August 1, 2024
by Osaka Metropolitan University
A new assessment tool has been developed to estimate fall risks in older populations. Credit: Osaka Metropolitan University
An aging society has posed a new global problem, the risk of falling. It is estimated that one in three adults over the age of 65 falls each year and the resulting injuries are becoming more prevalent.
To tackle this growing issue, Associate Professor Hiromitsu Toyoda and Specially Appointed Professor Tadashi Okano from Osaka Metropolitan University’s Graduate School of Medicine, together with Professor Chisato Hayashi from the University of Hyogo, have developed a formula and assessment tool for estimating fall risks that is simple for older adults to use. The tool was developed using data collected from older adults over a 10-year period from April 2010 to December 2019.
The results were published in Osteoporosis International.
The research team reviewed a total of 7,726 physical tests and data from the Japanese government’s Kihon Checklist self-reporting questionnaire of 2,381 participants who participated in community-based exercise groups. The data was analyzed under a contractual agreement between Sumoto City in Hyogo Prefecture and the University of Hyogo.
A history of falls and the inability to stand on one leg were previously reported as the primary indicators of fall risk, but the recent analysis found that poor oral and cognitive function were also contributing factors. Additionally, short-term participation in the exercise program was found to be ineffective.
“We believe that this tool will provide valuable information to health care providers for screening older adults at risk for falls and assist them in prevention and follow-up care,” said Professor Toyoda.
“We hope that municipalities will make extensive use of the system because preventing falls among older adults not only extends their life expectancy, but also helps control medical and long-term care costs.”
More information: Chisato Hayashi et al, Development and validation of a prediction model for falls among older people using community-based data, Osteoporosis International (2024). DOI: 10.1007/s00198-024-07148-8
Journal information: Osteoporosis International
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