Objective: This study evaluated the association between sleep patterns and the risk of being overweight/obese in Chinese children.
Methods: A total of 3,086 children (1,608 boys and 1,478 girls) between 7 and 14 years of age and studying in primary schools were recruited as eligible study participants in this study. We collected the information about children regarding sleep patterns, body height and weight, insomnia, healthy status, time allocation of daily activities, and demographic characteristics using a parental-reported questionnaire.
Results: Overweight/obese children were younger, predominantly male, and more prone to have suffered from illness in the past 12 months compared to normal-weight peers. They were also less prone to compensate for sleep deficits during weekends (47.6% vs 39.1%; χ (2)=11.637, P<0.001) and holidays (52.0% vs 42.0%; χ (2)=16.057, P<0.001). Sleep duration on weekdays did not affect the risk of being overweight/obese. The adjusted odds ratios for overweight/obesity (noncompensated) group using the compensated group as a reference were 1.197 (95% confidence interval [CI]: 1.004-1.493) during weekends and 1.309 (95% CI: 1.052-1.630) during holidays.
Conclusion: Compensation for sleep deficits on non-weekdays may ameliorate the risk of being overweight/obese in Chinese children. Moreover, no significant association between the risk of being overweight/obese and sleep duration on weekdays was demonstrated in the current study, which may be due to pervasive sleep insufficiency on weekdays in Chinese children.
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http://dx.doi.org/10.2147/NDT.S90838 | DOI Listing |
Psychol Serv
January 2025
Center for Health Equity Research and Promotion, Department of Veterans Affairs Pittsburgh Healthcare System.
Chronic insomnia is one of the most common health problems among veterans and can significantly impact health, function, and quality of life. Brief behavioral treatment for insomnia (BBTI), an adaptation of cognitive behavioral therapy for insomnia (CBT-I), was developed to help increase access to care outside of specialty settings. However, training providers alone is rarely sufficient, and implementation strategies are needed for successful uptake, adoption, and sustainable delivery of care.
View Article and Find Full Text PDFDiabetes Metab Res Rev
January 2025
Department of Human Genetics, Guru Nanak Dev University, Amritsar, India.
Aim: This review explores the increasing prevalence of Type 2 Diabetes Mellitus (T2DM) in children and adolescents, focusing on its etiology, risk factors, complications, and the importance of early detection and management. It also highlights the need for a multidisciplinary, family-centered approach in managing T2DM in pediatric populations, with an emphasis on nutrition, exercise, and lifestyle interventions.
Materials And Methods: A literature review was conducted using PubMed, Google Scholar, and Scopus to incorporate studies from 2015 to 2024 on T2DM in youths/adolescents/children, focusing on epidemiology, risk factors, and prevention strategies.
Diabetes Obes Metab
January 2025
Department of Medicine, Division of Endocrinology, Diabetes Research Center, Columbia University Irving Medical Center, New York, New York, USA.
Objective: Post-prandial glucose response (PPGR) is a risk factor for cardiovascular disease. Meal carbohydrate content is an important predictor of PPGR, but dietary interventions to mitigate PPGR are not always successful. A personalized approach, considering behaviour and habitual pattern of glucose excursions assessed by continuous glucose monitor (CGM), may be more effective.
View Article and Find Full Text PDFFront Comput Neurosci
December 2024
School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing, China.
Background: Automatic sleep staging is essential for assessing sleep quality and diagnosing sleep disorders. While previous research has achieved high classification performance, most current sleep staging networks have only been validated in healthy populations, ignoring the impact of Obstructive Sleep Apnea (OSA) on sleep stage classification. In addition, it remains challenging to effectively improve the fine-grained detection of polysomnography (PSG) and capture multi-scale transitions between sleep stages.
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