Association of real-time noise exposure with rest-activity circadian rhythms and sleep health: a 7-day longitudinal measure among Hong Kong nurses with night-shifts.

BackgroundStress among health care workers (HCWs) contributes to burnout, workforce attrition, and adverse patient outcomes. Although virtual reality (VR), psychoeducation, ecological momentary assessments (EMAs), and wearables have independently shown promise in stress research, no integrated digital suite has combined controlled stress induction, intervention delivery, and longitudinal real-world monitoring in HCWs.ObjectiveThis study aimed to evaluate the feasibility, engagement, and preliminary effectiveness of a multimodal Digital Health Monitoring and Intervention suite for Stress framework integrating VR simulation, psychoeducation, EMAs, and wearable biometrics. We examined (1) the impact of VR simulation and psychoeducation on stress outcomes and (2) associations between physiological and self-reported mental health outcomes.MethodsNinety-nine nurses (mean age 33.7, SD 8.9 yr, 87% female) were enrolled in 2023. We conducted a single-arm prospective cohort study (NCT05923398). Using convenience sampling, participants were recruited from social media advertisements, flyers, and email notices distributed through professional listservs. Participants completed ≥2-week baseline monitoring, a single VR session (2 runs separated by a brief psychoeducation intervention), and 12-week follow-up. In-VR stress was assessed using the Subjective Units of Distress Scale (SUDS) and 4-item Moral Injury Outcome Scale (MIOS-4), with synchronous heart rate variability. Longitudinal outcomes included weekly and biweekly EMAs alongside 70 wearable-derived features. Paired t tests, aligned rank transform ANOVA, and Pearson correlations informed study objectives, with P values adjusted for multiple comparisons. Qualitative content analysis classified emotional responses during and after VR.ResultsVR significantly increased subjective stress across checkpoints in both runs, with attenuation in Run B relative to Run A (all P<.001). No significant heart rate variability differences were observed between runs (P=.15). During VR, 92% (91/99) of participants felt stressed, 36% (36/99) reported anxiety or nervousness, and 51% (50/99)‐78% (77/99) endorsed anger, guilt, shame, and/or betrayal. Most (59/99, 60%) HCWs returned to an emotional baseline post-VR, although 12% (12/99) reported lingering distress. Immediate reliable improvements in anger, guilt, shame, and/or betrayal occurred for 50% (50/99)‐75% (74/99) of participants post intervention. Anxiety (mean −0.53, SD 2.34; P=.03) and stress (mean −3.05, SD 11.35; P=.01) decreased 2 weeks post intervention, but were not sustained at 12 weeks. Increased sleep restlessness was the only wearable feature showing significant changes (mean 2.46%, SD 5.43; Padj<.001). In-VR stress correlated with 12-week real-world stress (SUDS: r=0.57‐0.58; MIOS-4: r=0.58‐0.61; all P<.01). Data completion exceeded 90%, with 71% achieving full compliance.ConclusionsThis study moves beyond single-tool interventions to demonstrate the feasibility and preliminary effectiveness of an integrated, multimodal stress platform within a single coordinated framework. This trial demonstrates high engagement, short-term symptom responsiveness, ecological validity, and emotional safety. The framework provides a scalable model for proactive stress identification, skills training, and implementation in high-risk occupational settings. Randomized controlled trials are needed to establish sustained efficacy and optimize deployment for real-world implementation.

Sleep and schizophrenia spectrum.

Sleep disorders in the elderly and their management.

Associations of adverse childhood experiences and sleep in adulthood and older age: A nationwide cohort study.

BACKGROUND: There are few studies on the association between nighttime sleep duration and sleep quality with low back pain (LBP) in the Chinese population. This study aimed to investigate the longitudinal associations between middle-aged and older adults in China. METHODS: This study is a large-sample longitudinal cohort study and the data used in this study were from the China Health and Retirement Longitudinal Study (CHARLS) survey. Nighttime sleep duration was obtained from the self-reported of the participants and was divided into five groups of < 6h, 6 to < 7h, 7 to < 8h, 8 to < 9h, and ≥ 9h. Sleep quality was defined as days of restless sleep during the past week and was divided into four groups of < 1day, 1–2 days, 3–4 days, and 5–7 days. Multiple logistic regression models were used to analyze the relationship between nighttime sleep duration and sleep quality with LBP. Restricted cubic spline (RCS) was used to construct a dose-response relationship between nighttime sleep duration and LBP. RESULTS: A total of 11,233 participants were included in this study, and after 4 years of follow-up, the incidence of LBP was 9.51% (1068/11,233). Multiple logistic regression analyses showed that compared to participants who slept for 7–8h, sleep duration of < 6h and ≥ 9h were associated with a significant risk of LBP (Odds ratio (OR) = 1.66, 95% confidence interval (CI): 1.28–2.15; OR = 1.52, 95% CI: 1.07–2.16, respectively). And participants with 5–7 days of restless sleep were associated with a significant risk of LBP (OR = 1.64, 95% CI: 1.31–2.05). RCS analysis showed that a nighttime sleep duration of 7h had the lowest risk of LBP. Subgroup analysis revealed that participants aged under 58 years with sleep duration of < 6h were more likely to experience LBP (OR = 1.51, 95% CI: 1.08–2.12). However, when age was > 58 years, all participants were associated with a significant incidence of LBP, and those with sleep duration < 6h and > 9h had a higher potential for LBP occurrence (OR = 2.38, 95% CI: 1.59–3.59; OR = 1.94, 95% CI: 1.11–3.38). CONCLUSIONS: Short or long nighttime sleep, as well as poor sleep quality, are associated with an increased risk of incident LBP.

Oral cancer patients experience a heavy and fluctuating symptom burden during the perioperative period, which may compromise recovery and quality of life (QoL). This study aimed to characterize dynamic symptom networks to identify core symptoms and their trajectories across surgical stages. In this longitudinal study, 597 oral cancer patients were recruited from a tertiary hospital in China between September 2023 and October 2024. Symptoms were assessed using the MD Anderson Symptom Inventory for Head and Neck Cancer (MDASI-H&N) at admission (T1), postoperative day 3 (T2), day 7 (T3), and 1 month after surgery (T4). Network analysis was applied to identify core symptoms and clusters, and cross-lagged panel modeling was used to examine temporal inter-symptom relationships. A total of 527 patients were analyzed. Across the perioperative course, up to four clusters emerged; oral function-related and psychosomatic clusters consistently dominated. At T1-T2, the strongest cross-lagged effect was observed between distress and sleep disturbance (βCL = 0.13), with restless sleep showing the greatest strength (rIS = 2.38). From T2-T3, dental/gum problems predicted swallowing/chewing difficulty (βCL = 0.15), which had the highest in-strength (rIS = 0.96). QoL was most negatively associated with fatigue at T1 (r = -0.13) and with swallowing/chewing difficulty at T4 (r = -0.40). Core symptom clusters remained stable, but specific core and bridging symptoms shifted by stage. Symptom complexity peaked on postoperative day 3, identifying a critical intervention window. These findings provide evidence to guide precise, stage-specific symptom management and improve outcomes in oral cancer care.

This study aims to evaluate the associations of long-term exposure to five major air pollutants (PM2.5, PM10, NO2, SO2, and CO) with sleep duration and quality among middle-aged and older Chinese adults. This study used data from 14856 adults aged 45 and above participating in the China Health and Retirement Longitudinal Study (CHARLS). Changes in nocturnal sleep duration between baseline (2015) and follow-up (2018) were categorized into three groups: reductions ≥1 h, 1.5 h, or 2 h. The increase in the number of days with restless sleep at follow-up was defined as a deterioration in sleep quality. We used the STET model to estimate air pollution exposure and calculate the concentration differences over 1- or 2-year periods preceding each interview. We investigated the associations of exposure differences to five pollutants with sleep duration and quality through generalized linear mixed and ordinal logistic regression models. Interaction analyses were employed to identify potential effect modifiers. All 1-year exposure differences to air pollution positively correlated with reductions in sleep duration of both ≥1.5 h and ≥2 h. CO exposure demonstrated the highest risk for a ≥ 1.5 h reduction (OR = 1.451; 95% CI: 1.065-1.975) and a ≥ 2 h reduction (OR = 1.557; 95% CI: 1.135-2.135) per 1 μg/m3 increment. Higher exposure levels to PM2.5, PM10, NO2 and SO2 correlated with elevated risks of sleep quality deterioration. NO2 exposure demonstrated the highest risk, with a 22.3% higher risk per 10 μg/m3 increment (95% CI: 1.039-1.439). Pollutants affected sleep duration and quality in varying temporal patterns. Overall, 1-year exposure difference considerably impacted the sleep duration, while 2-year exposure difference significantly impacted the sleep quality. We also found that the air pollution's adverse impacts on sleep quality were especially significant for those living in urban areas. Long-term exposure to air pollution is associated with adverse sleep outcomes in middle-aged and older populations.

Global population aging elevates the importance of identifying modifiable risk factors for late-life depression. This study uniquely investigates the prospective association between cataracts and incident depressive symptoms, specifically differentiating between somatic and cognitive-affective domains. Using data from the English Longitudinal Study of Ageing (ELSA), we analyzed 4,584 participants. Cataract exposure was self-reported at wave 2, with incident depressive symptoms assessed at wave 4 using the CES-D-8 (cutoff ≥ 3). Multivariable logistic regression models adjusted sequentially for sociodemographics, health behaviors, and comorbidities were used to estimate associations, with sensitivity analyses (stratification, interaction tests) and multiple imputation for missing data. After multiple imputation, our cohort comprised 4,584 participants, of whom 581 (12.7%) developed incident depressive symptoms. In the fully adjusted model, baseline cataract was significantly associated with an increased risk of overall incident depression (OR 1.55, 95% CI 1.13-2.12; P = 0.007), which survived the Bonferroni-corrected threshold (P < 0.0167). Domain-specific analyses showed that cataract was associated with increased odds of somatic symptoms (OR 1.48, 95% CI 1.07-2.03; P = 0.018), whereas the association with cognitive-affective symptoms was not significant (OR 1.18, 95% CI 0.79-1.77; P = 0.420). Item-level analyses revealed that specific manifestations including 'could not enjoy life', 'restless sleep' and 'could not get going' reached nominal significance, though they did not survive strict multiple testing correction. Cataracts are independently associated with increased risk of incident depressive symptoms in older adults, particularly somatic manifestations. These findings highlight the importance of integrated ophthalmologic and mental healthcare pathways, suggesting that timely cataract treatment may represent a potential intervention point for mitigating depressive symptoms in aging populations.

BackgroundFew current studies explore the relationships among chemotherapy - related symptoms in breast cancer patients from different perspectives, and the link between symptoms and daily life is unclear.ObjectiveTo construct a symptom network for breast cancer patients during chemotherapy and explore symptom - symptom relationships from multiple perspectives.MethodsThe Anderson Symptom Inventory was used to collect symptom data and daily - life interference of 480 patients. R software built the symptom network, and edge - weight and centrality difference tests identified core symptom clusters.ResultsThe 480 female patients had a mean age of 52.46 years. Symptoms were common during chemotherapy, like fatigue and restless sleep. Fatigue was the core symptom in the overall network, but it varied among groups with different chemotherapy cycles and BMI. Distress had the greatest impact on daily life.ConclusionAttention should be paid to psychological and emotional symptoms, and priority symptoms for intervention should be selected based on the symptom network. Future research should develop dynamic symptom networks and centrality index trajectories using longitudinal data.Implications for practiceNurses can implement precise symptom management based on the symptom network. Meanwhile, comprehensive assessments of patients’ psychological and emotional problems should be initiated from the early stage of chemotherapy, and symptom management methods should be selected according to the severity of patients’ conditions to improve their psychological and emotional well - being.

This secondary data analysis aimed to determine the nature of the relationship between obstructive sleep apnea (OSA) risk, biological age acceleration, and nonspecific chronic low back pain (CLBP). In total, 199 adults aged 18-82 years who filled both STOPBANG and pain questionnaires subsetted for secondary analysis. Based on the STOPBANG questionnaire, 104 had a low OSA risk and 95 had an intermediate or high OSA risk. Dunedin Pace of Aging Computed from the Epigenome (DunedinPACE), Horvath's, Hannum's, PhenoAge, and GrimAge clocks were used to determine biological age and pace of biological aging. Individuals with low OSA risk reported increased DunedinPACE compared to those with intermediate/high OSA risk (p < 0.001). There was a significant correlation between the risk for OSA and biological age acceleration measured by PhenoAge as well as pace of biological aging (p < 0.05). Mediation analysis detected indirect effects of OSA risk on chronic pain outcomes through the pace of biological aging. Targeted interventions addressing OSA risk offers a promising therapeutic strategy. This could be particularly valuable for aging populations where both accelerated biological aging and chronic pain conditions are prevalent, offering a more holistic approach to improving nonspecific chronic pain outcomes through quality of sleep and restfulness.

There is little available literature comparing paediatric periodic limb movement disorder (PLMD) and paediatric obstructive sleep apnoea syndrome (OSA). This retrospective study aimed to examine the impact of PLMD, OSA and OSA with an elevated periodic limb movement index (PLMI) on sleep quality and daytime symptoms. This retrospective study examined 132 children who had been diagnosed with OSA (with or without elevated PLMI) and PLMD. All participants underwent overnight polysomnography. Patients were divided into three groups, patients with OSA with low PLMI, patients with OSA with elevated PLMI, and patients with PLMD. A comprehensive medical history was obtained for each participant, including comorbidities and sleep-related symptoms. Patients with PLMD were more likely to report prolonged sleep latency (p = 0.03). Children affected by both disorders were drowsier during the day (p = 0.04) and experienced more restless sleep (p < 0.01). There was no difference in total sleep time (p = 0.97) or sleep latency (p = 0.26) between the three groups, but patients with PLMD had lower REM% (p < 0.01), and children in the two OSA groups tended to have poorer sleep efficiency (p = 0.07). In conclusion, sleep quality worsened due to both OSA and PLMD on their own. However, sleep quality did not worsen further when OSA with elevated PLMI occurred. Although no significant differences were observed in total sleep time or sleep latency, parents of children with OSA and elevated PLMI reported worse daytime sleepiness and restless sleep.

BackgroundLate‐life depression (LLD) is a significant global public health challenge among older adults. Exploring central/influential symptoms with longitudinal study designs can enhance the efficacy of detection, early prevention, and interventions for LLD. This study aimed to identify key symptoms of LLD using a panel graphical vector autoregression (panel‐GVAR) model based on longitudinal national survey data.MethodsData from the China Health and Retirement Longitudinal Study (CHARLS) between 2013 and 2020, encompassing four waves, were utilized to construct a longitudinal depressive symptom network. Depressive symptoms were assessed using the 10‐item Center for Epidemiological Studies Depression Scale (CESD‐10). In expected influence (in‐EI) and out expected influence (out‐EI) were identified to characterize the interaction of symptoms within the temporal network, while expected influence (EI) was used to examine the interaction of symptoms in both the contemporaneous network and the between‐subjects network.ResultsA total of 1393 older adults were assessed. A persistently significant increase in the prevalence of depression was observed over time. In the temporal network, “restless sleep” (CESD7) and “could not get going” (CESD10) were the most influential symptom and most influenced symptom, respectively. In both the contemporaneous network and the between‐subjects network, “felt depressed” (CESD3) emerged as the most central symptom within the community of depressive symptoms.ConclusionsGiven the challenges associated with treating LLD and its adverse effects on daily life for older adults, timely interventions targeting identified key symptoms may help prevent and mitigate depression in this population.

INTRODUCTIONOlder Black adults face higher dementia risk, but it is unclear whether social engagement offsets the effects of depression and restless sleep.METHODSWe analyzed 1,905 Black adults aged 50+ from the 2016‐2020 Health and Retirement Study (HRS). Linear mixed‐effects models tested how depressive symptoms, restless sleep, and social engagement predicted baseline cognition and cognitive decline.RESULTSHigher depressive symptoms and restless sleep were associated with lower baseline cognition (about 0.2 and 0.5 points lower) and faster decline (β×time ≈ −0.07 and −0.05). Greater social engagement predicted higher baseline cognition (about 0.6 points higher) and slower decline (β×time ≈ 0.08). Social engagement also buffered the negative effects of depressive symptoms and restless sleep on cognitive decline but did not affect their baseline associations.DISCUSSIONSocial engagement may help older Black adults preserve cognitive health despite depression or poor sleep through accessible community, religious, and volunteer activities.HighlightsDepressive symptoms and restless sleep independently predicted poorer baseline cognition and faster cognitive decline among older Black adults, underscoring their distinct and additive roles in late‐life neurocognitive vulnerability.Higher social engagement, measured through volunteering, religious participation, and group involvement was associated with better cognitive functioning and slower decline across three Health and Retirement Study (HRS) waves, even after full adjustment for demographic, socioeconomic, and health covariates.Interaction effects showed that social engagement buffered the adverse cognitive effects of both depressive symptoms and restless sleep, indicating its role as a behavioral resilience factor in aging.Culturally embedded forms of engagement, particularly faith‐based and community‐centered participation, emerged as salient protective pathways that align with existing social practices within Black communities.Findings highlight the potential of community and faith‐based interventions to mitigate disparities in cognitive aging and to promote culturally meaningful strategies for sustaining brain health in older Black adults.

The relationship between insufficient sleep and prostate cancer incidence is unclear. Our goal was to investigate the association of sleep duration, restless sleep, and prostate cancer incidence and aggressiveness, and whether race influences any sleep-prostate cancer association. The Southern Community Cohort Study (SCCS) recruited study participants from 12 Southeastern states from 2002 to 2009. The cohort included nearly 35,000 males, predominantly African American (AA, 67%). Sleep exposures were measured via a baseline questionnaire at enrollment, which captured weekday and weekend sleep duration, weighted average sleep duration, and restless sleep. We used Cox proportional hazards models and multinomial logistic regression models to estimate associations between sleep and prostate cancer incidence and aggressiveness. During follow-up (median 10.9 years), 1345 men developed prostate cancer. Shorter sleep duration (< 6 h), in comparison to optimal duration (7-8 h), was suggestively associated with a decreased risk of prostate cancer in the overall cohort (adjusted hazard ratio (HR) = 0.83, (95% confidence interval (CI): 0.68-1.01) for sleep average; HR = 0.79, 95% CI: 0.65-0.95 for sleep weekdays; and HR = 0.81, 95% CI: 0.66-0.99 for sleep weekends), and among Black men (HR = 0.77, 95% CI: 0.62-0.97 for sleep average; HR = 0.76, 95% CI: 0.61-0.94 for sleep weekdays; and HR = 0.74, 95% CI: 0.59-0.94 for sleep weekends) when stratified by racial groups. Sleep duration and restless sleep were not associated with prostate cancer aggressiveness overall. Shorter sleep duration was suggestively associated with a decreased risk of prostate cancer, but sleep duration was not associated with aggressive prostate cancer. Stratified analysis suggests a reduction of prostate cancer risk among Non-Hispanic Black men with < 6 h of sleep, compared to those sleeping 7-8 h. This is an intriguing finding, and further research is needed to assess the impact of confounding factors on racial differences in prostate cancer development.

Impact of mean apnea-hypopnea duration on disease severity in obstructive sleep apnea: A retrospective study.

In search of "what really matters": Insights from a web-based survey on Patient-Centered Outcomes in GLUT1DS.

A preliminary analysis of large muscle group movements in adults with attention deficit hyperactivity disorder.

Accelerometers allow objective measures of dimensions (rest-activity rhythm (RAR), daytime activity, sleep, and chronotype) of the bio-behavioural manifestation of circadian rhythm (CR) using multiple metrics in large-scale studies. These dimensions are rarely examined together due to methodological challenges of using correlated data. To address this challenge, we propose a two-step approach consisting of data reduction of CR metrics using principal component analyses, followed by k-means clustering to identify groups of individuals with a similar profile using data from the Whitehall II (N = 3,991, mean age=69.4years) and UK Biobank (N = 54,995, mean age=67.5years) cohort studies. Our analyses identified nine CR clusters: two presented extreme (most robust/poorest) RAR and (highest/lowest) daytime activity, two robust RAR with opposite sleep profiles (longer and efficient/shorter and fragmented), one high-intensity physical activity, and four poor RAR (one characterised by late chronotype, two by low activity but opposite sleep profiles, and one by restless (agitated) sleep). The participants in these nine clusters differed on sociodemographic, behavioural and health-related factors. Findings were similar in these two independent cohort studies, highlighting the validity of our approach. Most previous studies have used only the RAR dimension of circadian rhythm, and here we show that this might be an oversimplification as demonstrated by nine clusters characterised by combinations of RAR, daytime activity, sleep, and chronotype. Our innovative approach demonstrates feasibility of using all dimensions to study the impact of circadian rhythm dysregulation on health.

BackgroundAs the leading cause of injury and injury-related death for older adults in the United States, falls can be consequential for function and mortality but are preventable. Sleep may be a modifiable risk factor for falls.MethodsData from 1795 female participants of the Study of Women’s Health Across the Nation (SWAN) were analyzed to examine whether frequent insomnia symptoms and shorter sleep duration are associated with an increased risk of falls or fall burden. At visit 12, assessed insomnia symptoms included frequency of restless sleep, trouble falling asleep, and waking early. Sleep duration was self-reported hours of sleep, dichotomized as fewer than <6 h/night and ≥6 h/night. At visit 15, participants reported the falls in the year prior. Log-binomial and multinomial logistic regression models were adjusted for demographic, health, and socioeconomic factors.ResultsWomen who reported frequent (5+ times/week) trouble falling asleep and frequent waking at baseline had a 30% increased risk (aRR = 1.30, 95% CI, 1.04-1.62) and 24% increased risk (aRR = 1.24, 95% CI, 1.03-1.49), respectively, of having fallen in the year prior at follow-up. Frequent trouble falling asleep and short sleep duration (<6 h) were both associated with higher odds of falling 3 or more times vs once or never prior to follow-up (aOR = 2.42, 95% CI, 1.26-4.63; aOR = 1.77, 95% CI, 1.08-2.93), respectively.ConclusionsMultiple indicators of poor sleep, including trouble falling asleep, frequent waking, and short sleep duration, were associated with an increased risk of falling and odds of higher fall burden in older adult women. Promoting adequate, high-quality sleep may be an essential component in fall prevention.