Association between healthy sleep patterns and depressive trajectories among college students: a prospective cohort study

Author:

Dan Zhang1,Qu Yang1,Zhai Shuang1,Li Tingting1,Xie Yang1,Tao Shuman2,Zou Liwei1,Tao Fangbiao1,Wu Xiaoyan1

Affiliation:

1. Anhui Medical University

2. The Second Hospital of Anhui Medical University

Abstract

Abstract Background: The purpose of this study was to identify different develpment trajectories of depression symptoms during college period, and prospectively investigate the associations healthy sleep patterns with trajectories of depression symptoms among college students from freshman through junior year. Methods: A total of 999 participants from the College Student Behavior and Health Cohort Study were included between April 2019 and June 2021. Healthy sleep patterns were defined by chronotype, sleep duration, insomnia, snoring, and daytime sleepiness. Latent growth curve model was used to identify trajectories of depression symptoms. Then binary logistic regression was used to examine association of the healthy sleep patterns with these trajectories. Results:In baseline survey, we found that a total of 100 (10.0%) participants had healthy sleep patterns’score equal to 5. Then, we used 5 surveys’data to identify 2 distinct trajectories of depression symptoms during college (decreasing: 82.5%; increasing: 17.5%). The healthy sleep patterns were associated with these trajectories, the better healthy sleep patterns significantly decrease the risk of increasing trajectories of depression symptoms in males (OR: 0.72, 95%CI: 0.54~0.97, P=0.031). Moreover, we found out that the healthy sleep patterns of college students can predict the future depressive symptoms in this study (all P<0.001). Conclusion:Our findings indicate that the better healthy sleep patterns may significantly decrease the risk of increasing trajectory of depression symptoms only in male college students. The results speak to a need for college student with depression symptoms to identify and address sleep problems when present, which could prevent or reduce depression detriments in later life.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3