Sleep and Depressive Symptoms in Sedentary Community-Dwelling Older Adults With Sleep Complaints: Findings From Ambulatory Sleep EEG

Abstract

Background

There is limited and inconsistent evidence on the association between electroencephalography (EEG) measured sleep and depressive symptoms among community-dwelling older adults. This study aimed to investigate the cross-sectional association between EEG-measured sleep and depressive symptoms.

Methods

Using baseline data from a randomized clinical trial, we included 66 sedentary community-dwelling older adults with sleep complaints (≥ 1 self-reported insomnia symptom). Sleep was measured using an in-home sleep EEG (Sleep Profiler™) for 2 nights and the Geriatric Depression Scale (GDS-15) was used to measure depressive symptoms. Multiple linear regression analyses were conducted with each sleep parameter as the primary predictor and GDS score as the outcome, adjusting for age, sex, race, education, marital status, chronic conditions, and Montreal Cognitive Assessment (MoCA) score.

Results

Several sleep variables were associated with depressive symptoms (GDS score), including a higher percentage of sleep stage N1 (B = 0.11, 95% confidence interval [CI]: 0.02 – 0.20) and N2 (B = 0.04, 95% CI: 0.00 – 0.08), a lower percentage of N3 sleep (B = −0.04, 95% CI: −0.08 to −0.01), greater wake after sleep onset (B = 0.01, 95% CI: 0.00 – 0.02), and a greater number of awakenings ≥90s/hour (B = 0.87, 95% CI: 0.21-1.53).

Conclusions

Our study reveals that among sedentary community-dwelling older adults with sleep complaints, more lighter sleep (stage N1, N2), less deep (N3) sleep, and increased awakenings are associated with more depressive symptoms. Sleep interventions aimed at enhancing sleep architecture may also help alleviate depressive symptoms in this population.

Keywords

depression sleep ambulatory EEG sleep architecture community-dwelling older adults

Get full access to this article

View all access options for this article.

References

Bao

Y-P

. Cooccurrence and bidirectional prediction of sleep disturbances and depression in older adults: Meta-analysis and systematic review. Neurosci Biobehav Rev. 2017;75:257-273.

Jackowska

Poole

. Sleep problems, short sleep and a combination of both increase the risk of depressive symptoms in older people: A 6-year follow-up investigation from the English Longitudinal Study of Ageing. Sleep Med. 2017;37:60-65.

Roberts

. Sleep complaints and depression in an aging cohort: A prospective perspective. Am J Psychiatr. 2000;157(1):81-88.

Smagula

. Sleep architecture and mental health among community-dwelling older men. J Gerontol B Psychol Sci Soc Sci. 2015;70(5):673-681.

Gould

. Subjective but not objective sleep is associated with subsyndromal anxiety and depression in community-dwelling older adults. Am J Geriatr Psychiatr. 2018;26(7):806-811.

Harvey

Chastin

Skelton

. Prevalence of sedentary behavior in older adults: A systematic review. Int J Environ Res Publ Health. 2013;10(12):6645-6661.

Patel

Steinberg

Patel

. Insomnia in the elderly: A review. J Clin Sleep Med. 2018;14(6):1017-1024.

del Pozo Cruz

. Sedentary behaviour is associated with depression symptoms: compositional data analysis from a representative sample of 3233 US adults and older adults assessed with accelerometers. J Affect Disord. 2020;265:59-62.

Yesavage

Sheikh

. 9/Geriatric depression scale (GDS) recent evidence and development of a shorter version. Clin Gerontol. 1986;5(1-2):165-173.

10.

Baglioni

. Sleep and mental disorders: a meta-analysis of polysomnographic research. Psychol Bull. 2016;142(9):969-990.

11.

Nasreddine

. The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695-699.

12.

Wancata

. The criterion validity of the Geriatric Depression Scale: A systematic review. Acta Psychiatr Scand. 2006;114(6):398-410.

13.

Marc

Raue

Bruce

. Screening performance of the 15-item geriatric depression scale in a diverse elderly home care population. Am J Geriatr Psychiatr. 2008;16(11):914-921.

14.

Finan

. Validation of a wireless, self-application, ambulatory electroencephalographic sleep monitoring device in healthy volunteers. J Clin Sleep Med. 2016;12(11):1443-1451.

15.

Levendowski

. The accuracy, night-to-night variability, and stability of frontopolar sleep electroencephalography biomarkers. J Clin Sleep Med. 2017;13(6):791-803.

16.

le Cessie

Goeman

Dekkers

. Who is afraid of non-normal data? Choosing between parametric and non-parametric tests. Eur J Endocrinol. 2020;182(2):E1-E3.

17.

Sawilowsky

Blair

. A more realistic look at the robustness and type II error properties of the t test to departures from population normality. Psychol Bull. 1992;111(2):352.

18.

Poncet

. Normality and sample size do not matter for the selection of an appropriate statistical test for two-group comparisons. Methodology. 2016;6:2.

19.

Mishra

. Descriptive statistics and normality tests for statistical data. Ann Card Anaesth. 2019;22(1):67-72.

20.

Jiang

. Sleep architecture and the incidence of depressive symptoms in middle-aged and older adults: A community-based study. J Affect Disord. 2024;352:222-228.

21.

Hein

. Alterations of neural network organisation during rapid eye movement sleep and slow-wave sleep in major depression: implications for diagnosis, classification, and treatment. Psychiatr Res Neuroimaging. 2019;291:71-78.

22.

Palagini

. REM sleep dysregulation in depression: state of the art. Sleep Med Rev. 2013;17(5):377-390.

23.

Alcántara

. Sleep disturbances and depression in the multi-ethnic study of atherosclerosis. Sleep. 2016;39(4):915-925.

24.

Gee

. The effect of non-pharmacological sleep interventions on depression symptoms: A meta-analysis of randomised controlled trials. Sleep Med Rev. 2019;43:118-128.

25.

Green

. A systematic review of the validity of non-invasive sleep-measuring devices in mid-to-late life adults: future utility for Alzheimer's disease research. Sleep Med Rev. 2022;65:101665.