Associations of sleep quality trajectory and social jetlag with comorbid symptoms of anxiety and depression among college students
10.16835/j.cnki.1000-9817.2024161
- VernacularTitle:大学生睡眠质量轨迹和社会时差与焦虑抑郁症状共患的关联
- Author:
XIANG Bo, NIU Yaqian, LI Tingting, XIE Yang, TAO Shuman, YANG Yajuan, ZOU Liwei, TAO Fangbiao, WU Xiaoyan
1
Author Information
1. Department of Maternal with Child and Adolescent Health, School of Public Health, Anhui Medical University, Hefei (230032) , Anhui Province, China
- Publication Type:Journal Article
- Keywords:
Sleep;
Anxiety;
Depression;
Comorbidity;
Mental health;
Students
- From:
Chinese Journal of School Health
2024;45(5):640-643
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students.
Methods:A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression.
Results:The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05).
Conclusions:Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.
