Albert F G Leentjens1, Anja J H Moonen, Kathy Dujardin, Laura Marsh, Pablo Martinez-Martin, Irene H Richard, Sergio E Starkstein, Sebastian Köhler. 1. From the Department of Psychiatry (A.F.G.L., A.J.H.M.), Maastricht University Medical Center, Maastricht; School for Mental Health and Neuroscience (A.F.G.L., A.J.H.M., S.K.), Maastricht University, Maastricht, the Netherlands; Neurology and Movement Disorders Unit (K.D.), Lille University Medical Center, Lille, France; Mental Health Care Line (L.M.), Michael E. DeBakey Veterans Administration Medical Center and Departments of Psychiatry and Neurology, Baylor College of Medicine, Houston, TX; Alzheimer Disease Research Unit and CIBERNED (P.M.-M.), Alzheimer Center Reina Sofia Foundation, Carlos III Institute of Health, Madrid, Spain; Departments of Neurology and Psychiatry (I.H.R.), University of Rochester School of Medicine and Dentistry, Rochester, NY; and School of Psychiatry (S.E.S.), University of Western Australia and Fremantle Hospital, Fremantle, Australia.
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.
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.