Association between sleep quality and quality of life among students: a cross sectional study

Abstract

Background Lack of sleep and on going sleep disorder can affect family health and interpersonal relationships. Objective The aim of study was to investigate the association between sleep quality and the probable determinants of quality of life among students of a public health faculty at Shahid Beheshti University of Medical Sciences (SBMU) in the 2015 academic year. Methods The data from a cross-sectional study of 275 students that randomly stratified sampling between different classes of college students of a public health faculty of Shahid Beheshti University of Medical Sciences were used in this study. The data were collected using a structured questionnaire consisted of modules on socio-demographic characteristics, the Petersburg Standardized Sleep Quality Questionnaire(PSQL) and the World Health Organization Quality of Life Questionnaire (WHOQOL-BREF). Data analysis was done with descriptive and logistic regression. All analyses were carried out using SPSS software V.19. Results A total of 275 students participated in this study. The mean age ± standard deviation (SD) was 22.1 ± 3.6 years. In the univariable model, students that were living in their own homes had the odds of 2.18 times more than the others to have a higher quality of life level [95% confidence interval (CI): 1.07-4.45]. Moreover, sleep disorder was negatively associated with the quality of life [odds ratio (OR) = 0.23; 95% CI: 0.12-0.46]. Conclusion These results will help university administrators and policy makers to identify factors associated with poor sleep and provide approaches to enhance sleep hygiene and relevant knowledge in university students. Living in a dormitoy while also suffering from sleep problems could significantly reduce the quality of life.

Sleep Disturbances Rate among Medical and Allied Health Professions Students in Iran: Implications from a Systematic Review and Meta-Analysis of the Literature

“…These studies did not use the PSQI, but rather self-report questionnaires. Finally, 17 investigations were included in the meta-analytical part of the study [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36]. Two studies reported the mean scores of the PSQI indicating poor sleep quality but not enough quantitative details enabling computation of the prevalence rate of sleep disturbances, and were therefore excluded with reason from the quantitative synthesis.…”

Sleep Quality, Mental and Physical Health: A Differential Relationship

“…Scores equal to or less than 30 are considered a risk. The SF-12 is a valid and reliable measurement tool, with an internal consistency exceeding 0.70 [ 25 ]. In the current sample, the Cronbach’s Alpha was 0.81 for the global score.…”

“…Sleep quality is a broad concept that includes several measures such as sleep latency, sleep efficiency, sleep disturbances, sleep duration, and use of sleeping medication among others [ 19 ]. Previous research has shown that poor sleep quality among university students is high [ 20 , 21 , 22 ] There is a significant amount of scientific literature that has previously addressed the relationship between sleep quality and HRQoL in adolescents [ 23 ] and young adults [ 24 , 25 ]. It has been found that people suffering from sleep disorders have lower levels of both physical and mental HRQoL showing moderate R 2 for the physical and mental components, although depending on the disorder, the impact of some disorders is more pronounced on the mental component or the physical component (e.g., apnea has a higher impact on physical health whereas insomnia has a higher impact on mental health) [ 26 ].…”

The Association of Oral Health Status, demographic characteristics and socioeconomic determinants with Oral health-related quality of life among children: a systematic review and Meta-analysis

“…The trend of pooled ORs according to country's Human Development Index [34] (range = 0.761-0.939), sample size (range = 260-1134), year of study and age of participants (range = 3-12 years) was calculated by cumulative regression analysis. HDI data was obtained from World Bank data [35].…”