Sleep and emotional disturbances are common among women with gestational diabetes mellitus (GDM) and are associated with poor glycemic control and adverse pregnancy outcomes (APOs). Mind-body approaches have been proposed as supportive strategies to improve psychological and metabolic health; however, longitudinal evidence during pregnancy remains limited. In this prospective controlled cohort study, 200 women with GDM were enrolled at 24 to 28 gestational weeks. Participants were classified into a mind-body integrative care group (routine prenatal care supplemented with structured mindfulness, relaxation, and sleep management components) or a routine-care group (routine prenatal care alone), according to the care pathway received under routine clinical practice. Outcomes were assessed at baseline, after 8 weeks, and at delivery. Sleep quality (Pittsburgh Sleep Quality Index), anxiety (7-item Generalized Anxiety Disorder Scale), depression (9-item Patient Health Questionnaire), and metabolic indicators (glycated hemoglobin [HbA1c], homeostasis model assessment of insulin resistance, high-sensitivity C-reactive protein) were measured. Multivariable logistic regression, Cox proportional hazards models, and counterfactual-based parallel mediation analyses were applied. After 8 weeks, exposure to mind-body integrative care was associated with lower odds of sleep disturbance (odds ratio = 0.61, 95% confidence interval = 0.38-0.98, P = .041) and more favorable metabolic profiles, including lower HbA1c, homeostasis model assessment of insulin resistance, and high-sensitivity C-reactive protein levels. The overall incidence of APOs was lower in the mind-body integrative care group than in the routine-care group (28.0% vs 42.0%, P = .038), corresponding to a directionally consistent reduction in APO risk in Cox analysis (hazard ratio ≈ 0.70). Mediation analyses suggested that changes in sleep quality (ΔPittsburgh Sleep Quality Index) and glycemic control (ΔHbA1c) represented the primary indirect pathways, jointly accounting for approximately 67% of the observed association. Exposure to mind-body integrative care was associated with better sleep quality, more favorable metabolic profiles, and a lower incidence of APOs among women with GDM. The observed psychological-metabolic mediation pattern supports the potential relevance of integrative, nonpharmacological approaches in prenatal care while underscoring the need for further randomized studies to establish causality.

Rethinking prevention through a gender lens Alyson J. McGregor, MD, MA shares how sex-specific data are redefining Lifestyle Medicine – and why University of South Carolina School of Medicine Greenville is building the model. When researchers began disaggregating cardiovascular outcomes by sex, one finding stood out: women who adopted lifestyle-based interventions – structured changes in nutrition, physical activity, sleep, and stress management – experienced an even greater reduction in cardiovascular risk than men following the same protocols. The female body, it appears, may be particularly responsive to lifestyle modification. Yet for decades, the evidence behind those interventions was built almost exclusively on male subjects.

Sleep and schizophrenia spectrum.

Purpose South Asian immigrant women face elevated cardiometabolic risk at lower body mass indices and higher rates of mood and anxiety disorders compared to White women. This study aims to evaluate the feasibility and effects of a culturally adapted lifestyle intervention combining Ashtanga-based yoga with mindfulness on mental, functional and cardiometabolic outcomes in South Asian immigrant women aged 40 years and older. Design/methodology/approach This single-arm, pre-post 12-week study enrolled 30 adult females from the South Asian community to participate in weekly sessions (mindfulness and yoga) plus home practice. Outcomes included self-reported questionnaires, objective assessments and feasibility measures. Findings On average, participants were 53 ± 6 years, body mass index 28.9 ± 4.2 kg/m², waist-to-hip ratio 0.81 ± 0.06, lived in the USA 28.9 ± 8.9 years and attended 8.1 ± 2.5 of 12 sessions. In all, 28 (93%) participants completed the study and were included in final analysis. Significant improvements were observed in questionnaires [FFMQ (p < 0.001), PHQ-8 (p < 0.001), PSQI (p = 0.02), Rosenberg Self-Esteem Scale (p = 0.005) and Godin Leisure-Time Physical Activity (p = 0.007)] and objective measures [MoCA (p = 0.01), Short Physical Performance Battery (p = 0.01) and handgrip strength (p < 0.001), systolic blood pressure (p = 0.015)]. Other laboratory measures were not significant at 12 weeks. Research limitations/implications Limitations include single-arm design, modest sample size and 12-week duration, hindering detectable changes in lipids/glucose markers. Interruptions from Spring Break and Ramadan also influenced attendance and activity. Future research includes an RCT with ≥ 6–12 months follow-up to test clinical endpoints and mechanistic markers stratified by baseline risk. Practical implications Community-delivered, culturally tailored yoga and mindfulness programs are feasible and acceptable in South Asian immigrant women and may serve as adjunctive strategies for mental health, sleep and vascular risk management. Originality/value This paper fulfills a need to study combined, culturally tailored lifestyle interventions in a high-risk population.

Background: Sleep disturbances are increasingly recognized as a major public health concern due to their negative impact on physical and psychological health. Non-pharmacological interventions have gained attention as sustainable alternatives to medication-based sleep management. Objective: This study aimed to examine the effect of neuromuscular relaxation (NMR) on sleep quality by evaluating changes in individual components of the Pittsburgh Sleep Quality Index (PSQI). The study also explored the role of adherence and selected demographic factors in shaping sleep-related outcomes over time. Methods: A prospective interventional study was conducted among adults with self-reported poor sleep quality. Participants engaged in NMR sessions three times per week for a duration of three months. Sleep quality was assessed using the PSQI at baseline and after completion of the intervention, with monthly follow-up assessments. Statistical analyses were performed to evaluate pre- and post-intervention changes, adherence effects, and demographic influences. Results: Significant improvements were observed across all PSQI components following the intervention. Greater adherence to NMR sessions was associated with more pronounced improvements in sleep latency and sleep duration. Progressive enhancement in sleep quality was noted over the three-month period. Certain demographic characteristics, such as age and body mass index, showed modest associations with the magnitude of improvement. Conclusion: Neuromuscular relaxation appear to be an effective non-pharmacological approach for improving multiple dimensions of sleep quality. Regular participation enhances outcomes, supporting the potential role of NMR as a safe and accessible intervention for individuals experiencing poor sleep.

Factors influencing quality of life over five years post-diagnosis in breast cancer survivors: Results from the E3N-Generations cohort.

Effects of Progressive Muscle Relaxation on Pain and Sleep: Randomized Controlled Study.

WCN26-381 Patients’ experiences and perspectives on sleep assessment and management in chronic kidney disease: A multicentre mixed-methods study

Impact of pediatric epilepsy on sleep architecture: A systematic review and meta-analysis.

The characteristics of depression and sleep status among elite Chinese badminton athletes.

Effectiveness of an interactive E-book versus traditional education for foundational cancer sleep management training: A cluster randomized controlled trial.

To explore the effect of repetitive transcranial magnetic stimulation (rTMS) on influenza-induced sleep disorders, verify its adjuvant value, and reveal the "influenza-immune inflammation-abnormal brain function-sleep disorder" pathway, a retrospective cohort study enrolled 55 adults (18-40 years, no comorbidities) with acute influenza (2023-2025, First Affiliated Hospital of Air Force Medical University). They were divided into positive control group (PC, n = 20, conventional treatment) and rTMS group (n = 16, conventional + rTMS: 10 Hz, 1x/day, 20-30 mins, 3000 pulses, 100% motor threshold, 3 days; split into pre-treatment [BT-rTMS] and post-treatment [AT-rTMS] subgroups). Twenty healthy people served as negative controls group (NC). Assessments included polysomnography (PSG), Sleep Disorder-Visual Analog Scale (SD-VAS), functional near-infrared spectroscopy (fNIRS) for frontal oxygenated hemoglobin, and ELISA for 9 blood indicators. Two-sample Mendelian randomization (TSMR), ROC models, and t-tests (P < 0.05) were used. TSMR showed influenza correlated with insomnia (IVW:P = 0.047, 95% OR = 1.001-1.134) and 27 brain structural changes (frontal most affected, n = 10). Serum IgM (IVW:P = 0.048, 95% OR = 1.001-1.193) and neutrophils (IVW:P = 0.003, 95% OR = 1.018-1.089) mediated sleep disorders, linking to SD-VAS and frontal gray matter. Left inferior frontal gyrus and right orbital gyrus were key. BT-rTMS had abnormal sleep (duration/efficiency/stages) vs NC, with higher right orbitofrontal cortex (R-OFC) and left ventrolateral prefrontal cortex (L-VLPFC) oxygenated hemoglobin (P < 0.05). AT-rTMS improved sleep vs PC, with lower R-OFC/L-VLPFC oxygenated hemoglobin (P < 0.05). A 7-indicator ROC model had AUC = 0.8571. rTMS improves influenza-related sleep disorders short-term by inhibiting frontal overactivation (R-OFC, L-VLPFC) and regulating immunity (IgM,neutrophils), offering a safe, rapid new approach for acute influenza sleep management.

In the twenty-first century, the increasing prevalence of chronic diseases and structural barriers in accessing healthcare services have necessitated a more active role for individuals in managing their own health. This transformation has shifted healthcare from a hospital-centered model toward daily life practices, emphasizing the concept of self-care. Although mobile health (mHealth) technologies offer significant potential in this context, the fragmentation of health data across multiple platforms and privacy concerns associated with cloud-based solutions hinder widespread user adoption. This study presents the design and development of a Mobile Health Tracking System that prioritizes user data privacy through an offline-first architecture and local data storage. The application was developed using the Flutter framework and the Dart programming language to support both Android and iOS platforms. Data persistence is ensured through an on-device SQLite database, preventing the sharing of sensitive health information with third-party servers by default. The system includes essential modules such as Body Mass Index (BMI) calculation, customizable user profiles, medication reminder mechanisms, blood pressure monitoring, heart rate tracking, sleep data management, and interactive health visualizations implemented using the fl_chart library. System performance was evaluated based on user interface responsiveness, database query execution times, and notification service stability. The results indicate that local database–based mHealth applications provide significant advantages in terms of data privacy, offline accessibility, and user trust. Furthermore, the findings demonstrate that Flutter’s single-codebase architecture offers a cost-effective and high-performance solution for developing cross-platform healthcare applications. Additionally, the application supports the generation of personalized PDF health reports from user data. To mitigate the risk of data loss during device changes, an optional Firebase-based cloud synchronization feature has been integrated, allowing users to back up and restore their data at their discretion.

Background and Objectives: Adults diagnosed with type 2 diabetes mellitus (T2DM) frequently exhibit diminished sleep quality, which is affected by their glycemic control. Both poor sleep and inadequate glycemic management increase the risk of complications worldwide. However, the relationship between sleep quality, daytime dysfunction, and glycemic control in adults with T2DM is not well understood. To address this gap, this study aimed to examine the association between overall sleep quality, including daytime dysfunction, and glycemic control in adults with T2DM. Materials and Methods: A hospital-based cross-sectional study included 200 T2DM patients (103 females, 97 males) from January 2019 to January 2020. The Pittsburgh Sleep Quality Index (PSQI) was administered to each participant to assess sleep quality, including daytime dysfunction. Glycemic control was assessed by measuring hemoglobin A1c (HbA1c) and fasting blood glucose (FBG) levels. The associations among sleep quality, daytime dysfunction, and glycemic metrics were examined utilizing both conventional statistical methods and Bayesian analytical approaches. Results: A total of 32% of patients had poor sleep quality (PSQI > 5), and 43.5% reported daytime dysfunction. Higher HbA1c and fasting blood glucose were each correlated with longer sleep-onset latency and greater daytime dysfunction. In multivariable analyses, higher HbA1c and longer sleep-onset latency were independently associated with poor sleep quality (generalized linear model, R2 = 0.602), whereas higher fasting blood glucose and longer sleep-onset latency were associated with greater daytime dysfunction severity (R2 = 0.378). Conclusions: Sleep quality and delay in falling asleep are interdependent with impaired glycemic control and daytime dysfunction in T2DM. Future randomized trials targeting sleep-onset latency are warranted to determine causal effects on glycemic outcomes.

Background: Obstructive sleep apnea is a common and sometimes fatal condition characterized by frequent pauses in breathing during sleep. It is estimated to affect between 9% and 38% of all adults. It affects between 5% and 10% of middle-aged adults and up to 20% or 30% of older people (65 years or older), and prevalence increases with age and obesity. Geographic differences exist because different countries and ethnic groups may experience different lifestyles, nutrition and genetic predisposition. According to estimates, up to 80% of people with moderate to severe apnea may not receive treatment. These figures highlight the critical need for accurate, real-time, and easy-to-use diagnostic tools that can be applied outside clinical settings to track sleep quality and identify apnea episodes early, allowing for rapid treatment and intervention. Approach: This study offers a novel option by using artificial intelligence (AI) for the evaluation of data from noninvasive sleep monitoring devices that record heart rate variability, brain wave activity, and breathing patterns according to the protocol followed by BTI company who leads the project. The AI system is able to detect apnea episodes, variations in typical breathing patterns, and assesses overall sleep quality. This method provides patients, dentists, and other healthcare professionals with useful information and allows for a more complete understanding of sleep quality which is really important for the quality of life of the whole society but, in particular, for elderly people. This system is being developed in cooperation with AI researchers, sleep specialists, and dentists of BTI company. As they are often the first medical professionals to notice sleep apnea symptoms during dental exams, dentists are essential to this effort.This system is training AI models using machine learning classifiers like Random Forest and SVM, deep learning architectures such as LSTMs and CNNs, Transformer models like BERT for sequential data, and exploring quantum machine learning techniques with QML frameworks like Pennylane and TensorFlow Quantum, all on time-series data from 6,317 patients. Results: By monitoring their sleep habits, users have a better understanding of their sleep health, which they share with dentists and other medical professionals for ongoing care. Additionally, the system’s alert feature is intended to facilitate prompt interventions by quickly informing users when severe cases of apnea occur. This system takes a proactive approach to sleep health management by offering real-time data and prediction capabilities, allowing users to seek treatment when necessary or make appropriate lifestyle changes. Implications: Integrating AI with sleep monitoring offers the potential to transform sleep health management with an accessible and effective tool for sleep apnea detection and quality assessment. Patients, people and, especially older adults, have an active role in managing their sleep health and it enables healthcare providers to make more informed decisions about treatment options.

Epilepsy is a neurological disorder characterized by recurrent seizures, affecting millions of people worldwide. While pharmacological treatments remain the cornerstone of epilepsy management, lifestyle factors play a significant role in modulating seizure frequency and quality of life for individuals with epilepsy. This expert review synthesizes key findings from seminal studies to explore the impact of various lifestyle factors, including diet, sleep, physical activity, and stress management, on epilepsy management. We also discuss potential mechanisms underlying these effects and highlight limitations in current research.

DiGeorge for the Otolaryngologist: A State-of-the-Art Review.

People living with dementia (PLWD) and mild cognitive impairment (MCI), and their family carers, often experience sleep disturbance which can impair daily living and care. There are limited options for effective long-term pharmacological management of sleep disturbance, yet recent advances in non-pharmacological approaches offer promising alternatives. TIMES is a novel, complex intervention, which aims to improve wellbeing for PLWD/MCI and their carers in primary care, by developing whole-person, tailored care plans that optimise management of sleep disturbance in context. Two-arm cluster-randomised (1:1), single-blinded, feasibility trial in 10 general practice sites in England, recruiting 64 patient-carer dyad participants (32 intervention + 32 treatment as usual). Co-primary objectives are to assess the feasibility and acceptability of conducting a subsequent definitive cluster-randomised controlled trial (cRCT) of the TIMES intervention. Secondary objectives include assessing the ability to collect data to address putative primary and secondary outcomes of a definitive cRCT. We will collect participant demographics at screening, and the following outcome measures at baseline, 9 and 15week follow-ups: Sleep Disorders Inventory (SDI); Epworth Sleepiness Scale (ESS); Activities of Daily Living assessed with the Disability Assessment for Dementia (ADL DAD); Dementia Quality of Life Measure (DEMQOL); EQ-5D 5 level (EQ-5D-5L); ICEpop Capability measure for older people aged ≥ 65 (ICECAP-O); Neuropsychiatric Inventory Questionnaire (NPI-Q); Client Service Receipt Inventory (CSRI); Telephone Montreal Cognitive Assessment (T-MoCA); patient medical records review; patient serious adverse events (SAEs). We will conduct Process Evaluation interviews and Discrete Choice Experiments to inform refinement of the intervention content and delivery. Our findings will inform the refinement and delivery of a subsequent definitive cRCT that tests the clinical and cost-effectiveness of the TIMES intervention compared with usual care. This study received approval from the Health Research Authority (HRA) and London-Harrow Research Ethics Committee (Reference: 24/LO/0123), and is sponsored by the University of Exeter (Reference: 2021-22-38). ISRCTN, ISRCTN54051676, registered 20 March 2024, https://www.isrctn.com/ISRCTN54051676 .

Rheumatoid arthritis (RA) is a prevalent chronic autoimmune disease associated with substantial disability as well as socioeconomic burden. Emerging evidence suggests that sleep disturbances may increase RA risk, yet the roles of sleep quality, sleep duration, as well as their long-term patterns remain unclear. Depression—a key psychoneuroimmunological factor—may mediate this association. The research aimed to explore the relationships of sleep quality (SQ), sleep duration (SD) and incident RA, as well as to explore the mediating role of depressive symptoms as well as the effects of long-term sleep trajectories. Data were obtained from the English Longitudinal Study of Ageing (ELSA), including adults free of RA at baseline. Cox proportional hazards models were employed to estimate the connection of SQ and SD with incident RA, adjusting for demographic, lifestyle, and health-related factors. Mediation analysis quantified the indirect effects of depressive symptoms. Group-based multi-trajectory modeling (GBMTM) was further applied to identify joint trajectories of SQ and SD and assess their connection with RA risk. During follow-up, 607 participants developed RA. Compared with those reporting good SQ, individuals with moderate (HR = 1.23, 95% CI: 1.02–1.48) or poor (HR = 1.50, 95% CI: 1.20–1.87) SQ had a significantly higher risk of RA. A linear connection was observed between shorter SD and increased RA risk, with each 1-hour reduction in sleep related with approximately 7% higher risk (HR = 1.07, 95% CI: 1.01–1.17). Depression partially mediated the associations between SQ, SD, and RA risk, accounting for about 40% and 44% of the total effects, respectively. GBMTM identified three distinct sleep trajectory groups, with the “persistently poor-quality/short-sleep” trajectory showing the highest RA risk (OR = 1.70, 95% CI: 1.11–2.56). Poor SQ and shorter SD are independently related with an elevated risk of RA among middle-aged and older adults, partly mediated by depression. Persistent adverse sleep patterns confer cumulative risk, highlighting the potential of sleep and mood management as modifiable targets for primary prevention of RA.

Despite the authoritative framework for hormone therapy provided by the 2025 European Society of Endocrinology Clinical Practice Guidelines for the Assessment and Management of Menopause and Perimenopause, there remains a notable absence of diagnostic and therapeutic protocols for sleep disorders. Given that sleep disorders affect 50%-55% of the perimenopausal population, they constitute an independent risk factor for severe adverse health outcomes. Leveraging landmark data from the 2024 Study of Women's Health Across the Nation (SWAN), persistent insomnia symptoms are associated with a 71% increased incidence of cardiovascular events, independent of vasomotor symptoms. Furthermore, the unique female phenotype of obstructive sleep apnea frequently leads to misdiagnosis in endocrine clinical practice. The "tipping point" of late perimenopause presents a critical window for intervention. A more comprehensive approach-combining mandatory screening with tiered sleep interventions-can enhance daytime functioning, prevent misdiagnosis, and reduce long-term cardiovascular disease incidence. Future guidelines should explicitly address this intersection to support more personalized care for middle-aged women.