Predictors Of Poor Sleep Quality Research Articles

Insight into sleep quality and its relationship with emotional intelligence: results of a cross-sectional study among Italian university students

BackgroundThis study aimed to investigate sleep habits and examine the relationship between sleep quality and its potential predictors, namely Emotional Intelligence (EI) and perceived health status.MethodsThe present cross-sectional study was conducted between February 13 and February 28, 2023, at the “Magna Græcia” University of Catanzaro, in the Southern part of Italy. The study involved undergraduate students who were 18 years or older, proficient in the Italian language, and with no restrictions on the major attended. They completed a self-administered survey on socio-demographic information, health status, sleep quality (Pittsburgh Sleep Quality Index-PSQI), EI, and perceived health status.ResultsThe majority of the sample (59.6%) was enrolled in medical or life science majors. The results showed a high prevalence of poor sleep quality and sleep latency was identified as the most affected aspect of it. The female gender and the self-perceived health status were the strongest predictors of poor sleep quality. Poor sleepers showed lower emotional clarity, emotional repair, and total EI scores. Moreover, as age increased, the odds of being classified as a poor sleeper increased by 7%.ConclusionThe survey highlights that poor sleep health is still a significant issue and empowering individuals to make proactive decisions to adopt healthy lifestyles in the early phase of life is of paramount importance. The study exhibited the interesting role of EI in influencing sleep quality, highlighting that when emotional events are insufficiently regulated, it may result in sleep disturbances. Therefore, the promotion of sleep quality requires an integrated yet innovative approach including emotion regulation.

Addressing Environmental Factors for SDG 3-Health and Wellbeing: Perceived Stress, Sleep Quality, and Coping among Medical Students in Pakistan

The objective of this study was to investigate the interplay between perceived stress, sleep quality, and coping mechanisms among medical students, with a view to understand their implications for Sustainable Development Goal 3 (SDG 3) - "Good Health and Well-being," and considering environmental factors. Conducted as a cross-sectional study and 300 medical university students (152 men, 148 women), aged 18 to 25 years (mean age = 22.73, SD = 1.78), were selected using stratified random sampling based on their academic year. The study employed the Perceived Stress Scale, General Sleep Scale, and Brief COPE to assess the study variables. The results revealed gender differences in coping strategies, with female students exhibiting higher scores in avoidant and emotion-focused coping, while male students leaned towards problem-focused coping. Notably, perceived stress and avoidant coping emerged as significant predictors of poor sleep quality (p<.05) among the participants. This study found significant relationship among use of green spaces, stress, sleep quality, and coping strategies among medical students, aligning with SDG 3's objective of ensuring healthy lives and promoting well-being for all. Furthermore, while the study did not directly address environmental factors, it indirectly emphasizes the importance of creating conducive environments for health and well-being. Environmental considerations such as access to green spaces and a healthy physical environment can influence individuals' stress levels and sleep quality, contributing to holistic health outcomes. Given these findings, the study recommends that counseling centers in universities develop strategies for managing students' stress and sleep quality, while promoting healthy coping skills. By addressing these factors comprehensively, universities can contribute to enhancing students' psychological well-being and advancing progress towards SDG 3 and create sustainable and healthy environments, as outlined in SDG 13 (Climate Action), to complement initiatives focused on fostering sustainable environments conducive to health and well-being.

Sleep quality and screen time among university professors: impact of emergency remote teaching amidst COVID-19 crisis.

Sleep plays a crucial role in maintaining physical and mental health. The COVID-19 pandemic has brought about unprecedented global changes, and disruptions in sleep quality have emerged as a challenge. The pandemic prompted a dramatic shift in the working landscape for university professors, necessitating emergency remote teaching (ERT). This transition substantially increased professors' screen time for academic and research endeavors. This study explores the relationship between screen time and sleep quality among university professors during the pandemic and examines associated factors, including psychological well-being. An electronic survey, covering demographics, education, screen time, sleep quality, and mental health, was administered to professors who worked during the spring semester of 2020. Standardized measures were used to assess sleep quality and mental health. Correlations, Mann-Whitney tests, and multivariate regression explored associations between screen time, sleep quality, and other variables. One hundred sixty participants exhibited poor sleep quality, subthreshold insomnia, and mild depression. Increased screen time correlated with poorer sleep quality, elevated stress levels, and heightened depression severity. Evening screen users reported more insomnia than daytime users. Depression emerged as a significant predictor of poor sleep quality and insomnia, along with evening screen use. This study among university professors underscores the impact of screen time on sleep quality during the COVID-19 pandemic. Participants faced poor sleep, largely influenced by heightened screen time due to ERT. Considering these findings, this study emphasizes the importance of curbing daytime screen exposure and abstaining from screens in the evening, especially for university professors reliant on technology for their professional responsibilities.

Photophobia is associated with lower sleep quality in individuals with migraine: results from the American Registry for Migraine Research (ARMR)

BackgroundPatients with migraine often have poor sleep quality between and during migraine attacks. Furthermore, extensive research has identified photophobia as the most common and most bothersome symptom in individuals with migraine, second only to headache. Seeking the comfort of darkness is a common strategy for managing pain during an attack and preventing its recurrence between episodes. Given the well-established effects of daily light exposure on circadian activity rhythms and sleep quality, this study aimed to investigate the relationship between photophobia symptoms and sleep quality in a cohort of patients with migraine.MethodsA cross-sectional observational study was conducted using existing data extracted from the American Registry for Migraine Research (ARMR). Participants with a migraine diagnosis who had completed the baseline questionnaires (Photosensitivity Assessment Questionnaire (PAQ), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-2 (PHQ-2)), and selected questions of the ARMR Sleep questionnaire were included. Models were created to describe the relationship of photophobia and photophilia with various sleep facets, including sleep quality (SQ), sleep disturbance (SDis), sleep onset latency (SOL), sleep-related impairments (SRI), and insomnia. Each model was controlled for age, sex, headache frequency, anxiety, and depression.ResultsA total of 852 patients meeting the inclusion criteria were included in the analysis (mean age (SD) = 49.8 (13.9), 86.6% (n = 738) female). Those with photophobia exhibited significantly poorer sleep quality compared to patients without photophobia (p < 0.001). Photophobia scores were associated with SQ (p < 0.001), SDis (p < 0.001), SOL (p = 0.011), SRI (p = 0.020), and insomnia (p = 0.005) after controlling for age, sex, headache frequency, depression, and anxiety, signifying that higher levels of photophobia were associated with worse sleep-related outcomes. Conversely, photophilia scores were associated with better sleep-related outcomes for SQ (p < 0.007), SOL (p = 0.010), and insomnia (p = 0.014).ConclusionResults suggest that photophobia is a significant predictor of poor sleep quality and sleep disturbances in migraine. These results underscore the necessity for comprehensive and systematic investigations into the intricate interplay between photophobia and sleep to enhance our understanding and develop tailored solutions for individuals with migraine.

Effects of diabetes mellitus complications on sleep quality among Saudi Arabian patients-A national study

ABSTRACT Introduction: In diabetes mellitus (DM) patients, obtaining a good night’s sleep is crucial for maintaining body caloric intake, controlling insulin levels, and reducing the likelihood of engaging in unhealthy behavior. Patients with poor sleep quality may experience impaired glycemia, playing a significant role in the development of chronic complications. This study aims to explore the effects of DM complications on sleep quality among Saudi Arabian patients. Patient and Methods: This is a cross-sectional study conducted among patients with diabetes. A self-administered, validated questionnaire translated into Arabic was distributed among diabetic patients using an online survey. The questionnaire includes sociodemographic characteristics (i.e. age, gender, marital status, etc.), the medical history of the patients, and a questionnaire about sleep quality. Results: Out of 4171 patients involved, 52.7% were females and 27.7% were aged between 40 and 60 years old. The prevalence of patients with perceived poor sleep quality was 24.1%. Significant predictors of poor sleep quality were the gender female, having social stressors, comorbid sleep disorders, associated comorbidities, increasing HbA1c levels, being overweight/obese, and diabetes complications. Furthermore, sleep disturbance, taking sleep medications, daytime sleepiness, and having bad dreams during sleep were also identified as prognostic factors for poor sleep quality. Conclusion: The subjective poor sleep quality of patients with diabetes was 24.1%. Poor sleep quality was significantly demonstrated by females who were having social stressors, comorbid sleep disorders, comorbidities, uncontrolled HbA1c levels, elevated BMI levels, and complications of diabetes. However, regular physical activity and adequate sleep were estimated to be the protective factors against poor sleep quality. Further research is needed to establish the effect of sleep quality among patients with DM.

Poor Sleep Quality in Jamaican Adults With Sickle Cell Disease: Prevalence, Risk Factors, and Association With Quality of Life

Poor sleep and chronic illnesses have a bidirectional relationship where presence of one can worsen the other. Sickle cell disease (SCD) is associated with significant morbidity and early mortality. In this study, we examine sleep quality, its predictors, and its association with quality of life in Jamaican adults with SCD. This cross-sectional study evaluated 177 well adult SCD patients for sleep quality using The Pittsburgh Sleep Quality Index (PSQI) and quality of life using the Adult Sickle Cell Quality of Life Measurement Information System (ASCQ-Me). Multiple linear regression models examined the predictors of poor sleep quality. The mean global PSQI score was 6.9 (SD 4.2) with 56.5% having poor sleep quality. Women had significantly worse scores for sleep efficiency (p 0.005), sleep latency (p 0.03) and higher use of sleeping medications (p 0.02). Those overweight/obese had significantly worse subjective sleep quality (p 0.001) and sleep efficiency (p 0.05). In multivariate regression analysis, overweight individuals had poorer sleep quality (OR: 2.9; 95% C.I.: 1.07, 7.88) than those with normal weight whereas those unemployed and looking for a job had lower prevalence of poor sleep quality (OR 0.2; 95% C.I.: 0.05, 0.77) compared to employed individuals. Participants with good sleep quality had significantly better functioning in all 5 domains of the ASCQ-Me. In conclusion, persons with SCD who are overweight or obese are at increased risk of poor sleep which can negatively affect quality of life. Patient populations and healthcare providers will need to manage the emerging burden of overweight/obesity.

Sleep quality and its association with anxiety, stress, sleep-related beliefs and attitudes and postural control in young adults: a cross-sectional study.

Adequate sleep is essential for young adults, as this age group primarily consists of students, job seekers, and working people constantly managing a hectic lifestyle. Poor quality of sleep, which is essential for physical and mental well-being in the short and long term, can result in impaired overall health. However, there exists a gap in the literature regarding the factors affecting sleep among young adults. Hence, the objective of this study was to find the prevalence of sleep-related parameters (sleep health, hygiene, and sleep-related beliefs and attitudes) and potential risk factors for sleep quality and to investigate the association between sleep and postural control in young adults. This prospective, cross-sectional, analytical study included 181 young adults, 113 (62.43 %) females, and 68 (37.57 %) males, with a mean age of 23.82±2.88 years. Sleep quality, health, beliefs, hygiene, stress, anxiety, and depression were assessed using questionnaires. Postural control was assessed using center of pressure (COP) indices. The overall prevalence of poor sleep quality was 79.01 % among young adults. Multiple linear regression showed that predictors explained 44 % of sleep quality variance (adjusted R square=0.44, f (12,168) = 20.91, p<0.05). Poor sleep-related beliefs and attitudes (95 % CI [0.037, 0.679], p=0.029), higher perceived stress (95 % CI [0.005, 0.219], p=0.039), higher anxiety severity (95 % CI [0.108, 0.526], p=0.003), and poor COP stability index A/P (95 % CI[4.986, 11.248], p=0.00) were found to be significant predictors of poor sleep quality. High anxiety and stress, and poor dysfunctional beliefs and attitudes about sleep are predictors of poor sleep quality in young adults. These factors may significantly affect sleep quality and the experience of restful sleep among young adults. Also, poor sleep quality is associated with reduced postural control (decreased stability in the A/P direction). These findings are crucial for improving young adults' overall health and well-being, as poor sleep is highly prevalent among this age group.

Impact of COVID-19 pandemic on sleep parameters and characteristics in individuals living with overweight and obesity.

Coronavirus disease 2019 (COVID-19) has been very challenging for those living with overweight and obesity. The magnitude of this impact on sleep requires further attention to optimise patient care and outcomes. This study assessed the impact of the COVID-19 lockdown on sleep duration and quality as well as identify predictors of poor sleep quality in individuals with reported diagnoses of obstructive sleep apnoea and those without sleep apnoea. An online survey (June-October 2020) was conducted with two samples; one representative of Canadians living with overweight and obesity (n = 1089) and a second of individuals recruited through obesity clinical services or patient organisations (n = 980). While overall sleep duration did not decline much, there were identifiable groups with reduced or increased sleep. Those with changed sleep habits, especially reduced sleep, had much poorer sleep quality, were younger, gained more weight and were more likely to be female. Poor sleep quality was associated with medical, social and eating concerns as well as mood disturbance. Those with sleep apnoea had poorer quality sleep although this was offset to some degree by use of CPAP. Sleep quality and quantity has been significantly impacted during the early part of the COVID-19 pandemic in those living with overweight and obesity. Predictors of poor sleep and the impact of sleep apnoea with and without CPAP therapy on sleep parameters has been evaluated. Identifying those at increased risk of sleep alterations and its impact requires further clinical consideration.

Sleep quality and mental health differences following Syria-Turkey earthquakes: A cross-sectional study.

This study explores the lasting mental health impact of the Syria-Turkey earthquakes in 2023 on a population affected by conflict and trauma. It analyzes pre- and post-event mental health and sleep quality differences, identifying predictors of outcomes. Studying the 2023 Syria-Turkey earthquakes' enduring mental health impact on conflict-affected individuals, this research informs better support and interventions for disaster survivors. This longitudinal, cross-sectional study examined the enduring mental health impact of the Syria-Turkey earthquakes. The present study involved N = 1,413 Syrian survivors, aged 18 years or older, who actively participated by contributing both pre- and post-earthquake data. A meticulously designed digital questionnaire with established metrics assessed sleep disturbances, depressive symptoms, and anxiety levels. Stratification variables (age, gender, education, marital status) were used for subgroup analysis. Arabic versions of PHQ-9, PSQI, and GAD-2 proved reliable for measuring depression, sleep quality, and anxiety. The majority of participants were female (73.6%) with tertiary education (83.3%). Post-earthquake, a higher percentage reported poor sleep quality (67.7% vs. 59.7%, p < .001) and increased prevalence of MDE (66.1% vs. 56%, p < .001). GAD did not differ significantly. Post-earthquake, women had a higher likelihood of poor sleep quality (OR: 1.58, 95% CI [1.19, 2.10], p < .001) and MDE (OR: 1.55, 95% CI [1.18 to 2.04], p = .003). Predictors varied before and after earthquakes; age and education were significant predictors of poor sleep quality, MDE, and GAD. This study reveals higher rates of poor sleep quality and major depressive episodes among earthquake-affected individuals, especially women. Age, education, and gender contribute to these outcomes. Targeted interventions and comprehensive mental health support are crucial for post-earthquake recovery.

Depression, Sleep Health & Sociodemographic Correlates in a Nationwide Survey: Implications for Depression Treatment During the COVID-19.

The COVID-19 pandemic has had a profound impact on mental health worldwide, with depression and sleep problems among the most common issues experienced by many individuals. Depression can lead to sleep problems, which can increase the risk of developing depressive symptoms. However, it is unclear which United States (US) sub-population was most affected by depression and sleep problems during the pandemic. We conducted a secondary analysis using self-reported data from the 2021 National Health Interview Survey (NHIS), focusing on adults aged 18 years and above (n=29,763). We utilized self-reported responses to questions about prescription medication and frequency of depressive feelings to determine participants' depression status. Appropriate weights were applied to account for the sampling design of the surveys. Our analysis involved descriptive statistics and chi-squared tests to compare sociodemographic, clinical, behavioral, and sleep-related characteristics between US adults with and without depression. Additionally, logistic regression was used to examine the associations between sleep duration, sleep quality and depression. The overall prevalence of depression in our sample was 44.4%. It were higher in certain demographic groups, including younger adults (18-39 years, 47.7%), non-Hispanic whites (47.9%), females (50.1%), those at the lower income bracket (52.2%), those with no college or degree (48.7%) uninsured individuals (45.2%), and those reporting poor general health (71.9%). Individuals with depression had a 12% increased odds of experiencing short sleep (aOR: 1.12, 95% CI:1.04-1.20, p<0.001), 34% increased odds of experiencing long sleep (aOR: 1.34, 95% CI: 1.20-1.50, p < 0.001) and more than 2.5 fold increased odds of reporting poor sleep quality (aOR:2.57, 95% CI: 2.40-2.78; p<0.0001). In the multivariate analysis, all variables (sex, race/ethnicity, education, health insurance coverage, marital status, general health status and use of sleep medications, smoking and alcohol use status) were significantly predictors of poor sleep quality, with the exceptions of age and family income. The findings emphasize the need to address sleep health in treating depression, especially during times of public health crises.

Poor sleep quality and its associated factors among working adults during COVID-19 pandemic in Malaysia.

In Malaysia, a nationwide movement control order (MCO), implemented to curb the COVID-19 spread, impacted on the lives of the working population which could impair sleep quality. This study aims to find the sleep quality status and its association with the socioeconomic, employment and lifestyle factors of working adults during the MCO period. A cross-sectional study was conducted among 500 eligible working adults. Data were collected using a structured questionnaire consisting of the Pittsburg Sleep Quality Index. The proportion of poor sleep quality is found to be 59.4%. Analysis shows that the use of electronic devices before sleep (OR=2.33, 95% CI=1.02-5.35, p-value=0.046), increased amount of workload (OR=0.45, p-value=0.005), decreased in amount of workload (OR=0.48, p-value=0.003) and distracted while working (OR=0.57, p-value=0.014) are the factors significantly associated with and are predictors of poor sleep quality. During crisis, there is a need for public health interventions for the working population to adopt a healthy lifestyle. Employers are recommended to support employees' well-being and to provide a healthy workplace during challenging times. Policy recommendations are also made to implement flexible working arrangements, workload management, workplace mental health support and legal protections on reasonable working hours, rest breaks and time off during crises.

Sleep quality in individuals with post-COVID-19 condition: Relation with emotional, cognitive and functional variables

The study aimed to assess sleep quality in PCC patients and its predictors by analysing its relationship with emotional, cognitive and functional variables, as well as possible differences based on COVID-19 severity. We included 368 individuals with PCC and 123 healthy controls (HCs) from the NAUTILUS Project (NCT05307549 and NCT05307575). We assessed sleep quality (Pittsburgh Sleep Quality Index, PSQI), anxiety (Generalized Anxiety Disorder, GAD-7), depression (Patient Health Questionnaire, PHQ-9), global cognition (Montreal Cognitive Assessment, MoCA), everyday memory failures (Memory Failures of Everyday Questionnaire, MFE-30), fatigue (Chadler Fatigue Questionnaire, CFQ), quality of life (European Quality of Life-5 Dimensions, EQ-5D), and physical activity levels (International Physical Activity Questionnaire, IPAQ). 203 were nonhospitalized, 83 were hospitalized and 82 were admitted to the intensive care unit (ICU). We found statistically significant differences in the PSQI total score between the PCC and HC groups (p < 0.0001), but there were no differences among the PCC groups. In the multiple linear regressions, the PHQ-9 score was a predictor of poor sleep quality for mild PCC patients (p = 0.003); GAD-7 (p = 0.032) and EQ-5D (p = 0.011) scores were predictors of poor sleep quality in the hospitalized PCC group; and GAD-7 (p = 0.045) and IPAQ (p = 0.005) scores were predictors of poor sleep quality in the group of ICU-PCC. These results indicate that worse sleep quality is related to higher levels of depression and anxiety, worse quality of life and less physical activity. Therapeutic strategies should focus on these factors to have a positive impact on the quality of sleep.

The prevalence and predictors of poor sleep quality and excessive daytime sleepiness in epilepsy: A single tertiary centre experience in Malaysia

Background and objectivePeople with epilepsy frequently encounter sleep disruptions that can stem from a variety of complex factors. Epilepsy-related sleep disturbance can lead to reduced quality of life and excessive daytime hypersomnolence. Identification of sleep disturbances may help in the overall management of epilepsy patients. This study was conducted to determine the prevalence and predictors of poor sleep quality and daytime sleepiness in epilepsy. MethodsA cross-sectional study on 284 epilepsy patients was performed in a local tertiary centre. The demographic and clinical epilepsy data were collected. The Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale (ESS) questionnaires were utilised to determine the quality of life and daytime hypersomnolence of epilepsy patients, respectively. ResultsPoor sleep quality was reported in 78 (27.5%) patients while daytime hypersomnolence was present in 17 (6%) patients. The predictors of poor sleep quality include structural causes (OR = 2.749; 95% CI: 1.436, 5.264, p = 0.002), generalised seizures (OR = 1.959, 95% CI: 1.04, 3.689, p = 0.037), and antiseizure medications such as Carbamazepine (OR = 2.34; 95% CI: 1.095, 5.001, p = 0.028) and Topiramate (OR 2.487; 95% CI: 1.028, 6.014, p = 0.043). Females are 3.797 times more likely score higher in ESS assessment (OR 3.797; 95% CI: 1.064, 13.555 p = 0.04). DiscussionSleep disturbances frequently coexist with epilepsy. Patients should be actively evaluated using the PSQI and ESS questionnaires. It is imperative to identify the key factors that lead to reduced sleep quality and heightened daytime sleepiness in patients with epilepsy, as this is essential to properly manage their condition.

Depression as a predictor of sleep quality in health workers who faced the COVID-19 pandemic in Mexico

Introduction: There is a relationship between depression and sleep quality; however, the impact of the COVID-19 pandemic on this association is unknown, especially for those health workers who faced the pandemic. Therefore, we aimed to identify the association between depression and sleep quality in health workers who faced the COVID-19 pandemic. Methods: A survey was performed on 150 health workers with at least 2 years of working tenure in a public maternal perinatal hospital in Mexico, between September and December 2021. Sociodemographic data, levels of sleep quality, depression, anxiety, and gastrointestinal function were obtained through a self-administered questionnaire. Cardiovascular risk was obtained according to age, lifestyle habits, blood pressure, anthropometry, body composition and biochemical measurements. Results: Those with depression were 10.3 times more likely to have poor sleep quality compared to those without depression, adjusted for gastrointestinal function (95% CI 2.92 – 36.54, p&lt;0.001). Those with depression were 7.23 times more likely to have poor sleep quality compared to those without depression, adjusted for gastrointestinal function, anxiety, and cardiovascular risk (95% CI 1.85-28.14, p&lt;0.001). Conclusion: Health workers’ depression should be considered a predictor of poor sleep quality, especially in those who faced the COVID-19 pandemic.

Sleep Quality Among People with Type 2 Diabetes Mellitus During COVID-19 Pandemic: Evidence from Qatar's National Diabetes Center.

Sleep disturbance is suspected to increase during the COVID-19 pandemic, and people with type 2 DM are known to have a higher risk of sleep disturbance. We aimed to determine the prevalence and determinants of sleep disturbance through Pittsburgh Sleep Quality Index (PSQI) during the COVID-19 pandemic. We randomly selected two hundred eighty-eight people with T2DM from the outpatient clinics of the National Diabetes Centre in Qatar. We used Chi-square, Mann-Whitney, Spearman, and Point Biserial correlation tests to examine the association between sleep quality and the independent variables. Finally, we conducted multiple logistics regression to identify the predictors of poor sleep quality and set the alpha level at 0.05. In our sample, the mean age (±SD) was 51.4 (± 9.5) years, and 64.3% of the study participants were males. The median (IQR) duration of diabetes was 10 (11) years. Additionally, 6.3% of the participants were on insulin. The median HbA1c was 7.6% (2.4). Three in ten patients reported poor sleep quality (PSQI>5); (n=103; 35.8%). Poor sleep quality was statistically associated with young age, previous history of sleep disturbance, prior diagnosis of sleep disorders, high depression score, and high perceived stress score. After adjusting for confounders, only high depressive symptoms score and previous history of sleep disorder were significant predictors of poor sleep quality (p < 0.001), with adjusted odd ratios of (aOR = 1.421; 95% CI: 1.242-1.625) and (aOR = 3.208; 95% CI: 1.574-6.537), respectively. The prevalence of poor sleep quality among people with T2DM during the COVID-19 pandemic is high. Physicians must screen for depression, stress, and previous history of sleep disorder to tackle poor sleep among T2DM.

Ofis Çalışanlarında Kas İskelet Sistemi Rahatsızlıklarının Uyku Kalitesi ile İlişkisi

Abstract&#x0D; Objective: The aim of the study was to evaluate the musculoskeletal pain frequency and relationships of musculoskeletal pains with the sleep quality among office workers. &#x0D; Materials and Methods: This cross-sectional study included 186 office workers evaluated in April-August 2022. The data were obtained through the personal information form, the Extended-Nordic Musculoskeletal Questionnaire, and the Pittsburgh Sleep Quality Index. &#x0D; Results: It was found that 83.3% of office workers had musculoskeletal pain and 74.7% had poor sleep quality. Knee pain (p=0.016; OR=3.670; 95% CI = 1.280-10.342) and lower back pain (p=0.003; OR=4.380; 95% CI= 1.680-11.517) were significant predictors of poor sleep quality. There was a moderate positive correlation between the number of body areas where the pain was reported and the PSQI score (r: 0.367, p

The role of symptoms severity, heart rate, and central sensitization for predicting sleep quality in patients with fibromyalgia.

Clinical predictors of sleep quality in patients with fibromyalgia syndrome (FMS) are still unknown. By identifying these factors, we could raise new mechanistic hypotheses and guide management approaches. We aimed to describe the sleep quality of FMS patients and to explore the clinical and quantitative sensory testing (QST) predictors of poor sleep quality and its subcomponents. This study is a cross-sectional analysis of an ongoing clinical trial. We performed linear regression models between sleep quality (Pittsburgh Sleep Quality Index [PSQI]) and demographic, clinical, and QST variables, controlling for age and gender. Predictors for the total PSQI score and its seven subcomponents were found using a sequential modeling approach. We included 65 patients. The PSQI score was 12.78 ± 4.39, with 95.39% classified as poor sleepers. Sleep disturbance, use of sleep medications, and subjective sleep quality were the worst subdomains. We found poor PSQI scores were highly associated with symptom severity (FIQR score and PROMIS fatigue), pain severity, and higher depression levels, explaining up to 31% of the variance. Fatigue and depression scores also predicted the subjective sleep quality and daytime dysfunction subcomponents. Heart rate changes (surrogate of physical conditioning) predicted the sleep disturbance subcomponent. QST variables were not associated with sleep quality or its subcomponents. Symptom severity, fatigue, pain, and depression (but no central sensitization) are the main predictors of poor sleep quality. Heart rate changes independently predicted the sleep disturbance subdomain (the most affected one in our sample), suggesting an essential role of physical conditioning in modulating sleep quality in FMS patients. This underscores the need for multidimensional treatments targeting depression and physical activity to improve the sleep quality of FMS patients.

0534 How objective sleep quality with Odds Ratio Product differs by diagnosis of COMISA, OSA, and insomnia

Abstract Introduction Recent research has highlighted differences in sleep quality for comorbid insomnia and obstructive sleep apnea (COMISA). We investigated how COMISA affects objective sleep quality measured with odds ratio product (ORP) compared to individuals without insomnia or moderate to severe OSA. Methods 410 participants (age 46.4±12.3; 174 females) recorded their sleep with in-home PSG using the Cerebra Sleep System and completed questionnaires. Sleep quality was measured using ORP derived from micro-analyzing frontal EEG channels. On the questionnaires, participants reported whether they experienced insomnia symptoms at least three times a week. Participants were classified as having no diagnosis if their RDI on the home PSG was &amp;lt; 15 and no insomnia symptoms. They were classified as insomnia only if they reported at least one insomnia symptom with an RDI &amp;lt; 15. They were classified as OSA only if they had an RDI ≥15 and reported no insomnia symptoms. Finally, they were classified as COMISA if they had an RDI ≥15 and reported at least one insomnia symptom. All analyses controlled for age and were corrected for multiple comparisons. Results 113(27.6%) patients were classified as having no diagnosis, 109(26.6%) as insomnia only, 83(20.2%) as OSA only, and 105(25.6%) as COMISA. There was a significant effect of diagnosis on ORPNREM (F3,405= 6.042, p&amp;lt;.001) and ORPTRT (F3,405= 3.799, p= 0.010). Participants with no diagnosis had lower ORPNREM than patients with OSA only (p= 0.039) and patients with COMISA (p&amp;lt;.001) and had lower ORPTRT than COMISA (p= 0.009). OSA severity based on the AHI was the only significant predictor of ORPNREM (p &amp;lt;.001, β= 0.321). Both AHI (p &amp;lt;.001, β=0.176) and number of insomnia symptoms (p=0.002, β=0.141) were significant predictors of ORPTRT. Conclusion Participants with no diagnosis had the lowest ORP indicative of better sleep quality than participants with evidence of sleep disorders. Having COMISA may have greater impacts on sleep quality than insomnia symptoms alone. OSA severity was the only predictor of poor sleep quality when looking at ORPNREM. Yet both OSA severity and insomnia symptoms were associated with higher ORPTRT indicating that individuals with COMISA may show alterations of sleep quality in different states throughout the night. Support (if any)

The impact of perceived social support on sleep quality in a sample of patients undergoing hemodialysis in Somalia.

The main objective of the present study is to examine the relationship between perceived social support and the quality of sleep and to determine the predictors of sleep quality in a sample of patients undergoing hemodialysis (HD) in Somalia. A sample of 200 patients with end-stage renal disease (ESRD) who were undergoing hemodialysis treatment approximately two to three times a week were included. All participants were administered a sociodemographic data form, the Multidimensional Scale of Perceived Social Support (MSPSS), the Insomnia Severity Index (ISI), and the Pittsburgh Sleep Quality Index (PSQI). Patients undergoing HD for less than 3 months prior to the study date were excluded. Of the patients undergoing hemodialysis, 200 patients aged between 18 and 68 years (mean = 52.29; SD = 14.13) gave consent and participated in the study. Sixty-three subjects (31.5%) reported poor sleep quality, defined as having a total PSQI score > 5. Forty-one subjects (20.5%) reported clinically significant (moderate-to-severe) insomnia. The majority of our patients undergoing HD reported remarkably high family support, but low friends and significant other support. Poor sleep quality significantly correlated with perceived friends' support and perceived total social support. While perceived family support significantly correlated with both family income and the duration of chronic kidney disease (CKD), perceived friends' support significantly correlated with age and family income. Hierarchical regression analyses showed that perceived family support and friends' support were significant predictors of poor sleep quality. Perceived friends' support was a significant predictor of insomnia severity. Perceived family support was a significant predictor of subjective sleep quality and sleep duration. Perceived friends' support was a significant predictor of subjective sleep quality, sleep duration, sleep latency, sleep disturbance, and daytime dysfunction. Family income was a significant predictor of sleep duration. Age and gender were significant predictors of sleep efficiency. The duration of CKD and duration of HD were significant predictors of sleep disturbance. This present study has highlighted the value of family as a principal support system in Somalian culture. Understanding the impact of perceived social support on the quality of sleep in patients undergoing HD will help healthcare providers and social services to focus on and improve the social support systems of the patients as an integral part of their treatment.

Sleep quality and associated factors among adult people living with HIV on follow-up at Dessie Town Governmental Health Facilities Antiretroviral Therapy Clinics, Northeast, Ethiopia, 2020, a multicenter cross-sectional study

BackgroundPoor sleep quality is an important health problem in people living with HIV. The exact cause of sleep disturbance is not well known, but it may relate to HIV itself, antiretroviral drug side effects, and other HIV-related disorders. As a result, the purpose of this study was to assess sleep quality and associated factors among adult HIV patients on follow-up at Dessie Town governmental health facilities’ antiretroviral therapy clinics in Northeast Ethiopia in 2020.MethodsA multi-center cross-sectional study was conducted among 419 adult people living with HIV/AIDS from February 1/2020 to April 22/2020 in Dessie Town governmental antiretroviral therapy clinics. A systematic random sampling method was used to select the study participants. An interviewer-administered method of data collection with a chart review was used. The Pittsburgh Sleep Quality Index was used to evaluate sleep disruption. A binary logistic regression was conducted to see the relationship between a dependent variable and independent variables. Variables with a p-value of < 0.05 and a 95% confidence interval were used to declare an association between factors and a dependent variable.ResultsA total of 419 study participants were enrolled in this study, with a response rate of 100%. The mean age of the study participants was 36 ± 6.5 SD years and 63.7% of the participants were female. The prevalence of poor sleep quality was found to be 36% (95% CI, 31–41%). Being female (AOR = 3.45, 95% CI: 1.52–7.79), viral loads 1000 copies/ml (AOR = 6.88, 95% CI: 2.79–16.9), CD4 cell count 200 cells/mm3 (AOR = 6.85, 95% CI: 2.42–19.39), WHO stage II and III (AOR = 4.29, 95% CI: 1.05–17.53), having anxiety (AOR = 10, 95% CI: 4.21–23.9.ConclusionThe findings of this study showed that more than one-third of the study participants had poor-quality sleep at the Dessie Town Health Facility ART clinic. Being female, low CD4 cell counts, viral load ≥1000 copies/ml, WHO stage II and III, depression, anxiety, sleeping in a communal bedroom, and living alone were predictors of poor sleep quality.