To determine whether a cumulative sleep debt (in a range commonly experienced) would result in cumulative changes in measures of waking neurobehavioral alertness, 16 healthy young adults had their sleep restricted 33% below habitual sleep duration, to an average 4.98 hours per night [standard deviation (SD) = 0.57] for seven consecutive nights. Subjects slept in the laboratory, and sleep and waking were monitored by staff and actigraphy. Three times each day (1000, 1600, and 2200 hours) subjects were assessed for subjective sleepiness (SSS) and mood (POMS) and were evaluated on a brief performance battery that included psychomotor vigilance (PVT), probed memory (PRM), and serial-addition testing, Once each day they completed a series of visual analog scales (VAS) and reported sleepiness and somatic and cognitive/emotional problems. Sleep restriction resulted in statistically robust cumulative effects on waking functions. SSS ratings, subscale scores for fatigue, confusion, tension, and total mood disturbance from the POMS and VAS ratings of mental exhaustion and stress were evaluated across days of restricted sleep (p = 0.009 to p = 0.0001). PVT performance parameters, including the frequency and duration of lapses, were also significantly increased by restriction (p = 0.018 to p = 0.0001). Significant time-of-day effects were evident in SSS and PVT data, but time-of-day did not interact with the effects of sleep restriction across days. The temporal profiles of cumulative changes in neurobehavioral measures of alertness as a function of sleep restriction were generally consistent. Subjective changes tended to precede performance changes by 1 day, but overall changes in both classes of measure were greatest during the first 2 days (P1, P2) and last 2 days (P6, P7) of sleep restriction. Data from subsets of subjects also showed: 1) that significant decreases in the MSLT occurred during sleep restriction, 2) that the elevated sleepiness and performance deficits continued beyond day 7 of restriction, and 3) that recovery from these deficits appeared to require two full nights of sleep. The cumulative increase in performance lapses across days of sleep restriction correlated closely with MSLT results (r = -0.95) from an earlier comparable experiment by Carskadon and Dement (1). These findings suggest that cumulative nocturnal sleep debt had a dynamic and escalating analog in cumulative daytime sleepiness and that asymptotic or steady-state sleepiness was not achieved in response to sleep restriction.
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Rev Cardiovasc Med
January 2025
Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, 230001 Hefei, Anhui, China.
Background: This study aimed to develop and validate a predictive model for major depression risk in adult patients with coronary heart disease (CHD), offering evidence for targeted prevention and intervention.
Methods: Using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, 1098 adults with CHD were included. A weighted logistic regression model was applied to construct and validate a nomogram-based prediction tool for major depression in this population.
Respirology
January 2025
Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia.
Background And Objective: The impact of lifetime body mass index (BMI) trajectories on adult lung function abnormalities has not been investigated previously. We investigated associations of BMI trajectories from childhood to mid-adulthood with lung function deficits and COPD in mid-adulthood.
Methods: Five BMI trajectories (n = 4194) from age 5 to 43 were identified in the Tasmanian Longitudinal Health Study.
BMC Public Health
January 2025
Amsterdam UMC location Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, the Netherlands.
Background: Developing interventions along with the population of interest using systems thinking is a promising method to address the underlying system dynamics of overweight. The purpose of this study is twofold: to gain insight into the perspectives of adolescents regarding: (1) the system dynamics of energy balance-related behaviours (EBRBs) (physical activity, screen use, sleep behaviour and dietary behaviour); and (2) underlying mechanisms and overarching drivers of unhealthy EBRBs.
Methods: We conducted Participatory Action Research (PAR) to map the system dynamics of EBRBs together with adolescents aged 10-14 years old living in a lower socioeconomic, ethnically diverse neighbourhood in Amsterdam East, the Netherlands.
NPJ Digit Med
January 2025
Graduate School of Data Science, Seoul National University, Seoul, Republic of Korea.
Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.
View Article and Find Full Text PDFNutrients
January 2025
Statistical Consulting Centre, National Institute for Applied Statistics Research Australia, School of Mathematics and Applied Statistics, University of Wollongong, Wollongong, NSW 2522, Australia.
: Obesity remains a global health challenge. Many commercial online weight loss programs are available, and they have advantages in terms of scalability and access. Few of these programs have been evaluated for effectiveness in a real-world context.
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