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Effects of age on the relationship between sleep quality and cognitive performance: Findings from the Human Connectome Project-Aging cohort

Published online by Cambridge University Press:  04 December 2023

Daniel E. Cohen ,
Hyun Kim Open the ORCID record for Hyun Kim [Opens in a new window] ,
Alina Levine ,
Davangere P. Devanand Open the ORCID record for Davangere P. Devanand [Opens in a new window] ,
Seonjoo Lee  and
Terry E. Goldberg Open the ORCID record for Terry E. Goldberg [Opens in a new window]
Daniel E. Cohen
Affiliation:
Division of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, USA
Hyun Kim*
Affiliation:
Division of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, USA Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
Alina Levine
Affiliation:
Division of Mental Health Data Science, New York State Psychiatric Institute, New York, NY, USA
Davangere P. Devanand
Affiliation:
Division of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, USA Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
Seonjoo Lee
Affiliation:
Division of Mental Health Data Science, New York State Psychiatric Institute, New York, NY, USA Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA
Terry E. Goldberg
Affiliation:
Division of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, USA Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA Department of Anesthesiology, Columbia University Irving Medical Center, New York, NY, USA
*
Correspondence should be addressed to: Hyun Kim, Division of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, USA. Email: monhykim@bu.edu.
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Abstract

Background:

The association between sleep quality and cognition is widely established, but the role of aging in this relationship is largely unknown.

Objective:

To examine how age impacts the sleep–cognition relationship and determine whether there are sensitive ranges when the relationship between sleep and cognition is modified. This investigation could help identify individuals at risk for sleep-related cognitive impairment.

Subjects:

Sample included 711 individuals (ages 36.00–89.83, 59.66 ± 14.91, 55.7 % female) from the Human Connectome Project-Aging (HCP-A).

Methods:

The association between sleep quality (Pittsburgh Sleep Quality Index, PSQI) and cognition (Crystallized Cognition Composite and Fluid Cognition Composite from the NIH Toolbox, the Trail Making Test, TMT, and the Rey Auditory Verbal Learning Test, RAVLT) was measured using linear regression models, with sex, race, use of sleep medication, hypertension, and years of education as covariates. The interaction between sleep and age on cognition was tested using the moderation analysis, with age as both continuous linear and nonlinear (quadratic) terms.

Results:

There was a significant interaction term between the PSQI and nonlinear age term (age2) on TMT-B (p = 0.02) and NIH Toolbox crystallized cognition (p = 0.02), indicating that poor sleep quality was associated with worse performance on these measures (sensitive age ranges 50–75 years for TMT-B and 66–70 years for crystallized cognition).

Conclusions:

The sleep–cognition relationship may be modified by age. Individuals in the middle age to early older adulthood age band may be most vulnerable to sleep-related cognitive impairment.

Keywords

cognitive assessmentsleeprisk factorsaging

Information

Type
Original Research Article
Information
International Psychogeriatrics , Volume 36 , Special Issue 12: Issue Theme: Neurocognitive Disorders , December 2024 , pp. 1171 - 1181
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Psychogeriatric Association

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Footnotes

Data used in preparation of this article were obtained for the Human Connectome Project Aging (HCP-A) database (https://www.humanconnectome.org/). As such, the investigators within the HCP-A contributed to the design and implementation of HCP-A and/or provided data but did not participate in the writing of this report. A complete listing of HCP-A investigators can be found at: https://www.humanconnectome.org/study/hcp-lifespan-aging

Daniel E. Cohen and Hyun Kim have equal contribution to authorship.

‡

This article was originally published with errors in the abstract which led to information being misconstrued. The errors have been rectified and the article updated. A correction notice has been published.

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