Force platform measurements as predictors of falls among older people - a review.
BACKGROUND
Poor postural balance is one of the major risk factors for falling. A great number of reports have analyzed the risk factors and predictors of falls but the results have for the most part been unclear and partly contradictory. Objective data on these matters are thus urgently needed. The force platform technique has widely been used as a tool to assess balance. However, the ability of force platform measures to predict falls remains unknown.


OBJECTIVE
The purpose of this systematic review was to extract and critically review the findings of prospective studies where force platform measurements have been used as predictors of falls among elderly populations.


METHODS
The study was done as a systematic literature review. PubMed, the Cochrane Central Register of Controlled Trials, and CINAHL databases from 1950 to April 2005 were used. The review includes prospective follow-up studies using the force platform as a tool to measure postural balance.


RESULTS
Nine original prospective studies were included in the final analyses. In five studies fall-related outcomes were associated with some force platform measures and in the remaining four studies associations were not found. For the various parameters derived on the basis of the force platform data, the mean speed of the mediolateral (ML) movement of the center of pressure (COP) during normal standing with the eyes open and closed, the mean amplitude of the ML movement of the COP with the eyes open and closed, and the root-mean-square value of the ML displacement of COP were the indicators that showed significant associations with future falls. Measures related to dynamic posturography (moving platforms) were not predictive of falls.


CONCLUSIONS
Despite a wide search only a few prospective follow-up studies using the force platform technique to measure postural balance and a reliable registration of subsequent falls were found. The results suggest that certain aspects of force platform data may have predictive value for subsequent falls, especially various indicators of the lateral control of posture. However, the small number of studies available makes it difficult to draw definitive conclusions.
Piirtola
Maarit
M
Department of Family Medicine, University of Turku, Turku, Finland. maarit.piirtola@utu.fi
Era
Pertti
P
D000058:Accidental Falls / Q000517:prevention & control*; D000368:Aged; D000369:Aged, 80 and over; D004867:Equipment Design; D006801:Humans; D004856:Postural Balance; D011187:Posture / Q000502:physiology*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D011597:Psychomotor Performance / Q000502:physiology*; D012107:Research Design; D012678:Sensation Disorders / Q000175:diagnosis*