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.

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 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 A Mediterranean Dietary Pattern Predicts Better Sleep Quality in US Women from the American Heart Association Go Red for Women Strategically Focused Research Network

Nutrients ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2830
Author(s):  
Faris M. Zuraikat ◽  
Nour Makarem ◽  
Marie-Pierre St-Onge ◽  
Huaqing Xi ◽  
Alekha Akkapeddi ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Mediterranean Diet ◽  
Dietary Pattern ◽  
Sleep Disturbances ◽  
Vegetable Consumption ◽  
Sleep Efficiency ◽  
Research Network ◽  
Poor Sleep ◽  
Linear Regression Models ◽  
Diet Pattern

Consumption of a Mediterranean diet has been linked to better sleep health in older, European populations. However, whether this dietary pattern is predictive of sleep quality in US women, a group prone to poor sleep, is unknown. This prospective cohort study of 432 US women (20–76 y; 60% racial/ethnic minority) evaluated whether compliance with a Mediterranean diet at baseline predicted sleep quality at 1-y follow-up. Alternate Mediterranean (aMed) diet scores and habitual sleep quality were computed from the validated Block Brief Food Frequency Questionnaire and Pittsburgh Sleep Quality Index (PSQI), respectively. Linear regression models evaluated prospective associations of the aMed diet pattern and its components with measures of sleep quality, after adjustment for age, BMI, race/ethnicity, education, and health insurance status. Higher baseline aMed scores were associated with lower PSQI scores (β = −0.30 ± 0.10, p < 0.01), indicative of better sleep quality, higher sleep efficiency (β = 1.20 ± 0.35, p < 0.001), and fewer sleep disturbances (β = −0.30 ± 0.12, p = 0.01) at 1-y. Fruit and vegetable consumption also predicted lower PSQI scores, higher sleep efficiency and fewer sleep disturbances (all p < 0.05). Higher legume intake predicted better sleep efficiency (β = 1.36 ± 0.55, p = 0.01). These findings suggest that adherence to a Mediterranean diet pattern should be evaluated as a strategy to promote sleep quality in US women.

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 Overnight Melatonin Concentration and Sleep Quality Are Associated With Clinical Features of Polycystic Ovary Syndrome

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A743-A743
Author(s):  
Adam T Evans ◽  
Heidi Vanden Brink ◽  
Jessica S Lim ◽  
Brittany Y Jarrett ◽  
Marla Elaine Lujan ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Polycystic Ovary ◽  
Reproductive Hormones ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Ovary Syndrome ◽  
Diagnostic Features ◽  
Wrist Actigraphy

Abstract Introduction: Women with polycystic ovary syndrome (PCOS) have an increased incidence of sleep disturbances compared to healthy women. Circulating melatonin (MEL) is elevated in women with PCOS, thought to reflect an increased daytime and blunted peak in overnight MEL, consistent with an altered circadian rhythm. Whether circadian disruptions coincide with sleep disturbances in women with PCOS or their symptom severity is unclear. Objective: To determine whether altered MEL production coincides with reduced sleep quality in women with PCOS and to examine whether there is a relationship between MEL production, sleep disturbances and the diagnostic features of PCOS. Methods: Women with PCOS (n=22) and controls (n=12) were recruited prospectively. PCOS was defined based on the 2018 International Guideline. Controls exhibited no more than 1 diagnostic feature of PCOS. Women underwent a reproductive history, clinical exam, and transvaginal ultrasound. Fasting blood samples were obtained to measure reproductive hormones. Urine samples were collected in the evening and upon awakening on 1-2 days and assayed for urinary 6-sulfatoxymelatonin as a proxy for daytime and overnight MEL production, respectively. The night:day (N:D) MEL ratio was determined to assess the rhythm of MEL production. Sleep quality and duration were assessed using the Pittsburgh Sleep Quality Index (PSQI) and via overnight wrist actigraphy. Differences between measures of urinary MEL and sleep quality were analyzed using two tailed t-tests. Associations between diagnostic features of PCOS and sleep-related measures were computed using Pearson partial correlations after adjusting for BMI. Results: No differences were detected in overnight MEL, daytime MEL, or the N:D ratio in women with PCOS versus controls. PCOS group experienced reduced weekend sleep efficiency vs. controls (81.18% vs. 87.76% p&lt;0.05), albeit no differences were detected in PSQI scores, sleep duration or total sleep efficiency determined via wrist actigraphy between groups. Longer menstrual cycle length correlated with poor sleep quality as defined by PSQI (rho=0.3662, p&lt;0.05) and FNPO was positively associated with overnight MEL (rho=0.3586, p&lt;0.05). Conclusions: Day and night MEL production and sleep quality did not differ between women with PCOS and controls despite weekend sleep efficiency being reduced in women with PCOS. Diagnostic features of PCOS were associated with MEL production and sleep disturbances suggesting that women with a more severe clinical presentation of PCOS may be more likely to experience altered MEL production or sleep disturbances. Further studies with a larger sample size are needed to understand the link between degree of symptomology in PCOS, MEL production, and sleep disturbances.

scholarly journals 0819 Objective Sleep Efficiency is Associated with Longitudinal Risk of High Depressive Symptoms in Pregnant Women

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A312-A312
Author(s):  
S Tsai ◽  
P Lee ◽  
C Gordon ◽  
E Cayanan ◽  
C Lee
Keyword(s):  
Depressive Symptoms ◽  
Sleep Quality ◽  
Pregnant Women ◽  
Quality Index ◽  
Sleep Disturbances ◽  
Pittsburgh Sleep Quality Index ◽  
Depression Scale ◽  
Sleep Efficiency ◽  
Poor Sleep ◽  
Subjective Sleep

Abstract Introduction Sleep disturbances are one of the most frequent complaints identified during routine prenatal care visits. Sleep and mood disturbances are often intertwined, and depression in particular is a leading cause of disability and disease burden worldwide. The purpose of this study was to examine the predictive association of objective actigraphic and subjective sleep disturbances with depressive symptoms in pregnant women. Methods We recruited 204 first-trimester pregnant women from a large university-affiliated hospital. They provided baseline socio-demographic and health information, wore a wrist actigraph for 7 days, and completed the Pittsburgh Sleep Quality Index and Center for Epidemiologic Studies - Depression Scale and repeated this again in the second and third trimesters. Each data collection was scheduled at least 8 weeks apart. Unadjusted and multivariable adjusted odds ratios with 95% confidence intervals were used to evaluate sleep disturbances at 1st trimester and risk of high depressive symptoms at follow-up. Results A total of 121 (59.3%) women had actigraphic sleep efficiency of &lt; 85% and 92 (45.1%) had Pittsburgh Sleep Quality Index global scores &gt; 5 indicative of poor sleep quality. In multivariable adjusted models, 1st trimester objectively measured sleep efficiency &lt; 85% was associated with 2.65-, 3.86-, and 5.27-fold increased odds having risk of high depressive symptoms at 2nd trimester, 3rd trimester, and both 2nd and 3rd trimesters, respectively. No subjective sleep disturbance variables were significantly associated with risk of high depressive symptoms in multivariate adjusted models. Conclusion Objectively assessed poor sleep efficiency in the 1st trimester plays a crucial role in the development of both elevated and persistent high depressive symptoms in pregnancy. Future studies using objective sleep measurements and clinical diagnostic interviews are warranted to examine whether early interventions to improve sleep may help reduce high depressive symptom risk and lower depression rates in women during pregnancy. Support This study was funded by the Ministry of Science and Technology, Taiwan (MOST-101-2314-B-002-049-MY3).

Sleep quality, anxiety and depression in advanced lung cancer: patients and caregivers

2020 ◽  
pp. bmjspcare-2018-001684
Author(s):  
Yuan He ◽  
Li-Yue Sun ◽  
Kun-Wei Peng ◽  
Man-Jun Luo ◽  
Ling Deng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Sleep Latency ◽  
Depression Scale ◽  
Advanced Lung Cancer ◽  
Anxiety And Depression ◽  
Poor Sleep ◽  
First Line ◽  
Self Rating

ObjectiveTo investigate the clinical implications of sleep quality, anxiety and depression in patients with advanced lung cancer (LC) and their family caregivers (FCs).MethodsA total of 98 patients with advanced LC and their FCs (n=98) were recruited from the Oncology Department in Nanfang Hospital. The Pittsburgh Sleep Quality Index (PSQI), consisting of seven components that evaluate subjective sleep quality, sleep latency, duration of sleep, sleep efficiency, sleep disturbances, sleep medication usage and daytime dysfunction, was used to assess sleep quality. Using the tool of Zung Self-rating Anxiety Scale (SAS) and Zung Self-rating Depression Scale (SDS), we tested the patients’ status of anxiety and depression, respectively.ResultsThe prevalences of poor sleep quality, anxiety and depression in patients were 56.1%, 48.9% and 56.1%, respectively, while those in FCs were 16.3%, 32.6% and 25.5%, respectively. Patients had higher PSQI, SAS and SDS scores than did FCs (p<0.05). Significant correlations were found between the patients’ and FCs’ scores of PSQI/SAS/SDS (p<0.05). Multivariate Cox regression analyses indicated that sleep disturbances in patients (HR 0.413, 95% CI 0.21 to 0.80, p=0.01) and the global PSQI score of FCs (HR 0.31, 95% CI 0.14 to 0.71, p=0.00) were independent risk factors for patients’ first-line progression-free survival (PFS). Moreover, patients’ sleep latency (HR 2.329, 95% CI 1.36 to 3.96, p=0.00) and epidermal growth factor receptor mutations (HR 1.953, 95% CI 1.12 to 3.38, p=0.01) were significant prognostic factors for their overall survival (OS).ConclusionsWe demonstrated that presence of sleep disturbances in patients with advanced LC and the global PSQI Score of their FCs may be risk predictors for patients’ poor first-line PFS. Patients’ sleep latency was a potential risk factor for their OS.

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.

THE RELATIONSHIP BETWEEN SMART PHONE USAGE AND SLEEP DISTURBANCES AND PSYCHOLOGICAL DISSTRESS AMONG STUDENTS

2017 ◽  
pp. 125-130
Author(s):  
Minh Tam Nguyen ◽  
Phuc Thanh Nhan Nguyen ◽  
Thi Thuy Hang Nguyen
Keyword(s):  
High School ◽  
High School Students ◽  
University Students ◽  
Sleep Quality ◽  
Sleep Disturbances ◽  
Public Health Problem ◽  
Smartphone Addiction ◽  
Poor Sleep ◽  
School Students ◽  
The Relationship

The increasing use of smartphone among young people is creating negative effects and is an important public health problem in many countries. Smartphone abuse and addiction may cause physical and psychological disorders among users. However, the awarenes on this issue has been inadequate due to lacking of evidence. Objectives: To describe the current situation of smartphone using among students at highschools and universities in Hue city and to examine the relationship between smartphone using and sleep disturbances and psychological disstress among participants. Methods: A cross-sectional study with a randomly selected sample of 1,150 students at highschools and universities in Hue city. SAS-SV scale was used to evaluate phone addiction status, K10 scale was used for psychological distress assessment and PSQI scale was used to examine the sleep quality. Results: The proportion of students at highschools and universities having smartphones was 78.0%. The rate of smartphone addiction among high school students was 49.1% and that among university students was 43.7%. There was 57.3% of high school students had poor sleep quality, and that of university students was 51.6%. There was a statistically significant association between smartphone addiction and sleep disturbances and psychological disstress among participants (p <0.05). Conclusion: The prevalence of smartphone addiction among students at highschools and universities is alarming and is related to sleep disturbances and psychological disstress among participants. There is a strong call to develop intervention to help students to aware and manage the use of smartphone effectively.

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.

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