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A data-driven analysis of industry-specific occupational injury risks and patterns.
1Department of Big Data Management and Application, School of Maritime Economics and Management, Dalian Maritime University, Dalian, Liaoning, China.
International Journal of Injury Control and Safety Promotion
|October 9, 2025
Summary
This study used Association Rule Mining (ARM) to analyze U.S. Occupational Safety and Health Administration (OSHA) data, revealing industry-specific injury patterns and risk factors to improve occupational safety interventions.
Area of Science:
- Occupational Safety and Health
- Data Mining
- Injury Epidemiology
Background:
- Despite progress, preventing severe occupational injuries remains a significant challenge across various industries.
- Effective safety management requires understanding industry-specific injury trends and risk factors.
Purpose of the Study:
- To conduct a data-driven investigation into severe occupational injuries using U.S. Occupational Safety and Health Administration (OSHA) data.
- To identify industry-specific injury profiles and interrelated risk patterns using Association Rule Mining (ARM) and thematic analysis.
Main Methods:
- Utilized publicly available severe occupational injury reports from the U.S. OSHA.
- Applied Association Rule Mining (ARM) to uncover co-occurrence patterns among risk factors.
- Incorporated thematic analysis to contextualize findings and identify industry-specific injury profiles.
Main Results:
- Identified distinct injury profiles: finger injuries in manufacturing, falls/burns in construction, lower limb injuries in transportation/wholesale, falls in retail, burns/hand injuries in mining, and lower back injuries in healthcare.
- Uncovered complex co-occurrence patterns between task type, environmental conditions, and affected body parts influencing injury severity.
- Highlighted sector-specific injury clusters and associated risk factors.
Conclusions:
- The findings provide valuable insights for developing targeted, sector-specific safety interventions.
- Emphasizes the critical role of occupational injury data analysis in informing evidence-based prevention strategies.
- Data-driven approaches are essential for enhancing occupational safety management and reducing severe injuries.
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