Abstract
Falls are prevalent in patients with Parkinson disease (PD). Previous work focused on the impact of motor and non-motor symptoms on falls and ignored the impact of environmental factors, such as residence, economic level, and nursing status. The aim of this study was to investigate the prevalence and risk factors of falls in patients with PD and explore the impact of residence on falls. A cross-sectional study of 100 patients with PD was carried out. Patients were recruited from Anhui Provincial Hospital (Hefei, Anhui province, China) between July 2017 and December 2020. Participants were grouped based on whether they had fallen in the previous 3 months, and demographic information was collected through detailed interviews. In addition, severity of motor symptoms, cognitive function, and self-care abilities were assessed with the Unified Parkinson's Disease Rating Scale part III (UPDRS-III), the Hoehn-Yahr (H&Y) scale, the Mini-Mental State Examination (MMSE), and the Barthel Index. The results were analyzed using student t-test, Mann-Whitney U-test, χ2 test and multivariate binary logistic regression analyses. A total of 42% of the patients had fallen in the previous 3 months. The patients who had fallen were older and with a longer disease period, a higher UPDRS-III score, a higher H&Y stage, a lower MMSE score, and a lower Barthel Index score (all p<0.05). According to the logistic regression analysis, living in a rural area (odds ratio (OR)=3.34, 95% confidence interval (CI) 1.15-9.65), MMSE<24 (OR=4.79, 95%CI 1.17-19.65), having sleep disorders (OR=4.97, 95%CI 1.74-14.2), and having a high UPDRS-III score (OR=1.07, 95%CI 1.02-1.11) were independent risk factors for falls. The incidence of falls was higher in rural areas. Urban and rural patients showed different levels of disease severity; rural patients had higher H&Y stages, higher UPDRS-III scores and lower Barthel Index scores. Falls are caused by a variety of factors in people with PD. Multidimensional factors should be considered comprehensively to develop a personalized plan to prevent falls in PD patients.
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