Average Sleep Research Articles

STUDY ON SOME ANTHROPOMETRIC CHARACTERISTICS AND LEARNING OUTCOMES OF THE SECOND YEAR MEDICAL STUDENTS WITH OBSTRUCTIVE SLEEP APNEA RISK AT CAN THO UNIVERSITY OF MEDICINE AND PHARMACY

Background: Obstructive sleep apnea (OSA) is a condition characterized by repeated pauses in breathing during sleep, which is frequently accompanied by snoring, daytime sleepiness, and decreased concentration. Several scales, including the STOP-BANG and EPWORTH scores, have been developed to screen people at high risk for OSA. There have been few studies on both OSA risk and anthropometric characteristics, academic performance in student populations, particularly medical students. Objectives: (1) Determine the proportion of medical students at risk of OSA based on STOP-BANG score, EPWORTH score, and their academic performance; and (2) Survey the association between some anthropometric characteristics, STOP-BANG score, daytime sleepiness, and poor academic performance of second-year medical students. Materials and method: A descriptive cross-sectional study was conducted on 565 second-year medical students at Can Tho University of Medicine and Pharmacy. Results: Our study included 565 students, 44.4% of whom were male. The average BMI was 21.0 kg/m2, the mean neck circumference was 32.9 cm, the mean waist circumference was 73.2 cm, the mean waist/hip ratio was 0.80, the mean systolic blood pressure was 116.2 mmHg, the mean diastolic blood pressure was 67.8 mmHg. The percentage of students at risk of OSA based on STOP-BANG scores was 13.5%, and 58.4% based on EPWORTH scores. Smoking affects 0.9% of students, hypertension affects 2.7%, snoring affects 16.6%, average sleep time is 6.59 hours, and poor academic performance affects 4.4%. According to the STOP-BANG transcript, the percentage of students with poor academic performance (<2.5) in the group at risk of OSA was higher than in the group without the risk of OSA (10.5% versus 3.5%, χ2=7.730, p=0.012). According to the EPWORTH score, the proportion of students with poor academic performance (<2.5) in the group at risk of OSA was lower than in the group without the risk of OSA (χ2=5.406, p=0.02). In multivariable logistic regression analysis, BMI ≥ 23kg/m2 was a risk factor for poor academic results (OR=2.5, p=0.043), while daytime sleepiness was a protective factor for poor academic results (OR = 0.384, p = 0.024). Conclusions: The percentage of students at risk of OSA based on STOP-BANG scores was 13.5%, and 58.4% based on EPWORTH scores. Second-year medical students at Can Tho University of Medicine and Pharmacy who are at risk of OSA according to STOP-BANG score have lower academic performance. Poor academic results were associated with BMI ≥ 23kg/m2.

Unraveling the Nexus: Exploring the Relationship between Exercise Habits and Sleep Quality in Older Adults.

The objective of this study is to investigate the impact of exercise habits on enhancing the sleep quality of older adults. The Pittsburgh Sleep Quality Scale and other questionnaires were utilized to assess the sleep quality of older adults aged 60 years and above in the H district. The sampling method employed was stratified random sampling. To analyze the influencing factors of sleep quality, the average treatment effect was estimated, the robustness of the results was assessed and statistical methods such as Logit regression and propensity score matching were employed. The study revealed that exercise habits strongly correlated with improved sleep quality in the older adult (p < 0.05), with the average total sleep quality score being 6.22 (±3.53). It was observed that older adults who engaged in exercise habits experienced a significant 12.66% increase in the likelihood of achieving good sleep. This investigation highlights the positive association between exercise habits and enhanced sleep quality among older adults. Additionally, age, physical pain and self-rated health statuses were identified as significant factors influencing sleep quality in this population. To enhance the sleep quality of older adults, this article recommends promoting relevant exercise habits, thus contributing to their overall well-being and quality of life.

A Comparison of Sleep Duration Accuracy Between Questionnaire and Accelerometer in Middle Childhood.

Purpose Healthy sleep is vital to children's well-being, and assessing sleep efficiently and accurately can help understand children's lifestyles. Due to the difficulty in objectively measuring sleep duration using wearable sensors in large-scale surveys of children, self-administered questionnaires are often used in Japan; however, their accuracy is uncertain. We evaluated and compared the accuracy of questionnaire-based sleep times to those of wearable sensors. Methods This observational study was conducted between November 2019 and January 2020. A self-administered questionnaire on lifestyle habits and ActiGraph GT3X+ (ActiGraph, Inc., Pensacola, USA) accelerometer data were collected from 40 fourth-grade elementary school students in Kagawa Prefecture, Japan. We analyzed measurements for 256 days out of 280 days (40 persons × 7 days) after excluding days when the rate of wearing the accelerometer was < 90%. Results The median sleep duration per accelerometry was 453 minutes, and the median time in bed was 519 minutes. Questionnaire-based time in bed was 11 minutes longer, with relatively high inter-individual variability. The difference in bedtime was 26 minutes earlier, and wake-up time was 12 minutes earlier for the questionnaire. The average sleep efficiency was 87.4%, and one-third of the children had sleep efficiency < 85%. Conclusion The difference in sleep duration by questionnaire compared to accelerometry was approximately 10 minutes, suggesting the questionnaire may determine sleep duration with accuracy.

Delayed melatonin circadian timing, lower melatonin output, and sleep disruptions in myopic, or short-sighted, children.

This study investigated the differences in melatonin circadian timing and output, sleep characteristics, and cognitive function in myopic and non-myopic (or emmetropic) children, aged 8-15 years. Twenty-six myopes (refractive error [mean ± standard error mean] -2.06 ± 0.23 diopters) and 19 emmetropes (-0.06 ± 0.04 diopters), aged 11.74 ± 2.31 years were recruited. Circadian timing was assessed using salivary dim-light melatonin onset (DLMO), collected half-hourly for 7 hours, beginning 5 hours before and finishing 2 hours after individual average sleep onset in a sleep laboratory. Nocturnal melatonin output was assessed via aMT6s levels from urine voids collected from 05:30 pm to 8:00 am the following morning. Actigraphy-derived objective sleep timing were acquired for a week prior to the sleep laboratory visit. Cognitive assessments of sustained attention (using psychomotor vigilance task [PVT]) and working memory (using digit spans) were performed on the night of sleep laboratory. Myopic children (9:07 pm ± 14 minutes) exhibited a DLMO phase-delay of 1 hour 8 minutes compared to emmetropes (7:59 pm ± 13 minutes), p = 0.002. aMT6s melatonin levels were significantly lower among myopes (18.70 ± 2.38) than emmetropes (32.35 ± 6.93, p = 0.001). Myopes also exhibited significantly delayed sleep onset, delayed wake-up time, poor and reduced sleep, and more evening-type diurnal preference than emmetropes (all p < 0.05). Finally, myopes showed a slower reaction time in the PVT (p < 0.05), but not digit span tasks at night. These findings suggest a potential association between circadian rhythm dysfunction and myopia in children.

Sleep disorders and their relation to injuries among young elite soccer players

Aim: to study the quality of sleep and the relationship between sleep disorders and injury among young elite soccer players.Methods: the study summarizes data from relevant questionnaires obtained through anonymous cohort testing of 236 male football players from leading football academies, two farm teams of leading Russian Premier League clubs and three national youth teams.Results: the average sleep duration in the study participants was 9 hours. The prevalence of sleep disorders was 7 % (PSQI, Pittsburgh Sleep Quality Index) and 10 % (ASBQ, Athlete Sleep Behavior Questionnaire) and among the youngest soccer players, this prevalence of violations was the lowest. Significant or moderate daytime sleepiness was found in 59 % of participants. The risk of serious disorders increased with age. Sleep disorders significantly affected injuries according to the results of the PSQI questionnaire and retrospective collection of information about injuries.Conclusion: the confirmed relationship between injuries and sleep disorders allows us to consider sleep quality improvement as an important component of injury and morbidity prevention among athletes of team sports.

Latent Profiles of Sleep Patterns in Early Adolescence: Associations With Behavioral Health Risk

PurposeThe present study characterized sleep profiles in a national longitudinal sample of early adolescents and examined whether profiles predicted later behavioral problems. MethodsThree waves of data (2016–2021) were obtained from the Adolescent Behavior and Cognitive Development study, including 3,326 participants with both weekday and weekend sleep data measured by Fitbit wearables (age range 10.58–13.67 years; 49.3% female). Latent profile analysis was utilized to identify sleep profiles using multiple sleep indicators (duration, latency, efficiency, wake minutes, wake counts, and midpoint). We then explored whether demographic predictors predicted profile membership and tested the latent sleep profiles' predictive utility of internalizing and externalizing symptoms. ResultsFour profiles were identified: average sleep (40.39%), high duration & high wakefulness (28.58%), high efficiency, low duration &low wakefulness (16.86%), and low duration & low efficiency (14.17%). Participants with older age, males, higher body mass index, and advanced pubertal status were more likely to be classified in the low duration & low efficiency profile than the average group. Participants with lower income, minority identification, older age, and higher body mass index were more likely to be classified in the high efficiency, low duration &low wakefulness than the average group. Participants with lower parental education and males were more likely to be in the high sleep duration & high wakefulness than the average group. The low duration & low efficiency group had the highest attention problems, social problems, and rule-breaking behaviors. DiscussionOur findings highlight unique sleep patterns in early adolescence and their prospective links with internalizing and externalizing problems.

OR07-04 Associations Of Sleep Patterns And Body Mass Index Among African Americans: The Jackson Heart Sleep Study

Abstract Disclosure: D. Duan: None. J.C. Jun: None. D.A. Johnson: None. R.S. Ahima: None. A.G. Bertoni: None. S. Redline: None. J.B. Echouffo Tcheugui: None. Background: Obesity and its metabolic complications disproportionately affect African Americans. Sleep may be a modifiable factor that can impact metabolic health. We used objective measures of sleep patterns to assess the relationship between sleep parameters and body mass index (BMI) among African Americans. Methods: The Jackson Heart Study was a prospective cohort study that recruited 5306 African American adults from 3 counties in Jackson, Mississippi, designed to evaluate the etiology of cardiovascular disease among African Americans. We performed a cross-sectional analysis including 913 participants in the Jackson Heart Sleep Ancillary Study (enrolled 2012-2016) who underwent 7-day wrist actigraphy and home sleep apnea tests. We used multivariable linear regression to assess the associations between BMI (outcome; log-transformed for normality) and actigraphy-derived sleep parameters (exposures) that described: sleep timing (sleep onset and mid-sleep time), sleep duration (total sleep duration and night to night variation measured by within-individual standard deviation), and sleep continuity (sleep maintenance efficiency and sleep fragmentation index). Models were adjusted for age, sex, socioeconomic factors, physical activity, smoking, alcohol use, and the presence of moderate to severe obstructive sleep apnea (Apnea Hypopnea Index &amp;gt; 15). Results: Among the included 684 participants with complete data on anthropometric measurements and key covariates (mean age 63 ± 11 years, 66% women, mean BMI 31.8 ± 6.9 kg/m2), average sleep onset was 23:10 ± 1.35 hrs, mid-sleep time was 2:55 ± 1.20 hrs, total sleep duration was 6.7 ± 1.15 hrs, median night-to-night variation was 1.2 hrs (IQR 0.8-1.5), median sleep maintenance efficiency was 88.9% (IQR 85.7-91.5), and median sleep fragmentation index was 28.4% (IQR 23.3-34). In adjusted models, sleep onset (β 0.013, p=0.02) and mid-sleep time (β 0.012, p=0.047) were positively associated with log transformed BMI, while sleep maintenance efficiency was negatively associated with log transformed BMI (β −0.004, p=0.009). Total sleep duration, night to night sleep duration variability, and average sleep fragmentation index were not associated with BMI in adjusted models. Conclusions: Later sleep timing and poor sleep continuity were associated with higher BMI among African Americans in the Jackson Heart Sleep Study. Our findings suggest the importance of circadian influence and sleep disruption as factors that influence metabolic health. Presentation: Thursday, June 15, 2023

THU341 Associations Of Longitudinal Nighttime Sleep Characteristics With Nighttime/Daytime Glucose Values As Assessed By Continuous Glucose Monitoring In Type 2 Diabetes

Abstract Disclosure: Y. Li: None. K.K. Danielson: None. J.C. Park: None. J. McAnany: None. F.Y. Chau: None. B. Prasad: None. E.C. Hanlon: None. S. Reutrakul: None. Background: Sleep disturbances have been shown to be associated with incident diabetes and poor glycemic control. Recently, evidence emerged that nightly sleep may affect glucose levels both during that night and the following day. In this study, we explored the association of serial measures of nightly sleep parameters with night/day glucose levels in patients with type 2 diabetes (T2D). Methods: Baseline data of 28 T2D patients participating in an ongoing study exploring the relationship between diabetes retinopathy (DR) and sleep (NCT 04547439) were included. Sleep was objectively recorded using 14-days actigraphy. Sleep parameters nightly included sleep duration, sleep efficiency, wake time after sleep onset (WASO), and mid-sleep time (MST, time between sleep time and waketime). Glucose was recorded using blinded continuous glucose monitors (CGM). CGM data were divided into nighttime and daytime glucose values, utilizing the sleep time from actigraphy. CGM parameters included mean glucose, percent time spent in range (TIR%; glucose values 70-180 mg/dL), percent time above range (&amp;gt;180 mg/dL), and percent time below range (&amp;lt;70 mg/dL). Glucose variability indices included percent coefficient of variation (%CV) and Continuous Overall Net Glycemic Action (CONGA). Longitudinal mixed linear regression models, adjusting for age, sex, insulin use and DR status, were used to determine the associations between sleep parameters and nighttime/subsequent daytime CGM values. Associations were considered statistically significant at p&amp;lt;0.01 due to the multiple comparisons. Results: Mean (SD) age was 55.0 (6.5) years, A1C was 7.8 (1.5)%, 57% of the participants were female and 60.1% had DR. Average sleep duration was 6.1 (1.0) hours, sleep efficiency was 79.8 (9.6)%, WASO was 49.0 (27.1) minutes and MST was 3:25 (1:23) AM. There were a total of 281 nights and 254 days of CGM recordings. For nighttime CGM analyses, sleep duration (mins) was significantly longer in %TIR of ≥70% vs. &amp;lt;70% (β=57, SE=13, p=0.0005), but there were no associations of duration with other CGM parameters. WASO (log) was positively associated with CONGA (β=2.3, SE=0.9, p=0.008). Earlier MST was associated with greater glucose variability including higher CONGA (β=−1.6, SE=0.4, p&amp;lt;0.0001), and %CV (β=−1.6, SE=0.4, p&amp;lt;0.0001). For the following day CGM analyses, only the association between earlier MST and greater time spent below range (β=−0.7, SE=0.2, p=0.006) was significant. Conclusion: Longer nightly sleep duration was associated with higher nighttime %TIR, while poor sleep continuity was associated with higher nighttime glucose variability. In contrast to previous findings, earlier sleep timing was associated with unfavorable glucose profiles both during nighttime and daytime. These pilot data highlighted the associations between nighttime sleep and metabolic control, and should be explored in a larger cohort. Presentation: Thursday, June 15, 2023

Is daily emotion suppression associated with poor sleep? The moderating role of culture.

Emotion suppression is widely assumed to be unhealthy. Yet, this conclusion may be limited to independent Western cultures that value self-expression. In a pre-registered, daily diary study of European American and East Asian college students, we tested whether culture moderates the effects of daily use of emotion suppression on sleep-a critical component of healthy living among young adults. A total of 117 college students (62 European Americans and 55 East Asians) completed two diaries per day for 14 days to assess (a) their daily use of emotion suppression every night and (b) subjective sleep quality and mood upon awakening every morning. Participants also wore actigraphy watches to provide behavioral measures of sleep. The data were collected between 2018 and 2020. We used multilevel models to test cultural differences in the effects of emotion suppression on sleep and mood measures at both between-person (average) and within-person (day-to-day) levels. For European Americans, greater use of emotion suppression across 2 weeks was associated with lower average subjective sleep quality and more tense (vs. calm) feelings upon awakening. At the within-person level, on days when European Americans used emotion suppression more than usual, they had less amount of sleep that night. In contrast, these associations were completely absent among East Asians. These results provide support for the cultural fit hypothesis that how emotion suppression affects sleep health varies by cultural contexts, depending on whether this regulatory behavior is normatively congruous or incongruous with the values prioritized in each culture. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Associated Risk Factors with The Prevalence of Diabetes and Prediabetes in Gopalganj District

People's lifestyles are changing a lot with time. Busy working life, indifference to ideal living, addiction to yummy junk food and lack of physical activity are causing many health hazards. Due to changes in lifestyle and dietary habits, the prevalence of several diseases has increased, among which diabetes can be identified as one of them. Diabetes is a chronic disease that affects people of all ages. There are several forms of diabetes. Type 2 is the most common. The number of people in Bangladesh who have type-2 diabetes has increased dramatically making it one of the country's major health problems. The rising prevalence of diabetes in Bangladesh is associated with overweight, age, family history of diabetic, physical activity, eating habit of high carbs food etc. So, we collected 320 individuals affected or take medication or checks themselves in any Diabetic Center in Gopalganj district for treatment or any suggestions. The aim of the study is to explain the status of diabetes affected peoples on average result and to find out any certain factor which relates to the disease. The variables included the age of the patient, job category, exercise time, meal plan and some other important factor that is considered to be related to diabetes. The dependent variable was chosen as the blood glucose level of the respondents. We used chi-square test and logistic regression to find any significant relation that can be described. Logistic regression analysis identified some important factors that significantly affect the blood glucose level of the respondents, namely average sleep time, rice for breakfast, diet, red meat, smoking and age. Keywords: Food habits, Diabetes, blood glucose level, Chi-square test, Logistic regression.

Wearable technology data-based sleep and chronic disease relationship

Objective: The aim of the study was to examine the cross-sectional relationship between sleep duration and 12 chronic diseases&#x0D; (obesity risk, diabetes, asthma, renal failure, hypertensive diseases, chronic obstructive pulmonary disease, cardiovascular diseases,&#x0D; ischaemic heart disease, pulmonary heart disease, immunodeficiencies and immune system disorders) by transferring the data to the&#x0D; national electronic patient record system through wearable device technology.&#x0D; Materials and Methods: The data of the study were obtained from the Ministry of Health “Turkey National Personal Health Record&#x0D; System” (The “e-Nabız”). Between 30.03.2023 and 28.05.2023, 315448 data from 27847 people (15167 male) were collected and&#x0D; analysed on the basis of province, rural status, age group, gender and presence of chronic diseases and average, minimum (min),&#x0D; maximum (max) sleep duration. Descriptive statistics, chi-square analysis, Independent Samples t-Test, One-way Analysis of Variance&#x0D; and Pearson’s correlation coefficient were used.&#x0D; Results: The max. and average sleep duration were significantly shorter in men. Max. sleep duration decreased while the average sleep&#x0D; duration increased with increasing age. Participants with asthma, chronic renal failure and cerebrovascular diseases had decreased&#x0D; average sleep duration. The frequency of those who slept for 7-8 hours, which is the ideal sleep duration, is lower in all chronic diseases.&#x0D; Conclusion: Most of the common chronic diseases may affect the sleep duration times and quality, which may further affect the&#x0D; prognosis of these patients.

Assessing ‘readiness’ by tracking fluctuations in daily sleep duration and their effects on daily mood, motivation, and sleepiness

Study objectivesConsumer sleep trackers issue daily guidance on ‘readiness’ without clear empirical basis. We investigated how self-rated mood, motivation, and sleepiness (MMS) levels are affected by daily fluctuations in sleep duration, timing, and efficiency and overall sleep regularity. We also determined how temporally specific these associations are. Methods119 healthy university students (64 female, mean age = 22.54 ± 1.74 years) wore a wearable sleep tracker and undertook twice-daily smartphone-delivered ecological momentary assessment of mood, motivation, and sleepiness at post-wake and pre-bedtime timings for 2–6 weeks. Naps and their duration were reported daily. Nocturnal sleep on 2471 nights were examined using multilevel models to uncover within-subject and between-subject associations between sleep duration, timing, efficiency, and nap duration on following day MMS ratings. Time-lagged analyses examined the temporal specificity of these associations. Linear regression models investigated associations between MMS ratings and sleep variability, controlling for sleep duration. ResultsNocturnal sleep durations were short (6.03 ± 0.71 h), and bedtimes were late (1:42AM ± 1:05). Within-subjects, nocturnal sleep longer than a person's average was associated with better mood, higher motivation, and lower sleepiness after waking. Effects of such longer sleep duration lingered for mood and sleepiness till the pre-bedtime window (all Ps < .005) but did not extend to the next day. Between-subjects, higher intraindividual sleep variability, but not sleep duration, was associated with poorer mood and lower motivation after waking. Longer average sleep duration was associated with less sleepiness after waking and lower motivation pre-bedtime (all Ps < .05). Longer naps reduced post-nap sleepiness and improved mood. Controlling for nocturnal sleep duration, longer naps also associated with lower post-waking sleepiness on the following day. ConclusionsPositive connections between nocturnal sleep and nap duration with MMS are temporally circumscribed, lending credence to the construction of sleep-based, daily ‘readiness’ scores. Higher sleep duration variability lowers an individual's post waking mood and motivation. Clinical trial idClinicalTrials.gov NCT04880629.

Associating night-shift work with lifetime use of sleep medication and sleep quality in a cohort of female nurses.

Night-shift workers often sleep at moments, not in sync with their circadian rhythm. Though the acute effects of night-shift work on sleep quality directly after a night shift are well described, less is known about the chronic effects of night-shift work on sleep. We associated ever-working night shifts and recently working night shifts (<4 wk) with lifetime use of sleep medication and melatonin, self-reported average sleep duration and sleep quality over the 4 wk preceding inclusion (measured using the Medical Outcomes Study Sleep scale). We explored trends in sleep outcomes with average frequency of night shifts per week, tenure of night-shift works in years, and time since last performed night work. This research was conducted within the Nightingale study which is a Dutch cohort study of 59,947 female registered nurses aged 18 to 65. Working night shifts was not associated with self-reported nonoptimal sleep length and sleep quality. However, we observed higher odds of lifetime use of sleep medication for nurses who ever-worked night shifts (OR 1.24; 95% CI 1.13, 1.35) and who recently worked night shifts (OR 1.13; 95% CI 1.05, 1.22); with night-shift work frequency and tenure being associated with lifetime use of sleep medication (P-value for trend < 0.001 for both). Odds for melatonin use were elevated for nurses who ever worked night shifts (OR 1.55; 95% CI 1.40, 1.71) and recently worked night shifts (OR 1.72; 95% CI 1.59, 1,86). The findings of this study have practical implications for healthcare organizations that employ nurses working night shifts. The observed associations between night-shift work and increased lifetime use of prescribed sleep medication and melatonin highlight the need for targeted support and interventions to address the potential long-term sleep problems faced by these nurses.

Sleep-Body Composition Relationship: Roles of Sleep Behaviors in General and Abdominal Obesity in Chinese Adolescents Aged 17-22 Years.

This study aimed to investigate the association between sleep behaviors and body composition, which was measured by bioelectrical impedance analysis (BIA) among Chinese adolescents. Overall, 444 students (65.3% females, 19.12 ± 1.177 years) completed questionnaires describing sleep characteristics. Sleep characteristics were derived from subjective means. Body composition was obtained from BIA by InBody 720 (Biospace Co. Ltd., Seoul, Republic of Korea). Regression models tested relationships between sleep and body composition after adjustment for covariates. Students with weekday nap duration (>30 min/d) exerted higher waist-height ratio (WHtR) (B = 0.013, FDR-corrected p = 0.080). Average sleep duration (≤7 h/d) was linked to more WHtR (B = 0.016, FDR-corrected p = 0.080). People with high social jetlag showed gained visceral fat area (B = 7.475), WHtR (B = 0.015), waist to hip ratio (B = 0.012), fat mass index (B = 0.663) and body fat percentage (B = 1.703) (all FDR-corrected p < 0.1). Individuals with screen time before sleep (>0.5 h) exhibited higher visceral fat area (B = 7.934, FDR-corrected p = 0.064), WHtR (B = 0.017, FDR-corrected p = 0.080), waist to hip ratio (B = 0.016, FDR-corrected p = 0.090), fat mass index (B = 0.902, FDR-corrected p = 0.069) and body fat percentage (B = 2.892, FDR-corrected p = 0.018). We found poor sleep characteristics were closely related to general and abdominal obesity.

The prevalence and associated factors of sleep deprivation among healthy college students in China: a cross-sectional survey.

The prevalence of sleep deprivation among college students is increasing and has a few associated factors. The present study analyzed 2,142 college students from 28 provinces in China. The Chinese version of the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep duration. Binary logistic regression was conducted to explore the sleep deprivation related factors. Age and gender were controlled as covariates. Among the 2,142 college students (27.7% male, 72.3% female), 1,620 (75.6%) reported the average sleep duration was below 7 h per day for one month, 49.3% (1,055/2,142) slept 6∼7 h (contains 6 h), 21.0% (449/2,142) slept 5∼6 h (contains 5 h), and 5.4% (116/2,142) slept <5 h. Age increased the risk of sleep deprivation, the adjusted odds ratio = 1.05 (95% CI [1.01∼1.10]). The adjusted odds ratio (A-OR) for sleep deprivation was higher for students of more than 60 min nap duration per day (A-OR = 2.35, 95% CI [1.45∼3.80]), and age growth (A-OR = 1.05, 95% CI [1.01∼1.10]). In contrast, A-ORs were lower among sleeping inconsistency between work and rest days (A-OR = 0.61, 95% CI [0.49∼0.75]), accustomed to staying up late (A-OR = 0.45, 95% CI [0.36∼0.57]), staying up late to work or study (A-OR = 0.62, 95% CI [0.49∼0.78]), stress (A-OR = 0.75, 95% CI [0.58∼0.98]), and repeated thoughts in bed had (A-OR = 0.79, 95% CI [0.62∼0.99]). Sleep deprivation is extremely common among healthy college students in China. It is necessary to perform methods maintaining enough sleep due to the current high incidence of sleep deprivation. Controlling the nap duration and getting enough sleep on rest days to replace missing hours of sleep on workdays might improve college students' sleep.

Quality of life, fatigue, sleep quality, and mental health in systemic lupus erythematosus patients with a high cardiovascular risk profile.

Systemic lupus erythematosus (SLE) patients report worse health-related quality of life (HRQL), fatigue, anxiety, depression, and sleep quality, when compared to the general population and other chronic diseases. Furthermore, cardiometabolic diseases are highly prevalent in SLE and are also associated with these parameters. Thus, it is plausible to suggest that SLE patients with a high cardiovascular risk may report worse results for these parameters. The aim of the study is to describe HRQL, fatigue, anxiety and depression symptoms, and sleep quality in a sample of SLE patients with a high cardiovascular risk profile (i.e., BMI between 25 and 40kg/m2 and/or dyslipidemia, hypertension, or diabetes). This was a cross-sectional study where patients were assessed for (i) demographic, anthropometric, and disease-related parameters, (ii) HRQL, (iii) fatigue, (iv) anxiety and depression symptoms, and (v) sleep quality. One-hundred patients completed the study; however, only 87 patients were assessed for sleep quality data. Patients averaged 41.7 ± 9years, and most patients were classified as overweight/obese (87%). SF-36 scores for physical and mental components summary were 51.3 ± 9.6 and 54.2 ± 15.6, respectively, with "bodily pain" and "role emotional" presenting the lower scores. The total SLEQOL score was 105.1 ± 42.0, with lower scores reported for "self-image" and "mood." Fatigue score was 30.8 ± 8.9, and 78% and 93% reported severe symptoms of anxiety and depression, respectively. The average sleep effectiveness was 82.9 ± 6.6%. Sleep latency, total time in bed (TTiB), and total sleep time (TST) were 8.4 ± 8.9, 495.8 ± 79.7, and 409.7 ± 69.9min, respectively. Patients reported an average of 17.8 ± 6.2 WE, with 4.5 ± 1.5min duration and a WASO of 77.7 ± 36.6min. Despite similar HRQL, fatigue, and sleep quality parameters to those reported by other SLE populations, SLE patients with a high cardiovascular risk had a higher prevalence of depression and anxiety. Understanding SLE patients' quality of life and psychological symptoms is of utmost importance to improve disease management. The findings of this study highlight the need for more intensive and global care regarding mental health when considering a high cardiovascular risk in SLE.

The role of sleep duration in suicide risk among sexual and gender minority adolescents

BackgroundShort sleep duration is linked with suicide risk in adolescence. Sexual and gender minority (SGM) adolescents experience substantially increased risk for suicide compared to their non-SGM peers. MethodsWe investigated the role of sleep duration in SGM adolescent suicide risk using population-based, cross-sectional data from the 2022 Minnesota Student Survey (MSS; N = 85,610, Mage = 14.8). Adolescents reported average school-night sleep duration; those reporting <6 h were classified as having very short sleep duration. The MSS additionally assessed past-year suicidal ideation and suicide attempt. Mediation analyses assessed the role of sleep duration in explaining associations between SGM identity and suicide risk. Further, to examine intervention mechanisms, among SGM adolescents (n = 20,171, 23.6%), a logistic regression model assessed associations among demographic factors, perceived parental care, and very short sleep duration. ResultsAs compared to non-SGM adolescents, SGM adolescents reported substantially higher prevalence of past-year suicidal ideation and suicide attempt and 2.6× higher prevalence of very short sleep duration (all p < 0.001). Mediation analyses demonstrated that very short sleep duration partially mediated the pathway between SGM identity and past-year suicidal ideation (15.5% mediated) and suicide attempt (17.2% mediated). Among SGM adolescents, a striking positive dose-response relationship was observed between level of perceived parental care and very short sleep duration. As perceived parental care decreased, so too did hours of sleep. DiscussionSleep duration is a crucial and understudied mechanism underlying suicide risk disparities affecting SGM adolescents. Family-based interventions may improve SGM adolescent sleep and reduce suicide risk.

Quality of Sleep and Factors Affecting Sleep Quality in Hospitalized Patients in the Orthopedics and Traumatology Clinic

Purpose: In this study, our purpose was to determine the sleep quality and the factors affecting sleep quality of the hospitalized patients orthopedics and traumatology clinic.&#x0D; Methods: This study was conducted as a descriptive study in a hospital between March 30 and June 16, 2022. The sample of the study consisted of 200 patients hospitalized in the orthopedics and traumatology clinic. The data of the study were collected through face-to-face interviews with the patients using the ‘’Sociodemographic and Descriptive Characteristics Questionnaire’’ and the ‘’Richard-Campbell Sleep Questionnaire’’.&#x0D; Results: The average Richard-Campbell Sleep Questionnaire scores of the patients were determined to be 43.33±28.31. While there was no statistically significant difference (p&gt;0.05) observed between the gender, preoperative or postoperative status, presence of noise, room lighting, room crowding, attached the body medical devices, treatment interventions during sleep hours, and Richard-Campbell Sleep Questionnaire score averages of the patients; a statistically significant difference was found in the Richard-Campbell Sleep Questionnaire score averages based on pain and medical diagnosis (p

Investigating the relationship between sleep and migraine in a global sample: a Bayesian cross-sectional approach

BackgroundThere is a bidirectional link between sleep and migraine, however causality is difficult to determine. This study aimed to investigate this relationship using data collected from a smartphone application.MethodsSelf-reported data from 11,166 global users (aged 18–81 years, mean: 41.21, standard deviation: 11.49) were collected from the Migraine Buddy application (Healint Pte. Ltd.). Measures included: start and end times of sleep and migraine attacks, and pain intensity. Bayesian regression models were used to predict occurrence of a migraine attack the next day based on users’ deviations from average sleep, number of sleep interruptions, and hours slept the night before in those reporting ≥ 8 and < 25 migraine attacks on average per month. Conversely, we modelled whether attack occurrence and pain intensity predicted hours slept that night.ResultsThere were 724 users (129 males, 412 females, 183 unknown, mean age = 41.88 years, SD = 11.63), with a mean monthly attack frequency of 9.94. More sleep interruptions (95% Highest Density Interval (95%HDI [0.11 – 0.21]) and deviation from a user’s mean sleep (95%HDI [0.04 – 0.08]) were significant predictors of a next day attack. Total hours slept was not a significant predictor (95%HDI [-0.04 – 0.04]). Pain intensity, but not attack occurrence was a positive predictor of hours slept.ConclusionsSleep fragmentation and deviation from typical sleep are the main drivers of the relationship between sleep and migraine. Having a migraine attack does not predict sleep duration, yet the pain associated with it does. This study highlights sleep as crucial in migraine management.

A Longitudinal Assessment of Sleep in Surface Warfare Officers During Training and Fleet Assignments: Preliminary Results

Several previous studies have assessed fatigue on USN warships, especially of enlisted Sailors. Our study, however, is focused explicitly on Surface Warfare Officers (SWOs) (N=34) during training and after returning to the fleet. The average daily sleep duration was 6.83±0.44 hours (62% of the SWOs sleeping &lt;7 hours/day). The average daily sleep duration was higher when SWOs were in training compared to their fleet assignment (p=0.068). SWOs slept 0.82 hours/day more on weekends compared to weekdays in fleet settings and 0.42 hours/day when in training. Sleep efficiency during the major sleep episodes was lower in fleet settings (p&lt;0.001), heart rate was higher (p=0.020), and HRV was lower (p&lt;0.001). These preliminary results suggest that chronic sleep deprivation is prevalent in SWOs, especially in fleet settings. The depressed HRV during fleet assignments may be explained by the high stress levels during these periods in conjunction with the increased sleep deprivation.