Sleep Quality and Its Association with Health-Related Clinical Outcomes and Biomarkers Among Rural Northern Thai Older Adults: A Cross-Sectional Study

Background/Objectives: Sleep disorders are common among older adults and have been increasingly linked to metabolic abnormalities and non-communicable diseases (NCDs). However, evidence on the relationship between sleep quality and health-related clinical outcomes and biomarkers in rural Northern Thailand remains limited. This study aimed to assess the association between sleep quality and health-related clinical outcomes and biomarkers among older adults in rural Northern Thailand. Methods: A cross-sectional study was conducted among 424 older adults in Phayao Province, rural Northern Thailand. Quota sampling was employed to ensure equal representation of participants with and without NCDs (n = 212 per group). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Physical health status was evaluated through measurements of blood pressure (BP), including systolic blood pressure (SBP) and diastolic blood pressure (DBP), and fasting blood sugar (FBS). Results: The participants’ mean PSQI score was 8.03 ± 4.86, and 29.7% had poor sleep quality (PSQI > 5). Hypertension (35.4%) and diabetes mellitus (17.5%) were the most common underlying diseases. The mean fasting blood sugar level was 116.33 ± 30.84 mg/dL, with 21.0% of participants presenting abnormal levels (≥126 mg/dL). Multivariable binary logistic regression demonstrated that each one-point increase in the overall PSQI score was significantly associated with higher odds of having an underlying disease (adjusted odds ratio [AOR] = 2.37; 95% confidence interval [CI]: 2.00–2.81), hypertension (AOR = 1.51; 95% CI: 1.37–1.66), diabetes mellitus (AOR = 1.42; 95% CI: 1.28–1.58), other non-communicable diseases (AOR = 1.94; 95% CI: 1.64–2.29), abnormal fasting blood sugar (AOR = 1.47; 95% CI: 1.33–1.63), elevated systolic blood pressure (AOR = 1.39; 95% CI: 1.28–1.51), and elevated diastolic blood pressure (AOR = 1.30; 95% CI: 1.19–1.43). Subjective sleep quality, sleep duration, and habitual sleep efficiency were also significantly associated with multiple health-related clinical outcomes and biomarkers. Although sparse data and quasi-complete separation may have influenced the precision of some regression estimates, the overall pattern of associations remained consistent and should be interpreted with appropriate caution. Conclusions: Higher overall PSQI scores were significantly associated with adverse health-related clinical outcomes and biomarkers among older adults in rural Northern Thailand. These findings highlight the clinical importance of routinely assessing sleep quality in older adults, particularly those with chronic conditions or increased cardiometabolic risk. Because of the cross-sectional design and the statistical uncertainty associated with sparse data in some regression models, the findings should be interpreted as evidence of associations rather than causal relationships. The observed associations are consistent with the likely bidirectional relationship between sleep disturbances and chronic diseases. Integrating sleep quality screening into routine health assessments, alongside comprehensive chronic disease management, may facilitate the early identification of older adults at increased cardiometabolic risk and support evidence-based health promotion strategies.