The relationship between real world ambulatory activity and falls in incident Parkinson's disease: Influence of classification scheme

Mactier, Karen, Lord, Sue, Godfrey, Alan, Burn, David and Rochester, Lynn (2015) The relationship between real world ambulatory activity and falls in incident Parkinson's disease: Influence of classification scheme. Parkinsonism & Related Disorders, 21 (3). pp. 236-242. ISSN 1353-8020

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Abstract

Introduction
Few studies have categorized falls in early Parkinson's disease (PD) and little is known about falls incidence and evolution. Fall incidence and frequency are reported to be ‘U’ shaped with respect to disease severity and may be influenced by time spent engaged in ambulatory activity.

Methods
Twelve months prospective falls in an incident PD cohort (n = 111) were reported and the relationship between falls and ambulatory activity was examined in a subgroup (n = 83). Fall events were collected using standardised protocols and were categorized by fall frequency (non-faller, single fall, recurrent falls) and also by a novel classification based on pre-fall event: (1) engaged in advanced activity; (2) ambulation; and (3) transition. Non-parametric statistics compared groups in both classifications.

Results
At baseline 23 (20.7%) of the cohort had fallen, increasing to 41 (36.9%) participants over 12 months. Total time spent walking was significantly lower for transition fallers compared with non-fallers and ambulation fallers (p = 0.041), who also had significantly increased disease severity. There were no significant relationships when fallers were categorized by frequency. We present an inverted U curve model depicting the relationship between falls and activity over time in PD, and propose that at this stage transition and ambulation fallers occupy different places on the curve.

Conclusions
Falls are more common than recognised in newly-diagnosed PD. Daily activity is reduced even in early disease for people who fall during transitions. Classification methods that take pre-fall event into account may be useful to understand the heterogeneity of this complex problem.

Item Type:	Article
Uncontrolled Keywords:	Parkinson's disease, Falls, Accelerometry, Physical activity
Subjects:	B900 Others in Subjects allied to Medicine G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Becky Skoyles
Date Deposited:	18 Sep 2018 15:35
Last Modified:	10 Oct 2019 19:00
URI:	http://nrl.northumbria.ac.uk/id/eprint/35773

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