Self-reported sleep problems among the elderly: A latent class analysis

Abstract

© 2017 Elsevier B.V. The present study utilized a person-centered approach to examine the different profiles of problem sleepers in a community sample of elderly. In addition, this study also explores how demographic and psychiatric variables may be related to these different profiles of sleep problems. A total of 515 participants (Mean age = 67 years, SD = 5) were administered self-report measures of sleep problems, depression and anxiety. Among them, 230 who reported significant problems in any of five selected sleep components were entered into a latent class analysis. The remaining 285 participants were assigned to a comparison control group. The profiles of ‘inadequate sleep', ‘disturbed sleep’, ‘trouble falling asleep’ and ‘multiple problems’ were identified. The ‘multiple problems’ group had significantly higher levels of depression and anxiety relative to the control group. Regression analyses indicated that these different profiles had contributed to a significant increase in variance explained in anxiety but not depression levels, on top of the severity of sleep problems and demographic variables. Although sleep problems occur among the elderly with considerable heterogeneity, they can generally be classified into four different profiles. Furthermore, the inclusion of sleep problem profiles can significantly enhance the prediction of anxiety symptoms.