Sleep Quality and Cognitive Function in the Elderly Population

2020 ◽  
Author(s):  
Seyed Valiollah Mousavi ◽  
Elham Montazar ◽  
Sajjad Rezaei ◽  
Shima Poorabolghasem Hosseini
Keyword(s):  
Regression Analysis ◽  
Cognitive Function ◽  
Sleep Quality ◽  
Sleep Disorders ◽  
Elderly Population ◽  
Sleep Latency ◽  
The Elderly ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Subjective Sleep

Background and Objective: Physiological process of sleep is considered as one of the influential factors of human’s health and mental functions, especially in the elderly. This research aimed at studying the association between sleep quality and the cognitive functions in the elderly population. Materials and Methods: A total of 200 elderly people (65 years and older) who were the members of retirees associa-tion in Mashhad, Iran, participated in this cross-sectional study. The participants were asked to answer the questionnaire of Pittsburgh Sleep Quality Index (PSQI) and Montreal Cognitive Assessment (MoCA) test. Correlation between the total scores of PSQI and MoCA was evaluated by Pearson correlation coefficient. In order to predict the cognitive func-tion based on different aspects of PSQI, multiple regression analysis by hierarchical method was used after removing confounding variables. Results: A significant association was found between PSQI and MoCA (P < 0.001, r = -0.55) suggesting that the com-ponents of use of sleeping medication (P < 0.001, r = -0.47), sleep disorders (P < 0.001, r = -0.37), sleep latency (P < 0.001, r = -0.34), subjective sleep quality (P < 0.001, r = -0.32), sleep duration (P < 0.001, r = -0.27), sleep effi-ciency (P < 0.001, r = -0.26), and daytime dysfunction (P < 0.001, r = -0.15) had significant negative correlation with cognitive function, and the four components of subjective sleep quality (P = 0.010, β = -0.15), sleep latency (P = 0.040, β = -0.13), sleep disorders (P = 0.010, β = -0.26), and use of sleeping medication (P = 0.010, β = -0.26) played a role in prediction of cognitive function in regression analysis. Conclusion: Poor sleep quality, sleep latency, insomnia, sleep breathing disorder, and use of sleeping medication play a determining role in cognitive function of the elderly. Thus, taking care of the sleep health is necessary for the elderly.

scholarly journals 697 Sleep Quality After COVID-19 Infection

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A272-A273
Author(s):  
Benjamin Hackett ◽  
Varun Badami ◽  
Sunil Sharma ◽  
Robert Stansbury
Keyword(s):  
Sleep Quality ◽  
Sleep Latency ◽  
Acute Infection ◽  
Secondary Data ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Telephone Surveys ◽  
Subjective Sleep ◽  
Delta Sleep ◽  
Novel Virus

Abstract Introduction COVID-19 has proven to be a novel virus with significant complications to an expanding number of body systems. Hallmark characteristics of COVID-19 include substantial inflammatory response which has been linked to sleep dysregulation in previous studies. We examined the change in sleep quality after acute COVID-19 infections requiring hospitalization. Methods We performed a retrospective, single-center observational study of 20 patients with acute COVID-19 infection requiring hospitalization. Eligible patients were contacted and completed telephone surveys of the Pittsburgh Sleep Quality Index (PSQI) prior to and 1 month after hospital discharge. A score of ≥5 was indicative of poor sleep quality. Secondary data were collected from EMR. Results The mean PSQI prior to COVID-19 infection was 6.1, worsening to 10.3 one month after acute infection, denoting a delta-PSQI of 4.2 (p = 0.0004). There were noted statistically significant differences in certain components of the PSQI including: subjective sleep quality 0.8 to 1.7 (delta 0.9, p = 0.0003), sleep latency 1.25 to 1.85 (delta 0.6, p = 0.03), sleep disturbance 1.05 to 1.5 (delta 0.45, p = 0.0009), and daytime dysfunction 0.3 to 1.45 (delta 1.15, p = 0.0005). Sleep latency and daytime dysfunction accounted for the most change. Two groups declared themselves with 6 of the 20 patients having improvement/no change in PSQI, and 14 having worsening. Between these groups certain differences were seen including: Pre-infection PSQI 9.67 vs 4.57 (p = 0.009), delta global PSQI -0.83 vs 6.36 (p &lt; 0.001), delta subjective sleep quality 0.17 vs 1.2 (p = 0.002), delta sleep latency -0.3 vs 1 (p = 0.01), delta sleep duration -0.3 vs 0.93 (p = 0.02), delta sleep efficiency -0.3 vs 0.71 (p = 0.02), and delta daytime dysfunction 0.17 vs 1.57 (p = 0.006). Conclusion In our study of patients hospitalized for COVID-19 infection specific components of sleep were different following infection. Sleep latency and daytime dysfunction contributed the most to PSQI change. Two groups declared themselves based on PSQI improvement vs worsening. Those with poor sleep prior to infection continued to have poor sleep, while those without prior sleep troubles developed worsened sleep quality. Support (if any):

scholarly journals The Epidemiology of Subjective Sleep Quality in the Citizens of Kermanshah, Iran

2020 ◽  
Vol 24 (2) ◽  
Author(s):  
Keivan Kakabaraee ◽  
Habibolah Khazaie ◽  
Azita Chehri ◽  
Maryam Seidy
Keyword(s):  
Quality Of Life ◽  
Sleep Quality ◽  
Sleep Disorders ◽  
Self Report ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Cross Sectional ◽  
Subjective Sleep ◽  
High Doses

Background: Subjective sleep quality plays a pivotal role in health, quality of life, and efficient performance. Objectives: The present study aimed to investigate the epidemiology of subjective sleep quality in the citizens of Kermanshah, Iran. Methods: This cross-sectional, descriptive study was conducted on all the citizens of Kermanshah in 2017. In total, 450 subjects were selected via multistage random sampling. Based on the inclusion criteria, 416 were evaluated using a self-report questionnaire of demographic characteristics and Petersburg sleep quality index (PSQI; Baisi et al., 1989). Results: In 79% of the participants, the mean score of PSQI was above the cutoff point (m = 6.64). The analysis of the questionnaires indicated the highest frequency of sleep disorders to be in the components of subjective sleep quality from the perspective of the respondents, delayed sleep, sleep disorders, and daily functional disorders. In addition, 10.6% of the subjects used very high doses of sedatives, while 10.3% used relatively high doses of these pills. Minimal sleep disorders were reported as well. Poor sleep quality was less common in women, and significant correlations were observed between age and sleep latency, sleep duration, sleep medication use, and daytime dysfunction due to sleepiness. Conclusions: According to the results, subjective sleep quality was favorable in the citizens of Kermanshah. Considering the significant effects of sleep quality on performance and quality of life, attention must be paid to this aspect of health by healthcare planners and managers.

scholarly journals 0824 Improving Subjective Sleep Quality Measures Through Mindfulness Training in the Elderly: Preliminary Data from the Mindfulness Sleep Therapy (MIST) Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A314-A314
Author(s):  
F Perini ◽  
K Foong Wong ◽  
J Teng ◽  
Z Hassirim ◽  
J Lin ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Repeated Measures ◽  
Controlled Trial ◽  
Quality Measures ◽  
The Elderly ◽  
Behavioural Intervention ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Significant Group ◽  
Subjective Sleep

Abstract Introduction Poor sleep is a modifiable risk factor for multiple chronic disorders. Mindfulness-based therapies potentially improve sleep by enhancing awareness and acceptance of internal and external experiences, thus reducing pre-sleep hyper-arousal. In this pre-registered, randomized controlled trial, we tested the effect of mindfulness-based treatment for insomnia (MBTI) on subjective sleep quality measures (Pittsburgh Sleep Quality Questionnaire, PSQI) in the elderly. Methods Participants above 50 years old with sleep difficulties (PSQI ≥ 5) (mean (sd) age = 62.0 (6.35), 44 female) attended either an 8-week MBTI (N = 34) or sleep hygiene education and exercise program (SHEEP; N = 35). Before and after the interventions, we collected PSQI, insomnia symptoms and features measures (Pre-Sleep Arousal Scale, PSAS; Insomnia Severity Index, ISI; Dysfunctional Beliefs and Attitudes about Sleep, DBAS-30), mindfulness (Five-Facets Mindfulness Questionnaire, FFMQ), and mood and anxiety (Back Depression Inventory, BDI; State-Trait Anxiety Inventory, STAI). PSQI and PSAS (N = 26 to date) were collected at 6-month follow-up. Data were analysed with repeated-measures ANCOVA with group as a between-subject variable for the first 69 participants who completed the study. Results We observed significant improvement across both groups for sleep measures (PSQI: F1,67=36.442, p&lt;.01; PSAS-Cognitive: F1,67=12.664, p&lt;.01; ISI: F1,67=36.442, p&lt;.0; DBAS: F1,67=28.749, p&lt;.01) and mood (BDI: F1,67=26.393, p&lt;.01; STAI-State: F1,67=4.608, p=.04; STAI-Trait: F1,67=7.687, p&lt;.01), but not for Mindfulness (F1,67=2.256, p=.14) nor PSAS-somatic. No significant group by time interactions were found. We observed a correlation between PSQI decreases and FFMQ increases in MBTI (r=-.53, p&lt;.01), but not in SHEEP (r=-.07, p=.70) participants. ANCOVA of 6-month PSQI data revealed a significant group by time interaction (F1,24=19.525, p=.03), with reduction from baseline in MBTI (t12=4.769, p&lt;.01), but not in SHEEP group (t12=3.813, p=.08). Conclusion Preliminary results support MBTI as an accessible but effective behavioural intervention with potential long-term benefits for improving sleep and mood, and reducing cognitive-emotional arousal in the elderly. Support This study was supported by an award from the 7th grant call of the Singapore Millennium Foundation Research Grant Programme

scholarly journals Obesity, Fasting Blood Sugar, Triglyceride and Physical Activity in Association With Sleep Quality in Iranian Adults in 2019

2021 ◽  
Author(s):  
Mazyar Haghgoo ◽  
Atoosa Saidpour ◽  
Hakimeh Sadeghzadeh ◽  
Samira Rabiei
Keyword(s):  
Physical Activity ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Sleep Latency ◽  
P Value ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Cross Sectional ◽  
Positive Correlation ◽  
Subjective Sleep

Abstract ObjectivesSleep is an essentially biological process for health and the pattern of sleep. Poor sleep quality is increasingly recognized as a risk factor for poor health outcomes such as obesity, diabetes, and cardiovascular disease. This study aimed to investigate the association between sleep quality, body mass index (BMI) and glycemic and lipid profiles in Iranian adults in 2020.This descriptive cross-sectional study was conducted on adults aged 18-60 years from both sexes. Participants were selected from those who referred to community centers in Tehran Municipality. Three hundred and fifty-three Volunteers who had inclusion criteria entered the study by convenience sampling. Information on anthropometric measurements, Physical Activity and dietary intake were collected. Sleep quality was assessed through PSQI questionnaire. Biochemical analysis was also conducted to investigate FBS, Insulin and lipid profile.ResultsBMI had positive correlation with subscale of “sleep disturbances” and “use of sleep medication” (P-value <0.001). Physical activity had a significant negative correlation with subscales of “subjective sleep quality” and “sleep latency”. FBS and TG had positive correlation with “sleep latency” and “Subjective sleep quality”, respectively (p-value<0.05). Weak sleep quality has association with obesity, disorder of glucose and triglyceride metabolism and lower level of physical activity.

scholarly journals The influence of subjective sleep quality on the association between eveningness and depressive symptoms.

2018 ◽  
Author(s):  
Charlotte Mary Horne ◽  
Ray Norbury
Keyword(s):  
Depressive Symptoms ◽  
Sleep Quality ◽  
Mediation Analysis ◽  
Depression Scale ◽  
Well Being ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
Increased Risk ◽  
Healthy Participants

Increasing evidence suggests that eveningness is associated with increased risk for depression. Eveningness, however, is also associated with poor sleep quality and the unique role of eveningness in depressive symptomatology remains to be elucidated. The goal of the current study, therefore, was to examine the inter-relationships between eveningness, subjective sleep quality and depressive symptoms in healthy participants free of current or previous depression and sleep disorder. Here, 167 healthy participants (mean age 24.16, 129/38 females/males) completed the reduced Morningness-Eveningness Questionnaire (rMEQ), the Pittsburgh Sleep Quality Index (PSQI) and the Centre for Epidemiological Studies Depression Scale (CES-D). Bootstrap mediation analysis for a simple mediation model including rMEQ, PSQI and CES-D was applied. Eveningness was associated with increased depressive symptoms and mediation analysis showed that this relationship was partly mediated by sleep quality. Our results suggest that indicators of depression observed in evening-type individuals cannot be attributed exclusively to disturbed sleep. We suggest that interventions that target both sleep quality and dysfunctionl cognitive styles would be optimal to promote well-being in evening-type individuals.

The Effect of Uncoupled Sleep and Dysfunctional Sleep Beliefs on Sleep Outcomes in Older Adults following Online Cognitive Behavioral Therapy for Insomnia: A Single-Group Non-randomized Trial (Preprint)

2021 ◽  
Author(s):  
Yvonne Kutzer ◽  
Lisa Whitehead ◽  
Eimear Quigley ◽  
Shih Ching Fu ◽  
Mandy Stanley
Keyword(s):  
Older Adults ◽  
Cognitive Behavioral Therapy ◽  
Sleep Quality ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Behavioral Therapy ◽  
Sleep Onset ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Subjective Sleep

BACKGROUND The current Covid-19 pandemic has brought about a marked interest in sleep health, as well as an increased demand for telehealth services, such as online Cognitive Behavioral Therapy for insomnia (CBT-I). Older adults in particular report a high rate of sleep problems. Recent studies have suggested that dysfunctional sleep beliefs could contribute to the high rates of self-reported insomnia in this age group. In addition, older adults have an increased rate of uncoupled sleep, e.g. displaying an insomnia complaint in the absence of objectively measured poor sleep. It is essential to determine the prevalence of coupled and uncoupled sleep in older adults and to examine the efficacy of online CBT-I to improve sleep outcomes. OBJECTIVE This study aims to assess objective and subjective sleep quality and dysfunctional sleep beliefs in a sample of community-dwelling older adults aged 60-80 years with and without uncoupled sleep in Western Australia following digitally delivered CBT-I. METHODS Objective sleep was measured using wrist actigraphy, and subjective sleep quality via sleep diaries and the Pittsburgh Sleep Quality Index (PSQI). Dysfunctional sleep beliefs were assessed by the Dysfunctional Beliefs and Attitudes about Sleep scale (DBAS-16) prior to and following a four-week online CBT-I programme. Linear mixed model and generalised linear mixed model analyses were conducted to examine objective and subjective sleep onset latency, total sleep time, wake after sleep onset and number of awakenings as well as PSQI and DBAS16 scores, respectively. RESULTS 62 participants (55 females; 88.7%) completed the study. CBT-I effectively reduced dysfunctional sleep beliefs and PSQI scores across all sleep classifications, even in good sleepers without a sleep complaint. Objective and self-reported changes in sleep parameters were mainly demonstrated in complaining poor sleepers. Complaining good sleepers reported a decrease in the number of subjective sleep awakenings only. CONCLUSIONS Online CBT-I was effective in improving the sleep outcomes of individuals who had both subjective and objective poor sleep. However, as the online CBT-I reduced dysfunctional sleep beliefs in all sleep groups, further examination of dysfunctional sleep beliefs and whether they mediate the outcomes of digital CBT-I in older adults will need to be conducted. CLINICALTRIAL Australian New Zealand Clinical Trials Registry (ANZCTR), ACTRN 12619001509156; http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378451 INTERNATIONAL REGISTERED REPORT RR2-32705

scholarly journals Prevalence and Determinants of Bad Sleep Perception among Italian Children and Adolescents

2020 ◽  
Vol 17 (24) ◽  
pp. 9363
Author(s):  
Serena Malloggi ◽  
Francesca Conte ◽  
Giorgio Gronchi ◽  
Gianluca Ficca ◽  
Fiorenza Giganti
Keyword(s):  
Sleep Quality ◽  
Depressed Mood ◽  
Behavioral Problems ◽  
Sleep Disturbances ◽  
Sleep Problems ◽  
Sleep Latency ◽  
Sleep Habits ◽  
Subjective Sleep Quality ◽  
Quality Perception ◽  
Subjective Sleep

Although sleep problems at young ages are well investigated, the prevalence of bad sleepers and the determinants of sleep quality perception remain unexplored in these populations. For this purpose, we addressed these issues in a sample of children (n = 307), preadolescents (n = 717), and adolescents (n = 406) who completed the School Sleep Habits Survey, addressing sleep quality perception, sleep habits, sleep features, daytime behavior and sleep disturbances, circadian preference, and dreaming. The sample was split in “good sleepers” and “bad sleepers”, based on the answer to the question item assessing overall subjective sleep quality. Being a bad sleeper was reported by 11.7% of the sample, with significant between-groups differences (children: 8.3%; preadolescents: 11.3%; adolescents: 15.3%; p = 0.01). At all ages, relative to good sleepers, bad sleepers showed higher eveningness, sleepiness, and depression, longer sleep latency, more frequent insufficient sleep, nocturnal awakenings, sleep–wake behavioral problems, and unpleasant dreams (all p’s ≤ 0.01). Sleep quality perception was predicted: in children, by depressed mood, eveningness, and unpleasant dreams (all p’s ≤ 0.01); in preadolescents, by sleep latency, awakening frequency, depressed mood, sufficiency of sleep, and unpleasant dreams (all p’s < 0.01); in adolescents, by awakening frequency, depressed mood, and sufficiency of sleep (all p’s < 0.001). In children, bad subjective sleep quality appears to be mainly determined by daytime psychological features, for example, depressed mood, whereas at later ages, sleep characteristics, such as frequent awakenings, add to the former determinants. This could depend on (a) the appearance, with increasing age, of objective sleep modifications and (b) a greater attention paid by adolescents to their sleep characteristics.

scholarly journals Assessing the impact of daylight exposure on sleep quality of people over 65 years old

2020 ◽  
Vol 41 (2) ◽  
pp. 183-192
Author(s):  
Lorna Flores-Villa ◽  
Jemima Unwin ◽  
Peter Raynham
Keyword(s):  
Sleep Quality ◽  
Elderly Population ◽  
The Elderly ◽  
Physical Activities ◽  
Sleep Disruption ◽  
Poor Sleep ◽  
Ageing Population ◽  
Poor Sleep Quality ◽  
Daylight Exposure ◽  
The Impact

Due to our social behaviours, people spend at least 80% of their time indoors, mostly under artificial light. In research and building design, daylight is considered a valuable asset because it is the primary source of free, good quality light and it is suggested that it has a positive influence on human performance, health and sleep quality. There is a tendency in the population for increasingly poor sleep quality with age, and this affects at least 50% of the elderly population. Research on sleep disruption has found that especially in the elderly population, interrupted sleep can affect alertness, cognitive performance and mood. This increases the risk of falls, increases fatigue and reduces some other mental functions. Exposure to daylight (indoors and outdoors) is expected to reduce sleep disruption. Physical activities and sleep quality were assessed using 32 participants living independently in the UK, aged between 65 and 95 years old. The study was divided into two seasons due to a considerable difference in daylight availability in summer and winter. In each season participants completed the Pittsburgh Sleep Quality Index (PSQI) questionnaire, Morningness–Eveningness Questionnaire (MEQ) and a seven-day sleep diary/log activity; where time spent outdoors was identified. It was expected that participants who reported less exposure to daylight during summer and winter would report worse sleep quality. However, this was not the case; subjective sleep quality did not differ greatly between summer and winter, even though exposure to daylight varies greatly between seasons. This study explores the relationship between exposure to daylight throughout two different seasons and people’s chronotypes, physical activities and sleep quality (between and within participants). This information is essential to find means of supporting an ageing population. Practical applications: In the built environment, daylight is an important feature to consider for the occupant’s health and wellbeing. This research provides real-world insight into the amount of daylight that active aged people are exposed to during two seasons in London, and how this could impact their overall sleep quality. The findings suggest that exposure to daylight could benefit people over 65 years old with poor sleep quality by reducing the number of awakenings during the night. This research provides a step towards understanding how daylight exposure effects people, and can be used to inform housing design for the ageing population.

scholarly journals Psychological Distress Induces Poor Sleep Quality: A Cross-Sectional Study of Pharmacy Students in Bandung City, Indonesia

2018 ◽  
Vol 11 (1) ◽  
pp. 369-375 ◽  
Author(s):  
Sofa D. Alfian ◽  
Henry Ng ◽  
Dika P. Destiani ◽  
Rizky Abdulah
Keyword(s):  
Psychological Distress ◽  
Sleep Quality ◽  
Undergraduate Students ◽  
Cross Sectional Study ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Cross Sectional Survey ◽  
Subjective Sleep Quality ◽  
Cross Sectional ◽  
Subjective Sleep

Introduction: Poor subjective sleep quality in undergraduate students has not been widely studied in Bandung city, Indonesia. Poor sleep quality has been related to a number of risk factors for poor health outcomes. Objective: To analyze the association between psychological distress and subjective sleep quality. Methods: A cross sectional survey was done in one of the universities of Bandung city, Indonesia. Data were collected from 290 undergraduate students selected through consecutive sampling. Pittsburg Sleep Quality Index (PSQI) and Kessler-10 questionnaire were administered. Results: The prevalence of psychological distress was well (43.1%), mild (28.6%), moderate (20.7%), and severe (7.6%). The overall sleep quality was poor and good in 84.5% and 15.5% of the students. There was a significant association between psychological distress and poor sleep quality (p=0.006). The multivariate analysis suggested that psychological distress was a predictor of poor sleep quality (OR 1.991; 95% CI, 1.311−3.026). Conclusion: There is a need for an awareness of the college resources to help manage the stress levels of students through effective coping strategy-related study habits.

scholarly journals Association between sleep hygiene and sleep quality in medical students

2017 ◽  
Author(s):  
Cameron Brick
Keyword(s):  
Medical Students ◽  
Sleep Quality ◽  
Sleep Hygiene ◽  
Future Research ◽  
Poor Sleep ◽  
Sleep Habits ◽  
Subjective Sleep Quality ◽  
Web Based ◽  
Subjective Sleep ◽  
Future Research Directions

The aim of the current study was to determine whether subjective sleep quality was reduced in medical students, and whether demographics and sleep hygiene behaviors were associated with sleep quality. A web-based survey was completed by 314 medical students, containing questions about demographics, sleep habits, exercise habits, caffeine, tobacco and alcohol use, and subjective sleep quality (using the Pittsburgh Sleep Quality Index). Correlation and regression analyses tested for associations among demographics, sleep hygiene behaviors, and sleep quality. As hypothesized, medical students’ sleep quality was significantly worse than a healthy adult normative sample (t=5.13, p&lt;.001). Poor sleep quality in medical students was predicted by several demographic and sleep hygiene variables, and future research directions are proposed.Brick, C., Seely, D. L., &amp; Palermo, T. M. (2010). Association between sleep hygiene and sleep quality in medical students. Behavioral Sleep Medicine, 8(2), 113–121. https://www.tandfonline.com/doi/abs/10.1080/15402001003622925

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