Obesity and sleep disorders are highly prevalent conditions with profound implications for public health. Emerging evidence highlights a bidirectional relationship between these two conditions, with each exacerbating the other in a complex interplay of behavioral, physiological, and hormonal mechanisms. Sleep deprivation and poor sleep quality contribute to energy imbalance through dysregulation of appetite hormones (e.g., leptin and ghrelin), increased caloric intake, and reduced physical activity. Conversely, sleep disorders such as obstructive sleep apnea syndrome (OSAS), insomnia, and restless leg syndrome (RLS) are significantly more common in individuals with obesity. This review explores the pathophysiological mechanisms underlying this relationship, including the roles of inflammation, autonomic dysregulation, and neuroendocrine pathways. Sleep loss exacerbates metabolic syndrome components, including insulin resistance and dyslipidemia, further perpetuating weight gain. Similarly, obesity-induced sleep disorders lead to pro-inflammatory states, vascular dysfunction, and sympathetic overactivation, compounding cardiometabolic risks. Specific conditions like OSA and RLS are examined as models of this interdependence, emphasizing their shared pathways and clinical implications. The bidirectional link between obesity and sleep disorders underscores the importance of integrating sleep assessment and management into obesity treatment strategies. Addressing this relationship could mitigate the progression of cardiometabolic comorbidities and improve overall health outcomes. Moreover, the intertwined dynamics between obesity, sleep disorders, and mental health-mediated by inflammatory pathways, hormonal dysregulation, and neurobehavioral factors-highlight the critical need for integrated treatment approaches targeting physical, psychological, and sleep-related dimensions to enhance health and quality of life.

Background: Obstructive sleep apnea (OSA) is characterized by repeated airway obstructions during sleep, causing hypopnea, apnea, intermittent hypoxia, and sleep fragmentation. The severity of OSA is measured using the apnea–hypopnea index (AHI), with AHI ≥ 5 indicating OSA. This study aims to assess the frequency and type of depressive disorder characteristics of OSA patients and to evaluate the impact on quality of life, also considering the presence of hyperactivity. Methods: A case-control study using OSA patients referred to Cagliari’s sleep disorder center. Controls were matched by age and sex from community databases. OSA diagnoses were made with AHI > 15. Depressive episodes were identified using BDI-SF, and H-QoL (Health related Quality of Life) was measured with the SF-12, focusing on item 10 for hyper-energy. Results: The clinical sample (n = 25) had a higher frequency of depressive episodes (36%) compared to controls (7% and 4%). Depressed OSA patients had worse H-QoL and higher hyper-energy scores, but the additional burden from depression was relatively low. Conclusions: The OSA sample has a higher frequency of depressive episodes compared to the general population. Depressive episodes in OSA patients are linked to higher scores on item 10 of the SF-12, indicating hyper-energy despite lower overall quality of life scores. While OSA significantly impacts quality of life, the additional burden from depression is less severe than in other chronic diseases. These findings suggest that depressive episodes in OSA may be related to rhythm dysregulation and hyperactivity (DYMERS).

Background/Objectives: Sleep disturbances often accompany mood disorders and persistent insomnia after mood symptoms have resolved may be a marker of poor outcome. The association between sleep symptoms and mood disorders seems to change with age and sex. This study aims to assess the frequency of depressive episodes and sleep disorders in the general population through an agile screening questionnaire and to evaluate the association of depressive episodes and sleep symptoms by sex and age categories. Methods: 774 women and 728 men from Sardinia aged > 16 years old were enrolled. The Patient Health Questionnaire (PHQ-9) was administered through a computer-assisted telephonic interview. Results: The frequency of depressive episodes was double in women (10.6% vs. 4.4%; p < 0.0001), with the highest values in women > 75 yo (17.4%). The frequency of sleep dysregulation was double in women (18.7% vs. 9.6%; p < 0.0001), with the highest values in women > 75 yo (35.9%) and the lowest in the group of men > 75 yo. The group of young males showed the lowest frequency of depressive episodes (1.4%) and a frequency of sleep dysregulation (9.1%) similar to that of the other groups of age and sex. Sleep dysregulation without depressive episodes presented a higher distribution in the elderly, both in males (20.7%) and in females (18.5%). No significative differences were found across sex and age groups in the distribution of depressive episodes without sleep dysregulation. Conclusions: The use of an agile screener such as PHQ9 in the general population and/or in populations at risk can be a valuable tool in finding those individuals in whom sleep dysregulation may represent an early warning signal, one that may be thoroughly evaluated to identify and treat possible sleep disorders early.

Background: Innovative approaches, such as virtual reality (VR)–based cognitive rehabilitation, are becoming essential to healthy aging. Objective: This study aims to evaluate the feasibility and generate preliminary evidence regarding the effectiveness of an immersive VR-based cognitive remediation intervention for older individuals with mild cognitive impairment (MCI). Methods: A total of 40 individuals aged 65 years and older, of both genders with MCI, will be recruited and randomly assigned to the experimental or control group. The experimental group will participate in a 6-week VR-based cognitive remediation program, while the control group will receive healthy lifestyle education. Feasibility will be assessed through measures, including dropout rates, side effects, and satisfaction with the program. Preliminary effectiveness will be evaluated using assessments of cognitive functions, quality of life, functional mobility, depression and anxiety symptoms, regulation of social and biological rhythms, body awareness, and physical activity levels. Results: Recruitment began in May 2024 and is expected to conclude by November 2025; to date, 153 participants have been recruited and screened, with 39 enrolled. Preliminary analyses are planned for January 2026 and follow-up analyses for January 2027. Conclusions: This trial will provide insights into the feasibility and preliminary effectiveness of a VR-based intervention for older adults with MCI, with implications for its integration into preventive and rehabilitative care. Trial Registration: ClinicalTrial.gov NCT06579378; https://clinicaltrials.gov/search?term=NCT06579378 International Registered Report Identifier (IRRID): DERR1-10.2196/85089