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BACKGROUND: Sleep and physical activity (PA) are thought to be interconnected with the development of rheumatoid arthritis (RA). However, the precise nature and extent of these relationships have yet to be fully quantified. This study aimed to quantify the longitudinal effects of sleep behaviors, PA, and genetic susceptibility on the incidence of RA and to estimate the combined effects and interactions among these exposures. METHODS: A total of 363,211 adults were derived from a large European cohort. We incorporated five sleep behaviors (sleep duration, insomnia, snoring, chronotype, and daytime sleepiness) to generate sleep patterns, which were defined based on healthy sleep scores. Multivariate-adjusted Cox proportional hazard models were conducted to assess the individual and combined associations of sleep patterns, PA, and genetic susceptibility with the risk of RA occurrence. Multiplicative and additive interactions were estimated by Pinteraction and relative excess risk due to interaction (RERI) between each of the two exposures. RESULTS: During a follow-up of 12.5 years, 4262 RA cases were ascertained. A healthy sleep pattern was associated with a decreased risk of RA in a dose-response manner, with an adjusted hazard ratio (HR) of 0.79 (95% confidence interval [CI] = 0.75-0.84), independent of traditional risk factors and genetic predisposition. Under the restricted cubic splines model, a non-linear association was detected for PA and RA risk. Participants in the intermediate quintile 3 showed the lowest risk for developing RA, with a HR 95% CI of 0.84 (0.76-0.92). Moreover, there was an additive interaction effect of intermediate sleep pattern and PA, with a 0.45 (95% CI = 0.02-0.87) RERI of developing RA. Additionally, individuals at high genetic risk had the greatest 10-year absolute risk reduction (10.58 per 1000 person-years) when adopting both favorable behaviors. CONCLUSIONS: A healthy sleep pattern and moderate PA were associated with a reduced risk of developing RA, which can offset the deleterious effects of predisposing genetic components. Implementing these modifiable lifestyle factors into public health practices is beneficial for RA prevention.

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BACKGROUND: The COVID-19 pandemic prompted various containment strategies, such as work-from-home policies and reduced social contact, which significantly altered people's sleep routines. While previous studies have highlighted the negative impacts of these restrictions on sleep, they often lack a comprehensive perspective that considers other factors, such as seasonal variations and physical activity (PA), which can also influence sleep. OBJECTIVE: This study aims to longitudinally examine the detailed changes in sleep patterns among working adults during the COVID-19 pandemic using a combination of repeated questionnaires and high-resolution passive measurements from wearable sensors. We investigate the association between sleep and 5 sets of variables: (1) demographics; (2) sleep-related habits; (3) PA behaviors; and external factors, including (4) pandemic-specific constraints and (5) seasonal variations during the study period. METHODS: We recruited working adults in Finland for a 1-year study (June 2021-June 2022) conducted during the late stage of the COVID-19 pandemic. We collected multisensor data from fitness trackers worn by participants, as well as work and sleep-related measures through monthly questionnaires. Additionally, we used the Stringency Index for Finland at various points in time to estimate the degree of pandemic-related lockdown restrictions during the study period. We applied linear mixed models to examine changes in sleep patterns during this late stage of the pandemic and their association with the 5 sets of variables. RESULTS: The sleep patterns of 27,350 nights from 112 working adults were analyzed. Stricter pandemic measures were associated with an increase in total sleep time (TST) (ß=.003, 95% CI 0.001-0.005; P<.001) and a delay in midsleep (MS) (ß=.02, 95% CI 0.02-0.03; P<.001). Individuals who tend to snooze exhibited greater variability in both TST (ß=.15, 95% CI 0.05-0.27; P=.006) and MS (ß=.17, 95% CI 0.03-0.31; P=.01). Occupational differences in sleep pattern were observed, with service staff experiencing longer TST (ß=.37, 95% CI 0.14-0.61; P=.004) and lower variability in TST (ß=-.15, 95% CI -0.27 to -0.05; P<.001). Engaging in PA later in the day was associated with longer TST (ß=.03, 95% CI 0.02-0.04; P<.001) and less variability in TST (ß=-.01, 95% CI -0.02 to 0.00; P=.02). Higher intradaily variability in rest activity rhythm was associated with shorter TST (ß=-.26, 95% CI -0.29 to -0.23; P<.001), earlier MS (ß=-.29, 95% CI -0.33 to -0.26; P<.001), and reduced variability in TST (ß=-.16, 95% CI -0.23 to -0.09; P<.001). CONCLUSIONS: Our study provided a comprehensive view of the factors affecting sleep patterns during the late stage of the pandemic. As we navigate the future of work after the pandemic, understanding how work arrangements, lifestyle choices, and sleep quality interact will be crucial for optimizing well-being and performance in the workforce.

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Sleep, an intrinsic aspect of human life, is experienced by individuals differently which may be influenced by personality traits and characteristics. Exploring how these traits influence behaviors and sleep routines could be used to inform more personalized and effective interventions to promote better sleep. Our objective was to summarize the existing literature on the relationship between personality traits and sleep patterns through a systematic review. An abstract and keyword search was conducted in PsycINFO, Cochrane and PubMed, collecting relevant literature, published between January 1980 and June 2024. A total of 1713 records were found, of which 18 studies were analyzed in the descriptive synthesis. Relevant studies covered populations in 11 different countries, Australia, China, Estonia, Finland, Germany, Italy, Japan, Poland, Turkey, the United Kingdom, and the United States, comprising a total of 58,812 subjects. All studies reported an association between a sleep pattern with at least one of the Big Five personality traits (agreeableness, conscientiousness, extraversion, neuroticism, openness to experience). Ten studies found associations between personality and sleep quality, all of which reported a link between neuroticism and sleep quality (effect sizes 0.183-0.40). Five studies found an association between conscientiousness and morningness (effect sizes 0.16-0.35). Other sleep patterns linked to personality traits included sleep duration, nightmare frequency and distress, sleep deficiency, sleep continuity, insomnia severity and sleep problems, sleep hygiene, sleep latency and daytime sleepiness. This novel systematic review confirms that sleep and personality traits are related, suggesting that those traits should be considered when trying to understand or change one's sleep behavior.

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While lifestyle choices or behavioral patterns remain the most significant factors influencing cancer risk, environmental exposure to certain chemicals, both manufactured and natural, may also contribute to an individual's likelihood of developing cancer. This interplay of factors, coupled with an aging demographic and shifting lifestyle patterns, has led to an increasing prevalence of cancer in recent years. This study examines the environmental and behavioral factors that contribute to anomalies in the immune system and increase the risk of developing cancer. Significant environmental and occupational factors include the contamination of air and water, exposure to radiation, contact with harmful microorganisms and pathogens, and workplace exposure to carcinogens such as asbestos, certain chemicals, and industrial pollutants. Behavioral factors, such as food, physical activity, stress, substance misuse, and sleep patterns, have a substantial impact on immunological function and the likelihood of developing cancer. For example, pollutants like benzene and arsenic can disrupt immune function and raise the risk of developing cancer. Similarly, lifestyle variables such as inactivity and poor nutrition have been linked to an increased risk of cancer. Long-term stress and substance abuse can also decrease immunological responses, increasing the risk of developing cancer. The review underlines the complexities of examining gene-environment interactions, as well as the importance of using several perspectives to fully comprehend these pathways. Future investigations should emphasize improved methodology and larger sample sizes. Public health campaigns should aim to reduce human exposure to cancer-causing compounds known as carcinogens while also encouraging the adoption of healthy behaviors and habits. Tailored preventive approaches that account for individual genetic vulnerabilities have the potential to improve cancer prevention and treatment.

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Sleep is established as an essential physiological need that impacts physical, emotional, and cognitive functions profoundly. Physiologically, inadequate sleep weakens immune function, heightening susceptibility to infections and chronic illnesses such as obesity, diabetes, and cardiovascular diseases. Hormonal disruptions due to sleep loss further exacerbate metabolic dysregulation, contributing to weight gain and other health complications. Emotionally, sleep deprivation leads to mood disturbances, including increased irritability, heightened stress responses, and a greater likelihood of mood disorders like depression and anxiety. These effects are compounded by cognitive impairments such as reduced alertness, impaired memory consolidation, and compromised decision-making abilities, akin to the impairments caused by alcohol consumption. Motor skills and coordination also suffer, elevating the risk of accidents, particularly in high-stress environments. For older adults, sleep quality is closely linked to cognitive function and overall longevity. Optimal sleep patterns are associated with slower brain aging and improved health outcomes. However, sleep disorders exacerbate existing conditions such as epilepsy and asthma, necessitating interventions like cognitive behavioral therapy (CBT) and medications such as melatonin to mitigate their impact. Education emerges as a crucial tool in promoting healthier sleep habits across all age groups. Addressing misconceptions about sleep and integrating sleep health into public health policies are essential steps toward improving overall well-being. Additionally, lifestyle factors such as diet and physical activity play significant roles in regulating sleep patterns, further emphasizing the interconnectedness of sleep with broader health outcomes. In summary, the articles underscore the intricate mechanisms through which sleep influences physiological functions and advocate for comprehensive approaches to enhance sleep hygiene and mitigate the adverse effects of sleep deprivation on human health.

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PURPOSE: Previous studies have analyzed the characteristics and prevalence of sleep disturbances among Italian children. Less attention has been paid, however, to the factors involved in sleep disturbances in the first two years of life. The goals of the present study were, therefore: 1) to provide a developmental trajectory of Italian infants' night awakenings and duration during the first two years of life and 2) to analyze which factors affect night awakenings the most over time. METHODS: Data for this study were collected in the NASCITA cohort. During the well-child visits conducted at 6, 12, and 24 months, pediatricians asked parents to report if the child had any sleep disturbances, especially frequent night awakenings. Univariate and multivariable analyses were performed to test the association between child and family variables and the likelihood of frequent awakenings. RESULTS: 2973 toddlers, out of 5054 initially enrolled newborns, were included in this study; 875 (29.4 %) of whom presented frequent awakenings in at least one visit (peak of prevalence of 19.8 % at 12 months). Bed-sharing (adjusted OR 2.53; 95%CI:2.05-3.12) and living in the northern Italy (aOR 2.25; 95%CI:1.80-2.81) were the variables more strongly associated with an increased likelihood of frequent awakenings in the binomial logistic regression, while sleeping alone was associated with a decreased chance (aOR 0.62; 95%CI 0.45-0.89). A short sleep duration (<11 h/day) was reported for 801 (26.9 %) at 12 months, for 743 (25.0 %) at 24 months of age; in 383 cases, the short sleep duration was reported at both time points. An association was observed between frequent awakenings at 12 or 24 months and short sleep duration (OR 1.23; 95%CI 1.05-1.44 -ꭓ2 6.25, p = 0.012). CONCLUSIONS: The current study identified some early predictors of frequent awakenings during the first two years of life. Since optimal sleep practices in children are essential for their development, effective, early interventions must be defined and integrated into pediatric care practices.

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Age-related sleep disorders share common pathways with sarcopenia. Prospective data from Latin American populations are scarce, and the association between sleep disorders and sarcopenia in Chileans remains unknown. Thus, we aimed to study the longitudinal association between sleep disorders and sarcopenia in a cohort study of 1116 community-dwelling Chilean older people ≥60 years old from the ALEXANDROS cohorts. After the exclusion criteria, 318 subjects were followed. Sociodemographic data, self-reported chronic diseases, sedentarism, sleep characteristics, anthropometric measurements, handgrip strength, and muscle performance were assessed. Results indicated that at baseline, the prevalence of sarcopenia was 24.10% without gender differences, and the prevalence of self-reported sleep problems was 23.3%, higher in women (26.46% versus 17.15% in men). The adjusted Cox regression models for sarcopenia showed an association between sarcopenia, sleep disorders (HR = 2.08, 95% IC 1.14-3.80), and long sleep duration (HR = 2.42, 95% IC 1.20-4.91). After 8.24 years of follow-up, there were 2.2 cases of sarcopenia per 100 person-years. This study demonstrates that sleep disorders are an independent risk factor for sarcopenia in Chilean older people. The identification of sleep disorders through self-reported data provides an opportunity for early identification of risk and cost-effective sarcopenia prevention.

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Objective: This study aims to explore the relationship between sleep patterns and depressive symptoms among adolescents, examining variations in depressive symptoms across different sleep qualities, durations, and habits. Method: A cross-sectional survey was conducted, gathering data from 8,775 Chinese adolescents on their demographics, lifestyle habits, sleep quality and duration, and depressive symptoms. The association between sleep parameters and depressive symptoms was analyzed using multivariate logistic regression. Findings: The findings reveal a significant correlation between sleep quality/duration and depressive symptoms. Specifically, adolescents with poor sleep quality had higher depressive scores (mean score = 14.62, standard deviation = 5.71), significantly exceeding those with better sleep quality (mean score = 11.54, standard deviation = 4.69). Adolescents with shorter sleep duration also showed significantly higher depressive scores than those with moderate sleep duration. Importantly, adolescents experiencing both poor sleep quality and shorter sleep duration were at a significantly increased risk of depressive symptoms (OR = 4.04, 95% CI: 3.53-4.62, P < 0.001). Further analysis indicated that older age and lower family economic status were independent predictors of a higher risk of adolescent depression (OR = 1.22, 95% CI: 1.08-1.38, P = 0.001), whereas factors such as gender, ethnicity, residence, being an only child, and parental education levels were not statistically significant. Conclusion: Among Chinese adolescents, poor sleep quality and shorter sleep duration are independent predictors of higher depressive symptom scores. Adolescents experiencing both of these conditions simultaneously have a significantly increased risk of depressive symptoms. Furthermore, older age and lower family economic status are also significantly related to an increased risk of depression in adolescents. These findings emphasize the importance of improving sleep quality and optimizing sleep duration for the prevention of adolescent depression. They also suggest the need for a comprehensive approach that addresses the multifaceted factors influencing adolescent mental health, including sleep patterns and socioeconomic disparities.

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This study investigated the association between underweight and sleep in young females across their menstrual cycles. A lifestyle-monitoring survey was conducted among 38 female university students aged 18-24 years in Japan from January to December 2023. Sleep data from 28 participants were analysed. Participants were categorized into underweight (n = 10) and control (n = 18) groups based on a baseline body mass index cut-off of 18.5 kg m-2. Sleep parameters were assessed using a daily sleep questionnaire, sleep sensor mats, and urinary melatonin metabolites across their menstrual cycles. The results indicated no significant differences in sleep patterns between the underweight and control groups or menstrual cycle phases, as assessed using both the daily sleep questionnaire and the sleep sensor mats. However, underweight participants experienced more difficulty maintaining sleep during the follicular phase. Body mass index significantly correlated with sleep efficiency (rs = 0.52) and wake after sleep onset (rs = -0.56). While urinary melatonin metabolite levels did not differ significantly between the groups or menstrual cycle phases, decreased levels during the luteal phase were more prevalent in the underweight group (7 of 10 participants) than in the control group (3 of 13 participants). This study suggests an association between underweight and sleep quality, especially nocturnal awakening, in young females. These findings underscore the importance of considering sleep quality in the management of underweight young females to improve their overall health outcomes.

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Mosquitoes occupy a wide range of habitats where they experience various environmental conditions. The ability of some species, such as the tiger mosquito, Aedes albopictus, to adapt to local conditions certainly contributes to their invasive success. Among traits that remain to be examined, mosquitoes' ability to time their activity with that of the local host population has been suggested to be of significant epidemiological importance. However, whether different populations display heritable differences in their chronotype has not been examined. Here, we compared laboratory strains originating from 8 populations from 3 continents, monitored their spontaneous locomotor activity patterns, and analyzed their sleep-like states. Overall, all strains showed conserved diurnal activity concentrated in the hours preceding the crepuscule. Similarly, they all showed increased sleep levels during the morning and night hours. However, we observed strain-specific differences in the activity levels at each phase of the day. We also observed differences in the fraction of time that each strain spends in a sleep-like state, explained by variations in the sleep architecture across strains. Human population density and the latitude of the site of geographic origin of the tested strain showed significant effects on sleep and activity patterns. Altogether, these results suggest that Ae. albopictus mosquitoes adapt to local environmental conditions via heritable adaptations of their chronotype.

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Insufficient sleep on weekdays has become a societal norm, and studies have shown that sleep deprivation increases the risk of depression. Although individuals often resort to weekend catch-up sleep (CUS) as a compensatory measure, the present evidence supporting its efficacy in mitigating the risk of depression is limited. This article attempts to explore the relationship between CUS and depression. In this study, a total of 5510 participants were included, characterized into two groups: nondepressed (n = 5051) and depressed (n = 459), with data extracted from the National Health and Nutrition Examination Survey (NHANES). Compared with people without CUS, those practicing CUS exhibited a significantly lower risk of depression (OR = 0.81, P = 0.048). In subgroup analysis, this reduction effect was only observed in males (OR = 0.70, 95 % CI 0.05 to 0.99, P = 0.04), middle-aged (>40, ≤60) (OR: 0.57, 95 % CI: 0.40 to 0.81, P = 0.002), married or living with parents (OR: 0.61, 95 % CI: 0.44 to 0.86, P = 0.004), groups with three or more family members (OR: 0.69, 95 % CI: 0.52 to 0.93, P = 0.01), and individuals without alcohol intake (OR: 0.24,95 % CI: 0.09 to 0.67, P = 0.006). Therefore, in the realm of depression treatment, doctors may consider advising patients to get adequate sleep on weekends as part of their overall treatment plan. At the same time, individuals can also choose weekend sleep as a proactive strategy for regulating their psychological status.

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BACKGROUND: This study examines the association between traditional cardiovascular health (CVH) metrics and major adverse cardiovascular events (MACE) incidence in individuals with diverse sleep patterns. METHODS AND RESULTS: We analyzed data from 208 621 participants initially free of cardiovascular disease (CVD) in the UK Biobank study. Sleep patterns were assessed using scores for chronotype, duration, insomnia, snoring, and daytime dozing. Traditional CVH scores were derived from the Life's Simple 7 metrics. Cox proportional hazards multivariate regression assessed associations between distinct combinations of CVH and sleep scores and MACE, including nonfatal myocardial infarction, nonfatal stroke, and CVD mortality. Over a mean follow-up of 12.73 years, 9253 participants experienced incident MACE. Individuals with both a healthy sleep pattern and ideal CVH levels had the lowest MACE risk compared with those with a poor sleep pattern and poor CVH levels (hazard ratio, 0.306 [95% CI, 0.257-0.365]; P<0.001). Elevated CVH scores were associated with a reduced risk of MACE across different sleep patterns. Similar trends were observed for individual MACE components, heart failure, and all-cause mortality. These findings remained robust in sensitivity analyses and across various subgroups. CONCLUSIONS: In individuals without known CVD, maintaining a favorable sleep pattern and achieving optimal CVH levels, as measured by traditional metrics, were associated with the lowest MACE risk. Enhanced CVH significantly reduced CVD risk, even in individuals with a poor sleep pattern. These results emphasize the importance of considering multiple dimensions of sleep health alongside CVH to mitigate CVD risk. REGISTRATION: URL: https://www.ukbiobank.ac.uk; Unique identifier: 91090.

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STUDY OBJECTIVES: To investigate the role of longitudinal change of sleep patterns in the incidence of cardiovascular diseases (CVD). METHODS: Based on UK Biobank, a total of 18 172 participants were enrolled. Five dimensions of healthy sleep including early chronotype, sleep 7-8 hours/day, free of insomnia, no snoring, and no frequent excessive daytime sleepiness were used to generate a healthy sleep score (HSS) ranging from 0 to 5. Corresponding to the HSS of 0-1, 2-3, and 4-5, the poor, intermediate, and healthy sleep patterns were defined. Based on changes in HSS across assessments 1 and 2, we calculated the absolute difference of HSS. For the change in sleep patterns, we categorized five profiles (stable healthy, worsening, stable intermediate, optimizing, and stable poor sleep patterns). The outcomes were incidence of CVD including coronary heart disease (CHD) and stroke. We assessed the adjusted hazard ratios and 95% confidence intervals (CIs) by Cox hazard models. RESULTS: Compared with participants with stable poor patterns, those who improved their sleep patterns or maintained healthy sleep patterns had a 26% and 32% lower risk of CVD, respectively. Stable healthy sleep pattern was associated with a 29% and 44% reduced risk of CHD and stroke. Per unit, longitudinal increment of the HSS was related to an 8% lower risk of CVD and CHD. Compared with individuals with constant HSS, those with decreased HSS had a 13% higher risk of developing CVD. CONCLUSIONS: Optimizing sleep patterns and maintaining a healthy sleep pattern may reduce the risk of CVD.

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AIM: Sleep duration and bedtime may play a role in children's cardiometabolic health, but research is lacking. This study examined associations between sleep patterns and cardiometabolic risk factors in Swedish nine-year-olds. METHODS: This cross-sectional study used data from three studies, where identical outcome measures were conducted in 411 nine-year-olds, 51% boys, between 2016 and 2020. Sleep was assessed with wrist-worn accelerometers and sleep journals. Children were grouped based on meeting the sleep guidelines of 9-11 h and going to bed early or late based on the median bedtime. Analysis of covariance was used to examine associations between sleep patterns and cardiometabolic risk factors. RESULTS: Meeting sleep guidelines and going to bed early were associated with lower metabolic syndrome score (-0.15 vs. 0.42, p = 0.029), insulin resistance (0.30 vs. 0.60, p = 0.025) and insulin levels (6.80 vs. 8.87 mIU/L, p = 0.034), compared with their peers who did not meet the guidelines and went to bed later. When adjusting for total sleep time, analyses still showed associations with the metabolic syndrome score (-0.19 vs. 0.50, p = 0.011). CONCLUSION: The findings indicate that good sleep patterns could help mediate positive overall cardiometabolic health in children.

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Background Video gaming is increasingly popular among young adults, potentially affecting health and daily routines, especially sleep patterns. In Al-Ahsa, Saudi Arabia, the impact of video gaming on sleep and health among young adults is not well understood. This study aims to explore this relationship, focusing on how video gaming habits influence sleep patterns and associated health outcomes. Methods This cross-sectional survey utilized an adapted online questionnaire to gather data on demographics, video gaming habits, sleep patterns, and body mass index from young adults in Al-Ahsa. Statistical analysis, including descriptive statistics, chi-square tests, and multivariable logistic regression, was applied to examine the associations between video gaming habits and sleep sufficiency. Results The study included 302 participants, including 165 (54.6%) females. A majority reported playing video games for less than one hour daily (36.1%), with 82.5% preferring online gaming. Notably, 54.3% of participants slept more than six hours nightly, yet challenges with sleep initiation were evident, as 48.0% went to bed past midnight. Multivariable logistic regression highlighted significant factors affecting sleep sufficiency: participants who played games after completing tasks had 80% lower odds of sleep insufficiency compared to those who played before tasks. Overweight participants were found to be 7.7 times more likely to experience sleep insufficiency compared to their underweight peers. Conclusion The study underscores a complex relationship between video gaming habits and sleep patterns among young adults in Al-Ahsa, with significant health implications. It suggests the necessity for interventions promoting balanced gaming habits and improved sleep hygiene to mitigate adverse health outcomes.

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Objectives: To explore the behavior patterns of students and working adults regarding the duration and quality of sleep and water intake in an urban environment and to identify the relationship between nighttime sleep extent and water intake with mood and cognitive performance. Methods: This was a descriptive correlational study conducted at Islamic International Medical College, Riphah University at the Pathology department from March to June 2022. A total of 160 participants with age range of 20 to 50 years completed a self-report questionnaire regarding sleep patterns, water intake, and perceptions of mood, concentration, and memory. Analyzed the relationship between sleep duration, water intake, mood, mindfulness/concentration, and memory using Kendall's Tau-b correlation coefficient in SPSS 22. Results: A significant number (28.7%) of participants had a sleep duration of ≤ 6 hours, with 41.3% sleeping after midnight. 82.5% of the participants switch off-screen just before sleeping. 63.7% have a routine water intake of less than 2 L/day. An aberrant statistically significant negative correlation between total sleeping hours and mood (τb = -.313, p = 0.004) was identified, showing a negative effect on mood with a sleeping time of ≥ 9 hours when compared with the other two groups (6-9 hours, τb = - .689, p = 0.001, ≤ 6hours, τb = - .697, p = 0.001). A significant correlation between daily water intake and concentration was found, wherein a decrease in daily water intake showed a negative effect on concentration (τb = .289, p = 0.008). Conclusions: Sleep duration and water intake patterns may affect mood and cognitive performance. Regular sufficient nighttime sleep and adequate hydration may help improve cognitive functioning and mood.

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BACKGROUND: In a world filled with technology, there's concern about the impact of screen time on children and teenagers. A recent study of 11,875 children aged nine to 10 in the US explored how screen time affects mental health, behaviour, school performance, sleep, and friendships. The results indicate that more screen time is mildly linked to worse mental health, more behaviour problems, lower academic performance, and poorer sleep, but slightly better peer relationships. However, these connections were weak, with socioeconomic status (SES) having a stronger influence on these outcomes. The study doesn't prove that screen time causes these issues, suggesting that increased screen time might not be directly harmful to children in this age group. The research adds to the understanding of how screen time impacts children's well-being and highlights the importance of promoting healthy habits. Our study aims to add to this literature by examining how screen time impacts sleep quality, dream recall, and academic performance in school-aged children. Understanding the potential consequences of screen time is crucial for promoting healthy habits and ensuring the overall well-being of children. Our research seeks to provide further insights into the relationship between screen time and key aspects of children's lives as its prevalence continues to rise. METHODS: The research incorporates a cohort of 1000 school-aged children, bifurcated evenly into two categories based on their daily screen exposure: a low screen time group (less than one hour daily, n = 500) and a high screen time group (over three hours daily, n = 500). The study probes into the correlation between screen time and various health parameters, such as sleep patterns, dream recall, and academic prowess. RESULTS: The analysis showed that children with low screen time had better sleep efficiency (90% vs. 75%), more frequent dream recall (70% vs. 30%), fewer nocturnal awakenings (0.5 vs. 1.5 times weekly), less daytime sleepiness (20% vs. 60%), and higher physical activity levels (60 vs. 30 minutes per day) compared to those with high screen time. They also had less weekend sleep variability (1.2 hours) and a lower risk of circadian rhythm disturbances (20% increased risk in the high screen time group). Additionally, a screen-free bedroom was more common in the low screen time group (85% vs. 30%), and parental involvement in sleep routines was higher (90% vs. 40%). Academically, the low screen time group achieved higher grades ('A' to 'A+' vs. 'B'), and they had more face-to-face social interactions (two vs. one hour per day). CONCLUSION: Escalating screen time is correlated with detrimental impacts on sleep efficiency, dream recall, physical activity, circadian rhythms, and academic performance in school-aged children. Fostering a screen-free bedroom environment and augmenting parental involvement in sleep routines may alleviate these adverse effects.

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Sleep is crucial for health and development. Evidence indicates that sleep changes over time and distinct subgroups may experience different longitudinal patterns. This study systematically reviewed the studies that used latent trajectory modeling to investigate sleep trajectories of children and adolescents aged 0-18 years, and summarized the associated determinants and health-related outcomes. We searched PubMed, Embase, CENTRAL, PsycINFO, and Web of Science, identifying 46 articles that met our criteria. To ensure the reliability of the review, only studies rated as good or fair in terms of methodological quality were included, resulting in a total of 36 articles. Group-based trajectories were identified on several sleep dimensions (i.e., sleep duration, general and specific sleep problems, and bed-sharing behavior) and three or four trajectories were reported in most studies. There was a convergence trend across sleep duration trajectories during the first six years of life. Studies on specific sleep problem (i.e., insomnia, night-waking, and sleep-onset difficulties) typically identified two trajectories: consistent, minimal symptoms or chronic yet fluctuating symptoms. Lower socioeconomic status, maternal depression, and night feeding behaviors were the most frequently reported determinants of sleep trajectories. Membership in a group with certain adverse patterns (e.g., persistent short sleep duration) was associated with increased risks of multiple negative health-related conditions, such as obesity, compromised immunity, neurological problems, substance use, or internalizing/externalizing symptoms. Generally, there is potential to improve the quality of studies in this field. Causality is hard to be inferred within the current body of literature. Future studies could emphasize early life sleep, incorporate more assessment timepoints, use objective measures, and employ experimental design to better understand changes of and mechanisms behind the various sleep trajectories and guide targeted interventions for at-risk subpopulations.

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Cardiovascular diseases (CVDs) are evolving as a cause of mortality and morbidity among young adults. Young adults, particularly those pursuing professional courses in colleges, face unique challenges that may influence their risk of developing CVD. Despite screening guidelines, CVD risk factors often go undetected in the young population, highlighting the need for increased awareness among adolescents. Sleep is an essential indicator of well-being, and its impact on cardiovascular risk factors is increasingly being recognized. An observational cross-sectional study was conducted among young adults aged 18 to 24 years pursuing professional courses in Dehradun, Uttarakhand, India. A total of 156 participants were recruited through multistage, systematic random sampling, and snowball sampling. Data on sleep patterns and cardiovascular morbidity were collected using a pretested questionnaire. Among the study participants, 46.8% reported having less than four hours of sleep on average, and 25% were suffering from sleep problems. The prevalence of diagnosed CVDs was low, with 6.14% reporting arrhythmias and 3.84% reporting hypertension. An association was found between sleep duration, sleep problems, and the presence of CVDs. Participants with shorter sleep durations and more severe sleep problems had a higher prevalence of CVDs. The findings suggest that sleep duration and sleep problems may be modifiable risk factors for CVDs among young adults. Effective health promotion activities focusing on behavior and lifestyle modifications are essential to preventing CVDs from an early age. The study emphasizes the importance of early intervention and health promotion strategies to reduce CVD risk factors in this population. Community-based research and behavior change communication initiatives are recommended to promote healthy sleep habits and prevent cardiovascular diseases among young adults beyond the college setting.