Sleep disruption as a predictor of quality of life among patients in the subpopulations and intermediate outcome measures in COPD study (SPIROMICS)

Abstract

Study objectives: Sleep quality is poor among patients with chronic obstructive pulmonary disease (COPD), and studies show that sleep disturbance is associated with low overall quality of life in this population. We evaluated the impact of patient-reported sleep quality and sleep apnea risk on disease-specific and overall quality of life within patients with COPD enrolled in the SPIROMICS study, after accounting for demographics and COPD disease severity.

Methods: Baseline data from 1341 participants [892 mild/moderate COPD (FEV1 ≥ 50% predicted); 449 severe COPD (FEV1 < 50%)] were used to perform three nested (blocks) regression models to predict quality of life (Short Form-12 mental and physical components and St. George's Respiratory Questionnaire). Dependent measures used for the nested regressions included the following: Block1: demographics and smoking history; Block 2: disease severity (forced expiratory volume 1 s; 6 min walk test); Block 3: risk for obstructive sleep apnea (OSA; Berlin questionnaire); and Block 4: sleep quality (Pittsburgh Sleep Quality Index [PSQI]).

Results: Over half of participants with COPD reported poor sleep quality (Mean PSQI 6.4 ± 3.9; 50% with high risk score on the Berlin questionnaire). In all three nested regression models, sleep quality (Block 4) was a significant predictor of poor quality of life, over and above variables included in blocks 1-3.

Conclusions: Poor sleep quality represents a potentially modifiable risk factor for poor quality of life in patients with COPD, over and above demographics and smoking history, disease severity, and risk for OSA. Improving sleep quality may be an important target for clinical interventions.

Clinical trial: SPIROMICS.

Clinical trial url: http://www2.cscc.unc.edu/spiromics/.

Clinical trial registration: ClinicalTrials.gov NCT01969344.

Figure 1.

Percentage of variance explained in SF12-Mental Health, SF-12 Physical Health, and St. George QOL as a function of Block 1, Block 2, Block 3, and Block 4 of the nested regression model.