Sleep Medication Use Research Articles

Mechanisms of sleep disturbances in long-term cancer survivors: a childhood cancer survivor study report.

Sleep problems following childhood cancer treatment may persist into adulthood, exacerbating cancer-related late effects and putting survivors at risk for poor physical and psychosocial functioning. This study examines sleep in long-term survivors and their siblings to identify risk factors and disease correlates. Childhood cancer survivors (≥5 years from diagnosis; n = 12 340; 51.5% female; mean [SD] age = 39.4 [9.6] years) and siblings (n = 2395; 57.1% female; age = 44.6 [10.5] years) participating in the Childhood Cancer Survivor Study completed the Pittsburgh Sleep Quality Index (PSQI). Multivariable Poisson-error generalized estimating equation compared prevalence of binary sleep outcomes between survivors and siblings and evaluated cancer history and chronic health conditions (CHC) for associations with sleep outcomes, adjusting for age (at diagnosis and current), sex, race/ethnicity, and body mass index. Survivors were more likely to report clinically elevated composite PSQI scores (>5; 45.1% vs 40.0%, adjusted prevalence ratio [PR] = 1.20, 95% CI = 1.13 to 1.27), symptoms of insomnia (38.8% vs 32.0%, PR = 1.26, 95% CI = 1.18 to 1.35), snoring (18.0% vs 17.4%, PR = 1.11, 95% CI = 1.01 to 1.23), and sleep medication use (13.2% vs 11.5%, PR = 1.28, 95% CI = 1.12 to 1.45) compared with siblings. Within cancer survivors, PSQI scores were similar across diagnoses. Anthracycline exposure (PR = 1.13, 95% CI = 1.03 to 1.25), abdominal radiation (PR = 1.16, 95% CI = 1.04 to 1.29), and increasing CHC burden were associated with elevated PSQI scores (PRs = 1.21-1.48). Among survivors, sleep problems were more closely related to CHC than diagnosis or treatment history, although longitudinal research is needed to determine the direction of this association. Frequent sleep-promoting medication use suggests interest in managing sleep problems; behavioral sleep intervention is advised for long-term management.

Depression, anxiety, lower sleep quality and social support in square cabin hospitals during Shanghai's COVID-19 lockdown, China.

To investigate and compare the associated factors of depression, anxiety, and other psychological differences between patients with Corona Virus Disease 2019 quarantined in square cabin hospitals (SCH) and isolation wards (IW) in China. Cluster sampling method was performed during Shanghai's Two-Month Lockdown in 2022. Hospital Anxiety and Depression Scale Depression subscale (HADS-D), 7-tiem Generalized Anxiety Disorder Scale (GAD-7), Pittsburgh sleep quality index (PSQI), and Perceived Social Support Scale (PSSS) were used to investigate psychological differences. The HADS-D and GAD-7 scores of SCH patients were significantly higher than those in IW (p < 0.001; p = 0.0295). Sleep latency (SCH-IW = -3.76, p < 0.001), sleep duration (SCH-IW = -2.22, p < 0.05), habitual sleep efficiency (SCH-IW = -4.11, p < 0.001), sleep disturbance (SCH-IW = -3.59, p < 0.001) and use of sleep medication (SCH-IW = -5.18, p < 0.001) of SCH patients were significantly worse. Depression was the main emotional problem of quarantined patients. Patients in SCH had lower social support. Sleep disorders and the lowest oxygen saturation ≤ 93% were risk factors for depression, while social support and child status were protective factors. Myalgia and constipation were risk factors for anxiety, while marital status was the protective factor. Patients quarantined in SCH had higher risks of depression and anxiety, lower sleep quality and social support. Somatic discomfort and sleep disorders exacerbated depression and anxiety, which could be ameliorated by social support and taken into consideration in future SCH construction.

Predictors of insomnia severity and sleep medication use: Are there any similarities?

Predictors of insomnia severity and sleep medication use: Are there any similarities?

The Interplay of Anxiety, Depression, Sleep Quality, and Socioeconomic Factors in Somali Hemodialysis Patients.

This study aimed to assess anxiety, depression, and sleep quality in kidney failure patients receiving hemodialysis (HD) in Somalia and examine the relationship between anxiety, depression, and sleep quality. We conducted a study with 200 kidney failure patients on HD treatment for over 3 months. Participants completed sociodemographic questionnaires, the Patient Health Questionnaire-9 (PHQ-9), the Hospital Anxiety and Depression Scale (HADS), the Insomnia Severity Index (ISI), and the Pittsburgh Sleep Quality Index (PSQI). Among the 200 participants (mean age = 52.3; SD = 14.13), 58.5% were men, 64% had CKD for 1-5 years, and 52.6% received HD for 1-5 years. Depressive symptoms were found in 61.5% (PHQ-9) and 37.5% (HADS depression subscale) of HD patients. Poor sleep quality (PSQI) was observed in 31.5% and significantly correlated with PHQ-9 (rs = 0.633), HADS anxiety (rs = 0.491), and HADS depression (rs = 0.529). The ISI score correlated significantly with PHQ-9 (rs = 0.611), HADS anxiety (rs = 0.494), and HADS depression (rs = 0.586). All PSQI components correlated with depression and anxiety, except sleep medication use. Hierarchical regression analysis revealed that HADS anxiety (β = 0.342) and HADS depression (β = 0.372) predicted ISI scores. HADS anxiety (β = 0.307) and HADS depression (β = 0.419) predicted PSQI scores. Higher anxiety and depression levels negatively correlated with various dimensions of sleep quality in kidney failure patients. Early identification and appropriate management of these psychological disturbances are crucial for enhancing patients' overall quality of life.

Impact of Medical School on the Relationship between Nutritional Knowledge and Sleep Quality-A Longitudinal Study of Students at Wroclaw Medical University in Poland.

The aim of this study was to investigate the impact of the first year of medical school on the relationship between nutritional knowledge and sleep. To achieve this, first-year medical students at Wroclaw Medical University were invited to participate in the study during both the initial and final months of their first academic year. The study included 570 students in the initial period and 705 in the latter. The research questionnaire comprised the KomPAN, assessing nutritional knowledge, and the Pittsburgh Sleep Quality Index (PSQI), evaluating sleep quality. The majority of students demonstrated at least sufficient nutritional knowledge, while approximately two-thirds of students experienced poor sleep in both periods. Notably, sleep quality further deteriorated in the second period (PSQI total score: 6.86 vs. 7.38, p = 0.0157). This change was influenced mainly by a decrease in sleep duration and an increase in the use of sleep medications (both p < 0.0001). The significant difference in overall sleep quality between different nutritional knowledge levels emerged only in the second semester, where students with the highest nutritional knowledge slept the best, while those with the lowest slept the worst (p = 0.0001). Crucially, in both periods, the use of sleep medications was highest among individuals with insufficient nutritional knowledge. Throughout the academic year, the usage increased for all except those with the highest nutritional knowledge, who exhibited the best sleep (p < 0.0001). The escalating use of sleep medications among medical students warrants greater attention, and leveraging the relationship between nutritional knowledge and sleep could prove beneficial, as positive habits in one domain may positively influence the other.

Sleep quality among family medicine physicians before and during COVID-19 in Jeddah, Saudi Arabia

Background: This study aimed to assess the sleep quality of family medicine physicians before and during the COVID-19 pandemic in Jeddah, Saudi Arabia, and to explore the associations between sleep quality and various demographic and health-related factors. Methods: A total of 109 family medicine physicians participated in this cross-sectional study. The Pittsburgh sleep quality index (PSQI) was utilized to evaluate sleep quality, encompassing seven components: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of sleep medication, and daytime dysfunction. Data were collected asking questions regarding both before and during the pandemic period. Descriptive statistics, paired-sample t-tests, and Chi-square tests were used for data analysis. Results: The study revealed significant changes in sleep quality components before and during the pandemic. While sleep latency and sleep duration improved, sleep disturbance, use of sleep medication, and daytime dysfunction worsened during the pandemic. The overall global PSQI score indicated a decline in sleep quality during the pandemic. Females reported poorer sleep quality than males. Participants with general anxiety disorder, diabetes mellitus, and hypertension experienced worse sleep quality. Other demographic and health-related factors exhibited mixed associations with sleep quality. Conclusions: The study highlights the nuanced impact of the COVID-19 pandemic on the sleep quality of family medicine physicians. The observed changes in sleep quality components and their associations with various factors underscore the need for tailored interventions to address sleep disturbances among healthcare professionals. These findings contribute to a comprehensive understanding of sleep quality dynamics in the context of a global crisis and emphasize the significance of promoting well-being among healthcare providers for enhanced patient care.

Anxiety and depression among patients with insomnia during the first wave and the release of the COVID-19 in Northeast China: A cross-sectional survey

BackgroundThe global coronavirus disease 2019 (COVID-19) pandemic seriously affected people's lives. We evaluated anxiety and depression among patients with insomnia in northeast China during the first wave and release of COVID-19, providing a basis for the clinical diagnosis and treatment of insomnia. MethodsWe enrolled 4211 patients with insomnia from January 2016 to February 2020, August 2020 to February 2022, August 2022 to December 2022, and January 2023 to February 2023, from our institution. Sleep quality was evaluated using the Athens Insomnia Scale, Insomnia Severity Index (ISI), and Pittsburgh sleep quality index (PSQI), while mood disorder and fatigue were evaluated using the Hhospital anxiety and depression scale (HAD), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Fatigue Scale-14 (FS-14). ResultsInsomnia with depression increased in prevalence after COVID-19 compared with before (12.8 % vs. 15.3 %, P < 0.05), while the age of patients decreased [(50.2 ± 15.2) vs. (47.5 ± 16.8), P < 0.05]. The number of patients with insomnia and severe depression increased compared with before COVID-19 (20.3 % vs. 25.3 %, P < 0.05). A higher proportion of patients with insomnia for >2 years had depression (P < 0.05). As the epidemic subsided, insomnia increased among young and male patients (young patients: 55.2 % vs. 37.0 %; male patients: 41 % vs. 27.4 %, respectively; P < 0.05). The proportion of patients with insomnia with anxiety and depression increased (53.8 % vs. 51.8 %，P < 0.05), the proportion with moderate to severe anxiety increased (7.6 % vs. 13.5 %, P < 0.05), and moderate and severe depression decreased (moderate: 25.6 % vs. 19.1 %, severe: 25.8 % vs. 20.3 %, P < 0.05, respectively). Middle-aged and elderly patients had higher PQSI scores in sleep latency, habitual sleep efficiency, subjective sleep quality, and use of sleep medications than young patients (P < 0.05). The PSQI score was positively correlated with the PHQ-9 score (r = 0.526), GAD-7 score (r = 0.563), and FS-14 score (r = 0.316) (P < 0.05). LimitationsThe study was single-center, the sample size was small, and assessment data were lacking from early in the epidemic. The scale is subjective, which may affect the accuracy. ConclusionInsomnia with depression increased during COVID-19. The patients were younger than before the epidemic, and a higher proportion with insomnia for >2 years had depression. The proportion of patients with insomnia with anxiety and depression was higher after the epidemic period, and the degree worsened. The proportion of insomnia with depression decreased after the epidemic period, and the degree alleviated. The proportion of young male patients with insomnia increased. Middle aged and elderly patients with insomnia had poor sleep quality, which was positively correlated with anxiety, depression, and fatigue.

Evaluation of racial and ethnic heterogeneity in the associations of sleep quality and sleep apnea risk with cognitive function and cognitive decline.

The prevalence of poor sleep quality and sleep apnea differs by race and ethnicity and may contribute to racial disparities in cognitive aging. We investigated whether sleep quality and sleep apnea risk were associated with cognitive function and decline and whether the associations differed by race/ethnicity. Participants from the Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE; N = 1690; mean age: 75.7 years) study, a cohort of Asian, Black, Latino, and White participants, completed a modified Pittsburgh Sleep Quality Index assessing subjective sleep quality, latency, duration, disturbances, sleep medication use, and daytime dysfunction. Sleep apnea risk was measured by questions about snoring, tiredness, and whether apnea was observed. Executive function and verbal episodic memory were assessed at three time points over an average of 2.7 years with the Spanish and English Neuropsychological Assessment Scale. We fit linear mixed-effect models and stratified analyses by race/ethnicity. Higher sleep apnea risk was associated with faster declines in verbal episodic memory ( sleep apnea = -0.02, 95% confidence interval [CI], -0.04, -0.001) but not in executive function. Poorer sleep quality was associated with lower levels of and faster decline in executive function but not in verbal episodic memory. Race/ethnicity modified these associations: compared to estimated effects among White participants, poorer global sleep quality ( sleep*time = -0.02, 95% CI, -0.02, -0.01) was associated with larger effects on decline in executive function among Black participants. Estimated effects of some individual sleep quality components were also modified by race/ethnicity; for example, sleep medication use was associated with faster declines in executive function ( sleep*time = -0.05, 95% CI, -0.07, -0.03) and verbal episodic memory sleep*time = -0.04, 95% CI, -0.07, -0.02) among Black participants compared to White participants. Observational evidence indicates sleep quality is a promising target for addressing racial/ethnic disparities in cognitive aging, especially among Black older adults. Sleep apnea risk was associated with faster declines in verbal episodic memory but not executive function among all participants.Global sleep quality was associated with lower levels of and faster decline in executive function but not verbal episodic memory among all participants.Black older adults were particularly susceptible to the estimated adverse cognitive impacts of global sleep quality, particularly the use of sleep medication.

Association Between Sleep Characteristics and Likelihood of Prodromal Parkinson's Disease: A Cross-Sectional Analysis in the HABIT Study.

Sleep is critical in health problems including Parkinson's disease (PD). This study examined the association between sleep characteristics and the likelihood of prodromal PD. At baseline examination of the Heart and Brain Investigation in Taicang (HABIT) study, potential PD biomarkers were obtained for 8777 participants aged over 50 years, and the probability of prodromal PD was assessed based on the Chinese expert consensus and Movement Disorder Society (MDS) criteria. General and component sleep characteristics were evaluated by the Pittsburgh Sleep Quality Index (PSQI). Median regression was applied to examine the association between sleep and the probability of prodromal PD, adjusting for age, sex, education level, physical activity, obesity, fast plasma glucose, lipids, and hypertension. Based on China criteria, a higher level of PSQI score was significantly associated with a higher probability of prodromal PD (β = 0.02, 95% CI: 0.01-0.03) and a higher risk of having an increased probability of prodromal PD (OR = 1.04, 95% CI: 1.02-1.05). Compared to participants with good quality sleep, those with poor quality sleep had a 0.07% increased probability of prodromal PD (95% CI: 0.01-0.13) and a 19% increased risk of having a high prodromal PD probability (95% CI: 1.04-1.20). Similar associations between sleep quality and the probability of prodromal PD were also observed using the MDS criteria. Subjective sleep quality, sleep latency, habitual sleep efficiency, daytime dysfunction, and use of sleep medications were also associated with the probability of prodromal PD. Poor sleep quality was associated with a high probability of prodromal PD. Sleep may be helpful for understanding and intervention of prodromal PD.

Perceived social support, perceived stress, and quality of sleep among COVID-19 patients in Iran: assessing measurement invariance of the multidimensional scale of perceived social support across gender and age.

Perceived social support (PSS) plays a considerable role in mental health. The Multidimensional Scale of Perceived Social Support (MSPSS) is one of the most widely used scales, leading to much research evidence. The present study investigated its measurement model, equivalence across gender (male and female) and age groups (older patients= above 60 and non-older patients= below 60), and concurrent validity. A cross-sectional survey was conducted between March and October 2020, on patients hospitalized due to COVID-19 in Tehran, Iran. The scales were administered to 328 COVID-19 patients (54.6% male, aged 21 to 92) from two general hospitals; participants completed MSPSS (including friends, family, and significant others subscales), Pittsburgh Sleep Quality Index (PSQI, include sleep latency, subjective sleep quality, habitual sleep efficiency, sleep duration, use of sleep medication, daytime dysfunction, and sleep disturbances subscales), and the Perceived Stress Scale-10 (PSS-10, to assess patients' appraisal of stressful conditions). The MSPSS three-factor structure was confirmed among COVID-19 patients by Confirmatory Factor Analysis (CFA). The results support the MSPSS internal consistency and configural, metric, and scalar invariance across gender and age groups. Nevertheless, small but significant differences were found across ages based on the latent factor mean of the MSPSS from friends, with a lower mean level in older patients. The coefficients of Cronbach's alpha (ranging from.92 to.96), the ordinal theta (ranging from.95 to.98), and Omega (ranging from.93 to.97) suggested high internal consistency of MSPSS. The concurrent validity of MSPSS was evidenced by its significant negative correlation with PSS-10 (τb = -.13, p <.01) and also subjective sleep quality (τb = -.22, p <.01), sleep disturbances (τb = -.26, p <.001), and daytime dysfunction (τb = -.26, p <.001). The MSPSS was valid and reliable for measuring individuals' perception of social support between males and females and older and non-older COVID-19 patients.

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.

Sleep quality and related factors among healthcare workers in designated quarantine hospital site in post-pandemic based on the health ecological model: a cross-sectional study in Nanjing, China.

This study aims to assess the status and related factors among healthcare workers (HCWs) in designated quarantine-hospital-site (DQHS) based on the model of health ecology. The cross-sectional study was conducted from April to May, 2022, which included 351 valid samples. We measured sleep quality using the Pittsburgh Sleep Quality Index, which encompasses seven dimensions: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each dimension is scored individually, contributing to an overall sleep quality score. Factors associated with the sleep quality of HCWs in DQHS were divided into individual, behavioral, interpersonal and social dimensions. Hierarchical linear regressions were conducted to identify the potential factors associated with sleep quality among HCWs in DQHS. HCWs in DQHS had a statistically higher sleep quality than the Chinese national norm. HCWs who were female, afraid of Coronavirus disease, had more negative emotions, frequently worked overtime, were married, and had a higher income were more likely to experience worse sleep quality (p < 0.05), while those who worked between 51 and 70 h weekly, treated over 10 patients daily, and engaged in more health behaviors may have better sleep quality (p < 0.05). This study revealed a worrying level of sleep quality among HCWs in DQHS. The government, hospital managers, and families should collaborate to ensure the sleep quality of HCWs in DQHS.

Monitoring the sleep health of adults: a scoping review of routine national surveillance systems.

The aims of this review were to identify existing national surveillance systems monitoring one or more domains of sleep health in adults, and to describe the specific sleep health indicators used. We systematically searched the gray and peer-reviewed literature for routinely conducted cross-sectional and longitudinal nationally representative health surveys that included the assessment of at least one domain of sleep health. The methodology involved: (1) targeted searches of the websites of national and international health agencies and statistics departments for 199 countries, (2) country-specific customized internet searches, and (3) country-specific electronic database searches of PubMed. A total of 19762 records were identified from both the gray and peer-reviewed literature. Sleep health surveillance at the national level was conducted by 51 countries (25.6%) across 69 national health surveys. Sleep quality (96.1% of countries that surveilled sleep) was the most frequently assessed followed by sleep duration (27.5%), sleep medication use (25.5%), sleep disorders (17.6%), daytime alertness (15.7%), sleep satisfaction (15.7%), and sleep timing (7.8%). Additionally, 34.8% of the surveys utilized multiple sleep health indicators. This study identified three significant gaps in the coverage of sleep health within national surveillance systems. Limited population sleep data in low- and middle-income countries, inconsistent use of sleep-related items in surveys and questionnaires, and substantial variability in the definitions of sleep health indicators. Advocacy for the inclusion of sleep health within national surveillance systems may be warranted given the important role sleep plays in public health.

SLEEP MEDICATION USE AND FALLS IN OLDER ADULTS WITH OSTEOPOROSIS

Abstract One third of older adults take sleep medications, but they are associated with fall risk. One in four older adults experiences a fall each year, costing the U.S. $50 billion dollars annually. Osteoporosis is linked to falls, but little research has examined sleep medication use and falls risk among older adults with osteoporosis. We examined the 2011 National Health and Aging Trends Study (NHATS). Outcomes were falls in the last month, falls in the last year, multiple falls in the last year, and fear of falling. Self-reported sleep medication use dichotomized for analysis (0= once/week or less; 1= 2 or more times/week) was the exposure of interest. Osteoporosis was self-reported (yes/no). Of 8,245 participants, 58% female, 68% white, and 20.5% had osteoporosis. Multivariable logistic regression showed, sleep medication users, compared to rare- or non-users, had higher odds of a fall in the last month (O.R. = 1.64, 95% CI: 1.10, 2.47), in the last 12 months (O.R. = 1.60, 95% CI: 1.20, 2.12), multiple falls in the last 12 months (O.R. = 1.64, 95% CI: 1.08, 2.50), and fear of falling (O.R. = 1.58, 95% CI: 1.18, 2.11). Osteoporotic sleep medication users show increased risk of falls, multiple falls per year, and fear of falling. As older adults with osteoporosis are at increased risk, reducing sleep medication use may decrease this risk, thus decreasing the need for costly medical care. This study contributes to clinicians’ efforts to reduce falls in vulnerable older adults and may reduce overall burden to Medicare.

SLEEP AND FREQUENT HOSPITALIZATIONS AT THE END OF LIFE FOR INDIVIDUALS WITH DEMENTIA

Abstract Older adults near end-of-life (EOL) are at risk for experiencing non-beneficial hospitalizations, negatively impacting their quality of life. Reasons for frequent hospitalizations include poorly managed symptoms of progressing chronic illnesses, many of which are exacerbated by poor sleep, and may differ depending on presence of dementia. This study characterized sleep for groups with and without frequent (two-or-more) hospitalizations in the final year of life using the National Health and Aging Trends Study. A subgroup of persons living with dementia (PLWD) was also explored. Means for difficulty falling asleep, trouble falling back to sleep, and use of sleep medications were compared for groups with and without frequent hospitalizations via one-tailed t-tests. Association between dementia and frequent hospitalizations was explored via Pearson Chi-Square. Individuals at EOL (n=529, 56% female, 68% white non-Hispanic, average age 80-85, 57% PLWD) were included, and 22% had frequent hospitalizations. Among the entire sample, those with frequent hospitalizations had worse sleep (more trouble falling back to sleep, p=.032, Cohens-d=.2). Sleep was also worse for those without dementia, but with frequent hospitalizations (difficulty falling back to sleep, Cohens-d=.3, p=.02) compared to those without frequent hospitalizations. There was no association between frequent hospitalization and presence of dementia (chi-square=.868 p=.352). However, the PLWD subgroup had worse sleep than those without dementia (difficulty falling asleep Cohens-d=.15, p=.04; use of sleep medications Cohens-d=.26, p=.002), yet sleep did not differ depending on frequent hospitalizations. These results indicate that further investigation into the relationship between dementia, sleep, and frequent hospitalizations at EOL is warranted.

SLEEP quality in patients with psoriatic arthritis and its relationship with disease activity and comorbidities: a cross-sectional study

The assessment of psoriatic arthritis is complex and multidimensional. It is increasingly common to include the patient perspective using patient-reported outcomes. Although some research has explored sleep quality in patients with psoriatic arthritis, most studies have had small sample sizes, failed to assess sleep quality considering the inflammatory process together with the psychological well-being of patients, and have not described any use of sleep medication. Further, research to date has not provided data on the relationship of sleep quality with axial forms. In this context, the objective of this study was to assess sleep quality in patients with psoriatic arthritis and its relationship with clinical characteristics, disease activity, functioning, disease impact, fatigue and psychological status. A cross-sectional study was conducted including 247 consecutive patients with PsA recruited during 2021. Sleep quality was measured using the Pittsburgh Sleep Quality Index. We assessed correlations of Pittsburgh Sleep Quality Index score with peripheral disease activity (Disease Activity Index for PSoriatic Arthritis), axial disease activity (Ankylosing Spondylitis Disease Activity Score-C-reactive protein and Bath Ankylosing Spondylitis Disease Activity Index), functioning (Bath Ankylosing Spondylitis Functional Index and Health Assessment Questionnaire), impact (Psoriatic Arthritis Impact of Disease questionnaire), anxiety, depression (Hospital Anxiety and Depression Scale) and fatigue (Functional Assessment of Chronic Illness Therapy-Fatigue) scores. A multiple linear regression model was constructed with PSQI as the dependent variable and as independent variables those that could influence sleep quality. Nearly two-thirds (63.15%) of patients had poor sleep quality. Poorer sleep quality was associated with being female, higher joint counts, greater peripheral and axial disease activity, fatigue, anxiety and depression, functioning and disease impact (p < 0.001). Multiple linear regression analysis found that pain (β: 0.3; p < 0.007) and fatigue β: − 0.1; p < 0.001 contributed 40% to the sleep quality model. Poor sleep quality was common among patients with psoriatic arthritis. Emotional factors (fatigue, anxiety) seemed more important than inflammatory factors in sleep quality.

The Relationship Between Nomophobia with Physical Activity and Sleep Quality in Community-Dwelling and Non-Frail Older Adults

Objective: Lack of physical activity, sleep problems and nomophobia are serious problems in adults. This study aimed to investigate the relationship between nomophobia with physical activity and sleep quality in non-frail older adults living in the community. Materials and Methods: The participants' fragility status was determined using the "Tilburg Frailty Indicator Survey," while nomophobia levels were assessed with the "Nomophobia Questionnaire," physical activity levels were measured using the "International Physical Activity Questionnaire-Short Form," and sleep quality was evaluated with the "Pittsburgh Sleep Quality Index (PSQI). Results: A total of 158 participants, 73 (46.8%) male and 85 (53.2%) female, were included in the study. While 5 (3.2%) of the participants were not nomophobic, 153 (96.8%) had nomophobia. 29 (18.4%) of the participants had no sleep problems, and 129 (81.6%) had sleep problems. As a result of the analysis, a weak negative correlation (r: -0.338, p&amp;lt;0.001) was found between physical activity and nomophobia. A positive and negligible correlation was observed between use of sleep medication, daytime dysfunction sub-scales, total PSQI scores and nomophobia (r:0.167-r:0.193, p&amp;lt;0.05). Conclusion: It was determined that as nomophobia increased in non-frail adult people, their physical activity levels decreased, and their sleep quality was negatively affected.

INDICADORES DO ESTILO DE VIDA DE SOLDADOS E CABOS DA POLÍCIA MILITAR DO MUNICÍPIO DE VITÓRIA-ES

Introduction: The lifestyle of military personnel can increase the risk of disease. Lifestyle can be considered a way of life involving values, choices, daily practices, forms of consumption, leisure habits, work, religion and socializing, expressing the characteristics of an individual or group, and can increase the risk of disease in military officers. Objective: This study aimed to compare the lifestyles of military police soldiers and corporals in the municipality of Vitória-ES. Materials and methods: 29 military police officers, 14 soldiers, and 15 corporals, had their lifestyles assessed using the Fantastic Lifestyle questionnaire, which included family and friends, physical activity, nutrition, smoking and drugs, alcohol, sleep, seat belts, stress, safe sex, type of behavior, introspection and work. Sleep quality was also assessed, by the Pittsburgh Sleep Quality Scale involving sleep factors such as subjective quality, latency, duration, habitual efficiency, disorders, use of sleep medication, and daytime dysfunction, as well as the classification of poor sleep quality, sleep disorders, and quality. Results: Corporals were found to have higher body mass (p= 0.012), BMI (p= 0.039), and length of service (p= 0.001). As for lifestyle, there was a difference (p= 0.025) in nutrition, with 43% of the soldiers being very good and 60% of the corporals being good. In terms of sleep quality, 60% of the soldiers had poor sleep quality and 40% of the corporals had some kind of sleep disorder. Conclusion: Corporals had higher body mass, BMI, and sleep disorders, while soldiers had poor sleep quality. Level of Evidence III; Study of Non-Consecutive Patients, without Uniformly Applied “Gold” Reference Standard.

Effects of age on the relationship between sleep quality and cognitive performance: Findings from the Human Connectome Project-Aging cohort.

The association between sleep quality and cognition is widely established, but the role of aging in this relationship is largely unknown. To examine how age impacts the sleep-cognition relationship and determine whether there are sensitive ranges when the relationship between sleep and cognition is modified. This investigation could help identify individuals at risk for sleep-related cognitive impairment. Sample included 711 individuals (ages 36.00-89.8359.66 ± 14.9155.7 % female) from the Human Connectome Project-Aging (HCP-A). The association between sleep quality (Pittsburgh Sleep Quality Index, PSQI) and cognition (Crystallized Cognition Composite and Fluid Cognition Composite from the NIH Toolbox, the Trail Making Test, TMT, and the Rey Auditory Verbal Learning Test, RAVLT) was measured using linear regression models, with sex, race, use of sleep medication, hypertension, and years of education as covariates. The interaction between sleep and age on cognition was tested using the moderation analysis, with age as both continuous linear and nonlinear (quadratic) terms. There was a significant interaction term between the PSQI and nonlinear age term (age2) on TMT-B (p = 0.02) and NIH Toolbox crystallized cognition (p = 0.02), indicating that poor sleep quality was associated with worse performance on these measures (sensitive age ranges 50-75 years for TMT-B and 66-70 years for crystallized cognition). The sleep-cognition relationship may be modified by age. Individuals in the middle age to early older adulthood age band may be most vulnerable to sleep-related cognitive impairment.

Associations between sleep medication use and alcohol consumption over 36 years in Finnish twins

BackgroundSleep medication use is an indicator of underlying sleep problems that might be induced by various factors such as alcohol use. However, the longitudinal relationship between drinking and sleep problems remains poorly understood. We investigated associations between sleep medication and alcohol use throughout adulthood, and examined the role of familial and potential confounding factors contributing to these associations. MethodsWe used information of zygosity and self-report questionnaire data over a follow-up period of 36 years from the Older Finnish Twin Cohort (N=13,851). ResultsLogistic regression analyses suggested consistent associations between sleep medication use and heavy/binge drinking at all four time points (OR range =1.36-3.18, P <0.05), implying that increased drinking is associated with increased sleep medication use over time. Cross-lagged path analyses suggested that moderate/heavy and binge drinking predict sleep medication use at most time points (OR range = 1.15-1.94, P <0.05), whilst sleep medication use predicts subsequent abstaining from alcohol (OR range =2.26-2.47, P <0.05). Within-pair analyses implied that familial factors play a role, and quantitative genetic modelling estimated genetic factors to explain approximately 80% of the lifetime association of sleep medication use with moderate/heavy and binge drinking. ConclusionsDrinking is associated with sleep medication use throughout adulthood. Further, our results suggest that drinking is likely to predict sleep medication use, thereby potentially constituting a risk factor for sleep problems, and that genetic factors contribute to the association. These findings are important in terms of better understanding the development of sleep and alcohol use disorders.