognvaldsdottir ◽  
E Johannsson ◽  
H M Soffia ◽  
R S Stefansdottir ◽  
S A Arngrimsson ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sleep Quality ◽  
Total Sleep Time ◽  
Linear Regression Analysis ◽  
Sleep Onset ◽  
Sleep Time ◽  
Free Living ◽  
Negatively Associated ◽  
Significant Difference ◽  
Objectively Measured

Abstract Introduction Sleep and physical activity are both important to health, but the demands of our modern schedule often require individuals to choose one over the other. In adolescents, the association between objectively measured sleep and physical activity is not well established in the literature. The aim of current study was to assess associations between free-living and physical activity and sleep among 15-year-old adolescents. Methods Free-living physical activity and sleep were assessed with wrist-worn accelerometers, sleep diary, and questionnaires during a 7-day period including school days and non-school days in 270 (161 girls) adolescents (mean age 15.8±0.3y) in Reykjavik, Iceland. Linear regression analysis was used to explore the associations between objectively measured physical activity and sleep. T-test was used to determine if there is a significant difference in objectively measured sleep between those who reported sports or exercising &lt;6 versus ≥6 h/week. Results Weekly mean physical activity (2040±466 counts/min of wear/day) was negatively associated with total sleep time (6.6±0.64 h/night) (β±SE=-3.5±0.7, p&lt;0.001). However, physical activity was also negatively associated with minutes of wake after sleep onset on non-school days (p=0.047) and standard deviation (i.e. night-to-night variability) of total sleep time over the week (p=0.028). Subjects who reported exercising ≥6 h/week (n=116) had lower night-to-night variability in bedtime (41.2±27.9 min) than those who did not (49.8±37.5 min), p=0.033. Conclusion The negative association between physical activity and sleep duration suggests that in more active individuals’ physical activity may be displacing sleep. However, greater physical activity is also associated with fewer minutes of awakening and a less variable sleep schedule, indicating better sleep quality. These findings suggest that physical activity is important for good sleep quality, but students should more closely consider sleep guidelines when designing an exercise schedule. Future studies should test how change in sleep patterns might influence physical activity. Support Icelandic Centre for Research, National Institute of Diabetes and Digestive and Kidney Diseases.

scholarly journals Spatial Usage and Circadian Rhythm for Older Adults in the Community in Taiwan

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 634-634
Author(s):  
Chih-Liang Wang ◽  
Ching-Ju Chiu
Keyword(s):  
Older Adults ◽  
Circadian Rhythm ◽  
Vigorous Physical Activity ◽  
Sleep Onset ◽  
Preliminary Finding ◽  
Objective Measure ◽  
Sleep Time ◽  
Exercise Frequency ◽  
Cross Sectional ◽  
Spatial Usage

Abstract Objective measure of lifestyle of the older adults living in the community is void in the literature. To obtain both objective and subjective measurements to ascertain mobile and day and night lifestyle of older adults living in the community, and to build lifestyle model of older adults in the community by sociodemographic character. This study is a cross-sectional research. 200 over-50-year older adults who own smartphone and live in southern Taiwan were interviewed. Wrist accelerometers to detect behavioral circadian rhythm, GPS app in smartphone to survey mobility, and questionnaire to assess psychological and social status. Preliminary finding of six participants (2 men and 4 women) was analyzed. Data show that participants about 60 years old have large discrepancies in comparison with participants in their 50s: lower sleep efficiency (73 vs 83), earlier Most active 10 hour midpoint (11.48vs 14.13 hour), higher interdaily variability (0.84 vs 0.75), wake after sleep onset (100.39vs 47.78 minutes), and higher exercise frequency (4.33 vs 1.66 times per week). In addition, men have more chronic disease, bigger waistline (103.5 vs 77.5 cm), higher BMI (30 vs 22.5), lower middle to vigorous physical activity time (39 vs 79 minutes), and more total sleep time (356 vs 317 minutes). Age and sex seem to be significant factors determining lifestyle of older adults. Other sociodemographic parameters will be further analyzed.

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