Large machinery-related agricultural injuries across a five-state region in the Midwest

Objective: High agricultural injury related mortality and morbidity rates persist. This study addressed a knowledge gap regarding large machineryrelated injury magnitude, consequences, and risk factors. Methods: From randomly selected Midwestern agricultural operations in 1999 and 2001, 7420 eligible households participated. Demographic, exposure, and injury data collected for four 6-month periods used a computer-assisted telephone interview. An a priori causal model enabled survey development, data analysis, and interpretation. Directed acyclic graphs, developed from this model, facilitated potential confounder identification for specific exposures in multivariate analyses. Results: The injury rate was 12.82 events per 1000 persons per year. Increased risk was associated with male gender, increasing age, state of residence, history of prior injury, and increasing hours worked per week. Conclusions: Large machinery-related agricultural injuries can result in significant consequences. Associated increased injury risks require further investigation and targeting of relevant interventions.