Search

Background Lower levels of physical activity are associated with lower Health-Related Quality of Life (HRQoL) in Parkinson's disease (PD). We evaluated the influence of quantitative physical activity parameters among other (disease-related) features representing other domains of the WHO International model for classification of Function, Disability, and Health (ICF) on HRQoL in PD. Methods Home-based movement data (DynaPort MiniMod ® ) was collected in 47 PD patients. Nine stepwise regression models were calculated, with consecutive outcome variables: Parkinson's Disease Questionnaire (PDQ) Summary Index (SI), PDQ-Mobility, PDQ-Activities of Daily Living (ADL). Demographic variables, disease-specific features, and quantitative physical activity parameters, were included as predicting variables in all analyses. The following three physical activity parameters were alternately included for both sedentary and active episodes: ‘percentage’ of 24 h spent within these episodes, ‘number of bouts’, and ‘mean bout lengths’ (MBL). Results Depression and ‘Total Energy Expenditure’ were the main predictors of overall HRQoL ( PDQ-S I), independent of the permutation of activity parameters. The same parameters predicted the PDQ-Mobility score. However, this result was altered when ‘MBL’ parameters were included into the model, ‘MBL’ of sedentary episodes additionally predicted HRQoL-Mobility. The PDQ-ADL score was associated with demographic, motor, and non-motor variables including cognitive status. After exclusion of demented PD patients, older age and cognitive impairment no longer constrained HRQoL-ADL. Discussion For the first time, we showed the influence of objective, home-based measured physical activity among depression and cognition on HRQoL in PD. This suggests that a multifactorial treatment approach would be most successful to increase HRQoL in PD.

BACKGROUND There is need for multidimensional quantitative assessment of cognitive driven activities of daily living (ADL) functions in Parkinson's disease (PD). OBJECTIVE To determine whether there is an ADL profile related to cognitive impairment in PD assessed by the Multiple Object Test (MOT). We assumed MOT performance to be lower in PD patients versus controls and in PD patients with more severe cognitive impairment. METHODS 50 PD patients with no cognitive impairment (PD-NC), 54 patients with PD-mild cognitive impairment (PD-MCI), 29 with Parkinson's disease dementia (PDD), and 40 healthy controls (HC) were investigated. Besides comprehensive cognitive testing, the MOT, a performance based test consisting of five routine tasks (e.g., preparing a cup of coffee), was applied. Quantitative (total errors and time) and qualitative (error type) MOT parameters were analyzed. RESULTS Total time and number of MOT errors was increased in PD patients compared to controls (p

Background: For the early diagnosis of Parkinson disease dementia (PDD), objective home-based tools are needed to quantify even mild stages of dysfunction of the activities of daily living (ADL). Objectives: In this pilot study, home-based physical behavior was assessed to examine whether it is possible to distinguish mild cognitive impairment (PD-MCI) from PDD. Methods: Fifty-five patients with mild to severe Parkinson disease (PD) participated in this cross-sectional study. Based on comprehensive neuropsychological testing, PD patients were classified as cognitively nonimpaired (PD-NC), PD-MCI or PDD. For physical behavior assessments, patients wore the accelerometer DynaPort® (McRoberts) for 3 days. Ordinal logistic regression models with continuous Y were applied to correct results for motor impairment and depressive symptoms. Results: After excluding 7 patients due to insufficient wearing time, 48 patients with a mean of 2 recorded days were analyzed (17 PD-NC, 22 PD-MCI, 9 PDD). ADL-impaired PDD patients showed fewer sedentary bouts than non-ADL-impaired PD-MCI (p = 0.01, odds ratio [OR] = 8.9, 95% confidence interval [CI] = 1.8-45.2) and PD-NC (p = 0.01, OR = 10.3, CI = 1.6-67.3) patients, as well as a longer sedentary bout length (PD-NC: p = 0.02, OR = 0.1, CI = 0.02-0.65; PD-MCI: p = 0.02, OR = 0.14, CI = 0.03-0.69). These differences were mainly caused by fewer (PD-NC: p = 0.02, OR = 9.6, CI = 1.5-62.4; PD-MCI: p = 0.01, OR = 8.5, CI = 1.5-37.3) but longer sitting bouts (PD-NC: p = 0.03, OR = 0.12, CI = 0.02-0.80; PD-MCI: p = 0.04, OR = 0.19, CI = 0.04-0.93). Tests assessing executive function, visuoconstruction and attention correlated significantly with specific activity parameters (ρ ≥ 0.3; p < 0.05). Conclusion: Objective assessment of physical behavior, in particular the detection of sedentary bouts, is a promising contributor to the discrimination between PD-MCI and PDD.