Linking Datasets to Characterize Injury and Illness in Alaska's Fishing Industry

Area of Science:

• Occupational Health
• Public Health Surveillance
• Injury Epidemiology

Background:

• Alaska's fishing industry is hazardous, yet nonfatal injury and illness data are limited.
• Existing data sources capture different segments of the industry, hindering comprehensive surveillance.

Purpose of the Study:

• To assess the utility of linking multiple datasets for nonfatal injury/illness surveillance in Alaska's fishing industry.
• To characterize injury and illness patterns, including types, causes, and circumstances, from 2012-2016.

Main Methods:

• Utilized probabilistic linkage methods to combine data from the Alaska Trauma Registry (ATR), Fishermen's Fund (FF), and US Coast Guard (USCG).
• Coded linked datasets to identify unique injury/illness cases and analyze characteristics and circumstances.
• Identified 3,014 unique injury/illness cases, with distinct patterns captured by each dataset (e.g., FF for small vessels, USCG for large vessels).

Main Results:

• The most frequent injury types were sprains/strains/tears (27%), cuts (15%), and fractures (11%).
• Common causes included contact with objects/equipment (41%), overexertion (27%), and slips/trips/falls (20%).
• Key activities leading to injury were hauling gear and walking/climbing, with 53% of injuries being of moderate severity.

Conclusions:

• Linking disparate datasets offers a more complete picture of nonfatal injuries and illnesses in Alaska's fishing sector.
• Findings highlight specific injury types, causes, and high-risk activities, crucial for targeted prevention.
• This integrated surveillance approach is vital for developing effective safety strategies in hazardous maritime industries.