Objectives:This study aims to assess sleep disorders among secondary school adolescents and explore the relationship between sociodemographic factors(age,gender,household income,and sleep duration)and the occurrence o...Objectives:This study aims to assess sleep disorders among secondary school adolescents and explore the relationship between sociodemographic factors(age,gender,household income,and sleep duration)and the occurrence of these disorders.Methods:A quantitative,descriptive,cross-sectional study,was conducted from November 20th,2022,to May 25th,2023,involving 200 secondary school students selected through convenience sampling.Data collection utilized a structured questionnaire divided into sociodemographic and sleep disorder sections.Validity was ensured by a panel of ten experts,and reliability was confirmed using Cronbach’s Alpha(0.77).Statistical analysis employed SPSS version 26.Results:Findings revealed that a majority of participants(70.5%)had low-level sleep disorders,followed by moderate disorders represented(29%).Significant associations were found between sleep disorders and gender(P=0.000),economic status for family(P=0.020),and nightly sleep duration(P=0.016).However,no significant relationship was observed between sleep disorders and family structure or age(P>0.05).Conclusions:The study highlights that most secondary school students experience mild sleep disorders,followed by moderate disorders.Notably,gender,income,and sleep duration showed significant correlations with sleep disorders.展开更多
Background:Non‐suicidal self‐injury(NSSI),suicidal ideation(SI),and suicide attempts(SA)are major concerns among college students.Sleep may be a modifiable factor,but its associations with NSSI,SI,and SA remain uncl...Background:Non‐suicidal self‐injury(NSSI),suicidal ideation(SI),and suicide attempts(SA)are major concerns among college students.Sleep may be a modifiable factor,but its associations with NSSI,SI,and SA remain unclear.Methods:A cross‐sectional survey of 10,498 college students using a selfreport questionnaire.Sleep health indicators include insomnia symptoms,duration,chronotype,snoring,and daytime sleepiness.Multivariable logistic regression models and restricted cubic spline analyses were used to examine associations between sleep patterns and self‐injurious behaviors.Results:The prevalence of NSSI,SI,and SA was 4.8%,29.7%,and 3.7%,respectively.Participants with higher healthy sleep scores exhibited significantly reduced risks of NSSI,SI,and SA,with dose‐response relationships observed.Each one‐point increase in the sleep score was associated with a 43%lower risk of NSSI(odds ratios(OR)=0.57,95%CI:0.52–0.62),a 37%lower risk of SI(OR=0.63,95%CI:0.61–0.66),and a 48%lower risk of SA(OR=0.52,95%CI:0.48–0.58).Conclusion:Healthy sleep patterns were significantly associated with reduced risks of NSSI,SI,and SA among Chinese college students.These findings underscore the importance of promoting comprehensive sleep health as a public health strategy to mitigate self‐injurious behaviors in young populations.展开更多
The quality of sleep may be a reflection of an el- derly individual＇s health state, and sleep pattern is an im- portant measurement. Recognition of sleep pattern by itself is a challenge issue, especially for elderly...The quality of sleep may be a reflection of an el- derly individual＇s health state, and sleep pattern is an im- portant measurement. Recognition of sleep pattern by itself is a challenge issue, especially for elderly-care community, due to both privacy concerns and technical limitations. We propose a novel multi-parametric sensing system called sleep pattern recognition system （SPRS）. This system, equipped with a combination of various non-invasive sensors, can mon- itor an elderly user＇s sleep behavior. It accumulates the de- tecting data from a pressure sensor matrix and ultra wide band （UWB） tags. Based on these two types of complemen- tary sensing data, SPRS can assess the user＇s sleep pattern automatically via machine learning algorithms. Compared to existing systems, SPRS operates without disrupting the users＇ sleep. It can be used in normal households with minimal deployment. Results of tests in our real assistive apartment at the Smart Elder-care Lab are also presented in this paper.展开更多
In the past, efforts have been made to determine the influence of sleep quantity and its deprivation, on functioning efficiency of human beings. However, determination of sleeping patterns that could improve intellect...In the past, efforts have been made to determine the influence of sleep quantity and its deprivation, on functioning efficiency of human beings. However, determination of sleeping patterns that could improve intellectual performance has been largely neglected. This study is designed to discover the effects of different sleeping patterns on academic performance among medical students. A descriptive study was carried out in King Edward Medical University in Lahore, Pakistan during a six-month time span from May 11th, 2011 to September 30th, 2011. Of the total population of 1350 students in King Edward Medical University, 591 undergraduates were included in the study. A questionnaire designed on sleeping patterns and academic performance was distributed in May 2011. What was described as outstanding students were greater in number in group 4 (7/19) 36.8% and group 6 (6/19) 31.6%. Above average students with sleeping patterns were in group 4 (13/37) 35.1% and group 6 (10/37) 27%. Average students were shown to have sleeping patterns of group 4 (11/25) 44% and group 6 (7/25) 28%. Below average students were shown to have sleeping patterns of group 4 (3/3) 100%. Most of our students had a reduction in the total amount of sleeping hours throughout the years. Midnight to 6 o’clock in the morning with an afternoon nap was the sleeping pattern that was most commonly seen in all groups. We concluded that different sleeping patterns do not affect the performance of medical students in the academic prospective. Many other factors may be involved in the lack of significant achievement, in order to prove that the sleeping patterns are not related to the academic performance, and more data would need to be collected.展开更多
Introduction:Sleep is fundamental to health,yet comprehensive data characterizing sleep patterns across China’s diverse population remain scarce.This national study systematically assessed sleep behaviors among Chine...Introduction:Sleep is fundamental to health,yet comprehensive data characterizing sleep patterns across China’s diverse population remain scarce.This national study systematically assessed sleep behaviors among Chinese residents aged 15 years and above.Methods:A population-based cross-sectional survey was conducted in 2024 among individuals aged 15 years and older,using multistage stratified cluster random sampling.Trained investigators collected data on sleep duration,sleep latency,bedtime,and wake-up time through standardized questionnaires.Statistical analyses incorporated sampling weights to ensure population representativeness,and stratified analyses examined sleep patterns across a range of demographic subgroups.Results:The population-weighted mean sleep duration among Chinese residents aged 15 years and older was 7.24[95%confidence interval(CI):7.16,7.32]hours in 2024.Mean bedtime and wake-up time were 22:08(21:58,22:18)and 6:18(6:06,6:30),respectively,with a mean sleep latency of 27.45(26.39,28.51)minutes.Age-stratified analyses revealed notable sex differences in sleep duration:among adults aged 18-44 years,females slept longer than males[7.66(7.59,7.73)hours versus 7.49(7.41,7.57)hours],whereas among those aged 45-64 years,females slept less[6.82(6.72,6.92)hours versus 6.97(6.90,7.04)hours].Rural adolescents slept longer than their urban counterparts[8.39(8.14,8.64)hours versus 8.00(7.78,8.22)hours].Both education level and occupation further influenced sleep duration and timing.Conclusion:Sleep patterns among Chinese residents vary substantially by age,sex,and socio-environmental context.Effective sleep health strategies must be population-specific and tailored,rather than relying on uniform recommendations.Public health interventions should explicitly address the distinct socioeconomic and environmental determinants that shape sleep in different population segments,thereby optimizing sleep outcomes across diverse settings.展开更多
目的系统总结不同饮食模式在改善成年人睡眠质量中应用的现状。方法计算机检索PubMed、Cochrane Library、Web of Science、Embase、MEDLINE、中国生物医学文献数据库、中国知网、万方数据库中与饮食模式在改善成年人睡眠质量中应用的...目的系统总结不同饮食模式在改善成年人睡眠质量中应用的现状。方法计算机检索PubMed、Cochrane Library、Web of Science、Embase、MEDLINE、中国生物医学文献数据库、中国知网、万方数据库中与饮食模式在改善成年人睡眠质量中应用的相关文献,检索时限为建库至2023年6月25日,对纳入的文献进行归纳总结。结果共纳入29篇文献,其中18篇为横断面研究、7篇为队列研究、4篇为随机对照试验,从干预时间、干预人群、饮食模式的类型、干预的结局指标和干预结果进行了分析和总结。结论得舒饮食、生酮饮食、地中海饮食、北欧饮食和健康植物性饮食对改善睡眠质量具有积极作用,且不同的饮食模式对睡眠障碍具有不同作用,进一步分析发现这些饮食模式的组成成分具有共性特征。未来应该注重探究微量营养素对睡眠质量的影响和使用更客观的评价指标,根据患者的具体情况设计个性化的饮食模式和干预方案。展开更多
文摘Objectives:This study aims to assess sleep disorders among secondary school adolescents and explore the relationship between sociodemographic factors(age,gender,household income,and sleep duration)and the occurrence of these disorders.Methods:A quantitative,descriptive,cross-sectional study,was conducted from November 20th,2022,to May 25th,2023,involving 200 secondary school students selected through convenience sampling.Data collection utilized a structured questionnaire divided into sociodemographic and sleep disorder sections.Validity was ensured by a panel of ten experts,and reliability was confirmed using Cronbach’s Alpha(0.77).Statistical analysis employed SPSS version 26.Results:Findings revealed that a majority of participants(70.5%)had low-level sleep disorders,followed by moderate disorders represented(29%).Significant associations were found between sleep disorders and gender(P=0.000),economic status for family(P=0.020),and nightly sleep duration(P=0.016).However,no significant relationship was observed between sleep disorders and family structure or age(P>0.05).Conclusions:The study highlights that most secondary school students experience mild sleep disorders,followed by moderate disorders.Notably,gender,income,and sleep duration showed significant correlations with sleep disorders.
基金National Natural Science Foundation of China,Grant/Award Number:32271135Key Research Base of Humanities and Social Sciences of the Ministry of Education,Grant/Award Number:22JJD190008。
文摘Background:Non‐suicidal self‐injury(NSSI),suicidal ideation(SI),and suicide attempts(SA)are major concerns among college students.Sleep may be a modifiable factor,but its associations with NSSI,SI,and SA remain unclear.Methods:A cross‐sectional survey of 10,498 college students using a selfreport questionnaire.Sleep health indicators include insomnia symptoms,duration,chronotype,snoring,and daytime sleepiness.Multivariable logistic regression models and restricted cubic spline analyses were used to examine associations between sleep patterns and self‐injurious behaviors.Results:The prevalence of NSSI,SI,and SA was 4.8%,29.7%,and 3.7%,respectively.Participants with higher healthy sleep scores exhibited significantly reduced risks of NSSI,SI,and SA,with dose‐response relationships observed.Each one‐point increase in the sleep score was associated with a 43%lower risk of NSSI(odds ratios(OR)=0.57,95%CI:0.52–0.62),a 37%lower risk of SI(OR=0.63,95%CI:0.61–0.66),and a 48%lower risk of SA(OR=0.52,95%CI:0.48–0.58).Conclusion:Healthy sleep patterns were significantly associated with reduced risks of NSSI,SI,and SA among Chinese college students.These findings underscore the importance of promoting comprehensive sleep health as a public health strategy to mitigate self‐injurious behaviors in young populations.
文摘The quality of sleep may be a reflection of an el- derly individual＇s health state, and sleep pattern is an im- portant measurement. Recognition of sleep pattern by itself is a challenge issue, especially for elderly-care community, due to both privacy concerns and technical limitations. We propose a novel multi-parametric sensing system called sleep pattern recognition system （SPRS）. This system, equipped with a combination of various non-invasive sensors, can mon- itor an elderly user＇s sleep behavior. It accumulates the de- tecting data from a pressure sensor matrix and ultra wide band （UWB） tags. Based on these two types of complemen- tary sensing data, SPRS can assess the user＇s sleep pattern automatically via machine learning algorithms. Compared to existing systems, SPRS operates without disrupting the users＇ sleep. It can be used in normal households with minimal deployment. Results of tests in our real assistive apartment at the Smart Elder-care Lab are also presented in this paper.
文摘In the past, efforts have been made to determine the influence of sleep quantity and its deprivation, on functioning efficiency of human beings. However, determination of sleeping patterns that could improve intellectual performance has been largely neglected. This study is designed to discover the effects of different sleeping patterns on academic performance among medical students. A descriptive study was carried out in King Edward Medical University in Lahore, Pakistan during a six-month time span from May 11th, 2011 to September 30th, 2011. Of the total population of 1350 students in King Edward Medical University, 591 undergraduates were included in the study. A questionnaire designed on sleeping patterns and academic performance was distributed in May 2011. What was described as outstanding students were greater in number in group 4 (7/19) 36.8% and group 6 (6/19) 31.6%. Above average students with sleeping patterns were in group 4 (13/37) 35.1% and group 6 (10/37) 27%. Average students were shown to have sleeping patterns of group 4 (11/25) 44% and group 6 (7/25) 28%. Below average students were shown to have sleeping patterns of group 4 (3/3) 100%. Most of our students had a reduction in the total amount of sleeping hours throughout the years. Midnight to 6 o’clock in the morning with an afternoon nap was the sleeping pattern that was most commonly seen in all groups. We concluded that different sleeping patterns do not affect the performance of medical students in the academic prospective. Many other factors may be involved in the lack of significant achievement, in order to prove that the sleeping patterns are not related to the academic performance, and more data would need to be collected.
基金Supported by the Chinese Sleep Research Society and the General Program of the National Natural Science Foundation of China(Grant No.81872721).
文摘Introduction:Sleep is fundamental to health,yet comprehensive data characterizing sleep patterns across China’s diverse population remain scarce.This national study systematically assessed sleep behaviors among Chinese residents aged 15 years and above.Methods:A population-based cross-sectional survey was conducted in 2024 among individuals aged 15 years and older,using multistage stratified cluster random sampling.Trained investigators collected data on sleep duration,sleep latency,bedtime,and wake-up time through standardized questionnaires.Statistical analyses incorporated sampling weights to ensure population representativeness,and stratified analyses examined sleep patterns across a range of demographic subgroups.Results:The population-weighted mean sleep duration among Chinese residents aged 15 years and older was 7.24[95%confidence interval(CI):7.16,7.32]hours in 2024.Mean bedtime and wake-up time were 22:08(21:58,22:18)and 6:18(6:06,6:30),respectively,with a mean sleep latency of 27.45(26.39,28.51)minutes.Age-stratified analyses revealed notable sex differences in sleep duration:among adults aged 18-44 years,females slept longer than males[7.66(7.59,7.73)hours versus 7.49(7.41,7.57)hours],whereas among those aged 45-64 years,females slept less[6.82(6.72,6.92)hours versus 6.97(6.90,7.04)hours].Rural adolescents slept longer than their urban counterparts[8.39(8.14,8.64)hours versus 8.00(7.78,8.22)hours].Both education level and occupation further influenced sleep duration and timing.Conclusion:Sleep patterns among Chinese residents vary substantially by age,sex,and socio-environmental context.Effective sleep health strategies must be population-specific and tailored,rather than relying on uniform recommendations.Public health interventions should explicitly address the distinct socioeconomic and environmental determinants that shape sleep in different population segments,thereby optimizing sleep outcomes across diverse settings.
文摘目的系统总结不同饮食模式在改善成年人睡眠质量中应用的现状。方法计算机检索PubMed、Cochrane Library、Web of Science、Embase、MEDLINE、中国生物医学文献数据库、中国知网、万方数据库中与饮食模式在改善成年人睡眠质量中应用的相关文献,检索时限为建库至2023年6月25日,对纳入的文献进行归纳总结。结果共纳入29篇文献,其中18篇为横断面研究、7篇为队列研究、4篇为随机对照试验,从干预时间、干预人群、饮食模式的类型、干预的结局指标和干预结果进行了分析和总结。结论得舒饮食、生酮饮食、地中海饮食、北欧饮食和健康植物性饮食对改善睡眠质量具有积极作用,且不同的饮食模式对睡眠障碍具有不同作用,进一步分析发现这些饮食模式的组成成分具有共性特征。未来应该注重探究微量营养素对睡眠质量的影响和使用更客观的评价指标,根据患者的具体情况设计个性化的饮食模式和干预方案。
