Fall and collision related injuries among pedestrians, sickness absence and associations with accident type and occupation

Abstract

Objectives: This study explores pedestrian fall accidents and collisions with other road users in the Swedish road transport system, and sickness absence (SA) in relation to accident type, injury, and occupation. Further, it studies the associations between accident type, occupation, and duration of SA.

Methods: Data from several national registers were used that included 15,359 working age pedestrians (20-64 years) receiving healthcare after a fall or collision throughout 2014-2016. Individual characteristics, accident type, injury, and occupation were presented and related to SA. Logistic regression was used to estimate odds ratios (OR), with 95% confidence intervals, for associations between accident type, occupation, and SA duration.

Results: About 11,000 pedestrians (72%) were involved in fall accidents in the road traffic environment and well over 4,000 in collisions with another road user; 22% of all injured pedestrians had a new SA. The population had a higher proportion of women and individuals in older age groups (≥45). Of the falls, 31% were due to snow or ice, and these were associated with a higher OR for both short SA (<90 days) 1.76 (95% CI 1.56-1.98) and long SA (≥90 days) 1.81 (95% CI 1.51-2.18), compared to the group slipping, tripping, and stumbling. The working sectors health & social care, and construction had the highest ORs for SA. A higher OR was found for health & social care, short SA 1.58 (95% CI 1.38-1.81), long SA 1.79 (95% CI 1.45-2.20) and for construction, short SA 1.56 (95% CI 1.24-1.96), long SA 1.75 (95% CI 1.26-2.44), compared to the sector finance, communication, & cultural service.

Conclusions: The OR for having short and long SA was higher in falls due to snow or ice and differed between occupational sectors.

Practical implications: This information contributes to the knowledge base for planning a safe road transport system for pedestrians.

Keywords: Insurance medicine; Register data; Sick leave; Traffic accidents; Walking.