Gait Slip-Induced Fall-Type Assessment Based on Regular Gait Characteristics in Older Adults.

ABSTRACT

Older adults could experience split falls or feet-forward falls following an unexpected slip in gait due to different neuromuscular vulnerabilities, and different intervention strategies would be required for each type of faller. Thus, this study aimed to investigate the key factors affecting the fall types based on regular gait pattern. A total of 105 healthy older adults who experienced a laboratory-induced slip and fall were included. Their natural walking trial immediately prior to the novel slip trial was analyzed. To identify the factors related to fall type, gait characteristics and demographic factors were determined using univariate logistic regression, and then stepwise logistic regression was conducted to assess the slip-induced fall type based on these factors. The best fall-type prediction model involves gait speed and recovery foot angular velocity, which could predict 70.5% of feet-forward falls and 86.9% of split falls. Body mass index was also a crucial fall-type prediction with an overall prediction accuracy of 70.5%. Along with gait parameters, 84.1% of feet-forward falls and 78.7% of split falls could be predicted. The findings in this study revealed the determinators related to fall types, which enhances our knowledge of the mechanism associated to slip-induced fall and would be helpful for the development of tailored interventions for slip-induced fall prevention.