[2026-03-05] Biopsychosocial Determinants of Sleep Quality in Community-Dwelling Older Adults With Type 2 Diabetes and Mild Cognitive Impairment

Chakrit Sattayarom; Aekkachai Fatai; Supaporn Voraroon; Umakorn Jaiyungyuen; Phenrung Wandee; Purin Srisasaluk; Sureewan Sawangha; Trakulwong Luecha; Jason Rydberg

doi:10.33165/rmj.2027.e278258

Authors

Chakrit Sattayarom Department of Community Health Nursing, Boromarajonani College of Nursing Suphanburi, Praboromarajchanok Institute, Suphan Buri, Thailand https://orcid.org/0009-0006-3735-1738
Aekkachai Fatai Department of Adult and Geriatric Nursing, Princess Agrarajakumari Faculty of Nursing, Chulabhorn Royal Academy, Bangkok, Thailand https://orcid.org/0009-0009-9825-0393
Supaporn Voraroon Department of Community Health Nursing, Boromarajonani College of Nursing Suphanburi, Praboromarajchanok Institute, Suphan Buri, Thailand
Umakorn Jaiyungyuen Department of Community Health Nursing, Boromarajonani College of Nursing Suphanburi, Praboromarajchanok Institute, Suphan Buri, Thailand
Phenrung Wandee Department of Community Health Nursing, Boromarajonani College of Nursing Suphanburi, Praboromarajchanok Institute, Suphan Buri, Thailand https://orcid.org/0009-0005-4352-5311
Purin Srisasaluk Department of Community Health Nursing, Boromarajonani College of Nursing Suphanburi, Praboromarajchanok Institute, Suphan Buri, Thailand https://orcid.org/0009-0005-8696-5210
Sureewan Sawangha Department of Community Health Nursing, Boromarajonani College of Nursing Suphanburi, Praboromarajchanok Institute, Suphan Buri, Thailand https://orcid.org/0009-0007-7619-9879
Trakulwong Luecha Department of Community Nursing, Faculty of Nursing, Burapha University, Chon Buri, Thailand https://orcid.org/0000-0002-2526-7751
Jason Rydberg Center for Program Evaluation, School of Criminology and Justice, University of Massachusetts Lowell, Massachusetts, US https://orcid.org/0000-0002-7756-2656

DOI:

https://doi.org/10.33165/rmj.2027.e278258

Keywords:

Sleep quality, Type 2 diabetes, Mild cognitive impairment, Biopsychosocial, Older adults

Abstract

Background: Community-dwelling older adults with type 2 diabetes mellitus (T2DM) and mild cognitive impairment (MCI) often report poor sleep, which may aggravate metabolic control and functional decline; yet sleep problems and their biopsychosocial drivers are underrecognized in primary care.

Objectives: To describe sleep quality, examine biopsychosocial correlates, and identify significant predictors of sleep quality in older adults with T2DM and MCI.

Methods: A cross-sectional study was conducted in 6 primary care units in Suphan Buri province, Thailand. Sleep quality was measured using the Pittsburgh Sleep Quality Index (PSQI). Biological factors included age, sex, body mass index, glycated hemoglobin (HbA_1c), diabetes duration, hypertension, comorbidities, and probable obstructive sleep apnea (OSA). Psychological factors were depressive symptoms (TGDS-15), diabetes-related distress (DDS-17), and diabetes self-efficacy. Social/environmental factors included perceived social support and environmental disturbance. Behavioral factors were diabetes self-care behaviors (SDSCA). Pearson’s correlations and hierarchical multiple regression were performed.

Results: Poor sleep was common (82.3%; PSQI > 5). Sleep quality correlated with depressive symptoms (r = 0.46), diabetes distress (r = 0.39), self-efficacy (r = -0.41), environmental disturbance (r = 0.34), and self-care (r = -0.32) (all P < .001). In the final model, HbA_1c (β = 0.11), probable OSA (β = 0.14), depressive symptoms (β = 0.28), diabetes distress (β = 0.17), self-efficacy (β = -0.22), environmental disturbance (β = 0.19), and self-care (β = -0.12) independently predicted PSQI, explaining 47% of variance (adjusted R² = 0.45).

Conclusions: Sleep quality in older adults with T2DM and MCI reflects a biopsychosocial profile dominated by psychological, environmental, and behavioral factors, with selected biological risks. Primary care nurses should integrate sleep screening with assessment of mood, diabetes distress, self-efficacy, OSA risk, and home sleep conditions to guide multicomponent interventions.

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