The prevalence and associated factors of sleep deprivation among healthy college students in China: a cross-sectional survey

Exploring anxiety and sleep disorders among Edna Adan university students in Somaliland: associated stressors and insights

BACKGROUND

970 million people around the world are living with mental illness. Mental illness is also one of the chronic diseases prevalent in Somaliland. Anxiety and sleep disturbances are the major types of mental illness commonly observed in young adults. The purpose of this study is to explore the anxiety, sleep disturbances, and their factor associated with Edna Adan University bachelor's students in Hargeisa, Somaliland.

METHODS

This study has used a cross-sectional study with 307 bachelor students of Edna Adan University as its participants from May to July 2024. GAD-7 was used to evaluate anxiety; MPAI was used to measure mobile phone addiction; and GSDS was used to measure sleep disturbances. Pre-test for associated factors questionnaire was carried to assess the validity and reliability of questionnaire. The acquired data was then univariate and analyzed in SPSS version 26.

RESULTS

Most 71.30% of the students reported having a good sleep quality, 63.50% had no problem with mobile phone addiction, and 61.20% experienced minimal to no anxiety. Academic stressors, financial pressure, and interpersonal relationships are the most frequently (9.10%) experienced linked factors with a very serious frequency (all of the time), followed by several other factors, such as teaching and learning-related stressors, mental illness and use of psychoactive substances, language barrier, body mass index (BMI) or daily meal problem, having doubt regarding the future or gambling behavior, and travel time to university.

CONCLUSION

This study shows that the students mainly have minimal to no anxiety, and no addiction to mobile phone while maintaining a good sleep quality. However, sleep disturbances and anxiety-associated factors such as academic stressors, financial pressure, and interpersonal relationships are commonly experienced in a very serious frequency (all of the time).

Sleep deprivation-induced shifts in gut microbiota: Implications for neurological disorders

Sleep deprivation is a prevalent issue in contemporary society, with significant ramifications for both physical and mental well-being. Emerging scientific evidence illuminates its intricate interplay with the gut-brain axis, a vital determinant of neurological function. Disruptions in sleep patterns disturb the delicate equilibrium of the gut microbiota, resulting in dysbiosis characterized by alterations in microbial composition and function. This dysbiosis contributes to the exacerbation of neurological disorders such as depression, anxiety, and cognitive decline through multifaceted mechanisms, including heightened neuroinflammation, disturbances in neurotransmitter signalling, and compromised integrity of the gut barrier. In response to these challenges, there is a burgeoning interest in therapeutic interventions aimed at restoring gut microbial balance and alleviating neurological symptoms precipitated by sleep deprivation. Probiotics, dietary modifications, and behavioural strategies represent promising avenues for modulating the gut microbiota and mitigating the adverse effects of sleep disturbances on neurological health. Moreover, the advent of personalized interventions guided by advanced omics technologies holds considerable potential for tailoring treatments to individualized needs and optimizing therapeutic outcomes. Interdisciplinary collaboration and concerted research efforts are imperative for elucidating the underlying mechanisms linking sleep, gut microbiota, and neurological function. Longitudinal studies, translational research endeavours, and advancements in technology are pivotal for unravelling the complex interplay between these intricate systems.

Comparative analysis of sleep parameters and structures derived from wearable flexible electrode sleep patches and polysomnography in young adults

Polysomnography (PSG) is the gold standard for clinical sleep monitoring, but its cost, discomfort, and limited suitability for continuous use present challenges. The flexible electrode sleep patch (FESP) emerges as an economically viable and patient-friendly solution, offering lightweight, simple operation, and self-applicable. Nevertheless, its utilization in young individuals remains uncertain. The objective of this study was to compare sleep data obtained by FESP and PSG in healthy young individuals and analyze agreement for sleep parameters and structure classification. Overnight monitoring with FESP and PSG recordings in 48 participants (mean age: 23 yr) was done. Correlation analysis, Bland-Altman plots, and Cohen's kappa coefficient assessed consistency. Sensitivity, specificity, and predictive values compared classification against PSG. FESP showed strong correlation and consistency with PSG for sleep monitoring. Bland-Altman plots indicated small errors and high consistency. Kappa values (0.70-0.84) suggested substantial agreement for sleep stage classification. Pearson correlation coefficient values for sleep stages (0.75-0.88) and sleep parameters (0.80-0.96) confirm that FESP has a strong application. Intraclass correlation coefficient yielded values between 0.65 and 0.97. In addition, FESP demonstrated an impressive accuracy range of 84.12-93.47% for sleep stage classification. The FESP also features a wearable self-test program with an error rate of no more than 8% for both deep sleep and wake. In young adults, FESP demonstrated reliable monitoring capabilities comparable to PSG. With its low cost and user-friendly design, FESP is a potential alternative for portable sleep assessment in clinical and research applications. Further studies involving larger populations are needed to validate its diagnostic potential.NEW & NOTEWORTHY By comparison with PSG, this study confirmed the reliability of an efficient, objective, low-cost, and noninvasive portable automatic sleep-monitoring device FESP, which provides effective information for long-term family sleep disorder diagnosis and sleep quality monitoring.