Lessons learned from using crash records for injury surveillance in the AFF sector.

Details

• Personal Author:
  Kum H-C ; Perez M ; Shipp E ; Trueblood A ; Vasudeo S ; Wu L
• Description:
  Introduction: Fatal injuries in the agriculture, forestry, and fishing (AFF) sector are grossly overrepresented compared to the rate across all sectors in the U.S., based on the National Census of Fatal Occupational Injury (CFOI). CFOI data indicate that transportation-related injuries are among the top contributors to these fatal events. However, little is known about motor vehicle crashes in AFF, specifically events involving logging trucks and agricultural vehicles in the southwest (SW) region (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas). The overarching goals of this ongoing project are (1) to develop an integrated database of AFF-related motor vehicle crashes that occurred on public roadways in the SW region and (2) use these data to conduct surveillance and research focused on identifying factors associated with higher injury severity events. Methods: Each state in the U.S. maintains a database of crash records for events occurring on their public roadways. These records include structured fields pertaining to person, vehicle, roadway, and environmental factors related to crash events and resulting injuries. In addition to the structured fields, records include free-text crash narratives where law enforcement officers provide additional details on crash causation. The present project includes the structured fields for crash records from Arkansas, Louisiana, New Mexico, Oklahoma, and Texas for the years from approximately 2010 to 2020. Narratives were obtained for Texas and Louisiana. To the extent feasible, the structured data fields across the five states were mapped to the Minimum Model Uniform Crash Criteria published by the National Highway Traffic Safety Administration to facilitate their integration. Descriptive statistics and geographic information system methods are used to identify the distribution of variables and identify spatial and temporal crash patterns. Multiple logistic regression models were constructed to identify factors associated with higher severity crashes involving logging trucks and farm vehicles. Finally, text mining methods including natural language processing applied to crash narratives are being used to better classify and understand AFF crashes. Results: At present, the surveillance system contains over 8 million records with nearly 9,000 AFF-related crashes. Analysis of the crash records yielded a protocol for appropriately identifying AFF crashes while also quantifying potential misclassification as an AFF event. Analyses also reflect fields that differ markedly between states and how this impacts the interpretation of findings, including the comparison of crashes and their contributing factors across states. Strengths of crash records include their availability and details that are not included in traditional surveillance systems or clinical records. Key limitations of crash records include a lack of injury-specific information including diagnoses codes and specific fields to reflect industry and occupation. Discussion: Despite their inherent limitations, crash records can be an important component of injury surveillance involving AFF vehicles in the SW region. They also can be used to identify potential risk factors for higher severity crashes which can inform the selection of countermeasures designed to address these factors.
• Subjects:
  Accidents, Occupational Air Pollutants, Occupational Dust Minerals Occupational Exposure Occupational Health Particulate Matter Preceptorship Safety
• Keywords:
  Accidents Accident Statistics Databases Logging Industry Motor Vehicles Surveillance Truck Drivers
• Publisher:
  National Institute for Occupational Safety and Health
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Abstract
• Place as Subject:
  OSHA Region 6 ; Texas
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  104-105
• NIOSHTIC Number:
  nn:20070066
• Citation:
  National Occupational Injury Research Symposium 2022 (NOIRS 2022): Preventing Workplace Injuries in a Changing World, May 10-12, 2022, Morgantown, West Virginia. Morgantown, WV: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, 2022 May; :104-105
• Federal Fiscal Year:
  2022
• NORA Priority Area:
  Agriculture, Forestry and Fishing
• Performing Organization:
  University of Texas Health Center at Tyler
• Peer Reviewed:
  False
• Start Date:
  20010930
• Source Full Name:
  National Occupational Injury Research Symposium 2022 (NOIRS 2022): Preventing Workplace Injuries in a Changing World, May 10-12, 2022, Morgantown, West Virginia
• End Date:
  20270929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:288377f300b3841e31f0e5a67a9601a50eb2f6171dd1fb5943189af7304e06e049f8ca28838540ad5e675645ca0b71ea3dafcdf30cc43f39db9450396163acfa
• Download URL:
  https://stacks.cdc.gov/view/cdc/181995/cdc_181995_DS1.pdf
• File Type:
  [PDF - 290.27 KB ]