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Randomized Controlled Trial
. 2009 Aug;67(2):135-41.
doi: 10.1016/j.jpsychores.2009.03.011. Epub 2009 Apr 25.

Frequency and Predictors of Obstructive Sleep Apnea Among Individuals With Major Depressive Disorder and Insomnia

Free PMC article
Randomized Controlled Trial

Frequency and Predictors of Obstructive Sleep Apnea Among Individuals With Major Depressive Disorder and Insomnia

Jason C Ong et al. J Psychosom Res. .
Free PMC article


Objective: Disturbances in sleep continuity are common among individuals with major depressive disorder (MDD) and can impact the course of depression and response to treatment. Several studies have examined depressive symptom severity among sleep-disordered patients with obstructive sleep apnea (OSA). In contrast, little is known about OSA in patients with MDD. The goal of this study was to examine the frequency and predictors of OSA in a sample of individuals with comorbid MDD and insomnia.

Methods: Participants were 51 individuals who enrolled in a treatment study on insomnia and depression, met criteria for MDD and comorbid insomnia, and underwent an overnight polysomnography evaluation. An apnea-hypopnea index >or=15 events per hour was used as a cutoff score for OSA. Regression analyses were conducted to examine clinical and demographic predictors of OSA severity as measured by the apnea-hypopnea index.

Results: The results revealed that 39% of the sample met criteria for OSA. The OSA group had significantly higher body mass index (BMI) scores and a significantly greater proportion of men. Regression analysis revealed that male sex, older age, and higher BMI were significant predictors of OSA severity. Neither depression severity nor insomnia severity was a significant predictor.

Conclusions: These findings indicate that the frequency of OSA is higher among individuals with comorbid MDD and insomnia than was previously found among people with either MDD or insomnia alone. In addition, previously identified predictors of OSA (male sex, older age, and high BMI) also apply to this population.


Figure 1
Figure 1
Patient Flow for Inclusion in the Study

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