Association of sleep disturbance with diabetic retinopathy

2020 ◽  
pp. 112067212097429
Author(s):  
Somsubhra Dutta ◽  
Sambuddha Ghosh ◽  
Srijit Ghosh
Keyword(s):  
Diabetic Retinopathy ◽  
Sleep Quality ◽  
Sleep Disturbance ◽  
Sleep Disturbances ◽  
Sleep Latency ◽  
Poor Sleep ◽  
Subjective Sleep Quality ◽  
Severe Difficulty ◽  
Normal Sleep ◽  
Internal Homogeneity

Purpose: Diabetes mellitus (DM) patients are more likely to experience sleep disturbances than normal. Sleep disturbances may contribute to the development of diabetic retinopathy (DR) by higher inflammatory markers in circulation. We investigated the association between sleep quality and DR. Methods: Institutional case control study with type 2 DM patients of <10 years duration and HbA1c ⩽8%; 70 cases with DR and 70 controls without DR (NODR) (power 0.8). Sleep quality was assessed by Pittsburg sleep quality index (PSQI) questionnaire and compared. Results: Cronbach’s alpha was 0.777 with high internal homogeneity. Global PSQI score in DR (7.44 ± 3.99; 95%CI 6.88, 9.42) was more than in NODR (4.30 ± 3.26; 95%CI 3.87, 6.45) ( p < 0.001). All sleep disturbance scores were more in DR except sleep duration. Poor sleep (PSQI score>5) was more prevalent in DR ( p = 0.000) and associated with increasing DR severity ( p = 0.026). Normal sleep latency was recorded in 78.57% and 42.85% patients in NODR and DR respectively ( p < 0.001). Severe difficulty in subjective sleep quality ( p = 0.024), sleep latency ( p = 0.002) and daytime dysfunction ( p < 0.001) was seen more in DR. Elevated daytime dysfunction was observed with increasing DR severity ( p = 0.008). The optimal cut-off for global PSQI score and sleep latency for DR was 5.5 (OR: 5.97; 95%CI 2.86, 12.47) and 25 min(OR: 4.89; 95%CI 2.32, 10.26) respectively. Conclusion: Sleep disturbance is positively associated with DR. Our study identifies cut off value for DR of a modifiable parameter like sleep latency. It emphasizes the need of sleep quality assessment for risk assessment of DR.

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 Association between depression and sleep quality in patients with systemic lupus erythematosus: a systematic review and meta-analysis

2021 ◽  
Author(s):  
Rulan Yin ◽  
Lin Li ◽  
Lan Xu ◽  
Wenjie Sui ◽  
Mei’e Niu ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Sleep Quality ◽  
Lupus Erythematosus ◽  
Sleep Disturbances ◽  
Cochrane Library ◽  
Poor Sleep ◽  
Moderate Correlation ◽  
Systemic Lupus ◽  
Poor Sleep Quality ◽  
Subjective Sleep Quality

Abstract Background Currently, there is no consistent understanding of the relationship between depression and sleep quality in patients with systemic lupus erythematosus (SLE). This study aimed to explore the correlation between depression and sleep quality in SLE patients. Methods Five English (PubMed, Web of Science, EMBASE, Cochrane Library, and CINAHL) databases were systematically searched from inception to January 12, 2021. Two authors independently screened publications and extracted data according to set inclusion and exclusion criteria. Statistical analyses were performed with STATA 16.0. Data were pooled using a random-effects model. Results A total of 9 identified studies matched the inclusion criteria, reporting on 514 patients with SLE in the analysis. A moderate correlation of depression with sleep quality was found (pooled r = 0.580 [0.473, 0.670]). Compared to good sleepers, patients with SLE and poor sleep quality had higher levels of depression (standardized mean difference =  − 1.28 [− 1.87, − 0.69]). Depression was associated with subjective sleep quality (r = 0.332 [0.009, 0.592]), sleep latency (r = 0.412 [0.101, 0.649]), sleep disturbances (r = 0.405 [0.094, 0.645]), daytime dysfunction (r = 0.503 [0.214, 0.711]), the four dimensions of Pittsburgh Sleep Quality Index (PSQI), while no significant correlation was found in the other three PSQI dimensions. Conclusion Depression had a moderate correlation with sleep quality in patients with SLE. Patients with poor sleep quality tended to have higher level of depression than that of good sleepers. Awareness of the correlation may help rheumatology physicians and nurses to assess and prevent depression and improve sleep quality in patients with SLE.

601 Comparison of Sleep Parameters in Children with Achondroplasia and Trisomy 21

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A236-A237
Author(s):  
Jodi Gustave ◽  
Kaelyn Gaza ◽  
Jennifer Marriner ◽  
Seema Rani ◽  
Abigail Strang ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Rem Sleep ◽  
Trisomy 21 ◽  
Sleep Disturbances ◽  
Sleep Latency ◽  
Sleep Efficiency ◽  
Sleep Architecture ◽  
Poor Sleep ◽  
Arousal Index ◽  
Sleep Parameters

Abstract Introduction Children with achondroplasia and Trisomy 21 (T21) have increased incidence of sleep disturbances including sleep disordered breathing. Abnormal sleep architecture has been documented in children with T21. It is important to continue to analyze sleep parameters in both groups since poor sleep quality is associated with neurocognitive impairment. Methods Following IRB approval, we performed a retrospective chart review of patients at Nemours/A.I. duPont Hospital for Children in Wilmington, DE with achondroplasia and T21 who underwent an initial polysomnogram (PSG) between 2015 and 2020. We compared sleep architecture parameters between the groups including sleep efficiency, total sleep time (TST), sleep latency, arousal index and concentration of N3 and REM sleep. Results In patients with achondroplasia (n=49, mean age 5.8 months and 63.3% male), 12% reported restless sleep. PSG data revealed TST of 392 minutes, mean sleep efficiency of 82%, mean sleep latency of 9.4 min, mean arousal index of 40, 22% REM sleep and 32% N3 sleep. In the patients with T21 (n=32, mean age 17.8 months and 50% male), 59% reported restless sleep. PSG data revealed TST of 393 minutes, mean sleep efficiency of 82%, mean sleep latency of 14 minutes, arousal index of 35, 15% REM sleep and 40% N3 sleep. The differences in REM and N3 sleep between the two groups were statistically significant (p-values of 0.001 and 0.04, respectively), but the differences in arousal index, TST and sleep efficiency were not. Conclusion Our study showed that children with T21 subjectively noted more restless sleep compared to patients with achondroplasia although TST and sleep efficiency were similar. Patients with achondroplasia had a higher arousal index that was not statistically significant. Children with achondroplasia had a shorter sleep latency and more robust REM concentration, likely due to their younger age. There was a higher concentration of N3 sleep in patients with T21. This is likely due to the decrease in REM concentration. In conclusion, it is important to establish expected sleep parameters in patients with achondroplasia and T21 to maximize sleep quality and mitigate negative neurocognitive effects of poor sleep. Support (if any):

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.

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.

Sleep quality and emotional reactivity cluster in bipolar disorders and impact on functioning

2017 ◽  
Vol 45 ◽  
pp. 190-197 ◽  
Author(s):  
B. Etain ◽  
O. Godin ◽  
C. Boudebesse ◽  
V. Aubin ◽  
J.M. Azorin ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Emotional Reactivity ◽  
Sleep Latency ◽  
Bipolar Disorders ◽  
Emotional Dysregulation ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Mood Symptoms

AbstractObjective:Bipolar disorders (BD) are characterized by sleep disturbances and emotional dysregulation both during acute episodes and remission periods. We hypothesized that sleep quality (SQ) and emotional reactivity (ER) defined clusters of patients with no or abnormal SQ and ER and we studied the association with functioning.Method:We performed a bi-dimensional cluster analysis using SQ and ER measures in a sample of 533 outpatients patients with BD (in remission or with subsyndromal mood symptoms). Clusters were compared for mood symptoms, sleep profile and functioning.Results:We identified three clusters of patients: C1 (normal ER and SQ, 54%), C2 (hypo-ER and low SQ, 22%) and C3 (hyper-ER and low SQ, 24%). C1 was characterized by minimal mood symptoms, better sleep profile and higher functioning than other clusters. Although highly different for ER, C2 and C3 had similar levels of subsyndromal mood symptoms as assessed using classical mood scales. When exploring sleep domains, C2 showed poor sleep efficiency and a trend for longer sleep latency as compared to C3. Interestingly, alterations in functioning were similar in C2 and C3, with no difference in any of the sub-domains.Conclusion:Abnormalities in ER and SQ delineated three clusters of patients with BD and significantly impacted on functioning.

scholarly journals Poor Sleep and Decision-Making Disturbance Are Associated With Suicidal Ideation in Pre-natal Depression

2021 ◽  
Vol 12 ◽  
Author(s):  
Ciqing Bao ◽  
Ling Xu ◽  
Weina Tang ◽  
Shiyu Sun ◽  
Wenmiao Zhang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Suicidal Ideation ◽  
Sleep Quality ◽  
Sleep Disturbance ◽  
Poor Sleep ◽  
Healthy Controls ◽  
Subjective Sleep Quality ◽  
Subjective Sleep ◽  
Post Natal Depression

Although many risk factors for suicidal ideation have been identified, few studies have focused on suicidal ideation and pre-natal depression. The purpose was to investigate the relationship between decision-making (DM) dysfunction and sleep disturbance on suicidal ideation in pre-natal depression. Participants included 100 women in the third trimester of pregnancy, including pregnant women with pre-natal depression who had recent suicidal ideation (n = 30), pre-natal depression without SI (n = 35) and healthy controls (n = 35). The Iowa Gambling Task (IGT) was used to evaluate the DM function and the Pittsburgh Sleep Quality Index (PSQI) was used to assess the sleep index. The Edinburgh Post-natal Depression Scale (EPDS) was used to assess suicidal ideation and the seriousness of depression. Overall, the two groups with pre-natal depression showed worse sleep quality and decreased DM function compared with healthy controls. The pre-natal depression with suicidal ideation group showed a significantly higher score in subjective sleep quality and a lower score in block 5 of IGT than the pre-natal depression without suicidal ideation group. Further correlation analysis showed that suicidal ideation positively correlated with subjective sleep quality, sleep duration, and daytime function, and negatively correlated with IGT scores. Sleep disturbance and impaired DM function may be risk factors for suicidal ideation in pre-natal depression.

scholarly journals Sleep quality and body weight status of Malaysian university students

2020 ◽  
Vol 26 (3) ◽  
pp. 461-470
Author(s):  
Nurul Fareeza Suhaimi ◽  
◽  
Zuriati Ibrahim ◽  
Siti Nur ‘Asyura Adznam ◽  
Sabariah Md Noor ◽  
...  
Keyword(s):  
Body Weight ◽  
University Students ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Weight Status ◽  
Sleep Latency ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Body Weight Status ◽  
Normal Body Weight

Introduction: Inadequate sleep duration is a modifiable behaviour linked with body weight, yet limited is known on the role of sleep quality with body weight status among university students. The study aimed to determine sleep quality and its association with body weight status among university students. Methods: A crosssectional study was conducted among 240 university students (24.6% males, 75.4% females) with a mean age of 21.22±1.24 years. Subjects were recruited from four faculties of University Putra Malaysia (UPM). Information on socio-demographic, sleep quality and anthropometric measurements were collected. Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality, whereby a summation score from seven components yielded a global score on sleep quality, with higher scores indicating poor sleep quality. Results: Majority of subjects were Malay (79.2%) with a mean body mass index of 22.6kg/m2. A majority (61.3%) had normal body weight, with the prevalences of underweight (UW), overweight (OW), and obesity (OB) at 12.9%, 19.6% and 6.3%, respectively. The mean global PSQI score was 5.76±2.64, with half of the respondents (50.4%) experiencing poor sleep quality. OW-OB experienced poorer sleep quality (6.53±2.79, p=0.004) and longer sleep latency (1.34±0.10, p=0.008) relative to UW-NW. OB subjects had substantially more frequent sleep disturbances compared to non-OB subjects (1.53±0.64, p=0.012). Conclusion: Findings suggest that OW-OB students at university are at a greater risk of having reduced sleep quality with longer sleep latency and frequent sleep disturbances. There is a need for a wellness initiative to reduce the incidence of obesity while fostering healthier sleeping habits among university students.

scholarly journals PEAR model and sleep outcomes in dementia caregivers: influence of activity restriction and pleasant events on sleep disturbances

2011 ◽  
Vol 23 (9) ◽  
pp. 1462-1469 ◽  
Author(s):  
Raeanne C. Moore ◽  
Alexandrea L. Harmell ◽  
Elizabeth Chattillion ◽  
Sonia Ancoli-Israel ◽  
Igor Grant ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Sleep Disturbance ◽  
High Activity ◽  
Sleep Latency ◽  
Subjective Sleep Quality ◽  
Activity Restriction ◽  
Subjective Sleep ◽  
Quality Sleep ◽  
Low Activity ◽  
Pleasant Events

ABSTRACTBackground:Sleep disturbance is a common consequence of providing care to a loved one with Alzheimer's disease (AD). We explored the usefulness of the Pleasant Events and Activity Restriction (PEAR) model for predicting multiple domains of sleep disturbance.Methods:Our sample consisted of 125 spousal AD caregivers. Participants completed the Pittsburg Sleep Quality Index (PSQI) and were questioned regarding the frequency with which they engaged in pleasant events and the extent to which they felt restricted in engaging in social and recreational activities in the past month. Participants were classified into one of three groups: HPLR = High Pleasant Events + Low Activity Restriction (= reference group; N = 38); HPHR/LPLR = either High Pleasant Events + High Activity Restriction or Low Pleasant Events + Low Activity Restriction (N = 52); and LPHR: Low Pleasant Events + High Activity Restriction (N = 35). These three groups were compared on the seven subscales of the PSQI.Results:Significant differences were found between the HPLR and LPHR groups on measures of subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbance, and daytime dysfunction. Additionally, significant differences were found between the HPLR and HPHR/LPLR groups on subjective sleep quality, sleep latency, and habitual sleep efficiency, and between the HPHR/LPLR and LPHR groups on sleep disturbance and daytime dysfunction.Conclusions:This study provides broad support for the PEAR model and suggests that interventions focusing on behavioral activation may potentially provide benefits to non-affective domains including sleep.

scholarly journals Associations between sleep quality and its domains and insufficient physical activity in a large sample of Croatian young adults: a cross-sectional study

BMJ Open ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. e021902 ◽  
Author(s):  
Lovro Štefan ◽  
Goran Sporiš ◽  
Tomislav Krističević ◽  
Damir Knjaz
Keyword(s):  
Physical Activity ◽  
Young Adults ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Smoking Status ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Subjective Sleep Quality ◽  
Cross Sectional ◽  
Insufficient Physical Activity

ObjectivesThe main purpose of the present study was to explore the associations between sleep quality and insufficient physical activity.DesignCross-sectional.SettingFaculties in Croatia.Participants2100 university students (1049 men and 1051 women) aged 18–24 years were recruited.Primary outcomeTo assess the domains of sleep quality (independent variables) and ‘insufficient’ physical activity (dependent variable), we used previously validated Pittsburgh Sleep Quality Index and International Physical Activity questionnaires. Logistic regressions were used to calculate the associations between the sleep quality and ‘insufficient’ physical activity.ResultsWhen sleep quality domains were entered separately into the model, very bad subjective sleep quality (OR 3.09; 95% CI 1.50 to 6.56), >60 min of sleep latency (OR 2.17; 95% CI 1.39 to 3.39), <7 hours of sleep (OR 1.56; 95% CI 1.24 to 1.96), <65% of habitual sleep efficiency (OR 2.26; 95% CI 1.26 to 4.05), sleep disturbances >1/week (OR 1.61; 95% CI 1.03 to 2.52), use of sleep medication >1/week (OR 3.35; 95% CI 1.83 to 6.10), very big daytime dysfunction problem (OR 2.78; 95% CI 1.57 to 4.93) and poor sleep quality (1.53; 95% CI 1.23 to 1.91) were associated with ‘insufficient’ physical activity. When all sleep quality domains were entered simultaneously into the model, the same significant associations remained, except for sleep disturbances. Both models were adjusted for gender, body mass index, self-rated health, life satisfaction, socioeconomic status, presence or absence of chronic diseases, smoking status, binge drinking and psychological distress.ConclusionsOur results show that ‘poor’ sleep quality is associated with ‘insufficient’ physical activity in young adults. In order to improve, special strategies and policies that leverage ‘good sleep’ quality are warranted.

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