Deteriorated sleep quality and influencing factors among undergraduates in northern Guizhou, China

Prevalence and related factors of sleep quality among Chinese undergraduates in Jiangsu Province: multiple models' analysis

Background and aims

In China, a significant number of undergraduates are experiencing poor sleep quality. This study was designed to investigate the prevalence of poor sleep quality and identify associated factors among undergraduates in Jiangsu Province, China.

Methods

A total of 8,457 participants were collected in 2022 using whole-group convenience sampling. The factors studied included basic demographics, family and social support, personal lifestyles, physical and mental health, mobile phone addiction index (MPAI), and the Connor-Davidson resilience scale (CD-RISC). The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. Four models, including weighted multiple linear regression, binary logistic regression, weighted linear mixed model, and logistic regression with random effects, were applied to identify associated factors for sleep quality.

Results

Of the 8,457 participants analyzed, 26.64% (2,253) were classified into the poor sleep quality group with a PSQI score >7. No significant relationship was found between sleep quality and gender, native place, economic level of family, physical exercise, dormitory light, dormitory hygiene, and amativeness matter. Risk factors for sleep quality identified by the four models included lower CD-RISC, higher MPAI, fourth grade or above, smoking, drinking, greater academic pressure, greater employment pressure, roommate sleeping late, noisy dormitory, poorer physical health status, poorer mental health status, and psychological counseling.

Conclusions

These findings provide valuable insights for university administrators, enabling them to better understand the risk factors associated with poor sleep quality in undergraduates. By identifying these factors, administrators can provide targeted intervention measures and counseling programs to improve students' sleep quality.

Factors associated with sleep disorders among university students in Jiangsu Province: a cross-sectional study

Objective

This study aims to establish the precise prevalence of sleep disorders among university students in Jiangsu Province. Utilizing a representative sample of students, we measured their sleep quality based on the Pittsburgh Sleep Quality Index (PSQI). Our objective is to quantitatively assess the magnitude of sleep quality and identify key factors. By detailed analysis of these relationships, our study seeks to provide actionable insights for the development of targeted interventions to enhance sleep quality within this population.

Methods

From October to November 2022, we conducted a cross-sectional web-based survey in Jiangsu Province, China. Using convenient cluster sampling in each college, a total of 8457 participants were selected. The PSQI was applied to assess sleep quality among university students. Data collected included sociodemographic details, scores from the Mobile Phone Dependence Index (MPAI) and psychological resilience measured by the Connor-Davidson Resilience Scale (CD-RISC).

Results

The overall prevalence of poor sleep quality among the participants was 39.30%. Binary logistic regression analysis revealed that higher physical activity (OR = 0.921; 95% CI: 0.779-1.090), earlier roommate bedtimes (OR = 0.799; 95% CI: 0.718-0.888), quieter dormitories (OR = 0.732; 95% CI: 0.647-0.828) and higher psychological resilience (OR = 0.982; 95% CI, 0.979-0.984) were protective factors linked to lower risk of poor sleep quality. Conversely, being a female student (OR = 1.238; 95% CI: 1.109-1.382), being a senior (OR = 1.582; 95% CI: 1.344-1.863), single-child status (OR = 1.195; 95% CI: 1.077-1.326), regular smoking (OR = 1.833; 95% CI: 1.181-2.847), regular alcohol consumption (OR = 1.737; 95% CI: 1.065-2.833), high academic stress (OR = 1.326; 95% CI: 1.012-1.736), high employment stress (OR = 1.352; 95% CI: 1.156-1.582), dissatisfaction with dormitory hygiene (OR = 1.140; 95% CI: 1.028-1.265), poor self-rated physical health (OR = 1.969; 95% CI: 1.533-2.529), poor self-rated mental health (OR = 2.924; 95% CI: 2.309-3.702) and higher mobile phone dependency were risk factors associated with an increased likelihood of poor sleep quality.

Conclusion

The sleep quality among university students should attract immediate attention. The development of public services and mental health education initiatives is crucial in enhancing the sleep health of this population.

Chronotypes and their association with sleep quality among Chinese college students of Anhui Province: a cross-sectional study

OBJECTIVES

To describe the prevalence of chronotype and sleep quality among Chinese college students and explore the relationship between chronotype and sleep quality.

DESIGN

A cross-sectional study.

SETTING

Four colleges and universities in Anhui, China, between November and December 2020.

PARTICIPANTS

A total of 4768 college students were recruited using a stratified, multistage, cluster sampling survey.

OUTCOME MEASURES

Morningness-Eveningness Questionnaire 19 was used to determine the chronotype of the students and the Pittsburgh Sleep Quality Index (PSQI) was used to measure their sleep quality. The multiple logistic regression model was used to explore the potential association between chronotype and sleep quality.

RESULTS

The self-reported proportions of evening-type (E-type), neutral-type and morning-type among college students were 51.17%, 45.14% and 3.69%, respectively. The mean PSQI score was 4.97±2.82 and the prevalence of poor sleep quality was 18.2%. After adjusting the covariates by multiple logistic regression analysis, E-type was positively associated with subjective sleep quality (OR=1.671, 95% CI 1.414 to 1.975), sleep latency (OR=1.436, 95% CI 1.252 to 1.647), sleep duration (OR=2.149, 95% CI 1.506 to 3.067), habitual sleep efficiency (OR=1.702, 95% CI 1.329 to 2.180), daytime dysfunction (OR=1.602, 95% CI 1.412 to 1.818) and overall poor sleep quality (OR=1.866, 95% CI 1.586 to 2.196).

CONCLUSIONS

College students mainly exhibited E-type, and an elevated prevalence of poor sleep quality existed among these students. The E-type was positively associated with poor sleep quality.

Study on lifestyle habits affecting sleep disorders at the undergraduate education stage in Xuzhou City, China

Background

In China, undergraduate students face both academic and career selection pressures, sleep is an important physiological process for them. Investigate the physical exercise, sleep quality of undergraduate students in the education stage in Xuzhou City, and analyze the factors affecting their sleep quality, to promote the health education and psychological health of undergraduate students.

Materials and methods

The Physical Activity Rating Scale-3 (PARS-3), the Pittsburgh Sleep Quality Index (PSQI), and the demographic information questionnaire were used to survey a whole-group sample of four undergraduate colleges and universities (Xuzhou Institute of Engineering, Xuzhou Medical University, China University of Mining and Technology, Jiangsu Normal University) in Xuzhou by cluster sampling, the general characteristics including gender, grade, height, weight, domicile, race, economic income, etc., were collected, and the data were analyzed and processed using chi-square tests and multi-factor logistic regression.

Results

3,366 valid questionnaires were collected from four undergraduate colleges and universities, including 1,355 males and 2,011 females. The detection rate of exercise in Jiangsu Normal University was lower than that in other universities, and the detection rate of sleep disorders was higher than that in other universities. Xuzhou Medical University, the highest detection rate of large exercise, Xuzhou Institute of Technology, the lowest detection rate of sleep disorders. There were significant differences in the detection rate of large amount of exercise among college students of different genders, grades, body types, and majors (χ2 = 259.172, P < 0.001; χ2 = 34.473, P < 0.001; χ2 = 36.026, P < 0.001; χ2 = 57.908, P < 0.001). There were significant differences in the detection rate of sleep disorders among college students with different gender, grade, family economic status, daily cell phone use time, cell phone purposeless usage, and exercise level (χ2 = 5.806, P = 0.016; χ2 = 47.5, P < 0.001; χ2 = 28.949, P < 0.001; χ2 = 55.866, P < 0.001; χ2 = 147.101, P < 0.001; χ2 = 9.129, P = 0.010). Multivariate logistic regression analysis showed that grade, family economic status, cell phone use time, cell phone purposeless usage is the main influencing factors of sleep disorders in college students.

Conclusion

The sleep problems of undergraduates are serious, especially in Jiangsu Normal University. Scientific and appropriate exercise is an important measure to solve the sleep problems of undergraduates. Colleges and universities should actively carry out health education, college students living habits such as cell phone use should be guided training.