In the U.S., the number one cause of fatal occupational injuries is highway transportation crashes (CDC, 2011 in MMWR). AFF workers experience substantially higher transportation-related injury rates compared to other workers. Additionally, all five states (AR, LA, NM, OK, TX) in the SW Ag Center region were among those with the highest or second highest rates (CDC, 2011).
National or regional estimates of nonfatal injury rates are not widely available and the most recent national study of fatal injury is over 20 years old. In 2009, a USDA report emphasized that, “Many details of public road crashes involving agricultural machinery and motor vehicles are unknown or lack sufficient detail to aid prevention efforts” (CASHRE/USDA, 2009). This assertion is still relevant. To our knowledge and of additional concern, none of the available studies of fatal or nonfatal injury focus on the SW Ag Center region. This lack of data substantially hinders the development of regionally specific outreach or interventions, which are important given the diversity of AFF operations across the U.S.
To address surveillance and research needs, this project includes two aims: (1) to construct a model system to support surveillance and research of nonfatal and fatal crashes involving AFF equipment and vehicles in the SW Ag Center region and 2) to develop and evaluate a process for identifying and extracting variables from crash narratives that aids in the identification and characterization of crashes involving AFF equipment, vehicles and workers. These aims will be addressed by merging crash records from AR, LA, NM, OK, and TX while also analyzing data from other sources. Our overall objective is to inform the development of surveillance systems while also filling gaps in our understanding of transportation-related injuries in AFF populations in the SW Ag Center region (PH Region 6).
Read the methodology: Methodology for Flagging Agriculturally-Related Crash Narratives Using Keywords
Excel Tool Spreadsheet: Excel Tool for Flagging Agriculturally-Related Crash Narratives Using Keywords
Eva Shipp, PhD