Occupational Fall Risk Assessment Tool for older workers.

No easy-to-use fall risk assessment tools have been devised to assess occupational fall risk in older workers. To develop an Occupational Fall Risk Assessment Tool (OFRAT) and report its predictive validity and reliability in older workers. The baseline fall risk assessment was completed by 1113 participants aged ≥60 years who worked ≥4 days/month in Saitama, Japan. Participants were followed up for falls during occupational activities for 1 year, and 30 participants were assessed twice for test-retest reliability. The following assessment measures were summed to form the OFRAT risk score: older age, male sex, history of falls, physical work participation, diabetes, use of medications increasing fall risk, reduced vision, poor hearing, executive dysfunction and slow stepping. The scores were then classified into four grades (0-2 points: very low, 3 points: low, 4 points: moderate and ≥5 points: high). During follow-up, 112 participants fell 214 times during work. The negative binomial regression model showed that participants with higher grades had a higher incidence rate ratio [95% confidence interval] for falls than those with very low grades (low: 1.64 [1.08-2.47], moderate: 4.23 [2.82-6.34] and high: 6.12 [3.83-9.76]). The intraclass correlation coefficient for risk score was 0.86 [0.72-0.93], and the weighted kappa coefficient for grade assessment was 0.74 [0.52-0.95]. The OFRAT is a valid and reliable tool for estimating the occupational fall risk in older workers. It may assist occupational physicians implement strategies to prevent falls in this group. © The Author(s) 2023. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Citation

Y Osuka, Y Okubo, Y Nofuji, K Maruo, Y Fujiwara, H Oka, S Shinkai, S R Lord, H Sasai. Occupational Fall Risk Assessment Tool for older workers. Occupational medicine (Oxford, England). 2023 Apr 26;73(3):161-166

Mesh Tags

PMID: 36893360

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