Nature and Science of Sleep最新文献

Purpose: Many shift nurses experience poor sleep quality, and the effect on nurses' cognitive function remains unclear. The study aims to investigate sleep status and explore its association with cognitive function.

Methods: This descriptive cross-sectional study was conducted in a tertiary care hospital in Fujian, China between March and September 2022. By convenience sampling method, 588 shift nurses participated in this study. The Pittsburgh Sleep Quality Index (PSQI) and Bergen Shift Work Sleep Questionnaire (BSWSQ) were used to assess sleep quality, while the Chinese version of Ascertain Dementia-8 (AD-8) was used to evaluate cognitive function. A PSQI score ≤7 is classified as good sleep quality, and a score >7 indicates poor sleep quality. An AD-8 score≥ 2 is considered indicative of memory impairment. Multivariate logistic regression analysis was conducted to explore the association between sleep status and memory impairment.

Results: A total of 310 (52.6%) participants presented poor sleep quality. Among them, 52.2% of participants had day shift-related sleep problems, 45.9% had evening shift-related sleep problems, 61.9% had night shift-related sleep problems, and 15.0% reported rest-day/vacation-related sleep problems. The prevalence of poor sleep quality and each shift-related sleep problem in the memory impairment group were higher than in the normal memory group (P<0.05). Multivariate logistic regression analysis indicated that poor sleep quality (OR=2.073, 95% CI: 1.398~3.072), evening shift-related sleep problems (OR=1.707, 95% CI: 1.028~2.835), night shift-related sleep problems (OR=1.859, 95% CI:1.104~3.129), and rest-day/vacation-related sleep problems (OR=2.069, 95% CI:1.170~3.659) was significantly associated with memory impairment.

Conclusion: This study highlights the prevalence of poor sleep quality among clinical nurses and identifies poor sleep quality and shift-related sleep problems (excluding day shift) as risk factors for memory impairment. Nurse managers should prioritize sleep quality and focus on cognitive function to enhance nurses' occupational health.

Objective: To investigate the effects of sleep quality, sleep deprivation, and napping on facial emotion recognition (FER) accuracy and speed.

Methods: This research included a cross-sectional study (102 qualified participants) and a randomized controlled study (26 in the napping group and 24 in the control group). The stimuli for the FER task were obtained from the Chinese Facial Affective Picture System (CFAPS). Four facial expressions (fearful, disgusted, sad, and angry) were used. The Pittsburgh Sleep Quality Index (PSQI), Self-Rating Anxiety Scale, and Self-Rating Depression Scale were used to measure participants' sleep quality and psychological conditions. In Study 1, FER ability was compared between good and poor sleepers. In Study 2, all participants were sleep-deprived for one night, and completed the FER task before and after sleep deprivation. After different interventions (ie, napping for one hour, or walking around for ten minutes), the participants completed the third FER task.

Results: Study 1: Poor sleepers were able to recognize sad expressions more accurately compared with good sleepers. Study 2: 30-h sleep deprivation had no significant effect on the accuracy (ACC). Napping after sleep deprivation improved the FER ACC of upper-face expressions and marginally significantly improved the FER ACC of disgusted expressions.

Conclusion: Better sleep quality was linked to lower FER accuracy, particularly in recognizing sad expressions, while no significant differences in recognition speed were observed. Additionally, 30 hours of sleep deprivation did not affect FER accuracy, but napping after sleep deprivation improved accuracy for upper-face and marginally for disgusted expressions.

Purpose: Cardiovascular disorders are the leading cause of mortality worldwide with obstructive sleep apnea (OSA) as the independent risk factor. Heart sounds are strong modalities to obtain clinically relevant information regarding the functioning of the heart valves and blood flow. The objective of this study was to use a small wearable device to record and investigate the changes in heart sounds during respiratory events (reduction and cessation of breathings) and their association with oxyhemoglobin desaturation (hypoxemia).

Patients and methods: Sleep assessment and tracheal respiratory and heart sounds were recorded simultaneously from 58 individuals who were suspected of having OSA. Sleep assessment was performed using in-laboratory polysomnography. Tracheal respiratory and heart sounds were recorded over the suprasternal notch using a small device with embedded microphone and accelerometer called the Patch. Heart sounds were extracted from bandpass filtered tracheal sounds using smoothed Hilbert envelope on decomposed signal. For each individual, data from 20 obstructive events during Non-Rapid Eye Movement stage-2 of sleep were randomly selected for analysis.

Results: A significant increase in heart sounds' intensities from before to after the termination of respiratory events was observed. Also, there was a significant positive correlation between the magnitude of hypoxemia and the increase in heart sounds' intensities (r>0.82, p<0.001). In addition, the changes in heart sounds were significantly correlated with heart rate and blood pressure.

Conclusion: Our results indicate that heart sound analysis can be used as an alternative modality for assessing the cardiovascular burden of sleep apnea, which may indicate the risk of cardiovascular disorders.

Objective: Our research explores how leisure-time sedentary behavior (SB) correlates with stroke risk. Additionally, we utilize the isotemporal substitution model (ISM) to examine how replacing brief durations of leisure-time SB with light physical activity (LPA), moderate physical activity (MPA), vigorous physical activity (VPA), and sleep might influence the risk of stroke.

Methods: This investigation tracked 478,198 participants from the UK Biobank. Data regarding individual leisure-time SB and PA were collected through a standardized questionnaire. A Cox proportional hazards model, alongside an isotemporal substitution model (ISM), was utilized.

Results: We identified 10,003 cases of incident stroke over 12.7 years. When compared to participants who engaged in leisure-time SB for less than 4 hours per day, the hazard ratios (HRs) for stroke incidence increased with more prolonged leisure-time SB: HRs were 1.06 (95% CI: 1.01 to 1.11) for 4-6 h/d, 1.16 (95% CI: 1.10 to 1.23) for 6-8 h/d, and 1.24 (95% CI: 1.15 to 1.33) for over 8 h/d. According to the ISM analysis, substituting leisure-time SB with various forms of PA could markedly reduce stroke risk. For individuals sleeping ≤8h/d, replacing one hour of leisure-time SB with an equivalent duration of LPA, VPA, or sleep corresponded to a 3.0%, 7.0%, and 22.0% decrease in stroke risk, respectively. Meanwhile, for those already sleeping more than 8h/d, substituting one hour of leisure-time SB with an equivalent duration of LPA or VPA resulted in a notable decrease in the risk of stroke by 6.0% and 18.0%, respectively.

Conclusion: The findings demonstrate that leisure-time SB and unhealthy sleep durations are confirmed risk factors for stroke. For individuals sleeping 8 hours or less per day, and for those who sleep more than 8 hours, substituting SB with an adequate amount of sleep or engaging in VPA, respectively, emerges as an effective strategy for reducing stroke risk.

Background: Survival in patients with sleep apnoea (SA) can be reduced by variables such as age, sex, and comorbidities. However, survival data in patients with SA in Colombia remains scarce.

Methods: This is a retrospective cohort study of patients diagnosed with SA between 2005 and 2022. Five-year survival was assessed using the Kaplan-Meier method, and survival curves were stratified by age, sex, and cardiovascular disease. Risk factors associated with survival were evaluated using Hazard Ratio (HR) by adjusting for confounding variables with a Cox regression model. A minimum sample size of 1537 patients were estimated to be necessary to estimate a survival incidence rate with a 5% precision.

Results: The five-year survival rate in the general population was 94.6%, with lower survival in patients over 65 years (88.5% vs 97.9%; p < 0.001) and in patients with cardiovascular disease (89% vs 95.2%; p < 0.001) compared to the control group. In the Cox regression, age showed an HR of 1.05 (95% CI: 1.02-1.07; p < 0.001). Male sex had an HR of 2.31 (95% CI: 1.25-4.25; p = 0.007), congestive heart failure an HR of 4.00 (95% CI: 2.31-6.94; p < 0.001), chronic obstructive pulmonary disease (COPD) an HR of 1.75 (95% CI: 1.04-2.96; p = 0.035), chronic kidney disease (CKD) an HR of 2.23 (95% CI: 1.31-3.78; p = 0.003), and metastatic cancer an HR of 4.96 (95% CI: 1.95-12.60; p = 0.001).

Conclusion: The study showed a high five-year survival rate in patients with SA. The risk factors associated with decreased overall five-year survival were age, male sex, cardiovascular disease, COPD, CKD, and metastatic cancer.

Purpose: The COVID-19 pandemic resulted in a shift to working and learning from home and a concomitant rise in the use of virtual communication technology, such as videoconferencing. The current study prospectively examined the association between videoconferencing and sleep in a sample of young adults attending a university during the pandemic. The effects of videoconferencing on health and wellness outcomes and academic performance were also evaluated.

Patients and methods: Participants completed the core Consensus Sleep Diary and reported engagement in videoconferencing, the use of electronic devices, and physical activity daily for 8 consecutive days. They also completed baseline measures of sleep, communication technology use, physical activity, and mental distress, as well as released their end-of-term GPA. Results were evaluated via multilevel modeling and path analysis.

Results: Participants with a heavier videocall volume lost 17 m of sleep and suffered nearly a 1% reduction in sleep efficiency for each additional hour of videoconferencing compared to those with a lower call volume. They also tended to spend more time awake during the night, have earlier sleep midpoints, and report worse sleep, although those trends did not reach statistical significance. For everyone, including individuals with lower videocall volume, earlier sleep midpoints, lower sleep quality, somewhat shorter sleep, and higher fatigue were reported on days with a relatively high videocall load compared to days with a low videocall load. Increased academic engagement with videoconferencing predicted lower academic performance and higher psychological distress: Both relationships were mediated by sleep. Use of videoconferencing for personal reasons, however, was directly associated with a reduction in distress.

Conclusion: Videoconferencing is an important determinant of sleep and may impact health and wellness as well as academic outcomes in young adults. The effects of virtual communication on sleep and human behavior warrant further study in this and other populations.

Purpose: The prevalence of Obstructive Sleep Apnea (OSA) is high, and there are many complications. Few studies have reported the relationship between OSA and kidney stones. The purpose of this study is to explore whether people at risk of OSA will increase the risk of kidney stones.

Methods: This was a cross-sectional study, and information was collected through the National Health and Nutrition Examination Survey conducted from 2015 to 2018. Multiple logistic regression analyses were employed to calculate the odds ratios (ORs) and their 95% confidence intervals (CIs) for the link between obstructive sleep apnea and the presence of kidney stones. Additionally, to assess causality and reduce observational biases, five distinct two-sample Mendelian randomization techniques were applied.

Results: Following the adjustment for relevant confounders, findings indicated a statistically significant correlation between obstructive sleep apnea (OSA) and higher prevalence of kidney stones (OR = 1.29; 95% CI: 1.00-1.66). Additionally, using the inverse-variance weighted approach in Mendelian randomization, results suggested a genetic predisposition to OSA might be causally linked to an elevated risk of developing kidney stones (OR: 1.00221, 95% CI 1.00056-1.00387).

Conclusion: OSA promotes the formation of kidney stones, and the treatment and management of OSA can improve or mitigate the occurrence of kidney stones.

Purpose: This study investigates the prevalence, risk factors, and clinical characteristics of positional obstructive sleep apnea (POSA) among pediatric patients diagnosed with obstructive sleep apnea (OSA).

Patients and methods: A total of 1,236 children aged 0 to 17 years who underwent nocturnal polysomnography (PSG) and completed the Sleep Questionnaire were included. After excluding those with an AHI <1, neurological or muscular disorders, or insufficient sleep time in specific positions, 908 patients remained: 158 with POSA and 750 with non-positional OSA (NPOSA). Propensity score matching (PSM) was applied at a 1:2 ratio, resulting in a final sample of 153 POSA and 306 NPOSA patients. Data analyses were performed using R software (version 4.2.3).

Results: The prevalence of POSA was 12.8%. After PSM, patients with POSA had a lower overall AHI (8.66 vs 10.30), REM-AHI (14.30 vs 17.40), and NREM-AHI (7.43 vs 8.77) compared to those with NPOSA. POSA patients also had a shorter total sleep time (411 vs 427 minutes), spent less time in the supine position (168 vs 225 minutes), and more time in non-supine positions (241 vs 202 minutes) than NPOSA patients. Additionally, while the supine AHI was higher in POSA patients (15.60 vs 10.30), the non-supine AHI was lower (5.00 vs 11.00) compared to NPOSA patients. The minimum oxygen saturation was slightly higher in POSA patients (0.88 vs 0.87). All differences were statistically significant (P < 0.05). Risk factors for POSA included mild OSA, allergic rhinitis, non-allergic rhinitis, and obesity.

Conclusion: The prevalence of POSA in children is lower than in adults, and its severity is less than that of NPOSA. Compared to NPOSA patients, POSA patients had significantly higher AHI during supine sleep and lower AHI during non-supine sleep. POSA patients also spent more time in non-supine positions, suggesting that avoiding supine sleep may help reduce apnea events. These findings highlight the importance of monitoring and managing sleep posture in POSA patients.

Background: Central obesity, as measured by examination instruments, has been shown to be associated with both OSA and short sleep duration. However, objective measurement tools like CT, MRI, and DXA are expensive, cause radiation exposure, and have limited availability, especially in resource-limited settings. Thus, this study aimed to demonstrate the relevance of Body Mass Index (BMI) and Waist-to-Height Ratio (WHtR) as surrogate indicators of visceral obesity in the assessment of OSA and short sleep duration. We also intend to evaluate whether WHtR, in combination with BMI, can be a suitable surrogate marker for visceral adiposity.

Methods: We recruited 333 adults with complete polysomnographic (PSG) records retrospectively. Logistic regression helped to assess the association of BMI and WHtR as surrogates for central adiposity with OSA and short sleep duration. Moreover, ROC curve analysis was conducted to evaluate the predictive ability of BMI and WHtR.

Results: Following the relevant adjustments, logistic regression analysis results showed that the combination of WHtR and BMI acting as central obesity surrogates was significantly associated with OSA and short sleep duration (p<0.05). According to univariate regression analysis, sleep latency and wake after sleep onset were independent predictors of the risk of central obesity in patients with short sleep duration and OSA. Additionally, ROC curve analysis demonstrated that the combination of BMI and WHtR provided a better assessment of central adiposity in patients with OSA and short sleep duration, compared to each measure alone.

Conclusion: BMI and WHtR are significantly associated with OSA and short sleep duration, and might serve as a potential surrogate marker for central obesity. Sleep latency and wake after sleep onset can independently predict the risk of central obesity in patients with short sleep time and OSA. Thus, larger prospective studies are needed to verify our findings.