Women aged 20 to 30 who reported having trouble sleeping were 4 times significantly more likely to have experienced depression.
Ortiginal Reserch by Rifath Ara Alam Barsha, MBBS, MPH and Mian B. Hossain, PhD.
Depression and sleep disorder
Depression is one of the most common psychiatric disorders. In the United States, depressive disorders were the second leading cause of years lived with disability in 2010 . Women are more likely to have depression than men. During 2013–2016, 10.4% of US women aged 20 or older had depression in a given 2-week period and were almost twice as likely as men (5.5%) to have had depression. Although this sex difference persists throughout the female lifespan, it seems to vary according to reproductive stage (puberty, the week or so before menstruation, after pregnancy, and perimenopause). Female hormonal fluctuation may be a trigger for depression . Depression is associated with decreased physical, cognitive, and social function; it is often chronic and impairs quality of life . Depression is predicted to be the leading cause of disease burden by 2030, and it is already the leading cause of disease burden in young adult women worldwide . Therefore, treatment and prevention of depression have become an important topic in the field of public health.
Sleep is an important determinant of a person’s overall health and well-being. Sleep, as a critical health-related factor, plays a role in the development of many diseases and even all-cause mortality. Sleep disturbance is one of the most common health complaints among young adults . Although 7 to 9 hours of sleep per night on weeknights is recommended for young and midlife adults , 40% of US adults have reported fewer than 7 hours of sleep per night . Of young adults aged 19 to 29, 67% reported not getting enough sleep to function properly . Many psychosocial, biological, and environmental factors contribute to insufficient sleep and sleep disturbance among young adults. The high prevalence of sleep-related disturbances may be partially due to increased academic, social, and work demands. Female sex is also a risk factor for sleep problems. Several studies showed that young adult women are twice as likely as young men to have poor sleep. Thus, young women appear to be a particularly vulnerable population to both sleep problems and depression.
Previous studies suggested an association between depression and sleep disturbances in older people) and an association between sleep disturbances and poor quality of life among women. Less research has been conducted among young adults, who are at particular risk of sleep problems and alterations in circadian timing as a result of developmental and social influences. This age group is at an important stage of life, when early interventions or treatment of sleep problems may have clinical implications. Little research has explored the relationship between sleep and depression among young women, even though the correlates of depression may differ between young women and older women. Understanding the relationships between sleep and depression and correlates among young women may increase the potential to intervene and improve mental health outcomes before they become clinically concerning. The objective of our study was to assess the relationship between trouble sleeping and depression among US women aged 20 to 30 and to determine whether trouble sleeping increased the odds of depression in this population. We hypothesized that ever having trouble sleeping would be associated with depression among women in this age group.
The sleep disorders questionnaire was administered in the home by computer-assisted personal interview during the initial survey participant interview. Participants were asked the following question about trouble sleeping: “Have you ever told a doctor or other health professional that you have trouble sleeping?” If the participant’s response to this question was yes, she was considered to have trouble sleeping.
Depressive symptoms were assessed via the Patient Health Questionnaire-9 (PHQ-9), a self-administered questionnaire that assesses depressive symptoms according to the guidelines of the fourth edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-IV) . Each question is scored according to the frequency of the symptom during the previous 2 weeks, and responses are made on the following scale: not at all , several days , more than half the days , and nearly every day . The PHQ-9 is considered an effective tool for assessing depressive symptoms and a reliable tool for determining instances of both subthreshold and major depression among population samples . A total PHQ-9 score greater than 9 (of a possible 27) indicates the presence of depression in single-screening assessments , and we used this cutoff. Depression was treated as the dependent variable in our analysis.
Approximately 9.3% of sample of 1,747 women reported having depression in the previous 2 weeks . The prevalence of having trouble sleeping was 19.6%. Among women who reported trouble sleeping, 22.3% reported having depression in the previous 2 weeks. Most (55.9%) of the women in our sample were aged 20 to 25. Most were non-Hispanic white (59.4%), followed by Hispanic (17.7%), non-Hispanic black (13.5%), and other races (9.4%). About two-fifths (41.9%) had some college. Most women (48.1%) were married or living together, and about 25.4% were living below 100% of the FPL. Most respondents had health insurance coverage (75.6%). More than half (57.9%) reported ever using marijuana, and marijuana use was more common among women who reported having a sleep problem (70.3%).
Depression was significantly more prevalent among women who reported ever having trouble sleeping (22.6%) than among women reporting no trouble (6.5%) and significantly more prevalent among women aged 20 to 25 (10.7%) than among women aged 26 to 30 (8.1%). The prevalence of depression was higher among women who did not complete high school (12.9%) than among women with a high school degree (11.3%), some college (10.7%), or a college degree or above (4.1%). Similarly, the prevalence of depression was also significantly higher among women living below 100% of the FPL (12.9%) than among women in other categories of income, among women without health insurance than among women with health insurance (12.8% vs 8.3%), among women with diabetes than among women without diabetes (24.0% vs 9.3%), and among women who ever used marijuana than among women who never used it (12.9% vs 5.4%).
Our study demonstrated a strong and significant association between trouble sleeping and depression in a nationally representative sample of US women aged 20 to 30. Young women who reported trouble sleeping were significantly more likely to have depression than those who had no sleep problems. After adjusting for several socioeconomic, demographic, and health-related factors (ie, race/ethnicity, age, education, marital status, family size, poverty status, health insurance status, diabetes, and marijuana use), the association remained significant.
Although previous research is scant in similar populations, our findings on sleep problems among young women are consistent with those in a previous study of young women in Australia, which showed an increased risk of depression among women who reported sleep difficulties . Another important finding of our study is that women with lower educational attainment were more likely to report depression than those with more education; for example, women with only some college were significantly more likely than women with a college degree or more to report depression. An association between lower educational attainment and higher risk for depressive disorders was shown in previous studies. A meta-analysis found a 3% decrease in the log odds ratio for depression for each additional year of education. Several studies also documented the relationship between educational attainment and sleep problems: higher levels of education were associated with fewer sleep complaints. Our finding on the relationship between education and depression may be important because it strengthens evidence for the idea that obtaining higher levels of education may protect against depression among young women. Considering the possible protective role of education against depression, we further analyzed the interaction between education and sleep. However, the interaction model was not significant; hence, we did not present these findings here.
We also found a higher prevalence of depression among women living below the FPL. This finding is also congruent with previous research findings. One study reported a higher prevalence of depression in people of low socioeconomic status. In that study, women had a 40% greater risk of past-month depression than men, and women with income levels below the FPL had twice the risk of depression of men. Therefore, interventions aimed at reducing the burden of depression may need to target vulnerable populations of young women who have limited financial resources.
We found that depression was significantly associated with health insurance status and was less common among women with health insurance than among those without. This finding may be particularly important because previous research showed that uninsured people with depression and other mental illnesses were less likely than insured people to receive appropriate care. Furthermore, our study found that women with diabetes were significantly more likely to have depression. The prevalence of depression is higher among people with diabetes than among the general population . Therefore, health care providers should be aware of mental as well as physical health when treating patients with diabetes. This finding implies that health care professionals may have an important role in moderating the psychological burden of a diabetes diagnosis by addressing the patient’s psychosocial support.
Comorbidity of depression and marijuana use has been studied extensively, with evidence showing a high prevalence of depression among marijuana users. Our study found a higher prevalence of depression among young women who ever used marijuana than among women who had never used it, which is consistent with previous research. However, we could not differentiate between recreational and medical marijuana use. Given the changing political landscape of marijuana use, further studies focused on the potential effects and differences between recreational and medical marijuana use on depression among young women will be needed to shape prevention and treatment strategies.
Although our χ2 test found that women aged 20 to 25 were significantly more likely than women aged 26 to 30 to report depression, this relationship between age and depression was not significant after we adjusted for other covariates. That this relationship became nonsignificant may have been due to the small sample size or the effects of other factors contributing to the relationship. However, one previous study documented that the prevalence of major depression decreased with age. Therefore, younger age may be significantly associated with depression, and future research should further investigate the relationship between age and depression.
The study has several strengths. Our research included a large, population-based, representative sample of young women in the assessment of the association between sleep disturbances and depression, allowing broad generalization of the results. Additionally, the NHANES data set provides information on a large sample of the general population, rather than on a specific patient group, and thereby provides information on the degree of disease burden at this level. Moreover, we made statistical adjustments for differences in a number of health and lifestyle covariates. Such an approach provided a more detailed assessment of the strength of the association.
The study has several limitations. Although some people may have sleep disturbances before developing depressive symptoms, some may have a depression disorder before the onset of sleep disturbances. The cross-sectional design of our analysis did not allow for interpretation of the direction of the relationship, and a causal relationship cannot be inferred. Moreover, the cross-sectional design and use of secondary data limited the scope of the variable of interest. Additionally, our study estimated the prevalence of trouble sleeping among young women who ever reported having sleep disturbances to a doctor or a health professional. Therefore, we could not differentiate between women with recent sleep disturbances and women with former sleep disturbances. Another limitation of the study was that most of the information collected was self-reported. However, despite these limitations, we believe this nationally representative sample provides some insight into associations between sleep disturbance and depression among young women in the United States.
Women aged 20 to 30 with sleep disturbances should have access to screening and treatment from health professionals. The association between trouble sleeping and depression has public health implications: young women seeking treatment for sleep problems may need to be screened for depression. Interventions that are designed to help such women may result in a decreased prevalence of depression in this population. Sleep is essential, and healthy sleep should be as important as healthy nutrition and physical activity in promoting overall health.
1. Murray CJL, Atkinson C, Bhalla K, Birbeck G, Burstein R, Chou D, et al. The state of US health, 1990–2010: burden of diseases, injuries, and risk factors. JAMA 2013;310(6):591–608.10.1001/jama.2013.13805 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
2. Brody DJ, Pratt LA, Hughes JP. Prevalence of depression among adults aged 20 and over: United States, 2013–2016. NCHS Data Brief 2018;(303):1–8. [PubMed] [Google Scholar]
3. Albert PR. Why is depression more prevalent in women? J Psychiatry Neurosci 2015;40(4):219–21. 10.1503/jpn.150205 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
4. Daly EJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Gaynes BN, Warden D, et al. Health-related quality of life in depression: a STAR*D report. Ann Clin Psychiatry 2010;22(1):43–55. [PubMed] [Google Scholar]
5. Li Y, Wu Y, Zhai L, Wang T, Sun Y, Zhang D. Longitudinal association of sleep duration with depressive symptoms among middle-aged and older Chinese. Sci Rep 2017;7(1):11794.10.1038/s41598-017-12182-0 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
6. Hicks RA, Mistry R, Lucero K, Lee L, Pellegrini R. The sleep duration and sleep satisfaction of college students: striking changes over the last decade (1978–1988). Percept Mot Skills 1989;68(3 Pt 1):806.10.2466/pms.1918.104.22.1686 [PubMed] [CrossRef] [Google Scholar]
7. Ford DE, Kamerow DB. Epidemiologic study of sleep disturbances and psychiatric disorders. An opportunity for prevention? JAMA 1989;262(11):1479–84.10.1001/jama.1989.03430110069030 [PubMed] [CrossRef] [Google Scholar]
8. Hirshkowitz M, Whiton K, Albert SM, Alessi C, Bruni O, DonCarlos L, et al. National Sleep Foundation’s sleep time duration recommendations: methodology and results summary. Sleep Health 2015;1(1):40–3.10.1016/j.sleh.2014.12.010 [PubMed] [CrossRef] [Google Scholar]
9. Levenson JC, Shensa A, Sidani JE, Colditz JB, Primack BA. The association between social media use and sleep disturbance among young adults. Prev Med 2016;85:36–41.10.1016/j.ypmed.2016.01.001 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
10. Gradisar M, Wolfson AR, Harvey AG, Hale L, Rosenberg R, Czeisler CA. The sleep and technology use of Americans: findings from the National Sleep Foundation’s 2011 Sleep in America poll. J Clin Sleep Med 2013;9(12):1291–9.10.5664/jcsm.3272 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
11. Yang C-M, Wu C-H, Hsieh M-H, Liu M-H, Lu F-H. Coping with sleep disturbances among young adults: a survey of first-year college students in Taiwan. Behav Med 2003;29(3):133–8.10.1080/08964280309596066 [PubMed] [CrossRef] [Google Scholar]
12. Hale L, Do DP, Basurto-Davila R, Heron M, Finch BK, Dubowitz T, et al. Does mental health history explain gender disparities in insomnia symptoms among young adults? Sleep Med 2009;10(10):1118–23.10.1016/j.sleep.2008.12.011 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
13. Leger D, Guilleminault C, Dreyfus JP, Delahaye C, Paillard M. Prevalence of insomnia in a survey of 12,778 adults in France. J Sleep Res 2000;9(1):35–42.10.1046/j.1365-2869.2000.00178.x [PubMed] [CrossRef] [Google Scholar]
14. Yokoyama E, Kaneita Y, Saito Y, Uchiyama M, Matsuzaki Y, Tamaki T, et al. Association between depression and insomnia subtypes: a longitudinal study on the elderly in Japan. Sleep 2010;33(12):1693–702.10.1093/sleep/33.12.1693 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
15. Roberts RE, Shema SJ, Kaplan GA, Strawbridge WJ. Sleep complaints and depression in an aging cohort: a prospective perspective. Am J Psychiatry 2000;157(1):81–8.10.1176/ajp.157.1.81 [PubMed] [CrossRef] [Google Scholar]
16. Byles JE, Mishra GD, Harris MA. The experience of insomnia among older women. Sleep 2005;28(8):972–9.10.1093/sleep/28.8.972 [PubMed] [CrossRef] [Google Scholar]
17. Johnson CL, Paulose-Ram R, Ogden CL, Carroll MD, Kruszon-Moran D, Dohrmann SM, et al. National Health and Nutrition Examination Survey: analytic guidelines, 1999–2010. Vital Health Stat 2 2013;(161):1–24. [PubMed] [Google Scholar]
18. Hunter JC, DeVellis BM, Jordan JM, Sue Kirkman M, Linnan LA, Rini C, et al. The association of depression and diabetes across methods, measures, and study contexts. Clin Diabetes Endocrinol 2018;4(1):1.10.1186/s40842-017-0052-1 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
19. Hayley AC, Williams LJ, Venugopal K, Kennedy GA, Berk M, Pasco JA. The relationships between insomnia, sleep apnoea and depression: findings from the American National Health and Nutrition Examination Survey, 2005–2008. Aust N Z J Psychiatry 2015;49(2):156–70.10.1177/0004867414546700 [PubMed] [CrossRef] [Google Scholar]
20. Kroenke K, Spitzer RL. The PHQ-9: A new depression diagnostic and severity measure. Psychiatr Ann 2002;32(9):509–15. 10.3928/0048-5713-20020901-06 [CrossRef] [Google Scholar]
21. Jackson ML, Sztendur EM, Diamond NT, Byles JE, Bruck D. Sleep difficulties and the development of depression and anxiety: a longitudinal study of young Australian women. Arch Women Ment Health 2014;17(3):189–98.10.1007/s00737-014-0417-8 [PubMed] [CrossRef] [Google Scholar]
22. Lorant V, Deliège D, Eaton W, Robert A, Philippot P, Ansseau M. Socioeconomic inequalities in depression: a meta-analysis. Am J Epidemiol 2003;157(2):98–112.10.1093/aje/kwf182 [PubMed] [CrossRef] [Google Scholar]
23. Grandner MA, Patel NP, Gehrman PR, Xie D, Sha D, Weaver T, et al. Who gets the best sleep? Ethnic and socioeconomic factors related to sleep complaints. Sleep Med 2010;11(5):470–8.10.1016/j.sleep.2009.10.006 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
24. Gellis LA, Lichstein KL, Scarinci IC, Durrence HH, Taylor DJ, Bush AJ, et al. Socioeconomic status and insomnia. J Abnorm Psychol 2005;114(1):111–8.10.1037/0021-843X.114.1.111 [PubMed] [CrossRef] [Google Scholar]
25. Kessler RC, Berglund P, Demler O, Jin R, Koretz D, Merikangas KR, et al.; National Comorbidity Survey Replication. The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R). JAMA 2003;289(23):3095–105.10.1001/jama.289.23.3095 [PubMed] [CrossRef] [Google Scholar]
26. McWilliams JM. Health consequences of uninsurance among adults in the United States: recent evidence and implications. Milbank Q 2009;87(2):443–94.10.1111/j.1468-0009.2009.00564.x [PMC free article] [PubMed] [CrossRef] [Google Scholar]
27. Bădescu SV, Tătaru C, Kobylinska L, Georgescu EL, Zahiu DM, Zăgrean AM, et al. The association between diabetes mellitus and depression. J Med Life 2016;9(2):120–5. [PMC free article] [PubMed] [Google Scholar]
28. Chen C-Y, Wagner FA, Anthony JC. Marijuana use and the risk of major depressive episode. Epidemiological evidence from the United States National Comorbidity Survey. Soc Psychiatry Psychiatr Epidemiol 2002;37(5):199–206.10.1007/s00127-002-0541-z [PubMed] [CrossRef] [Google Scholar]
29. Kessler RC, Birnbaum HG, Shahly V, Bromet E, Hwang I, McLaughlin KA, et al. Age differences in the prevalence and co-morbidity of DSM-IV major depressive episodes: results from the WHO World Mental Health Survey Initiative. Depress Anxiety 2010;27(4):351–64.10.1002/da.20634 [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Note: This article is based on “ Trouble Sleeping and Depression Among US Women Aged 20 to 30 Years ” dated 2020 Apr 2 and published in PMC