Subgrouping Poor Sleep Quality in Community-Dwelling Older Adults with Latent Class Analysis - The Yilan Study, Taiwan

Relationship Between Sleep Problems and Memory Impairment Among Nurses

BACKGROUND

Sleep problems are common among nurses and can lead to various health problems. Further, the relationship between multiple sleep problems and memory impairment in clinical nurses remains unknown. Therefore, in this study, we aimed to explore the relationship between sleep problems and memory impairment among nurses.

METHODS

Multistage cluster-stratified random sampling was performed from tertiary hospitals in Shandong, China. Overall, a total of 1833 nurses were included in the final analysis. The Chinese version of the Pittsburgh Sleep Quality Index and prospective and retrospective memory questionnaire were administered to the participants.

RESULTS

The sleep quality of the nurses decreased during the normal epidemic prevention and control period compared with that before the epidemic in terms of sleep duration, sleep efficiency, and sleep disturbances. Nurses who reported cumulative or specific sleep problems (e.g., high sleep latency, sleep disturbances, and daytime dysfunction) and those in the "daily disturbances" and "poor sleep quality" groups had a higher risk of memory impairment than the others.

CONCLUSION

Sleep problems might be important for memory impairment among nurses. These findings may help identify nurses at considerable risk of memory impairment in clinical practice.

Efficacy of epidural esketamine on postoperative sleep quality after laparoscopic and robotic lower abdominal surgeries: a study protocol for randomised, double-blind, controlled trial

INTRODUCTION

Postoperative sleep disturbances significantly impair postoperative recovery. The administration of intravenous esketamine has been shown to potentially improve postoperative sleep quality. However, the effectiveness of epidural esketamine in improving postoperative sleep quality remains to be elucidated. This study aims to explore the impact of both intraoperative and postoperative use of epidural esketamine on the postoperative sleep quality of patients undergoing minimally invasive lower abdominal surgeries.

METHODS AND ANALYSIS

This randomised, double-blind, parallel-group, placebo-controlled trial will be conducted at the Fudan University Shanghai Cancer Centre. A total of 128 adults undergoing minimally invasive lower abdominal surgeries will be randomly allocated in a 1:1 ratio to either the esketamine group or the placebo group. In the esketamine group, epidural esketamine will be administered intraoperatively (0.2 mg/kg) and postoperatively (25 mg). Postoperatively, all patients will receive epidural analgesia. The primary outcome of the study is the incidence of poor sleep quality on the third day after surgery. The sleep quality assessment will be conducted using the Pittsburgh Sleep Quality Index and a Numeric Rating Scale of sleep. The main secondary outcomes include postoperative pain and anxiety and depression scores. The postoperative pain, both rest pain and movement pain, will be assessed using a Numerical Rating Scale within 5 days after surgery. Anxiety and depression scores will be evaluated using the Hospital Anxiety and Depression Scale both before and after the surgery. Safety outcomes will include delirium, fidgeting, hallucinations, dizziness and nightmares. The analyses will be performed in accordance with intention-to-treat principle ETHICS AND DISSEMINATION: Ethics approval has been obtained from the Ethics Committee of the Shanghai Cancer Centre (2309281-9). Prior to participation, all patients will provide written informed consent. The results of the trial are intended to be published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

ChiCTR2300076862.

The sleep patterns and their associations with mental health among nursing home residents: a latent profile approach

BACKGROUND

Nursing home residents commonly experience poor sleep conditions. However, few studies have explored the potential sleep patterns among nursing home residents. This study aimed to identify the sleep patterns in nursing home residents, compare residents' characteristics across sleep patterns, and examine the relationships between sleep patterns and residents' mental health (i.e., depressive and anxiety symptoms).

METHODS

This cross-sectional study was conducted in 27 nursing homes in Jinan, China, from March to June 2018. In total, 353 participants were recruited via convenience sampling, and of which, 326 completed the survey. A latent profile analysis was performed to identify sleep patterns based on the seven dimensions of the Pittsburgh Sleep Quality Index. Bivariate analyses were conducted to compare residents' characteristics among the sleep patterns. Mixed-effects logistic regression analyses were adopted to investigate the relationships between sleep patterns and residents' mental health.

RESULTS

Three sleep patterns were identified, including 'good sleepers', 'poor sleepers without hypnotic use', and 'poor sleepers with hypnotic use'. Residents' gender, education, pain, instrumental activities of daily living, and number of chronic conditions were significantly differentiated across the sleep patterns. Compared with 'good sleepers', 'poor sleepers without hypnotic use' were significantly associated with more depressive symptoms (OR = 3.73, 95% CI = 2.09, 6.65, p < 0.001), but not with anxiety symptoms (OR = 2.04, 95% CI = 0.97, 4.29, p = 0.062); whereas 'poor sleepers with hypnotic use' had significantly more depressive (OR = 5.24, 95% CI = 2.54, 10.79, p < 0.001) and anxiety symptoms (OR = 5.02, 95% CI = 2.13, 11.83, p < 0.001).

CONCLUSIONS

This study reveals three distinct sleep patterns in nursing home residents and their significant associations with residents' mental health. These findings can inform future research to develop appropriate and tailored intervention strategies for improving sleep and promoting mental health for nursing home residents.

Association of Sleep Patterns with Type 2 Diabetes Mellitus: A Cross-Sectional Study Based on Latent Class Analysis

Sleep duration, sleep quality and circadian rhythm disruption indicated by sleep chronotype are associated with type 2 diabetes. Sleep involves multiple dimensions that are closely interrelated. However, the sleep patterns of the population, and whether these sleep patterns are significantly associated with type 2 diabetes, are unknown when considering more sleep dimensions. Our objective was to explore the latent classes of sleep patterns in the population and identify sleep patterns associated with type 2 diabetes. Latent class analysis was used to explore the best latent classes of sleep patterns based on eleven sleep dimensions of the study population. Logistic regression was used to identify sleep patterns associated with type 2 diabetes. A total of 1200 participants were included in the study. There were three classes of sleep patterns in the study population: "circadian disruption with daytime dysfunction" (class 1), "poor sleep status with daytime sleepiness" (class 2), and "favorable sleep status" (class 3). After controlling for all confounding factors, people in class 2 have significantly higher prevalence of type 2 diabetes than those in class 3 (OR: 2.24, 95% CI 1.26-4.00). Sleep problems have aggregated characteristics. People with sleep patterns involving more or worse sleep problems have higher significantly prevalence of T2DM.

Exploration of college teachers' psychological adaptation to online teaching during the COVID-19 pandemic using potential profile analysis

The present study used a person-centered approach to examine college teachers' psychological adaptation to online teaching and its relationship with demographic variables. A total of 2104 college teachers were surveyed using the Psychological Adaption to Online Teaching Scale between March 25 and March 31, 2020. Data were analyzed using latent profile analysis, chi-square test, and multinomial logistic regression analysis. Based on their psychological adaptation during online teaching immediately after the coronavirus disease 2019 (COVID-19) outbreak, college teachers were divided into three latent profiles: common, maladaptive, and positive. Among these, the common type accounted for the largest proportion (56.1%), while the maladaptive type accounted for the smallest (10.9%). There were significant differences in the distribution of psychological adaptation latent types in college teachers with different educational backgrounds and professional titles. A better educational background and higher professional title is closely related with college teachers' psychological adaptation to online teaching.

Sleep quality of Singapore residents: findings from the 2016 Singapore mental health study

Given the importance of sleep for physical and mental wellbeing, it is crucial to understand the extent of insomnia among community dwellers. However, there is a paucity of population wide epidemiological studies to estimate the prevalence of poor sleep quality. This present study aimed to 1) characterize the sleep quality of a nationally representative sample (n = 6126) of Singapore residents using Pittsburg Sleep Quality Index (PSQI) and 2) identify the sociodemographic correlates of poor sleep in this population. A total of 27.6% of respondents reported poor sleep quality (PSQI score ≥5). Sociodemographic correlates of poor sleep quality in the Singapore population included, but were not limited to, females (AOR = 1.44, 95% CI = 1.17 to 1.77, p-value = 0.001), Malays (vs Chinese) (AOR = 1.53, 95% CI = 1.23 to 1.9, p-value < 0.001), Indians (vs Chinese) (AOR = 1.22, 95% CI = 1.02 to 1.47, p-value = 0.03), ex-smokers (vs non-smokers) (AOR = 1.43, 95% CI = 1.07 to 1.92, p-value = 0.02), persons with comorbid mental health conditions (vs no mental health conditions) (AOR = 14.11, 95% CI = 6.52 to 30.54, p-value < 0.01), and persons with physical multimorbidity (vs no physical conditions) (AOR = 1.63, 95% CI = 1.24 to 2.15, p-value < 0.001). The prevalence of poor sleep in Singapore is comparable to that of other countries in the Asian region. Targeted public health campaigns to psycho-educate vulnerable groups on the importance of good sleep hygiene may improve the overall wellbeing of residents in Singapore.

•

Sleep is important for physical and mental health, however data on population wide prevalence of insomnia is scarce.

•

Using the Pittsburgh Sleep Quality Index, we found that 27.6% of this nationally representative sample had poor sleep.

•

Sociodemographic correlates of poor sleep quality in our population included females, Malays, Indians, and ex-smokers.

•

Persons with comorbid mental health conditions and physical multimorbidity were found to have poor sleep quality.

•

Targeted psychoeducation to the relevant subgroups could improve sleep quality of Singapore residents.

Sleep Problems and New Occurrence of Chronic Conditions during the COVID-19 Pandemic in the UK

The COVID-19 pandemic has negatively impacted upon sleep health. Relatively little is known about how this may influence the population's health subsequently. This prospective longitudinal study aims to examine the consequences of sleep problems for physical and mental health during the COVID-19 pandemic in the UK, using data from the Understanding Society: COVID-19 Study, a large-scale population-based survey with 12,804 adults aged 16 and above. A measure of sleep problems was derived from Pittsburgh Sleep Quality Index (PSQI) questions, reflecting seven dimensions of sleep quality. Binary logistic regressions were applied to investigate the relationship between sleep problem and the incidence of cardiovascular disease (CVD), hypertension, diabetes, obesity, arthritis and an emotional, nervous or psychiatric problem over the 15 months follow-up period. The analysis confirms that sleep problems are prevalent and vary between sub-groups among adults. Notably, sleep problems are then significantly associated with a higher risk of cardiovascular disease, hypertension, diabetes, obesity, arthritis and emotional, nervous or psychiatric problems, independent of demographic, socioeconomic, familial and health confounders. Our findings suggest promoting good sleep hygiene should be prioritised during the pandemic, and more generally as part of wider programmes aimed at promoting good physical and mental health.

Different item characteristics of a mild cognitive impairment screening tool in the community-based Yilan Study: application of the item response theory

BACKGROUND

This study aimed to use item response theory (IRT) to explore the item-by-item characteristics of a mild cognitive impairment (MCI) screening tool using community-based data.

METHODS

The Yilan Study is a community-based study that has been conducted since 2012. Until March 2020, 2230 older adults were interviewed according to the household registration data. IRT was applied to determine the item-by-item distinctive characteristics of the Eight-item Interview to Differentiate Aging and Dementia (AD8).

RESULTS

The MCI characteristics in the AD8 items have varying degrees of item response threshold. In all circumstances, item AD8-8, which is related to self-rated memory ability, had a low item response threshold. AD8-5 and AD8-7, which are related to the comparisons of time-oriented functional status, had slightly lower thresholds, especially for those aged 65-79 years or without activity limitations. Conversely, AD8-1, AD8-2, AD8-3, AD8-4, and AD8-6 had similar item response thresholds and discriminative power; these items have more detailed functional descriptions or examples for illustration.

CONCLUSIONS

Concise and understandable elements are often expected in community-based screening tools. For community-based health screening and population empowerment in the early detection of MCI, assessment tool items with detailed functional descriptions and examples for illustration have similar validities in most of the population. Items related to self-rated memory ability might be less valid. More examples may be needed for items constructed for comparing time-oriented functional status, especially in extremely old adults and individuals with activity limitations.

Association between quality of life, sleep quality and mental disorders in Iranian older adults

Aging as a major challenge can affect the development and growth of countries all around the world. This study aimed to identify the subgroups of the elderly based on the quality of life (Qol), sleep quality, and common mental disorders and assess the role of demographic characteristics on the membership of participants in each latent class. This cross-sectional study was conducted on 1064 people over the age of 60 years. The sample was selected through cluster sampling in northern Iran. All participants completed six sets of checklists and questionnaires. Data analysis was performed using latent class analysis. Three latent classes were identified; namely, (1) healthy (66.8%), (2) anxious and with poor sleep quality (28.6%), and unhealthy (4.6%). Being Female significantly increased the odds of membership in classes 2 and 3 compared to class 1. Furthermore, living in urban areas increased the odds of belonging to class 2 and class 3 compared to class 1. Illiteracy was also shown to increase the odds of being in class 3 in comparison to class 1. Results from the present indicate that the co-occurrence of health problems in 33.2% of the elderly was observed in various forms. The results of this study can be used in prioritizing health programs for the elderly and emphasizing high-risk groups.

Sleep Quality and Insomnia Severity among Italian University Students: A Latent Profile Analysis

Insomnia is a widespread sleep disorder associated with physical and mental health conditions. Although the heterogeneity of insomnia presentations has been acknowledged, research investigating clinically meaningful insomnia subtypes is still ongoing. This study aimed at exploring insomnia subtypes according to widely-used measures of symptoms severity and sleep quality among Italian university students using a latent profile analysis. Data were collected from 490 students reporting relevant insomnia symptoms through an online cross-sectional survey comprising the Insomnia Severity Index, the Pittsburgh Sleep Quality Index, the 21-item Depression Anxiety Stress Scale, and the Short Form-12. Latent profile analysis identified five insomnia subtypes. The severe insomnia (8.8%) group showed the highest insomnia severity, with diverse complaints concerning sleep quality and daytime functioning. Moderate insomnia with sleep duration complaints (8.4%) and moderate insomnia with medication use (15.9%) subgroups were characterized by middle range insomnia severity, with problems of sleep continuity and sleep medication use, respectively. Subthreshold insomnia with sleep latency complaints (20.4%) and subthreshold insomnia (46.5%) groups showed attenuated insomnia symptoms. Higher psychological complaints and worse quality of life were associated with greater sleep complaints. Overall, these findings highlight the relevance of sleep quality domains in identifying insomnia subtypes and might help optimize insomnia treatments.

Evaluation of Sleep Disturbances in Patients with Nocturnal Epileptic Seizures in a Romanian Cross-Sectional Study

(1) Background: Based on the premise that epilepsy is frequently associated with hypnopathies, in this study we aim to analyze the prevalence of sleep disturbances among patients with epilepsy, with exclusively or predominantly nocturnal seizures, in relation to demographic factors as well as clinical and electroencephalography (EEG) aspects. (2) Methods: 69 patients with nocturnal epilepsy were included in our study. Sleep disturbances were measured with the Pittsburgh Sleep Quality Index (PSQI) questionnaire, followed by a long-term video-EEG monitoring during sleep. We analyzed the PSQI results in relation to patients' gender and age and determined the correlations between the PSQI scores and the modifications on video-EEG recordings, in comparison to a control group of 25 patients with epilepsy but without nocturnal seizures. (3) Results: We found a statistically significant difference between the PSQI of patients with nocturnal seizures compared to those without nocturnal epileptic manifestations. In the experimental group, the mean PSQI score was 7.36 ± 3.91 versus 5.04 ± 2.56 in controls. In women, the average PSQI score was 8.26, whilst in men it only reached 6.41, highlighting a statistically significant difference between genders (p ˂ 0.01). By examining the relationships between the PSQI scores and certain sleep-related factors, evidenced on the nocturnal video-EEG, we found a statistically significant difference between PSQI values of patients who reached the N2 stage, and those who reached the N3 stage of nonrapid eye movement (NREM) sleep, highlighting that those with a more superficial nocturnal sleep also had higher PSQI scores. There were no statistically significant differences regarding the PSQI scores between patients with or without interictal epileptiform discharges, and also in the few patients with nocturnal seizures where we captured ictal activity. (4) Conclusions: we evidenced in this study a poor quality of sleep in patients with nocturnal epilepsy, mostly in women, independent of age. We observed that sleep disturbances were due to superficial and fragmented sleep with frequent microarousals, not necessarily caused by the electrical epileptiform activity.

Differential Effects of Sleep Disturbance and Malnutrition on Late-Life Depression Among Community-Dwelling Older Adults

BACKGROUND

Late-life depression is a complex phenomenon that cannot be fully understood simply as depression occurring in older adults, prompting researchers to suggest that it represents a component of geriatric syndrome. Given the inherent complexity and multifactorial nature of geriatric syndrome, understanding the interactions between the comorbid conditions involved is important for establishing appropriate preventive strategies. While sleep disturbance and malnutrition are common manifestations of geriatric syndrome, they have also been regarded as indicators of late-life depression. However, the differential effects of sleep disturbance and malnutrition on late-life depression and their interrelationships remain unclear.

OBJECTIVE

The objective of this study was to examine the effects of sleep disturbance and malnutrition on depression and the interactions between them among community-dwelling older adults.

METHODS

Sleep disturbance and malnutrition in 1,029 community-dwelling older adults from Suwon Geriatric Mental Health Center were assessed using the Pittsburgh Sleep Quality Index (PSQI) and Mini Nutritional Assessment (MNA), respectively. The Korean version of the Short Form of the Geriatric Depression Scale (SGDS-K) was used to evaluate depressive symptoms. Sociodemographic parameters were recorded. A multiple linear regression analysis was conducted to examine the effects of sleep and nutrition on depressive symptoms after adjusting for covariates. The effect size and conditional effects of sleep disturbance and malnutrition on late-life depression were assessed using Cohen's f² values and the Johnson-Neyman technique, respectively.

RESULTS

After possible confounders were adjusted, the SGDS-K score was positively associated with the PSQI score (standardized beta = 0.166, P < 0.001) and negatively associated with the MNA score (standardized beta = -0.480, P < 0.001). The local effect size of the associations was small for PSQI and medium for MNA. A significant interaction was observed between the PSQI and MNA scores. The result of the Johnson-Neyman technique indicated that the influence of PSQI on SGDS-K became weaker and insignificant as nutritional status worsened. However, the association between the MNA and SGDS-K scores was significant regardless of PSQI.

CONCLUSION

Both sleep disturbance and malnutrition were significantly associated with late-life depression, although malnutrition may be more critically associated with depression than sleep disturbance in community-dwelling older adults.

The impact of physical pain and depression on sleep quality in older adults with chronic disease

AIMS AND OBJECTIVES

This study's purpose was to identify the correlates of sleep quality in older adults with chronic disease.

BACKGROUND

Sleep quality is a common problem in older adults that may be affected by physical and mental status.

DESIGN

A cross-sectional correlational design was employed.

METHODS

The study was conducted between July 2019 and April 2020 in a teaching hospital of southern Taiwan. The Geriatric Depression Scale, Pittsburgh Sleep Quality Index and Numerical Rating Scale were used to assess depression, sleep quality and physical pain respectively.

RESULTS

Of the 120 older adults (age >65 years) with chronic disease, the average Pittsburgh Sleep Quality Index score was 5.67. A total of 45.8% subjects had sleep disturbance. Older adults who were living with a partner and those who urinated at night were significantly more likely to report sleep disturbance. The presence of sleep disturbance was associated with greater levels of depression and higher levels of physical pain.

CONCLUSION

Living with a partner, nocturia, physical pain and depression were associated with the presence of sleep disturbance in older adults with chronic disease.

RELEVANCE TO CLINICAL PRACTICE

The results of this study can help healthcare providers understand the factors associated with sleep disturbance in older adults with chronic disease, thereby facilitating the early resolution of sleep disturbance issues in this population.

Duration of night sleep and cognitive performance of community older adults

OBJECTIVE

to analyze the relationship between the duration of self-reported night sleep and the cognitive performance of older adults.

METHOD

the sample consisted of 156 older adults registered in Family Health Units (FHUs) in a city of São Paulo, divided into quartiles according to the duration of night sleep. Data collection was performed using a characterization questionnaire, Addenbrooke's Cognitive Exam - Revised (ACE-R) and Pittsburgh Sleep Quality Index (PSQI). Descriptive, comparative and correlational statistical analyses were performed.

RESULTS

the older adults obtained a mean of 61.94 points in ACE-R and 55.1% presented good sleep quality. Comparative analyses showed differences between the groups only in the cognitive domain of verbal fluency (p=0.018). The post-hoc analyses showed that older adults who slept more hours, a mean of 8.85 hours (Q1), had lower scores when compared to those who slept a mean of 6.11 hours (Q3) (p=0.004) and of 4.52 hours (Q4) (p=0.045). The adjusted model with application of the stepwise method showed a relationship between the independent variables of schooling and sleep duration and the domain verbal fluency.

CONCLUSION

it is concluded that sleep duration is related to the verbal fluency cognitive domain.

The association between sleep quality and quality of life: a population-based study

OBJECTIVES

This study aimed to evaluate the association between sleep quality and quality of life (QoL).

METHODS

This cross-sectional study included 225,541 adults (101,133 men, 124,408 women) who participated in the 2018 Korean Community Health Survey. Multiple sociodemographic and psychosocial variables were evaluated and compared between participants with poor (n = 67,619) and good sleep quality (n = 157,922); sleep quality was subjectively determined using the Pittsburgh Sleep Quality Index (PSQI). The EuroQol five-dimension (EQ-5D) index scores were adjusted for multiple confounding factors and compared between the good and poor sleep quality groups. A logistic regression analysis was used to identify determinants of the lowest quartile of QoL.

RESULTS

The mean EQ-5D index scores were significantly lower in the poor sleep quality group (score 0.85) than in the good sleep quality group (score 0.92; p < 0.001). The multivariate odds ratio (OR) for the lowest quartile of the EQ-5D index scores in the poor sleep quality group versus that in the good sleep quality group was 1.95 (95% confidence interval [CI], 1.89-2.00). Participants with poor sleep quality were more likely than those with good sleep quality to have some or severe problems with physical activity (OR, 1.46; 95% CI, 1.41-1.51), self-control (OR, 1.35; 95% CI, 1.29-1.42), daily activity (OR, 1.44; 95% CI, 1.39-1.50), pain (OR, 1.81; 95% CI, 1.77-1.86), and anxiety/depression (OR, 2.24; 95% CI, 2.17-2.31).

CONCLUSION

Poor sleep quality is associated with impaired QoL, particularly if some or severe problems with anxiety/depression are present.

Cardiovascular and Pre-Frailty Risk Assessment during Shelter-In-Place Measures Based on Multimodal Biomarkers Collected from Smart Telemedical Wearables

Wearable devices play a growing role in healthcare applications and disease prevention. We conducted a retrospective study to assess cardiovascular and pre-frailty risk during the Covid-19 shelter-in-place measures on human activity patterns based on multimodal biomarkers collected from smartwatch sensors. For methodology validation we enrolled five adult participants (age range: 32 to 84 years; mean 57 ± 22.38; BMI: 27.80 ± 2.95 kg/m²) categorized by age who were smartwatch users and self-isolating at home during the Covid-19 pandemic. Resting heart rate, daily steps, and minutes asleep were recorded using smartwatch sensors. Overall, we created a dataset of 464 days of continuous measurement that included 50 days of self-isolation at home during the Covid-19 pandemic. Student’s t-test was used to determine significant differences between the pre-Covid-19 and Covid-19 periods. Our findings suggest that there was a significant decrease in the number of daily steps (−57.21%; −4321; 95% CI, 3722 to 4920) and resting heart rate (−4.81%; −3.04; 95% CI, 2.59 to 3.51) during the period of self−isolation compared to the time before lockdown. We found that there was a significant decrease in the number of minutes asleep (−13.48%; −57.91; 95% CI, 16.33 to 99.49) among older adults. Finally, cardiovascular and pre-frailty risk scores were calculated based on biomarkers and evaluated from the clinical perspective.

Sleep Disturbance is Associated With Higher Plasma Aβ Levels in Cognitively Normal Adults-A Population-Based Cross-Sectional Study

Objective: Growing evidence suggests that sleep disturbance is a risk factor for Alzheimer's disease (AD). Amyloid-β (Aβ) deposition in the brain is a main pathophysiology of AD. Considering that peripheral Aβ level is associated with brain Aβ deposition, the present study investigated the relationship between sleep disturbance and plasma Aβ levels.

Methods: This is a population-based cross-sectional study. A total of 1,459 participants from a village in the suburbs of Xi'an, China, were enrolled from January 3, 2017 to March 26, 2017. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and a PSQI score of <5 points was considered as good sleep quality and a PSQI score of >10 points as poor sleep quality. Cognitive function was assessed with the Mini-Mental State Examination (MMSE). Fasting venous blood was taken in the morning, and the plasma Aβ levels were measured using ELISA. The relationships between plasma Aβ levels and sleep quality were analyzed using multiple linear regression.

Results: Among the participants, 231 had poor sleep quality (15.83%). The log-transformed Aβ₄₀ level had significant differences among the different sleep groups (F = 3.216, p = 0.040). The log-transformed Aβ₄₀ level was higher in the poor sleep quality group than that in the general sleep quality group [87.17 (73.42, 107.34) vs. 89.69 (74.81, 125.79) pg/ml, p = 0.016]. In bivariate analysis, sleep quality was negatively associated with the log-transformed plasma Aβ₄₀ level (β = −0.025, p = 0.011).

Conclusion: In the community population, poorer sleep quality is associated with a higher plasma Aβ₄₀ level. This indicated that sleep disturbance might also involve in dysfunction of peripheral Aβ clearance.

Health-related quality of life among Chinese primary care patients with different lower urinary tract symptoms: a latent class analysis

PURPOSE

No previous study has used a data-driven approach to explore symptom subclasses among patients with lower urinary tract symptoms (LUTS). The objectives of this study were to use latent class analysis (LCA) to identify distinct classes of LUTS among primary care patients and to assess the class differences in health-related quality of life (HRQOL).

METHODS

In this cross-sectional study, 500 patients were randomly recruited, and 18 symptoms according to the International Continence Society 2002 criteria were assessed. Classes were identified by LCA. Patient HRQOL was measured using the 12-item Short Form Health Survey (version 2), the modified Incontinence Impact Questionnaire-Short Form and the HRQOL item from the International Prostate Symptom Score.

RESULTS

Six distinct LUTS classes were identified: "asymptomatic" (26.0%), "mild symptoms" (22.6%), "moderate multiple symptoms" (17.0%), "urgency symptoms" (13.8%), "urinary incontinence" (12.0%) and "severe multiple symptoms" (8.6%). Multinomial regression analysis found differences in the gender distribution and prevalence of heart diseases across classes, and multiple linear regression found that patients with "severe multiple symptoms" and "urinary incontinence" had the poorest HRQOL.

CONCLUSION

Almost three quarters of the primary care patients in this study were suffering from varying degrees of LUTS. The poor HRQOL in "severe multiple symptoms" and "urinary incontinence" implies that patients in these classes require additional attention and treatments.

The Sleep Side of Aging and Alzheimer's Disease

As we age, sleep patterns undergo significant modifications in micro and macrostructure, worsening cognition and quality of life. These are associated with remarkable brain changes, like deterioration in synaptic plasticity, gray and white matter, and significant modifications in hormone levels. Sleep alterations are also a core component of mild cognitive impairment (MCI) and Alzheimer's Disease (AD). AD night time is characterized by a gradual decrease in slow-wave activity and a substantial reduction of REM sleep. Sleep abnormalities can accelerate AD pathophysiology, promoting the accumulation of amyloid-β (Aβ) and phosphorylated tau. Thus, interventions that target sleep disturbances in elderly people and MCI patients have been suggested as a possible strategy to prevent or decelerate conversion to dementia. Although cognitive-behavioral therapy and pharmacological medications are still first-line treatments, despite being scarcely effective, new interventions have been proposed, such as sensory stimulation and Noninvasive Brain Stimulation (NiBS). The present review outlines the current state of the art of the relationship between sleep modifications in healthy aging and the neurobiological mechanisms underlying age-related changes. Furthermore, we provide a critical analysis showing how sleep abnormalities influence the prognosis of AD pathology by intensifying Aβ and tau protein accumulation. We discuss potential therapeutic strategies to target sleep disruptions and conclude that there is an urgent need for testing new therapeutic sleep interventions.

The Development of a Rapid Classification Scale for Sleep Quality in Community-Dwelling Older Adults - The Yilan Study, Taiwan

OBJECTIVE

Poor sleep quality is prevailing, deleterious, but heterogeneous in older adults. This study aimed to develop a simplified instrument to screen and classify poor sleep quality in community-dwelling older adults, by which stepped care with needs-based interventions could be implemented.

METHODS

Cohorts of adults aged 65 years and older were used to develop the Rapid Classification Scale for Sleep Quality (RCSSQ). Poor sleep quality was defined with the Pittsburgh Sleep Quality Index (PSQI). Established subgroups of poor sleep quality in the development dataset (n = 2622) were used as the criterion standard. Two independent validation datasets (n = 964 and 193, respectively) were used to examine the external validity. Questions in the PSQI were examined by the stepwise multinomial logistic regressions to determine the optimal numbers of items in the RCSSQ. On the premise of item parsimony and instrument validity, the optimal combination of reduced items was determined.

RESULTS

In the development dataset, the 4-item RCSSQ (RCSSQ-4) was the optimal predictive model. In terms of internal validity, the accuracy rates to identify PSQI-defined poor sleep quality and its subgroups in the developmental dataset by the RCSSQ-4 were 89.0% and 79.9%, respectively. Meanwhile, the RCSSQ-4 also had good external validity in the validation datasets to detect PSQI-defined poor sleep quality (accuracy rates: 89.1-90.7%). Furthermore, the profiles of PSQI component scores and comorbid conditions for the predicted subgroups in the validation dataset were comparable with the criterion standard.

CONCLUSION

The RCSSQ-4 is a valid instrument for screening and subgrouping poor sleep quality in community-dwelling older adults. The RCSSQ-4 may help guide tailored interventions under the context of stepped care in the community.

Anxiety and depressive symptoms among COVID-19 patients in Jianghan Fangcang Shelter Hospital in Wuhan, China

Fangcang shelter hospitals were established in China during the coronavirus disease 2019 (COVID-19) pandemic as a countermeasure to stop the spread of the disease. To our knowledge, no research has been conducted on mental health problems among patients in Fangcang shelter hospitals. This study aimed to determine the prevalence and major influencing factors of anxiety and depressive symptoms among COVID-19 patients admitted to Fangcang shelter hospitals. From February 23, 2020, to February 26, 2020, we obtained sociodemographic and clinical characteristics information of COVID-19 patients in Jianghan Fangcang Shelter Hospital (Wuhan, China) and assessed their mental health status and sleep quality. Data were obtained with an online questionnaire. The questionnaire consisted of a set of items on demographic characteristics, a set of items on clinical characteristics, the Self-Rating Anxiety Scale, Self-Rating Depression Scale, and Pittsburgh Sleep Quality Index. Three hundred seven COVID-19 patients who were admitted to Jianghan Fangcang Shelter Hospital participated in this study. The prevalence of anxiety and depressive symptoms were 18.6% and 13.4%, respectively. Poor sleep quality and having ≥ two current physical symptoms were independent risk factors for anxiety symptoms. Female sex, having a family member with confirmed COVID-19, and having ≥ two current physical symptoms were independent risk factors for depressive symptoms. Anxiety and depressive symptoms were found to be common among COVID-19 patients in Fangcang Shelter Hospital, with some patients being at high risk.