scholarly journals Prevalence and correlates of total sleep time among the older adults during COVID-19 pandemic in Bangladesh

2021 ◽  
Vol 1 ◽  
pp. 100008
Author(s):  
Sabuj Kanti Mistry ◽  
ARM Mehrab Ali ◽  
Md. Sabbir Ahmed ◽  
Uday Narayan Yadav ◽  
Md. Safayet Khan ◽  
...  
Keyword(s):  
Older Adults ◽  
Total Sleep Time ◽  
Sleep Time

scholarly journals Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study

10.2196/19732 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e19732
Author(s):  
Ben Kim ◽  
Sandra M McKay ◽  
Joon Lee
Keyword(s):  
Older Adults ◽  
Heart Rate ◽  
Logistic Regression ◽  
Home Care ◽  
Total Sleep Time ◽  
Care Service ◽  
Sleep Time ◽  
Wearable Devices ◽  
Wearable Device ◽  
Deep Sleep

Background Frailty has detrimental health impacts on older home care clients and is associated with increased hospitalization and long-term care admission. The prevalence of frailty among home care clients is poorly understood and ranges from 4.0% to 59.1%. Although frailty screening tools exist, their inconsistent use in practice calls for more innovative and easier-to-use tools. Owing to increases in the capacity of wearable devices, as well as in technology literacy and adoption in Canadian older adults, wearable devices are emerging as a viable tool to assess frailty in this population. Objective The objective of this study was to prove that using a wearable device for assessing frailty in older home care clients could be possible. Methods From June 2018 to September 2019, we recruited home care clients aged 55 years and older to be monitored over a minimum of 8 days using a wearable device. Detailed sociodemographic information and patient assessments including degree of comorbidity and activities of daily living were collected. Frailty was measured using the Fried Frailty Index. Data collected from the wearable device were used to derive variables including daily step count, total sleep time, deep sleep time, light sleep time, awake time, sleep quality, heart rate, and heart rate standard deviation. Using both wearable and conventional assessment data, multiple logistic regression models were fitted via a sequential stepwise feature selection to predict frailty. Results A total of 37 older home care clients completed the study. The mean age was 82.27 (SD 10.84) years, and 76% (28/37) were female; 13 participants were frail, significantly older (P<.01), utilized more home care service (P=.01), walked less (P=.04), slept longer (P=.01), and had longer deep sleep time (P<.01). Total sleep time (r=0.41, P=.01) and deep sleep time (r=0.53, P<.01) were moderately correlated with frailty. The logistic regression model fitted with deep sleep time, step count, age, and education level yielded the best predictive performance with an area under the receiver operating characteristics curve value of 0.90 (Hosmer-Lemeshow P=.88). Conclusions We proved that a wearable device could be used to assess frailty for older home care clients. Wearable data complemented the existing assessments and enhanced predictive power. Wearable technology can be used to identify vulnerable older adults who may benefit from additional home care services.

scholarly journals Caudate Volume Mediates the Interaction between Total Sleep Time and Executive Function after Acute Exercise in Healthy Older Adults

2019 ◽  
Vol 5 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Junyeon Won ◽  
Alfonso J. Alfini ◽  
Lauren R. Weiss ◽  
Casandra C. Nyhuis ◽  
Adam P. Spira ◽  
...  
Keyword(s):  
Older Adults ◽  
Executive Function ◽  
Acute Exercise ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Healthy Older Adults

scholarly journals Sleep continuity and total sleep time are associated with task-switching and preparation in young and older adults

2014 ◽  
Vol 23 (5) ◽  
pp. 508-516 ◽  
Author(s):  
Kristine A. Wilckens ◽  
Sarah G. Woo ◽  
Kirk I. Erickson ◽  
Mark E. Wheeler
Keyword(s):  
Older Adults ◽  
Task Switching ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Sleep Continuity

scholarly journals Home-Based Sleep Sensor Measurements in an Older Australian Population: Before and during a Pandemic

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 5993
Author(s):  
Mahnoosh Kholghi ◽  
Claire M. Ellender ◽  
Qing Zhang ◽  
Yang Gao ◽  
Liesel Higgins ◽  
...  
Keyword(s):  
Older Adults ◽  
Time Course ◽  
Total Sleep Time ◽  
Sleep Onset ◽  
Sleep Time ◽  
Community Dwelling ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Short Sleep Duration

Older adults are susceptible to poor night-time sleep, characterized by short sleep duration and high sleep disruptions (i.e., more frequent and longer awakenings). This study aimed to longitudinally and objectively assess the changes in sleep patterns of older Australians during the 2020 pandemic lockdown. A non-invasive mattress-based device, known as the EMFIT QS, was used to continuously monitor sleep in 31 older adults with an average age of 84 years old before (November 2019–February 2020) and during (March–May 2020) the COVID-19, a disease caused by a form of coronavirus, lockdown. Total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, time to bed, and time out of bed were measured across these two periods. Overall, there was no significant change in total sleep time; however, women had a significant increase in total sleep time (36 min), with a more than 30-min earlier bedtime. There was also no increase in wake after sleep onset and sleep onset latency. Sleep efficiency remained stable across the pandemic time course between 84–85%. While this sample size is small, these data provide reassurance that objective sleep measurement did not deteriorate through the pandemic in older community-dwelling Australians.

scholarly journals 0828 Descriptive Model of Sleep Quality in the Older Adults

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A315-A316
Author(s):  
P K Morelhao ◽  
G L Fernandes ◽  
V Dokkedal-Silva ◽  
G N Pires ◽  
S Tufik ◽  
...  
Keyword(s):  
Older Adults ◽  
Sleep Quality ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Descriptive Model ◽  
Subjective Sleep ◽  
Sleep Parameters ◽  
The City

Abstract Introduction Poor sleep quality is a health condition that impacts the quality of life of the older population. In the literature, there are questions about which objective sleep parameters should be considered to describe precisely the definition of sleep quality. There is ongoing debate with this term usually being used in relation to subjective sleep perception. This study aimed to investigate which objective and subjective sleep parameters contribute to a measurement of sleep quality in older adults. Methods A cross-sectional study using a representative sample of adults from the city of São Paulo, Brazil was performed. We used a dataset from the 2015 Epidemiological Study of Sleep from the City of São Paulo (EPISONO), including only individuals aged 60 years or more. We used exploratory factor analysis and structural equation modelling to identify relevant variables to a descriptive model of sleep quality. Results A total of 152 older adults were included. The final model consists of two factors, objective sleep quality which comprises sleep efficiency, total sleep time and sleep latency, and poor sleep perception, constituted by scores in the Pittsburgh Sleep Quality Index and Insomnia Severity Index. Conclusion The results suggested that sleep quality had both an objective (sleep efficiency, total sleep time, latency of sleep onset) and subjective dimensions (subjective questionnaires). These results may be useful in the clinical scenario, serving as leads for a better understanding of the sleep quality in aging patients. Future studies may also benefit from this descriptive model to further researches other associations, such as sleep and pain in this population. Support The study was supported by Associação Fundo de Incentivo à Pesquisa (AFIP) and Coordenação de Aperfeiçoamento de Nível Superior (CAPES). ST and MLA received support from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

scholarly journals Relationship Between Sleep and Function in Older Adults With Mild Cognitive Impairment

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 619-619
Author(s):  
Miranda McPhillips ◽  
Junxin Li ◽  
Darina Petrovsky ◽  
Nancy Hodgson
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Sleep Quality ◽  
Physical Function ◽  
Daytime Sleepiness ◽  
Total Sleep Time ◽  
Social Activity ◽  
Sleep Onset ◽  
Sleep Time ◽  
And Function

Abstract Our objective was to examine relationships between sleep characteristics and function in community-dwelling older adults with cognitive impairment. Sleep measures included actigraphy (total sleep time, wake after sleep onset, efficiency, awakenings), Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale. Promis Physical Function Short Form and Promis Item Bank Social were used to measure physical function and social activity. We used Spearman’s correlation and multivariate linear regression. In bivariate analyses, physical function was significantly related to daytime sleepiness, wake after sleep onset and awakenings; social activity was significantly related to sleep quality, daytime sleepiness, total sleep time, wake after sleep onset and number of awakenings. Controlling for cognition and age, sleep quality was independently associated with physical function (β= -0.80; p= 0.002). Relationships between sleep and social activity did not remain significant in multivariate analyses. Preliminary results suggest subjective sleep quality is most related to physical function.

Comparative efficacy and safety of hypnotics for insomnia in older adults: a systematic review and network meta-analysis

SLEEP ◽  
2020 ◽  
Author(s):  
Hsiao-Yean Chiu ◽  
Hsin-Chien Lee ◽  
Jen-Wei Liu ◽  
Shi-Jun Hua ◽  
Pin-Yuan Chen ◽  
...  
Keyword(s):  
Older Adults ◽  
Low Dose ◽  
Total Sleep Time ◽  
Meta Analysis ◽  
Sleep Onset ◽  
Sleep Time ◽  
Sleep Efficiency ◽  
Sleep Onset Latency ◽  
Efficacy And Safety ◽  
Onset Latency

Abstract Study Objectives To compare the efficacy and safety of various hypnotics for identifying the best treatments for insomnia in older adults. Methods We searched the EMBASE, PubMed, ClinicalTrials.gov, and ProQuest Dissertations and Theses A&I databases from the inception to September 12, 2020. Only randomized controlled trials comparing hypnotics with either another hypnotic or placebo for insomnia treatment in elderly people were included. Sleep outcomes, including total sleep time, sleep onset latency, wake after sleep onset, sleep efficiency, were derived from polysomnography, valid questionnaires, or sleep diaries. Results We identified 24 articles with 5917 older adults. Eszopiclone and low-dose doxepin were ranked the optimal therapy for prolonging objective and subjective total sleep time (26.69 and 28.19 min), respectively, compared to placebo. Zaleplon was the most effective therapy in reducing objective and subjective sleep onset latency (–21.63 and –15.86 min) compared with control. Temazepam was the best treatment for objective and subjective wake after sleep onset (–25.29 and –22.25 min) compared with control. Low-dose doxepin appeared to be the effective treatment for increasing objective sleep efficiency (6.08%) Triazolam showed the higher risk of overall adverse events (odds ratio, 1.96, 95% confidence interval 1.03–3.74) when compared to zaleplon. Conclusions Considering study quality and the potential adverse effects of benzodiazepines and nonbenzodiazepines, low-dose doxepin seems to be the optimal pharmacotherapy for the improvements in total sleep time and sleep efficiency. Future RCTs investigating the treatment effects of hypnotics, particularly low-dose doxepin, on insomnia in older adults are warranted. PROSPERO Registration number: CRD42016046301.

scholarly journals Consumer-Grade Wearable Device for Predicting Frailty in Canadian Home Care Service Clients: Prospective Observational Proof-of-Concept Study (Preprint)

2020 ◽  
Author(s):  
Ben Kim ◽  
Sandra M McKay ◽  
Joon Lee
Keyword(s):  
Older Adults ◽  
Heart Rate ◽  
Logistic Regression ◽  
Home Care ◽  
Total Sleep Time ◽  
Care Service ◽  
Sleep Time ◽  
Wearable Devices ◽  
Wearable Device ◽  
Deep Sleep

BACKGROUND Frailty has detrimental health impacts on older home care clients and is associated with increased hospitalization and long-term care admission. The prevalence of frailty among home care clients is poorly understood and ranges from 4.0% to 59.1%. Although frailty screening tools exist, their inconsistent use in practice calls for more innovative and easier-to-use tools. Owing to increases in the capacity of wearable devices, as well as in technology literacy and adoption in Canadian older adults, wearable devices are emerging as a viable tool to assess frailty in this population. OBJECTIVE The objective of this study was to prove that using a wearable device for assessing frailty in older home care clients could be possible. METHODS From June 2018 to September 2019, we recruited home care clients aged 55 years and older to be monitored over a minimum of 8 days using a wearable device. Detailed sociodemographic information and patient assessments including degree of comorbidity and activities of daily living were collected. Frailty was measured using the Fried Frailty Index. Data collected from the wearable device were used to derive variables including daily step count, total sleep time, deep sleep time, light sleep time, awake time, sleep quality, heart rate, and heart rate standard deviation. Using both wearable and conventional assessment data, multiple logistic regression models were fitted via a sequential stepwise feature selection to predict frailty. RESULTS A total of 37 older home care clients completed the study. The mean age was 82.27 (SD 10.84) years, and 76% (28/37) were female; 13 participants were frail, significantly older (<i>P</i>&lt;.01), utilized more home care service (<i>P</i>=.01), walked less (<i>P</i>=.04), slept longer (<i>P</i>=.01), and had longer deep sleep time (<i>P</i>&lt;.01). Total sleep time (r=0.41, <i>P</i>=.01) and deep sleep time (r=0.53, <i>P</i>&lt;.01) were moderately correlated with frailty. The logistic regression model fitted with deep sleep time, step count, age, and education level yielded the best predictive performance with an area under the receiver operating characteristics curve value of 0.90 (Hosmer-Lemeshow <i>P</i>=.88). CONCLUSIONS We proved that a wearable device could be used to assess frailty for older home care clients. Wearable data complemented the existing assessments and enhanced predictive power. Wearable technology can be used to identify vulnerable older adults who may benefit from additional home care services.

Integrative Review of the Relationship Between Sleep Disturbances and Episodic Memory in Older Adults

2018 ◽  
Vol 20 (4) ◽  
pp. 440-451 ◽  
Author(s):  
An-Yun Yeh ◽  
Susan J. Pressler ◽  
Bruno J. Giordani ◽  
Bunny J. Pozehl ◽  
Ann M. Berger
Keyword(s):  
Older Adults ◽  
Episodic Memory ◽  
Sleep Disturbances ◽  
Slow Wave Sleep ◽  
Total Sleep Time ◽  
Sleep Time ◽  
Lower Percentage ◽  
Eligibility Criteria ◽  
The Relationship ◽  
Selection Of

Impaired episodic memory in older adults has been linked to many factors. One of these factors is sleep disturbances, which are reported by more than 50% of older adults. The relationship between episodic memory and sleep disturbances remains unclear, however, because of the multiple types of measures of sleep and episodic memory used in previous studies. The purpose of this integrative literature review was to integrate and compare findings on this relationship in adults aged 65 years. An electronic search was conducted in PubMed, Cumulative Index to Nursing and Allied Health Literature, PsychINFO, and Medline for material published from the inception of the databases to December 2016. The literature search produced 13 data-based, peer-reviewed, and primary research articles that met eligibility criteria. The synthesized results from these articles provide evidence that older adults with 6–8 hr of self-reported total sleep time had better episodic memory than older adults with ≤5 hr or ≥9 hr of total sleep time. Shorter length and lower percentage of slow-wave sleep were associated with reduced episodic memory in older adults, but the results were controversial. Selection of different measurements and inconsistent variables across studies increased the difficulty of synthesizing and comparing the results. The diversity of covariates controlled in the included articles raise questions regarding which covariates should be controlled in such studies of sleep and episodic memory in older adults. The numerous study limitations were thus major barriers to understanding the relationship between sleep disturbances and episodic memory.

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