Print Friendly  |  
  • LinkedIn
  • Add to Favorites


 Weight Shift Leading Cause of Falls, Canadian Researchers Find

“Incorrect weight shifting” was the most likely culprit in senior falls, Canadian researchers have determined.

Researchers in British Columbia analyzed video from 227 falls in two separate nursing homes over three years. Weight shifting problems accounted for 41 percent of them, followed by tripping or stumbling (21 percent).

There were three categories of problems—hitting or bumping, loss of support, and collapse—that accounted for 11 percent of the falls, the researchers said.

The seniors were more likely to fall while walking forward (24 percent), standing quietly (13 percent), or sitting down (12 percent), the researchers found.

“Compared with previous reports from the long term care setting, we identified a higher occurrence of falls during standing and transferring, a lower occurrence during walking, and a larger proportion due to center-of-mass perturbations than base-of-support perturbations,” the researchers said.

The research team included Simon Fraser University Professors Stephen Robinovitch and Fabio Feldman. Their findings were published Wednesday in The Lancet.

“By providing insight into the sequences of events that most commonly lead to falls, our results should lead to more valid and effective approaches for balance assessment and fall prevention in long term care,” the researchers said in interpreting their data.

In order to conduct their study, the researchers installed digital cameras in common areas of the two Canadian homes.

“When a fall occurred, facility staff completed an incident report and contacted our teams so that we could collect video footage,” the researchers wrote. “A team reviewed each fall video with a validated questionnaire that probed the cause of imbalance and activity at the time of falling. We then tested whether differences existed in the proportion of participants falling due to the various causes, and while engaging in various activities, with generalized linear models, repeated measures logistic regression, and log-linear Poisson regression.”​​​

Facebook.png   Twitter   Linked-In   ProviderTV   Subscribe

Sign In