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Severity Analysis for Occupational Heat-related Injury Using the Multinomial Logit Model
1Safety Automation and Visualization Environment (SAVE) Laboratory, Department of Civil, Construction, and Environmental Engineering, University of Alabama, Tuscaloosa, USA.
Safety and Health at Work
|July 22, 2024
Summary
Occupational heat-related injuries (HRIs) pose increasing risks due to climate change. This study identified key factors like age, gender, industry, and heat exposure that influence HRI severity, informing targeted prevention.
Area of Science:
- Occupational Health
- Environmental Health
- Public Health
Background:
- Workers face significant heat exposure risks in various work environments.
- Climate change exacerbates the problem of heat-related injuries (HRIs).
- Understanding factors contributing to HRI severity is crucial for worker safety.
Purpose of the Study:
- To identify critical factors influencing the severity of occupational heat-related injuries.
- To analyze the relationship between worker demographics, environmental conditions, and HRI outcomes.
Main Methods:
- Analysis of historical injury reports from the Occupational Safety and Health Administration (OSHA).
- Application of text mining and model-free machine learning techniques.
- Utilized the Multinomial Logit Model (MNL) to assess impact factor relationships.
Main Results:
- Higher risk of fatal HRIs observed in middle-aged, older, and male workers across construction, service, manufacturing, and agriculture sectors.
- Increased heat index, collapses, heart attacks, and fall accidents correlated with greater HRI severity.
- Symptoms like dehydration and dizziness were associated with reduced fatality risk.
Conclusions:
- Worker age, gender, industry, heat index, and secondary injuries significantly impact HRI severity.
- Tailored preventive strategies and targeted training are essential for mitigating HRI risks across diverse worker populations.
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