Skip to Main Content
 
Translator disclaimer

ABSTRACT

Objective: This study explored the association of stress and depression with a multidimensional sleep problems construct in a sample of 2-year college students. Participants: The sample consisted of 440 students enrolled in 2-year study from Fall 2011 to Fall 2013. Methods: Participants in an obesity prevention study completed surveys assessing sleep, stress, and depression at baseline, 4, 12, and 24 months. Multilevel models predicting sleep problems were conducted to distinguish episodic from chronic reports of stress and depression. Results: Participants were primarily women (68%), white (73%), young adults (M age = 22.8), with an average of 8.4 hours of sleep per night. Neither stress nor depression was predictive of sleep quantity; however, they were predictive of sleep quality. Conclusions: Results show that sleep quality rather than sleep quantity may be the greater health concern for young adults, suggesting that intervention programs targeting depression, stress management, and healthy sleep patterns are warranted.

Acknowledgments

The authors thank the students and the staff at Anoka-Ramsey Community College, Inver Hills Community College, and St. Paul College for the support and help with this project.

Conflict of interest disclosure

The authors have no conflicts of interest to report. The authors confirm that the research presented in this article meet the ethical guidelines, including adherence to the legal requirements, of the United States and received approval from the Institutional Review Board of the University of Minnesota.

Funding

This research was supported through a grant from NHLBI (1 U01 HL096767-01: Leslie A. Lytle, Principal Investigator).

Log in via your institution

Log in to Taylor & Francis Online

Purchase * Save for later
Online

Article Purchase 48 hours to view or download: USD 45.00 Add to cart

Issue Purchase 30 days to view or download: USD 105.00 Add to cart

* Local tax will be added as applicable
 

Further reading

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.