Modeling depression in Parkinson disease Disease-specific and nonspecific risk factors

Albert F. G. Leentjens*, Anja J. H. Moonen, Kathy Dujardin, Laura Marsh, Pablo Martinez-Martin, Irene H. Richard, Sergio E. Starkstein, Sebastian Kohler

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

33 Citations (Web of Science)

Abstract

Objective: To construct a model for depression in Parkinson disease (PD) and to study the relative contribution of PD-specific and nonspecific risk factors to this model. Methods: Structural equation modeling of direct and indirect associations of risk factors with the latent depression outcome using a cross-sectional dataset of 342 patients with PD. Results: A model with acceptable fit was generated that explained 41% of the variance in depression. In the final model, 3 PD-specific variables (increased disease duration, more severe motor symptoms, the use of levodopa) and 6 nonspecific variables (female sex, history of anxiety and/or depression, family history of depression, worse functioning on activities of daily living, and worse cognitive status) were maintained and significantly associated with depression. Nonspecific risk factors had a 3-times-higher influence in the model than PD-specific risk factors. Conclusion: In this cross-sectional study, we showed that nonspecific factors may be more prominent markers of depression than PD-specific factors. Accordingly, research on depression in PD should focus not only on factors associated with or specific for PD, but should also examine a wider scope of factors including general risk factors for depression, not specific for PD.
Original languageEnglish
Pages (from-to)1036-1043
JournalNeurology
Volume81
Issue number12
DOIs
Publication statusPublished - 17 Sep 2013

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