Healthy Sleep Patterns Research Articles

Sleep Patterns, Genetic Susceptibility, and Incident Chronic Kidney Disease: A Prospective Study of 370 671 Participants

ObjectivesUnhealthy sleep behaviors may be potential risk factors for chronic kidney disease (CKD). We aimed to examine the associations of combined sleep patterns and genetic susceptibility with incident CKD.MethodsThis large-scale prospective cohort study included 370,671 participants without CKD at baseline (2006–2010) in UK Biobank data. Five sleep behaviors were made up of sleep duration, insomnia, snoring, chronotype, and daytime sleepiness according to questionnaire. Overall sleep patterns by summing the five scores were created. Weighted genetic risk score of kidney function was calculated. Incident CKD was recorded from death register, primary care, and hospital inpatient records. A subset of 41,130 individuals who participated both the initial assessment visit and follow-up visit (2012+) was also used.ResultsDuring a median follow-up of 10.6 years (about 3.9 million person-years), we documented 6,365 patients with incident CKD. In five sleep behaviors, sleep 7–8 h/day, free of insomnia and no frequent daytime sleepiness were independently associated with incident CKD, with a 12% (95%CI 7–16), 9% (3–14), 13% (9–18) lower risk, respectively. Compared to those with a sleep score of 0–1, participants with a score of 5 had a 21% (10–31%) lower risk of CKD. 17.1% of CKD in this cohort could be attributed to total poor sleep pattern. Participants with high genetic risk and intermediate or poor sleep pattern showed the highest risk of CKD (OR = 2.58, 95%CI 2.24–2.96; OR = 2.59, 95%CI 2.02–3.32, respectively), although there was no significant interaction between sleep patterns and genetic risk categories. Among individuals who participated both the initial assessment visit and follow-up visit, we found that the association between amelioration of sleep pattern and risk of CKD was significant after fully adjustment (OR = 0.60, 95%CI 0.36–0.99), compared with group of stable sleep pattern.ConclusionIn this large prospective study, participants with a healthy sleep pattern was associated with a significant reduction of incident CKD risk no matter they had a high, intermediate, or low genetic risk.

Relationship between sleep pattern and bone mineral density in patients with osteoporotic fracture.

Background:Evidence investigating sleep pattern in relation to bone health in elderly participants with osteoporosis remains sparse. We aimed to assess the relationship between sleep pattern incorporating five sleep characteristics (snoring, midnight waking up, insomnia, sleep duration, and daytime napping) and bone mineral density (BMD) in elderly participants with osteoporotic fracture.Methods:A cross-sectional study was conducted to include eligible elderly patients from the Department of Orthopedics who were admitted to hospital due to an osteoporotic fracture. Sleep pattern was constructed based on total sleep scores and categorized into healthy, intermediate, and poor pattern groups. Multivariable logistic regression model was used to assess sleep pattern in relation to risk of low BMD.Results:A total of 169 elderly patients with osteoporotic fracture were included in this study (mean age: 71.91 years; 87.57% females). There were 36 (21.30%), 107 (63.31%), and 26 (15.38%) patients with healthy, intermediate, and poor sleep pattern, respectively. Compared with healthy sleep pattern, no significant relationship between intermediate sleep pattern and BMD was detected [odds ratio (OR) = 1.72, 95% confidence interval (CI): 0.74, 3.97, p = 0.21), while poor pattern was significantly associated with decreased BMD (OR = 3.50, 95% CI: 1.10, 11.14, p = 0.034).Conclusion:The majority of elderly patients with osteoporotic fracture had unhealthy sleep pattern; poor sleep pattern was significantly related to reduced BMD when compared with healthy pattern. Further high-quality evidence is needed to assess and validate the relationship between sleep pattern and risk of low BMD in the elderly.

The association between sleep and depressive symptoms in US adults: data from the NHANES (2007-2014).

To assess the association of sleep factors (sleep duration, trouble sleeping, sleep disorder) and combined sleep behaviours with the risk of clinically relevant depression (CRD). A total of 17 859 participants (8806 males and 9053 females) aged 20-79 years from the National Health and Nutrition Examination Survey (NHANES) 2007-2014 waves were included. Sleep duration, trouble sleeping and sleep disorder were asked in the home by trained interviewers using the Computer-Assisted Personal Interviewing (CAPI) system. The combined sleep behaviours were referred to as 'sleep patterns (healthy, intermediate and poor)', with a 'healthy sleep pattern' defined as sleeping 7-9 h per night with no self-reported trouble sleeping or sleep disorders. And intermediate and poor sleep patterns indicated 1 and 2-3 sleep problems, respectively. Weighted logistic regression was performed to evaluate the association of sleep factors and sleep patterns with the risk of depressive symptoms. The total prevalence of CRD was 9.5% among the 17 859 participants analysed, with females having almost twice as frequency than males. Compared to normal sleep duration (7-9 h), both short and long sleep duration were linked with a higher risk of CRD (short sleep: OR: 1.66, 95% CI: 1.39-1.98; long sleep: OR: 2.75, 95% CI: 1.93-3.92). The self-reported sleep complaints, whether trouble sleeping or sleep disorder, were significantly related with CRD (trouble sleeping: OR: 3.04, 95% CI: 2.59-3.56; sleep disorder: OR: 1.83, 95% CI: 1.44-2.34). Furthermore, the correlations appeared to be higher for individuals with poor sleep pattern (OR: 5.98, 95% CI: 4.91-7.29). In this national representative survey, it was shown that there was a dose-response relationship between sleep patterns and CRD.

Adherence to a Healthy Sleep Pattern and Risk of Chronic Kidney Disease: The UK Biobank Study

ObjectiveTo examine the association of a healthy sleep pattern, characterized by sleep of 7 to 8 h/d, morning person, no insomnia, no frequent snoring, and no daytime sleepiness, with the risk of chronic kidney disease (CKD). MethodsWe included 392,218 European adults, aged 38 to 73 years, who were free of CKD at recruitment between March 13, 2006, and October 1, 2010, from the UK Biobank study. Data on sleep behaviors were collected through questionnaires at recruitment. Cox proportional hazards regression models were used to assess the relations between the healthy sleep score and risk of CKD. ResultsWe identified 18,842 incident CKD cases after a mean follow-up of 11.1 (SD 2.2) years. The healthy sleep score was inversely associated with the risk of CKD in a dose-dependent manner (P for trend, <.001). Compared with the participants with a poor sleep pattern (score of 0-1), the multivariate adjusted hazard ratio of CKD was 0.77 (95% CI, 0.71 to 0.84) for those with the healthiest sleep pattern (score of 5). In addition, we found that the inverse association was stronger in individuals without history of hypertension compared with individuals with hypertension at baseline (P for interaction, .003) and in those 60 years of age or younger compared with their older counterparts (P for interaction, <.001). ConclusionOur data suggest that adherence to an overall healthy sleep pattern is associated with a lower risk of CKD, especially for individuals without history of hypertension and those who are younger.

Healthy Sleep Patterns and Common Mental Disorders Among Individuals with Stable Cardiovascular Disease: A Prospective Cohort Study

Healthy Sleep Patterns and Common Mental Disorders Among Individuals with Stable Cardiovascular Disease: A Prospective Cohort Study

Socio-psychological features of correction of adolescents’ emotional stress in the family

This article gives information about the socio-psychological features of adolescents’ emotional stress in the family and the ways of getting rid of stress for both parents and adults. Adolescence is an important period for developing social and emotional habits which are lifeblood for mental well-being. Adopting healthy sleep patterns, exercising regularly and developing coping are included in these habits.

Unilateral colonization of fungal infection presenting as renal mass in young patient: A case report

Getting a sufficient quantity of sleep is an important aspect of maintaining a healthy sleep pattern. A good night-sleep is the natural cure for all health problems. Sleeping disorders affect people of all ages, although adults (18-60) are the most common sufferers these days. If a person does not get enough sleep during the day, he or she may develop major health problems such as high blood pressure, high sugar, and drowsiness most of time. As a result, the person may develop Parkinson’s disease, Alzheimer’s disease, or insomnia, among other ailments. The sleep cycle is normally divided into two stages i.e. NON REM and REM. Depending on the age category, the entire cycle takes between 7 - 10 hours to complete. The REM stage will take 90 minutes to complete. This stage is regarded as the most powerful stage of the sleep cycle. This aids in improving one’s ability to memorise information. An experiment using a mouse as a model organism has shown that REM sleep can help a person retain things for a long time even when brain activity is silenced, whereas optogenetically manipulating the brain can help patients to forget events that occurred before sleep. To obtain optimal health, a person needs to take adequate sleep on a daily basis. Keywords: hypothalamus; memory; neuronal modulation; optogenetic activity; sleep; synapse.

Association of healthy lifestyle including a healthy sleep pattern with incident type 2 diabetes mellitus among individuals with hypertension

BackgroundEvidence is limited regarding the association of healthy lifestyle including sleep pattern with the risk of complicated type 2 diabetes mellitus (T2DM) among patients with hypertension. We aimed to investigate the associations of an overall healthy lifestyle including a healthy sleep pattern with subsequent development of T2DM among participants with hypertension compared to normotension, and to estimate how much of that risk could be prevented.MethodsThis study examined six lifestyle factors with T2DM cases among hypertension (227,966) and normotension (203,005) and their interaction in the UK Biobank. Low-risk lifestyle factors were defined as standard body mass index (BMI), drinking alcohol in moderation, nonsmoking, engaging in moderate- to vigorous-intensity physical activity, eating a high-quality diet, and maintaining a healthy sleep pattern.ResultsThere were 12,403 incident T2DM cases during an average of 8.63 years of follow-up. Compared to those with 0 low-risk lifestyle factors, HRs for those with 5–6 were 0.14 (95% CI 0.10 to 0.19) for hypertensive participants, 0.13 (95% CI 0.08 to 0.19) for normotensive participants, respectively (ptrend < 0.001). 76.93% of hypertensive participants were considerably less likely to develop T2DM if they adhered to five healthy lifestyle practices, increased to 81.14% if they followed 6-factors (with a healthy sleep pattern). Compared with hypertension adults, normotensive people gain more benefits if they stick to six healthy lifestyles [Population attributable risk (PAR%) 83.66%, 95% CI 79.45 to 87.00%, p for interaction = 0.0011].ConclusionsAdherence to a healthy lifestyle pattern including a healthy sleep pattern is associated with lower risk of T2DM in hypertensives, and this benefit is even further in normotensives.

Observational and genetic evidence highlight the association of human sleep behaviors with the incidence of fracture

We combined conventional evidence from longitudinal data in UK Biobank and genetic evidence from Mendelian randomization (MR) approach to infer the causality between sleep behaviors and fracture risk. We found that participants with insomnia showed 6.4% higher risk of fracture (hazard ratio [HR] = 1.064, 95% CI = 1.038–1.090, P = 7.84 × 10−7), falls and bone mineral density (BMD) mediated 24.6% and 10.6% of the intermediary effect; the MR analyses provided the consistent evidence. A U-shape relationship was observed between sleep duration and fracture risk (P < 0.001) with the lowest risk at sleeping 7–8 h per day. The excessive daytime sleepiness and “evening” chronotype were associated with fracture risk in observational study, but the association between chronotype and fracture did not show in MR analyses. We further generated a sleep risk score (SRS) with potential risk factors (i.e., insomnia, sleep duration, chronotype, and daytime sleepiness). We found that the risk of fracture increased with an increasing SRS (HR = 1.087, 95% CI = 1.065–1.111, P = 1.27 × 10−14). Moreover, 17.4% of the fracture cases would be removed if all participants exhibited a healthy sleep pattern. In conclusion, insomnia had a causal effect on fracture, falls had a larger intermediary effect than BMD in this association. Individuals with fracture risk could benefit from the intervention on unhealthy sleep pattern.

Association of sleep and circadian patterns and genetic risk with incident type 2 diabetes: a large prospective population-based cohort study.

To examine the association of incident type 2 diabetes (T2D) risk with sleep factors, genetic risk, and their combination effects. Large prospective population-based cohort study. This population-based prospective cohort study included 360 403 (mean (s.d.) age: 56.6 (8.0) years) participants without T2D at baseline from the UK Biobank. Genetic risk was categorised as high (highest quintile), intermediate (quintiles: 2-4), and low (lowest quintile) based on a polygenic risk score for T2D. Sleep scores, including long or short sleep duration, insomnia, snoring, late chronotype, and excessive daytime sleepiness, were categorized as an unfavourable, intermediate, or favourable sleep and circadian pattern. During a median follow-up of 9.0 years, 13 120 incident T2D cases were recorded. Among the participants with an unfavourable sleep and circadian pattern, 6.96% (95% CI: 6.68-7.24%) developed T2D vs 2.37% (95% CI: 2.28-2.46%) of participants with a favourable sleep and circadian pattern (adjusted hazard ratio (HR): 1.53, 95% CI: 1.45-1.62). Of participants with a high genetic risk, 5.53% (95% CI: 5.36-5.69%) developed T2D vs 2.01% (95% CI: 1.91-2.11%) of participants with a low genetic risk (adjusted HR: 2.89, 95% CI: 2.72-3.07). The association with sleep and circadian patterns was independent of genetic risk strata. Participants in the lowest quintile with an unfavourable sleep and circadian pattern were 3.97-fold more likely to develop T2D than those in the lowest quintile with a favourable sleep and circadian pattern. Sleep and circadian patterns and genetic risk were independently associated with incident T2D. These results indicate the benefits of adhering to a healthy sleep and circadian pattern in entire populations, independent of genetic risk.

Sleep pattern and bone mineral density: a cross-sectional study of National Health and Nutrition Examination Survey (NHANES) 2017-2018.

Accumulated evidence demonstrates that sleep duration, which is one aspect of sleep pattern, is associated with the risk of osteoporosis. However, the related studies on the association between sleep patterns and the risk of osteoporosis were limited. Therefore, this research aims to investigate the association of sleep patterns with BMD and the risk of osteoporosis among individuals aged 50years and older. Participants aged ≥ 50years from the NHANES database were included in the present study. The diagnosis of osteoporosis was based on the results of BMD testing. Moreover, all the participants were divided into different sleep pattern groups according to nocturnal sleep duration and bedtime. In addition, this study used multivariate linear regression models to evaluate the association between sleep patterns and BMD and exploited multiple logistic regression models to investigate the odds ratios (ORs) for osteoporosis. Finally, 1,865 individuals (non-osteoporosis: N = 1,713; osteoporosis: N = 152) aged over 50years old with complete data were analyzed. The results of multivariate linear regression models showed that individuals with normal sleep duration/later bedtime or long sleep duration/later bedtime had lower femoral BMD than those with normal sleep duration/usual bedtime. Moreover, subjects with long sleep duration/later bedtime had a higher risk of osteoporosis compared with those with normal sleep duration/usual bedtime. In addition, subgroup analyses revealed the association of sleep patterns with BMD and the risk of osteoporosis appeared to be more pronounced among individuals aged ≥ 65years or females. This study demonstrated that sleep patterns are associated with BMD and the risk of osteoporosis. Poor sleep patterns contribute to decreased bone mass and the increased risk of osteoporosis. Therefore, a healthy sleep pattern is favorable for the prevention of osteoporosis.

Healthy Sleep Patterns and Risk of Incident Arrhythmias

BackgroundEmerging evidence has linked sleep behaviors with the risk of cardiac arrhythmias. The various sleep behaviors are typically correlated; however, most of the previous studies only focused on the individual sleep behavior, without considering the overall sleep patterns. ObjectivesThe purpose of this study was to prospectively investigate the associations between a healthy sleep pattern with the risks of cardiac arrhythmias. MethodsA total of 403,187 participants from UK Biobank were included. A healthy sleep pattern was defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness. Weighted genetic risk score for atrial fibrillation was calculated. ResultsThe healthy sleep pattern was significantly associated with lower risks of atrial fibrillation/flutter (AF) (HR comparing extreme categories: 0.71; 95% CI: 0.64-0.80) and bradyarrhythmia (HR: 0.65; 95% CI: 0.54-0.77), but not ventricular arrhythmias, after adjustment for demographic, lifestyle, and genetic risk factors. Compared with individuals with a healthy sleep score of 0-1 (poor sleep group), those with a healthy sleep score of 5 had a 29% and 35% lower risk of developing AF and bradyarrhythmia, respectively. Additionally, the genetic predisposition to AF significantly modified the association of the healthy sleep pattern with the risk of AF (P interaction = 0.017). The inverse association of the healthy sleep pattern with the risk of AF was stronger among those with a lower genetic risk of AF. ConclusionsOur results indicate that a healthy sleep pattern is associated with lower risks of AF and bradyarrhythmia, independent of traditional risk factors, and the association with AF is modified by genetic susceptibility.

Associations of Dietary Pattern and Sleep Duration with Cognitive Decline in Community-Dwelling Older Adults: A Seven-Year Follow-Up Cohort Study.

A few studies have linked dietary patterns and sleep to cognitive decline. To examine the independent and joint associations of dietary patterns and sleep with cognitive decline. Our analysis included 2,307 participants aged 55- 89 years at baseline from the China Health and Nutrition Survey. Dietary intake was assessed using weighing methods in combination with 24 h dietary recalls for three consecutive days. Exploratory factor analysis was applied to identify major dietary factors. Cognition was assessed in 1997, 2000, 2004, 2006, and 2015. Five dietary patterns were identified: dairy-fruits-fast foods, grains-vegetables-pork, plant-based food, beans-mushroom, and beverages-nuts patterns. Beans-mushroom pattern and sleep duration of 8 h/day were defined as healthy habits. There was a positive association between the beans-mushroom pattern and change in the global cognitive Z-score over seven years (β (95% CI) for quintile 5 versus quintile 1:0.17 (0.05, 0.30)). Compared to individuals with sleep duration of 8 h/day, those with sleep duration of≤5 h/day (β (95% CI): - 0.23 (- 0.45, - 0.00)) or > 10 h/day (- 0.52 (- 0.73, - 0.32)) had a greater decrease in global cognitive Z-score. Compared to individuals with no healthy patterns, those with a healthy dietary pattern only (β (95% CI): 0.18 (0.08, 0.28)), healthy sleep pattern only (0.13 (0.04, 0.23), and both healthy dietary and sleep patterns (0.19 (0.08, 0.31)) had a relative increase in global cognitive Z-score. Our findings highlight the importance of involving both diet and sleep as intervention priorities for the potential prevention of cognitive decline.

Adherence to a healthy sleep pattern is associated with lower risks of all-cause, cardiovascular and cancer-specific mortality.

Individual unhealthy sleep behaviours have been associated with increased risks of all-cause mortality and deaths due to cardiovascular disease (CVD) or cancer. The evidence regarding the association of sleep patterns with these risks is limited. To examine the associations of sleep patterns with all-cause, CVD and cancer mortality in a large prospective cohort. This prospective cohort study included 283,443 adults from UK Biobank without CVD and cancer at baseline. We created a healthy sleep score and sleep patterns combining five individual sleep behaviours. During a mean (standard deviation) of 8.9 (1.1) years (2.5 million person-years) of follow up, a total of 7936 all-cause deaths, 762 CVD-caused deaths, and 4540 cancer-caused deaths occurred during follow up. One point increase of the healthy sleep score was associated with a 4-11% lower risk of all-cause mortality (Hazard Ratio [HR], 0.94; 95% CI, 0.92-0.96), CVD mortality (HR, 0.89; 95% CI, 0.83-0.95) and cancer mortality (HR, 0.96; 95% CI, 0.93-0.99), with adjustment for age, sex, assessment centres, smoking status, alcohol intake status, socioeconomic status and physical activity. Compared with participants with an unfavourable sleep pattern, those with a favourable sleep pattern had 24-42% lower risks of all-cause and CVD mortality. The association with all-cause mortality tended to be stronger among underweight participants and those with insufficient physical activity. A healthy sleep pattern was associated with lower risks of all-cause mortality and mortality from CVD and cancer. Our findings highlight the importance of improving overall sleep behaviours in lowering mortality.

Relationship between Sleep and Hypertension: Findings from the NHANES (2007-2014).

Background: To evaluate the association of sleep factors (sleep duration, self-reported trouble sleeping, diagnosed sleep disorder) and combined sleep behaviors with the risk of hypertension. Methods: We analyzed 12,166 adults aged 30–79 years who participated in the 2007–2014 National Health and Nutrition Examination Survey. Sleep duration, self-reported trouble sleeping and sleep disorders were collected using a standardized questionnaire. We included three sleep factors (sleep duration, self-reported trouble sleeping and sleep disorder) to generate an overall sleep score, ranging from 0 to 3. We then defined the sleep pattern as “healthy sleep pattern” (overall sleep score = 3), “intermediate sleep pattern” (overall sleep score = 2), and “poor sleep pattern” (0 ≤ overall sleep score ≤ 1) based on the overall sleep score. The definition of hypertension was based on self-reported antihypertensive medication use or biological measurement (systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg). We used weighted logistic regression models to investigate the associations between sleep and hypertension. Results: The overall prevalence of hypertension was 37.8%. A short sleep duration (OR = 1.20, 95% CI: 1.08 to 1.33, p = 0.001), self-reported trouble sleeping (OR = 1.45, 95% CI: 1.28 to 1.65, p < 0.001) and sleep disorder (OR = 1.33, 95% CI: 1.07 to 1.66, p = 0.012) were related to the risk of hypertension. Poor sleep patterns were closely correlated with the risk of hypertension (OR = 1.90, 95% CI: 1.62 to 2.24). Conclusions: Participants with poor sleep patterns were associated with an increased risk for hypertension.

Associations Between Sleep Quality and Health Span: A Prospective Cohort Study Based on 328,850 UK Biobank Participants.

ObjectiveTo examine the associations between sleep quality and health span using a prospective cohort design based on the UK Biobank (UKB).Materials and MethodsThis longitudinal cohort study enrolled 328,850 participants aged between 37 and 73 years from UKB to examine the associations between sleep quality and risk of terminated health span. End of health span was defined by eight events strongly associated with longevity (cancer, death, congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, and diabetes), and a sleep score was generated according to five sleep behavioral factors (sleep duration, chronotype, sleeplessness, daytime sleepiness, and snoring) to characterize sleep quality. The hazard ratio (HR) and 95% confidence intervals (CIs) were calculated by multivariate-adjusted Cox proportional hazards model. Moreover, we calculated population attributable risk percentage (PAR%) to reflect the public health significance of healthy sleep quality.ResultsCompared with poor sleep quality, participants with healthy sleep quality had a 15% (HR: 0.85, 95% CI: 0.81–0.88) reduced risk of terminated health span, and those of less-healthy sleep quality had a 12% (HR: 0.88, 95% CI: 0.85–0.92) reduced risk. Linear trend results indicated that the risk of terminated health span decreased by 4% for every additional sleep score. Nearly 15% health span termination events in this cohort would have been prevented if a healthy sleep behavior pattern was adhered to (PAR%: 15.30, 95% CI: 12.58–17.93).ConclusionHealthy sleep quality was associated with a reduced risk of premature end of health span, suggesting healthy sleep behavior may extend health span. However, further studies are suggested for confirmation of causality and potential mechanism.

Introducing Sleep Hygiene to the Church of Sidang Jemaat Allah Bethlehem Congregation, Bogor, West Java

Insomnia is one of the most common health problems. Approximately one-third of adults show symptoms related to insomnia. Around 9%-15% of people have sleeping disorders dan suffer the consequences of it in the daytime, and roughly 6% suffer from diagnosed insomnia. Although the prevalence and significant effects of insomnia have been known, sleep disorders are still rarely diagnosed and receive proper treatments. Lack of sleep will create sleep debt that the body will have to compensate for by adding more sleep time in the next day. Should this compensation fail to be fulfilled, the individual will suffer from excessive sleepiness, memory problems, difficulty concentrating, and disturbances in performing daily activities. Chronic lack of sleep can also decrease memory and cognitive abilities, trigger mood disorders and even cause hallucination. The Sidang Jemaat Allah Bethlehem church (GSJA) is one of the biggest churches in Bogor. The people of GSJA’s knowledge of healthy sleep patterns and their sleep quality was unknown. Therefore, it was necessary to provide sleep health education to raise the awareness of the importance of healthy sleep patterns, both the quantity and the quality, in practicing a healthy lifestyle. We also assessed their sleep quality using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. The data show that out of 41 participants, 30 of them (73.11%) have poor sleep quality (score ≥ 5) and most of them were in the 71-80-year-old age group. The participants' level of understanding about sleep hygiene has increased after the event.

Sleeping patterns and childhood obesity: an epidemiological study in 1,728 children in Greece.

Sleep is an essential normal function for children's growth and development, but over the years, lifestyle changes have resulted in insufficient sleep, a factor that may be associated with increased childhood obesity. The aim of this study was to evaluate the association between sleep duration and sleep patterns separately on weekdays and weekends regarding children's weight status. This study was conducted among Greek students (55.1% girls) in 2014-2016. Children's weight status was classified according to the International Obesity Task Force tables and guidelines. Sleep duration was determined based on the sleep and wake time that children reported, separately for weekdays and weekends. Classification and regression tree analysis was used to derive sleep patterns and evaluate their relation to children's weight status. Multiadjusted analysis revealed an inverse association between average duration of sleep on weekdays and weekends with the likelihood of being overweight/obese (odds ratio per 1 hour 0.82; 95% confidence interval, 0.73-0.92). This was more prominent on weekends than on weekdays. Children who had lower duration on weekdays, but catch-up sleep duration on weekends, were 2% (95% confidence interval, 0.97-0.99) less likely to be overweight/obese compared to those children having both less or increased sleep duration on weekdays and weekends. Sleep duration and sleep patterns seem to be associated with childhood weight status. Interventions should be developed to educate parents on the importance of an adequate sleep duration and healthy sleep patterns for their children's healthy development.

Variation in Sleep Pattern Due to Lockdown among Collegiate Students

Background: Due to the vast spread of corona virus, lockdown was announced in many countries, andhence many people are facing psychological, physical, economic and social changes. Students at the collegeexperience a variety of sleep problems which can have a direct effect on academic success, health and mood.Sleep disruption and excessive daytime sleep are common problems for students.Subject and Method: 141 college students between the age of 17 to 24 were taken from various colleges.The structured Pittsburgh Sleep Quality Index was used and was circulated amongst students through Googleforms and the sleep log, and demographic sheet was used to test sleep length, daytime sleepiness and relatedsleep issues.Study Design: A cross sectional study.Results: The result, on the basis of the sleep pattern of college students, was classified into 5 categories:(healthy sleep pattern, mild, moderate, severe and worst). 53.90% out of 141 respondents o had healthy sleeppattern range (0-5), 39.71% had mild sleep pattern range (6-10), 4.96% out of 141 respondents had moderatesleep pattern range (11-15), and 1.41% out of 141 respondents had severe sleep pattern range (16-20).Conclusion: In our study we found that during the lockdown majority of college students had a healthysleep pattern and least of the college students had a severe sleep pattern range.

The influence of remote learning on sleep patterns of teenagers

A healthy sleep pattern is crucial to the overall health and wellbeing of teenagers, and poor sleep patterns can harm school performance. Due to stay-at-home orders mandated by the governor of Ohio in March 2020, students were converted to remote learning. The purpose of this study was to compare the sleep patterns of teenagers before the stay-at-home orders and during remote learning. Individual chronotypes impact peak productivity, and remote learning imposed by the COVID-19 pandemic provides a unique opportunity to study how teenagers may take advantage of their chronotype for optimal learning. Data was collected using an online survey distributed to teenagers in the Greater Cincinnati area. The survey completed by 141 participants compared teenagers' overall sleep habits and attitude towards school before and during the remote learning period. During the stay-at-home orders, teenagers participating in remote learning extended their sleep duration by 1-2 hours, resulting in 83% of surveyed teenagers receiving healthy sleep amounts and 55% reporting feeling more rested. Sleep patterns of teenagers were also altered by the stay-at-home orders, as seen by the significant shift to later bedtimes and wake times. Later wake times and bedtimes align with the self-reported night owl chronotype reported by a majority of respondents. These results can help create more effective learning periods for adolescents that optimize personal chronotype.