Sleep disturbances—including insomnia, obstructive sleep apnea, and circadian rhythm disruption—are increasingly recognized as important yet understudied contributors to Type 2 Diabetes Mellitus (T2DM). Prior reviews typically focus on single disorders or mechanisms, limiting understanding of how different scientific traditions conceptualize the sleep–T2DM relationship. This narrative review followed RAMESES publication standards to synthesize how four research disciplines—endocrinology, sleep medicine, behavioral science, and chronobiology—have investigated sleep disturbances in T2DM. Searches were conducted in PubMed, Scopus, Web of Science, ProQuest, and EBSCO (final search: 17 January 2025). Of 2,074 records identified, 62 English-language documents met inclusion criteria. Studies were appraised using tradition-specific criteria, and findings were integrated through chronological storyline development and cross-tradition synthesis. Across traditions, insufficient, fragmented, or mistimed sleep was consistently linked to insulin resistance, impaired glucose tolerance, appetite dysregulation, and adverse body composition. Endocrinology emphasized hormonal, inflammatory, and oxidative pathways; sleep medicine focused on obstructive sleep apnea (OSA) and insomnia, with mixed evidence for continuous positive airway pressure (CPAP) effects on HbA1c. Behavioral research highlighted the influence of disturbed sleep on appetite, self-regulation, and treatment adherence. Chronobiology demonstrated the metabolic consequences of circadian misalignment and variability in melatonin signaling. Although key mechanistic themes converged, the majority of studies were observational or short-term experimental, limiting causal inference; instead, each tradition emphasized distinct explanatory frameworks and variables of interest in linking sleep with metabolic outcomes. Sleep disturbances appear to be modifiable components of a broader metabolic and psychosocial network in T2DM. Incorporating structured sleep assessment and targeted interventions—such as cognitive behavioral therapy for insomnia (CBT-I), CPAP for obstructive sleep apnea, and circadian-based strategies including scheduled light exposure and sleep–wake regularization—may enhance clinical outcomes. A tradition-sensitive synthesis clarifies sources of divergence in the literature and provides a foundation for more coherent, mechanism-informed research.
Patients may be less likely to be screened by their PCP for OSA compared to CVD. The ASCVD risk score and STOP-BANG questionnaire assess overlapping cardiometabolic risk factors. This study examined the correlation between ASCVD and STOP-BANG scores and whether combining them alters OSA screening performance compared to STOP-BANG alone. A cross-sectional secondary analysis of 201 participants (ages 40–75) from two National Sleep Research Resource datasets were utilized. Spearman correlations were calculated between ASCVD, STOP-BANG, and apnea–hypopnea index (AHI). Diagnostic performance metrics (sensitivity, specificity, positive and negative predictive values, likelihood ratios, area under the curve) were calculated for ASCVD (≥ 7.5
Sleep is fundamental for optimal health and well-being. Many adults do not attain adequate sleep due to detrimental sleep habits. An instrument to assess sleep hygiene could be valuable in evaluating patients’ sleep and might facilitate improvements in sleep and sleep-related health. We developed a comprehensive, 20-item sleep hygiene survey, the Atlantic Sleep Hygiene Questionnaire (ASHQ), based on an extensive review and critical analysis of the current sleep hygiene literature. ASHQ was administered to more than 750 consecutive adult patients in a sleep clinic. Patients also completed surveys measuring sleepiness (Epworth Sleepiness Scale, ESS) and fatigue (Fatigue Severity Scale, FSS), as well as a single-item analog survey of sleep quality (Sleep Quality Scale, SQS), and these were compared to the ASHQ. An exploratory ASHQ score of 8 or more (detrimental sleep habits) was significantly associated with abnormal sleepiness (ESS score of 10 or greater, out of a maximum of 24) and abnormal fatigue (FSS score of 36 or greater, out of a maximum of 63). Worse sleep hygiene (higher ASHQ scores) was also associated with lower subjective sleep quality based on SQS scores. Hence, ASHQ scores directly correlated with subjective sleepiness, fatigue and overall sleep quality. ASHQ may provide a novel approach to assess sleep hygiene and could potentially improve sleep, quality of life and general health, as well as specific medical conditions in which sleep may play a role.
Atopic dermatitis (AD) is a common inflammatory skin disorder in infants and is frequently associated with sleep disturbances. Although the relationship between disease severity and sleep quality is well established, the effect of lesion localization on sleep has not been thoroughly investigated. This retrospective cross-sectional study included 60 infants aged 6–36 months diagnosed with AD and 60 age-matched healthy controls. Sleep quality was assessed using the Children’s Sleep Habits Questionnaire (CSHQ), which, although originally developed for older children, has been used in younger populations in previous studies. Disease severity was evaluated using the Scoring Atopic Dermatitis (SCORAD) and Patient-Oriented Eczema Measure (POEM) indices. Lesion localization was determined through clinical examination and categorized as face/neck, trunk/extremities, or generalized (involvement of two or more regions). Parametric and nonparametric tests were used for intergroup comparisons. Relationships between variables were examined using Spearman’s correlation analysis, and multivariate regression analysis was employed to identify independent associations. The AD group exhibited significantly higher total CSHQ scores (p < 0.001). Sleep onset latency, night awakenings, bedtime resistance, and sleep duration problems were more pronounced in infants with AD. Positive correlations were observed between SCORAD/POEM scores and CSHQ scores (p < 0.001). Infants with facial and neck involvement had lower sleep quality compared to those with lesions confined to the trunk and extremities (p < 0.01). The greatest degree of sleep disturbance was observed in infants with generalized involvement. In infants with AD, both disease severity and lesion localization are associated with poorer sleep quality. The finding that facial and neck involvement is linked to greater sleep disturbance highlights the importance of considering anatomical distribution during clinical assessment. Early interventions, including regular emollient use and proactive anti-inflammatory treatment, may help mitigate potential cognitive, emotional, and behavioral risks in this vulnerable age group.
Abstract Background Electrocardiogram (ECG) and photoplethysmogram (PPG) signals offer moderate ability to distinguish Obstructive Sleep Apnea (OSA) patients, including those with comorbid Major Depressive Disorder (MDD), from healthy individuals. This study investigated whether analyzing these signals during specific sleep stages could improve the detection of MDD within an OSA cohort. Methods Polysomnography data from 53 participants (OSA-only, OSA with MDD, and healthy controls) was analyzed. Recordings were segmented into 5-min intervals of pure sleep stages. Results Deep-Sleep was identified as the most discriminative stage, yielding the highest number of significant features and with strong effect sizes for both ECG and PPG. Using Deep-Sleep PPG features related to vascular stiffness, distinguishing Controls from OSA was performed with 100% accuracy. For the more complex task of identifying MDD within the OSA group, combining PPG timing delays in the peripheral pulse wave and one ECG entropy feature achieved 89.33% accuracy, with an AUC of 0.91. Conclusion This single-site research demonstrates that deep-sleep-stage-specific analysis improves the power of ECG and PPG signals to differentiate between Controls, OSA, and OSA with MDD. This framework has the potential for developing an accurate ECG and PPG-based system to screen for depression in patients with sleep disorders, overcoming delays in the assessment due to long waiting periods in sleep clinics. The translation of this research requires a large, multi-site database for the evaluation of wearable devices for this application.
The original Sleep Disorders Questionnaire (SDQ, 1994) contained a 12-item sleep apnea subscale (SDQ-SA). SDQ was shortened by factor analysis in 2024 (SDQ-2) and contains a 14-item subscale “Sleep Disordered Breathing” (SDQ2-SDB). This is the first external validation study of the new scale using polysomnography, with a concurrent validation against four commonly used sleep-disordered breathing questionnaires. Members of a large urban police force (n = 733) completed the SDQ2-SDB, Berlin, STOP-Bang, NoSAS, and GOAL questionnaires. A subgroup (n = 101) also volunteered for a laboratory polysomnogram (PSG). SDQ2-SDB scores were analyzed by ANOVA in both samples. For the NPSG subgroup, Receiver Operating Characteristics (ROC) of the five apnea scales were calculated at a criterion of AHI ≥ 15. A correlation matrix among the five scales was also calculated. The NPSG subgroup with higher measured AHI showed significantly higher SDQ2-SDB scores. In the whole sample, SDQ2-SDB scores were significantly higher in males compared with females, in older compared to younger individuals, and in those with higher BMI. Age x Sex, Age x BMI and BMI x Sex effects were also significant. The areas under the ROC curve (AUC) were: SDQ2-SDB = 70
Helping professionals, including clergy, experienced disproportionate sleep disturbance during the COVID-19 pandemic. Unlike other groups of helping professionals, little is known about sleep quality or predictors of poor sleep quality among clergy. This investigation sought to fill this important gap. This investigation was a secondary analysis of baseline data from the Selah trial, a preference-based, randomized, waitlist-controlled trial of stress management interventions delivered during the pandemic. Baseline data collection occurred between April 2020- October 2021. Lifestyle factors (e.g., physical activity), mental health outcomes (e.g., symptoms of anxiety and depression), stress (e.g., symptoms of stress), and sleep quality were measured using validated questionnaires. Poor sleepers were categorized using a global Pittsburgh Sleep Quality Index score > 5. Logistic regressions were used to model predictors of good versus poor sleepers. Data were available from 286 clergy. Participants were on average 52.8 (SD 11.6) years of age. Approximately 66
Sleep disturbance symptoms (SDS) are common among US adults. Given the number of affected individuals, it is not surprising that there is a wide range of available remedies. These include prescription medicines, over the counter (OTC) options such as medications and dietary supplements, as well as the repurposing of recreational substances. A cross-sectional survey was developed and deployed via the Ipsos KnowledgePanel® platform to generate a sample representative of the US adult population. Qualified subjects were those that reported at least 2 nights of SDS per month or less than 2 nights of difficulty due to the use of an active treatment. The primary purpose was to identify subjects with recent SDS to assess how they manage their symptoms. A total of 2,223 individuals entered the survey, with 1,299 qualifying for participation as per the qualification criteria (58
Abstract Background Sleep disturbances are prevalent and linked to adverse neurological outcomes. While conventional transcranial magnetic stimulation (TMS) shows promise, protocols typically require high intensities and prolonged courses. ExoTMS is a novel technology targeting cortical regions involved in sleep regulation. Aim To evaluate ExoTMS efficacy in improving subjective sleep quality in individuals with sleep disturbances. Methods In this multicenter, single-blinded, sham-controlled study, 43 adults were assigned to an active (n = 31, 70% motor threshold (MT)) or a sham (n = 12, 5% MT) group. Subjects underwent six sessions targeting the left dorsolateral prefrontal cortex (dlPFC). Outcomes were assessed at baseline and a 3-month follow-up via Pittsburgh Sleep Quality Index (PSQI), Perceived Stress Scale (PSS-10), Sleep and Stress Assessment, Subject Satisfaction Questionnaire, and Therapy Comfort Questionnaire. Results At baseline, active subjects demonstrated poor sleep (average PSQI 9.7 ± 3.4). At 3 months, the active group showed a significant reduction (-4.7 points, p < 0.0001), with 48.3% of subjects achieving the minimal clinically important difference and 55.2% reaching clinical remission. Active stimulation was particularly effective in reducing sleep onset latency by 46.3 min in subjects with prolonged baseline latency. Additionally, 82.1% of active subjects reported improved stress coping, compared to 63.6% in the sham group. ExoTMS treatment was well tolerated, with all subjects reporting “0” on the Numerical Analog Pain Scale. Conclusion These findings suggest that ExoTMS may represent a promising and well-tolerated non-invasive intervention for improving sleep quality. Trial registration NCT07027657 (ClinicalTrials.gov), registered on June 11, 2025.
One reliable sociodemographic predictor of sleep is marital status. Being lonely, separated, residing away from a spouse may have distinct consequences, particularly for middle-aged and older persons. The objective is to determine the association between sleep disorders and current marital status among Indian population aged 45 years and above, stratified into gender and age group. Longitudinal ageing study in India (LASI) is an ongoing cohort study to collect information on health aspects of ageing in India. Current study is conducted using 1st wave of LASI data set (April 2017 to December 2018). Sleep disorders including sleep disturbance was assessed using the Jenkin Sleep Scale (JSS-4). It covers four sleep related questions in last one month and participants were classified as presence or absence of sleep disorder. We have assessed the association of sleep disorder (outcome/ response variable) with current marital status (explanatory/ exposure variable) adjusted with covariate using multivariable logistic regression. P value < 0.05 was considered statistically significant. STATA version 17 was used for analysis. Sleep disorder was highest among participants in live-in relationship (15.88
Patients with obstructive sleep apnea (OSA) often present altered upper airways (UA) receptors. This study aimed to validate conscious sensory abilities related to oropharyngeal airflow perception in individuals with OSA and controls, as a first step toward developing a clinical screening approach based on airflow perception. The oropharynx was subjected to experimenter-induced mechanical modifications, generating variations in its volume and wall tension. Seven conditions modified airflow in an aggravating or facilitating manner, each item scored 1 when matching the expected response and 0 otherwise, yielding a total sensitivity score ranging from 0 to 7. This prospective study included 112 participants: 41 with OSA and 71 controls (60 questionnaire-negative and 11 PSG-confirmed non-OSA). To limit bias, experimenters were blinded to participants' group assignment, and participants were blinded to their PSG results and questionnaire scores. Participants demonstrated significant somesthetic perception of airflow variations, with scores above zero (p < 0.01) and exceeding predefined pragmatic thresholds (up to 51 https://clinicaltrials.gov/study/NCT06092710
Accurate assessment of sleep is vital, but the gold standard, polysomnography, is costly and impractical for large-scale studies. An alternative is wearable accelerometers, which reduce participant burden and avoid biases associated with subjective reporting e.g. recall biases. This study aimed to develop and validate a method for estimating time in bed (TIB), total sleep time (TST), sleep efficiency (SE), sleep onset latency (SOL), and wake after sleep onset (WASO) utilizing machine learning applied to thigh-accelerometry data. Data on 309 nights from 134 children aged 4–17 years was used to develop a method utilizing two machine learning models applied to data from thigh-worn accelerometers to estimate sleep metrics. Inputs were collected simultaneously from the Zmachine Insight + and raw data from thigh-worn accelerometers, trained using k-fold cross-validation and validated in a participant-disjoint internal hold-out set. The method was then externally validated against polysomnography in an independent sample of 136 children aged 8–16 years. The independent validation showed overestimations of 28.0 min for bedtime and 11.2 min for wake time, with ICC of 0.59 and 0.55. TIB and TST were overestimated by 14.0 and 3.3 min with ICC of 0.59 and 0.56, respectively. The correlation for estimating SE, SOL and WASO was weak with ICC of 0.21, 0.01 and 0.04, respectively. This method demonstrated sufficient accuracy for assessing bedtime, wake time, TIB and TST at the group level when validated in an independent sample against polysomnography, although wide limits of agreement suggest limited precision for individual-level assessments. Low agreement for SE, SOL and WASO indicated insufficient accuracy of the method for these metrics.
Abstract Background Many patients have positional obstructive sleep apnoea (OSA) with an apnoea-hypopnoea index (AHI) that is two-fold higher in supine sleep than in non-supine sleep. In these patients, the proportion of time spent in supine sleep influences the overall AHI. With the example of OSA patients treated with a mandibular advancement device (MAD), the aim of this study was to test the hypothesis that between-measurement differences in the proportion of supine sleep time are a significant factor affecting changes in AHI. Methods One hundred sixty-five adult OSA patients treated with MAD were included in the study. Data on AHI, supine sleep time, age, sex, body mass index (BMI), Epworth Sleepiness Scale (ESS) scores, mandibular protrusion, patient-reported use, and adverse effects of the MAD were retrospectively collected from medical records or the Swedish Sleep Apnoea Register. Results Among included patients, 27.3% (45/165) had both positional OSA at baseline and a ≥ 50% difference in the proportions of supine sleep time between baseline and follow-up. A generalized linear model showed that changes in the proportion of supine sleep time had a statistically significant impact on the change in overall AHI from baseline to follow-up of similar size as the effect the MAD. Conclusions Changes in the proportion of supine sleep time are an important contributor to between -measurements changes in overall AHI in many patients treated with MAD. Positional OSA must be acknowledged not only in OSA diagnostics but also in MAD treatment follow-up.
Actigraphy is widely used in research settings to objectively assess sleep–wake patterns; however, inconsistencies in device algorithms, hardware capabilities, and scoring procedures pose challenges for comparing data across devices. This study investigated the agreement between two commonly used wrist actigraphs (i.e., Philips Actiwatch Spectrum Plus ActiGraph CentrePoint Insight) and offers a systematic procedure to improve comparability in sleep indicators. Thirteen participants (Mage = 19 years, SD = 3 years; 85
Based on the bidirectional communication mechanism of the gut-brain axis, this study aims to systematically elucidate the interactive pathways between gut microbiota and insomnia, review the research progress of microbiota-targeted interventions for insomnia, and analyze the current bottlenecks in clinical translation, so as to provide theoretical basis and novel insights for the precise prevention and treatment of chronic insomnia. Relevant articles on gut microbiota and insomnia published between January 2021 to January 2026 were retrieved from PubMed/Embase databases. Data from case-control studies, randomized controlled trials, animal experiments, and Mendelian randomization studies were integrated. The associated mechanisms, intervention strategies, and existing problems between gut dysbiosis and insomnia were summarized from three dimensions: neural pathways, metabolites, and immune inflammation. Gut microbiota and insomnia form a vicious cycle via the gut-brain axis. Gut dysbiosis disrupts sleep-wake cycle and circadian rhythm through vagal nerve transmission, disordered short-chain fatty acids/tryptophan metabolism, and IL-6/TNF-α-mediated neuroinflammation. Insomnia patients are characterized by reduced microbial diversity, decreased short-chain fatty acid-producing bacteria, and enrichment of pathogenic bacteria. Interventions such as probiotics, prebiotics, and fecal microbiota transplantation can improve sleep parameters, but are limited by inconsistent efficacy, unclear long-term safety, and non-standardized regimens. Individualized multi-omics precise regulation is the key to breakthrough. Gut microbiota serves as a crucial target for insomnia prevention and treatment, which modulates sleep processes through multiple pathways of the gut-brain axis. Future research should improve long-term safety evaluation, establish standardized diagnosis and treatment systems, and promote individualized microbiota interventions based on multi-omics technologies, facilitating the translation of microecological strategies from basic research to precise clinical application in insomnia.
Poor sleep quality is increasingly recognized as a public health concern due to its strong association with hypertension and cardiovascular morbidity. Although the burden of sleep disorders is rising globally, evidence from low-income settings such as Ethiopia remains limited. This study aimed to assess poor sleep quality and its associated factors among hypertensive patients attending follow-up care in Southwest Ethiopia. An institution-based cross-sectional study was conducted from June to July 2024 among 364 systematically selected hypertensive patients. Data were collected using interviewer-administered questionnaires. The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality, with scores ≥ 5 indicating poor sleep. Substance use was measured using the Fagerström Test for Nicotine Dependence, Severity of Dependence Scale, and CAGE questionnaire. Bivariate and multivariable logistic regression analyses were performed, and variables with p < 0.05 were considered statistically significant. The prevalence of poor sleep quality was 54.4
The apnea–hypopnea index (AHI) is the standard metric for grading obstructive sleep apnea (OSA) severity but does not capture cumulative oxygen desaturation; hypoxic burden (HB), integrating desaturation area per hour, may better reflect physiological load, but its diagnostic performance remains uncertain. We conducted a retrospective diagnostic study of adults undergoing Peripheral Arterial Tonometry—Home Sleep Apnea Testing (PAT-HSAT) (WatchPAT®) between 2016 and 2025. After prespecified exclusions, 1,171 patients with AHI3
Meta-analyses confirm caffeine’s sleep-disrupting effects, but qualitative insights into perceived disruptions in non-Western, high-pressure contexts remain scarce. To examine how the timing of caffeine intake, culturally embedded in chai consumption, influences subjective and objective sleep onset latency and dream recall among Indian young adults, with particular attention to occupational differences between students vs. professionals. Sequential mixed-methods cross-sectional study was conducted among 200 healthy Indian young adults aged 18–35 years (80 students, 120 professionals) from Maharashtra, India. Phase 1: semi-structured interviews (N = 200). Phase 2: validated questionnaires (Pittsburgh Sleep Quality Index, Morningness-Eveningness Questionnaire, Caffeine Consumption Questionnaire) and 7-night actigraphy (n = 50 subset). Thematic analysis was performed using NVivo 12; quantitative data were analysed using SPSS v.26. Late caffeine intake (after 6 PM) (last intake after 18:00 h) was reported by 57.5
Sleep disturbances are increasingly recognized as a significant yet often overlooked burden among people living with HIV (PLHIV). Thus, our study aims to assess the prevalence of poor sleep quality and investigated the associated factors among PLHIV on antiretroviral therapy (ART). We conducted a hospital-based cross-sectional study from December 17th, 2023 and November 22nd,2024. A total of 514 PLHIV treated at the Centre National de Référence de Recherche et de la Prise en Charge du Sida (CNRRPEC) of the National University Hospital Center Hubert Koutoucou Maga (CNHU-HKM) in Cotonou, Benin were included in the final analysis. Sleep quality of the participants was investigated using the Pittsburg Sleep Quality Index (PSQI). Binary logistic regression analysis was performed to identify factors associated with poor sleep quality. In the multivariable analysis, variables with p-values less than 0.05 were considered statistically significant, with a 95
Sleep is a critical component of athletic performance and recovery, yet female athletes often face unique challenges that may hinder their ability to achieve optimal sleep. This narrative literature review examines the importance of sleep for female athletic performance and synthesizes evidence on the physiological, psychological, and social factors influencing sleep quality and duration in female athletes, including hormonal fluctuations across the menstrual cycle, psychological stressors, societal expectations, and training demands. Relevant literature was identified through targeted searches of PubMed, Web of Science, and SportDiscus, focusing on studies related to sleep, performance, and recovery in female athletic populations. Collectively, the findings highlight sleep as a foundational element of performance and well-being and suggest that individualized, female-specific sleep strategies may support improved recovery, performance consistency, and overall health. Addressing the unique sleep-related challenges faced by female athletes may inform more effective training practices and support systems within sport.
