OIICS coding of agricultural injuries mined from Maine PCR records (2008-2022) reveals significant differences in injury source, event, and nature by age group and sex

ObjectivesAgricultural injuries are known to be under-reported in existing surveillance systems. OIICS codes are a standardized classification system developed by the Bureau of Labor Statistics (BLS) which ensure consistency in reporting and analysis of workplace incidents over time across industry sectors. Our study examines OIICS coded injuries obtained via mining emergency response (Pre-Hospital Care Report) records (PCRs) to improve tracking, documentation, and understanding of agricultural injury trends. MethodsWe analyzed frequencies of OIICS subcodes for Primary Injury Source, Event/Exposure, Nature of Injury, and Body Part classifications for 1,583 injuries among agricultural workers in Maine, spanning January 2008 to December 2022. To streamline the dataset and subsequent analysis, subcodes within each category were thematically grouped. We summarized and visualized grouped code frequencies by subject sex, age category, season of injury, and study subperiod. Chi-square tests were used to assess differences in injury patterns by sex and age group. ResultsReported injuries increased over time from 420 in 2008-2011 to 631 in 2019-2022. The most frequently reported classifications were: Tractors/PTOs (Injury Source), Fall (Event), Multiple parts (Body Part), and Pain (Nature of Injury). A marked increase in Nonclassifiable Source subcodes and Fall Event subcodes was observed in 2019-2022 relative to earlier periods. Significant differences by sex were found for injury Event subcodes: The most frequent source of injuries for females were animals, versus objects and equipment being the most frequent source for males. Nature of Injury also varied significantly by sex. All four OIICS categories (Source, Event, Nature, Body Part) showed significant variation by age group. Older subjects reported more injuries due to falls and overexertion, while younger were more frequently subject to exposure, intentional self-injury, injury in fires, and injuries involving farm vehicles and equipment. ConclusionInjury counts rose across each successive study period. All injury subcodes differed significantly by age category, while injury Event and Body Part codes also varied significantly by sex. This suggests that injury risks are not uniform across demographics, and tailored safety interventions by sex and age group may be more effective in reducing agricultural injuries.