Effect of the Implementation of a Structured Diet Management Plan on the Severity of Obstructive Sleep Apnea: A Systematic Review

Revolutionizing Sleep Health: The Emergence and Impact of Personalized Sleep Medicine

Personalized sleep medicine represents a transformative shift in healthcare, emphasizing individualized approaches to optimizing sleep health, considering the bidirectional relationship between sleep and health. This field moves beyond conventional methods, tailoring care to the unique physiological and psychological needs of individuals to improve sleep quality and manage disorders. Key to this approach is the consideration of diverse factors like genetic predispositions, lifestyle habits, environmental factors, and underlying health conditions. This enables more accurate diagnoses, targeted treatments, and proactive management. Technological advancements play a pivotal role in this field: wearable devices, mobile health applications, and advanced diagnostic tools collect detailed sleep data for continuous monitoring and analysis. The integration of machine learning and artificial intelligence enhances data interpretation, offering personalized treatment plans based on individual sleep profiles. Moreover, research on circadian rhythms and sleep physiology is advancing our understanding of sleep's impact on overall health. The next generation of wearable technology will integrate more seamlessly with IoT and smart home systems, facilitating holistic sleep environment management. Telemedicine and virtual healthcare platforms will increase accessibility to specialized care, especially in remote areas. Advancements will also focus on integrating various data sources for comprehensive assessments and treatments. Genomic and molecular research could lead to breakthroughs in understanding individual sleep disorders, informing highly personalized treatment plans. Sophisticated methods for sleep stage estimation, including machine learning techniques, are improving diagnostic precision. Computational models, particularly for conditions like obstructive sleep apnea, are enabling patient-specific treatment strategies. The future of personalized sleep medicine will likely involve cross-disciplinary collaborations, integrating cognitive behavioral therapy and mental health interventions. Public awareness and education about personalized sleep approaches, alongside updated regulatory frameworks for data security and privacy, are essential. Longitudinal studies will provide insights into evolving sleep patterns, further refining treatment approaches. In conclusion, personalized sleep medicine is revolutionizing sleep disorder treatment, leveraging individual characteristics and advanced technologies for improved diagnosis, treatment, and management. This shift towards individualized care marks a significant advancement in healthcare, enhancing life quality for those with sleep disorders.

Effects of common lifestyle factors on obstructive sleep apnea: precautions in daily life based on causal inferences

Background

This study aimed to evaluate the causal impact of common modifiable lifestyles on obstructive sleep apnea (OSA), which is beneficial for recommendations to prevent and manage OSA.

Method

Published genome-wide association study (GWAS) summary statistics were used to perform two-sample Mendelian randomization (MR). Variants associated with each exposure of smoking, drinking, and leisure sedentary behaviors at the genetic level were used as instrumental variables (IVs). Then, inverse-variance weighting (IVW) was considered the primary result for causality. Moreover, several complimented approaches were also included to verify the observed associations. MR-PRESSO and MR-Egger intercept were applied to test the horizontal pleiotropy. To assess heterogeneity, Cochran's Q test by IVW and MR-Egger were applied.

Results

Regular smoking history increased OSA risk in all applied approaches [OR (95% CI)IVW = 1.28 (1.12, 1.45), p = 1.853 × 10-4], while the causality of lifetime smoking index [OR (95% CI)IVW = 1.39 (1.00, 1.91), p = 0.048], alcohol intake frequency [outliers removed OR (95% CI)IVW = 1.26 (1.08, 1.45), p = 0.002], and coffee intake behavior [OR (95% CI)IVW = 1.66 (1.03, 2.68), p = 0.039] on OSA risk were not always consistent in other approaches. In addition, no robust causal associations were observed for the effect of sedentary leisure behaviors on OSA risk. In sensitivity analysis, we observed no sign of horizontal pleiotropy or heterogeneity.

Conclusion

Ever regularly smoking has a robust causal role in increasing OSA risk, which should be discouraged as precautions from developing OSA.

Obesity and Leukemia: Biological Mechanisms, Perspectives, and Challenges

PURPOSE OF REVIEW

To examine the epidemiological data on obesity and leukemia; evaluate the effect of obesity on leukemia outcomes in childhood acute lymphoblastic leukemia (ALL) survivors; assess the potential mechanisms through which obesity may increase the risk of leukemia; and provide the effects of obesity management on leukemia. Preventive (diet, physical exercise, obesity pharmacotherapy, bariatric surgery) measures, repurposing drugs, candidate therapeutic agents targeting oncogenic pathways of obesity and insulin resistance in leukemia as well as challenges of the COVID-19 pandemic are also discussed.

RECENT FINDINGS

Obesity has been implicated in the development of 13 cancers, such as breast, endometrial, colon, renal, esophageal cancers, and multiple myeloma. Leukemia is estimated to account for approximately 2.5% and 3.1% of all new cancer incidence and mortality, respectively, while it represents the most frequent cancer in children younger than 5 years. Current evidence indicates that obesity may have an impact on the risk of leukemia. Increased birthweight may be associated with the development of childhood leukemia. Obesity is also associated with worse outcomes and increased mortality in leukemic patients. However, there are several limitations and challenges in meta-analyses and epidemiological studies. In addition, weight gain may occur in a substantial number of childhood ALL survivors while the majority of studies have documented an increased risk of relapse and mortality among patients with childhood ALL and obesity. The main pathophysiological pathways linking obesity to leukemia include bone marrow adipose tissue; hormones such as insulin and the insulin-like growth factor system as well as sex hormones; pro-inflammatory cytokines, such as IL-6 and TNF-α; adipocytokines, such as adiponectin, leptin, resistin, and visfatin; dyslipidemia and lipid signaling; chronic low-grade inflammation and oxidative stress; and other emerging mechanisms. Obesity represents a risk factor for leukemia, being among the only known risk factors that could be prevented or modified through weight loss, healthy diet, and physical exercise. Pharmacological interventions, repurposing drugs used for cardiometabolic comorbidities, and bariatric surgery may be recommended for leukemia and obesity-related cancer prevention.

A Dietary and Lifestyle Intervention Improves Treatment Adherence and Clinical Outcomes in Overweight and Obese Patients with Obstructive Sleep Apnea: A Randomized, Controlled Trial

The study's objective was to assess the impact of Mediterranean diet/lifestyle interventions for weight loss on positive airway pressure (PAP) adherence, body mass index (ΒΜΙ), sleepiness, and blood pressure measurements (BP) in patients with obstructive sleep apnea (OSA). We designed a randomized, controlled trial, including overweight and obese patients with moderate to severe OSA, randomized to standard care (SCG, n = 37) or a Mediterranean diet group (MDG, n = 37). The SCG received healthy lifestyle advice, while the MDG underwent a 6-month behavioral intervention aiming to enhance weight loss and adherence to a Mediterranean diet. PAP adherence, BMI, Epworth Sleepiness Scale (ESS), and BP measurements were evaluated pre- and post-intervention. Post-intervention PAP use was higher in the MDG compared to the SCG (6.1 vs. 5.4, p = 0.02). Diet/lifestyle intervention was one of the most significant predictive factors for PAP adherence (OR = 5.458, 95% CI = 1.144-26.036, p = 0.03). The SCG demonstrated a rise in BMI, while the MDG displayed a decline (0.41 vs. -0.75, p = 0.02). The MDG also demonstrated a substantial reduction in adjusted SBP (-5.5 vs. 2.8, p = 0.014) and DBP (-4.0 vs. 2.5, p = 0.01). Ultimately, incorporating a dietary/lifestyle intervention with standard care yields superior PAP adherence, BMI, and BP measurements in contrast to standard care alone, emphasizing the advantages of dedicating more time and support within the MDG.