Effects of Insomnia and Depression on CPAP Adherence in a Military Population
Initial self-reported depression and insomnia prior to the diagnosis and treatment of obstructive sleep apnea with continuous positive airway pressure therapy did not reliably predict short- and long-term adherence in a sample of active-duty military and veteran patients.
Statistical Analysis
Linear regression methods were used to characterize any potential relationships between the predictor variables and the target outcome variables associated with CPAP adherence at 3 and 12 months. Scatterplots were produced to assess whether linear structure was sufficient to characterize any detectable relationships, or whether there existed more complex, nonlinear relationships. The best-fitting linear regression line was examined in relation to the confidence bands of the corresponding LOESS line to determine whether a more complicated model structure was needed to capture the relationship.
Standard tests of assumptions required for these methods were also carried out: QQ plots of residuals to test for normality, the Durbin-Watson test for independence of residuals, and the nonconstant variance score test for heteroskedasticity (ie, Breusch-Pagan test). The results of these assumptions tests are reported only in cases in which the assumptions were revealed to be untenable. In cases in which suspicious outlying observations may have biased analyses, robust versions of the corresponding models were constructed. In no cases did the resulting conclusions change; only the results of the original analysis are reported. All analyses were carried out in R (R Foundation, r-project.org). Statistical significance was defined as P < .05.
Results
Our study population was predominately male (90%) with a median age of 41 years (range 22-65) and BMI of 29.8 (range 7.7-57.2)(Table 1). 
Predictors of CPAP Adherence
OSA severity, as measured by the AHI, was the only promising predictor of CPAP use at 3 months (b, 2.128; t80, 2.854; P = .005; adjusted R2, 0.081). The severity of self-reported daytime sleepiness prior to a diagnosis of OSA, as measured by the ESS, did not predict 3-month CPAP adherence (b, 0.688; t77, 0.300; P = .765; adjusted R2, -0.012). Self-reported depression as measured by the CES-D also did not predict CPAP use at 3 months (b, -0.078; t80, -0.014; P = .941; adjusted R2, -0.012). Similarly, self-reported insomnia, as measured by the ISI, did not predict 3-month CPAP adherence (b, 1.765; t80, 0.939; P = .350; adjusted R2, -0.001). Furthermore, a model that incorporated both depression and insomnia proved no better at accounting for variation in 3-month CPAP use (R2, -0.012). Demographic variables, such as age, sex, or BMI did not predict 3-month CPAP adherence (all Ps > .20). Finally, median CPAP pressure approached statistical significance as a predictor of 3-month CPAP adherence (b, 9.493; t66, 1.881; P = .064; adjusted R2, 0.037) (Figure 1). 
CPAP Use at 12 months
The results for CPAP use at 12 months mirrored the results for 3 months with one main exception: OSA severity, as measured by the AHI, did not predict CPAP use at 12 months (b, 1.158; t52, 1.245; P = .219; adjusted R2, 0.010). Neither adding a quadratic predictor nor log transforming the AHI values produced a better model (R2, -0.0007 vs R2, 0.0089, respectively). The severity of self-reported daytime sleepiness, as measured by the ESS, did not predict 12-month CPAP adherence (b, -2.201; t50, -0.752; P = .456; adjusted R2 = -0.0086). Self-reported depression as measured by the CES-D also did not predict CPAP use at 12 months (b, 0.034, t52, 0.022; P = .983; adjusted R2, -0.092). Self-reported insomnia, as measured by the ISI, also did not predict 12-month CPAP adherence (b, 1.765; t80, 0.939; P = .350; adjusted R2 = -0.001). Furthermore, a model that incorporated both depression and insomnia proved no better at accounting for variation in 12-month CPAP use, (R2, -0.0298). 
