Agriculture-related Injuries: Discussion in Canadian Media

J Agromedicine. 2020 Jul;25(3):312-318. doi: 10.1080/1059924X.2020.1720881. Epub 2020 Jan 27.

Abstract

Objectives: This study examined news media reporting on farm injuries in Canada for the occurrence of prevention messages and factors related to whether an event was reported in more than one article. Methods: This study used a media database maintained by the Canadian Agricultural Safety Association (CASA), which stores publicly available news media reports of agricultural injuries and fatalities in Canada. Media reports were obtained for the years 2010 through 2017. Reports were coded as whether they reported a fatal or non-fatal injury, age and gender of those affected, urban or rural media, as well as whether they involved machinery, or were in French. Logistic regression was used to determine which variables predicted an event being reported more than once, and whether a report included a prevention message. Results: The database identified 856 relevant articles. Only 6.3% of the articles included a prevention message, and 34.7% were duplicate articles. Fatal injuries were more likely to be reported in multiple articles (odds ratio: 2.44). There was also significant variation in the occurrence of multiple reports across the years of the study. Prevention messages were more likely to occur when at least one child or female victim was involved in an event. However, only year of publication remained significantly associated with the occurrence of a prevention message in multivariable regression (odds ratio: 0.85). Conclusion: Prevention messages are rare in media reporting of farm injuries and are decreasing over time. Improved reporting is needed to aid in farm injury prevention.

Keywords: Wounds and injuries; farms; journalism.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Occupational / prevention & control
  • Accidents, Occupational / statistics & numerical data*
  • Canada / epidemiology
  • Farmers / statistics & numerical data*
  • Farms / statistics & numerical data
  • Humans
  • Mass Media / statistics & numerical data*
  • Wounds and Injuries / epidemiology*
  • Wounds and Injuries / prevention & control