Purpose: The purpose of this study was to assess sleep quality and to identify predictors of poor sleep quality in nursing students. Methods: The participants surveyed were 302 individuals at G College located in Kangwon-do. The participants completed the questionnaire including demographic characteristics, health behavior, and the Pittsburgh Sleep Quality Index (PSQI) for sleep quality. The BMI was calculated using height and weight. For the statistical analysis, $X^2$ test, Spearman correlation, and logistic regression were performed using the SAS window (version 9.2) program. Results: From the 302 individuals, 219 (72.5%) had poor sleep quality. The results showed significant correlations between physical activity and sleep quality, as well as between sleep duration and sleep quality. The BMI and sleep quality did not show any significant relationship. The factors affecting sleep quality were sleep latency (OR, 4.167; 95% CI, 1.406-12.344), sleep duration (OR, 6.717; 95% CI, 2.386-18.912), and sedentary hours (OR, 2.971; 95% CI, 1.095-8.064). Conclusion: The study demonstrates that poor sleep quality is common in nursing students, and intervention study is needed to improve sleep quality in nursing students. Additional studies are needed to determine the relationship between BMI and sleep quality.
Objectives: This study examined the association of the sleep quality and patterns with the dietary behavior, including snack and beverage consumption, taste preferences, as well as lifestyle of university students. Methods: The subjects were 406 university students in Cheongju, Korea, and the data were collected using a self-administered questionnaire. They were divided into two groups according to the Pittsburgh Sleep Quality Index (PSQI): good-quality sleepers (PSQI score ≤ 5) and poor-quality sleepers (PSQI score > 5). The data were analyzed using a χ2-test, independent t-test, and analysis of covariance using the SPSS 25.0 program. Results: Fifty-two percent of university students were categorized as poor-quality sleepers by the PSQI. Students classified as poor-quality sleepers had delayed bedtimes, and a shorter duration in bed and total sleep hours than the good-quality sleepers did. Poor-quality sleepers were more prevalent among those who were female, having irregular mealtimes, or frequent late night meals. They also consumed fast food frequently, such as fried chicken and hamburgers, and noodles when adjusted for gender. In addition, drinks with caffeine over milk were dominant among poor-quality sleepers. Furthermore, the preferences for spicy and salty tastes and longer smartphone usage were more prevalent in those with poor-sleep quality. Conclusions: These results showed that more than 50% of university students reported disturbed sleep and poor quality sleep was associated with less desirable snack consumption and taste preference, more smartphone usage, and others. Therefore, nutrition education program along with lifestyle changes promoting sufficient sleep are encouraged to provide for university students, particularly those who have poor sleep quality.
Objectives More than half of the elders suffer from chronic sleep disturbances. Moreover, sleep disturbances are more prevalent in patients with depressive disorder than in community dwelling elderly. In this study, we aim to estimate the risk factors of poor sleep quality and its effect on quality of life in patients with late life depression. Methods This study included 159 depressive patients aged 65 years or older who completed Pittsburgh Sleep Quality Index (PSQI). A global PSQI score of 5 or greater indicates a poor sleeper. Structural diagnostic interviews were performed using the Korean version of Mini International Neuropsychiatric Interview (MINI). Depression was evaluated by the Korean form of Geriatric Depression Scale (KGDS). Global cognition was assessed by Mini-Mental State Examination in the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease assessment packet. Quality of life was evaluated by the Korean version of Short-Form 36-Item Health Survey (SF-36). Results The frequencies of poor sleepers were 90.5% in major depressive disorder, 71.8% in minor depressive disorder, 47.1% in subsyndromal depressive disorder, and 73.0% in all types of depressive disorders. Multivariate logistic regression analysis indicated that female [odds ratio (OR) = 2.83, 95% confidence interval (CI) = 1.20-6.67] and higher KGDS score (OR = 1.13, 95% CI = 1.05-1.21) were risk factors of poor sleep quality in patients with late life depression. In the analysis of ANCOVA adjusted for age, gender, education and KGDS score, the mean scores of vitality mental health and mental component summary of SF-36 were lower in poor sleepers than in good sleepers. Conclusions Poor sleepers among patients with late life depression are very common and are associated with female and higher KGDS scores. Poor sleep quality causes a significant negative effect on mental health quality. So researchers and clinicians should be more vigilant in the evaluation and treatment of sleep disturbances in patients with late life depression.
Objectives The purpose of this study was to identify differences in sleep by Sasang constitutional type using Pittsburgh Sleep Quality Index(PSQI). Methods The subjects of this study were 3,578 people who had information on Sasang constitutional type and PSQI among the data established at the Korean Medicine Data Center. We compared each item score in PSQI (subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication, daytime dysfunction) and PSQI global scores by Sasang constitutional type using analysis of variance. Logistic regression was conducted to calculate the odds ratio of poor sleep by Sasang constitutional type. Results & Conclusions The SE type showed statistically significantly higher scores than the TE type and SY type in subjective sleep quality, sleep latency, habitual sleep efficiency, sleep disturbance, and PSQI global score, indicating poor sleep compared to other constitutional types. The odds ratio for poor sleep also shows that even after adjusting sex, age, height, and weight, the SE type was significantly higher than other constitutional types, indicating that the SE type could be a risk factor for poor sleep.
Purpose: The purposes of this study were to (a) explore the prevalence of sleep patterns of middle-aged women; (b) identify the relationship between subjective sleep quality and its related variables; and (c) predict the possible explanations of how the related factors affect subjective sleep quality of middle-aged women. Methods: A total of 256 women aged 40-60 years were purposely sampled and given self-administered questionnaires in a cross-sectional, correlation coefficient design. The data was analysed using t-test, one-way ANOVA, Pearson's correlation coefficients, and stepwise multiple regression. Results: The results were as follows; (a) a total of 40% of the women were poor sleepers as defined by a global PSQI score >5; (b) there were significant differences in quality of sleep related to type of family, number of present illnesses, and use of medication; (c) health promoting behaviors, family functioning, depression, and climacteric symptoms were significantly related to subjective sleep quality; and (d) 34% of variance in subjective sleep quality can be explained by climacteric symptoms, depression, type of family, and spouse. Conclusions: Our findings suggested a high proportion of poor sleeping in middle-aged women. Poor sleeping appeared to have poor health promoting behaviors, lower family functioning, worse depression, and higher climacteric symptoms. Climacteric symptoms, depression, type of family, and spouse were independent risk factors for poor sleeping. Nurse professionals should screen for sleep problems in middle-aged women with a biopsychosocial and behavioral aspect.
Purpose: The purpose of this study was to identify the degree of sleep quality and its associated factors in adults. Methods: The data was collected from 986 adults aged 19 to 64 by convenience sampling. Subjects completed a questionnaire composed of Pittsburgh Sleep Quality Index (PSQI), Beck Depression Inventory, and other questions that self-rated health and sociodemographic variables. Statistical methods used included descriptive statistics, simple logistic regression, and multiple logistic regression analyses. Results: The global PSQI score was 5.7. About 45% of the subjects were poor sleepers (global PSQI score >5). Multiple logistic regression analyses showed that factors significantly associated with sleep quality were depression and poor self-rated health in young and middle-aged adults. Depression was the most significant associated factor. The presence of a spouse was also associated with sleep quality in young adults. Conclusion: These findings suggest that people with poor sleep quality should have their health carefully screened for depression. In addition, we recommend the development of a nursing program for improving sleep quality.
The release of hormones and the metabolism of human body are controlled by the circadian rhythm related to sleep-wake cycle. Growth hormone, prolactin, thyroid stimulating hormone, cortisol, glucose, and insulin-secretion rates fluctuate according to the sleep-wake cycle. In addition, sleep is related to the appetite regulation and carbohydrate and other energy metabolism. Hypocretin (orexin), an excitatory neuropeptide, regulates waking and diet intake, and the poor sleep increases diet intake. The short sleep duration increases one's body mass index and impairs the function of the endocrine and metabolism, causing increases in the risk of glucose intolerance and diabetes. The poor sleep quality and sleep disorders have similar impact on the metabolic function. In short, the sleep loss and the poor quality of sleep have a detrimental effect on the endocrine and energy metabolism. The improvement of sleep quality by the future research and appropriate clinical treatment would contribute to the decrease of the metabolic diseases such as diabetes.
Jung, Soo Hyun;Park, Jung Hyun;Yoon, Hyung Jun;Kim, Jung Ho;Kim, Nam Cheol;Kim, Sang Hoon
Journal of the Korean society of biological therapies in psychiatry
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v.24
no.3
/
pp.173-183
/
2018
Objectives : The aim of study was to estimate the prevalence of poor sleep quality and depressive symptoms as well as to examine the moderating effect of positive psychology on the relationship between poor sleep quality and depressive symptoms among Korean university students. Methods : A total of 2,338(1,071 male and 1,267 female) university students at seven universities of four cities in Korea were randomly selected to participate in a survey. Data were collected by self-report questionnaires, including Pittsburgh Sleep Quality Index(PSQI), Beck Depression Inventory(BDI), Satisfaction with Life Scale(SWLS), Positive Psychotherapy Inventory(PPTI), and sociodemographic characteristics. Results : The prevalence was 44.8% for poor sleep quality and 14.4% for depressive symptoms among Korean university students. By moderated regression analysis, the results showed that poor sleep quality(${\beta}=0.453$, p<0.001) aggravated depressive symptoms of university students, and life satisfaction(${\beta}=-0.087$, p<0.001) and happiness(${\beta}=-0.145$, p<0.001) respectively buffered the negative effect of the poor sleep quality on depressive symptoms. Conclusion : This study showed very high prevalence of poor sleep quality and depressive symptoms among Korean university students. Overall, these findings demonstrates that positive psychology can be effective in the enhancement of subjective and psychological well-being and may help to reduce depressive symptom levels. In the context of public health, positive psychology can be used as preventive, easily accessible and non-stigmatizing tools.
Journal of Physiology & Pathology in Korean Medicine
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v.34
no.1
/
pp.37-44
/
2020
Previous studies have reported an association between poor sleep and various symptoms and diseases, such as fatigue, obesity, depression, and anxiety. The effects of poor sleep may differ by age and sex. In addition, sleep characteristics and their effects may vary according to Sasang constitutional type. The aim of this study was to investigate the associations between sleep quality, fatigue, and quality of life and to assess whether these differ by constitutional type. Participants were individuals aged 40-69 years living in two Korean communities in 2012-2014. Sleep quality, fatigue, and quality of life were measured using the Pittsburgh Sleep Quality Index (PSQI), the Fatigue Severity Scale, and the 12-item Short Form Health Survey, respectively. The effects of total PSQI score and PSQI component scores were analyzed using a generalized additive model. A Korean Sasang constitutional diagnostic questionnaire was used to assess Sasang constitution. Data for 5,793 participants were analyzed. Poor sleep quality was related to greater fatigue, and lower physical and mental quality of life. The PSQI components including subjective sleep quality, sleep latency, sleep disturbances, use of sleep medications, and daytime dysfunction were associated with fatigue and physical and mental quality of life. Sleep quality was significantly lower in So-Eum compared to So-Yang and Tae-Eum. PSQI component scores for fatigue and quality of life differed significantly by Sasang constitution: for Tae-Eum, sleep latency and use of sleep medications; for So-Eum, daytime dysfunction; and for So-Yang, use of sleep medications and daytime dysfunction. The effects of different aspects of sleep quality differ by Sasang constitution. To improve sleep quality, interventions need to be tailored to constitutional type.
Seo, Bok-Nam;Jeong, Kyoungsik;Baek, Younghwa;Lee, Siwoo
Journal of Physiology & Pathology in Korean Medicine
/
v.35
no.1
/
pp.42-46
/
2021
The purpose of this study was to investigate the relationship between sleep quality and sleep duration according to individual characteristics, and the relationship between sleep quality and cold type. A total of 1998 participants aged 30-55 who participated in a community cohort study at KIOM's Oriental Medicine Data Center (KDC) was analyzed. Cold type was diagnosed with a common the Questionnaire of Cold Pattern Identification (8 items). Sleep quality was assessed by the Pittsburgh Sleep Quality Index. The participants in this study were classified into 1193 with cold type and 805 with non-cold type. The poor sleep quality was found in more women than men, and the Body Mass Index (BMI) was higher in the non-cold type. In the cold type group, average sleep quality was poor and sleep duration was short. There was a statistically significant correlation between cold score, sleep quality, and sleep duration. Cold type was related to the sleep quality. The risk of poor sleep quality increased 1.46 with increased cold type (95% CI = 1.16-1.84, p <.001). In particular, it was found that various programs to improve the quality of sleep, focusing on the cold type among personal characteristics, are needed to maintain adequate sleep to improve the sleep quality. In the future, when analyzing the relationship between cold type and sleep quality, it is thought that an attempt to derive other objective quantitative indicators is needed.
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