Use of employer administrative databases to identify systematic causes of injury in aluminum manufacturing

Am J Ind Med. 2007 Sep;50(9):676-86. doi: 10.1002/ajim.20493.

Abstract

Background: Employer administrative files are an underutilized source of data in epidemiologic studies of occupational injuries.

Methods: Personnel files, occupational health surveillance data, industrial hygiene data, and a real-time incident and injury management system from a large multi-site aluminum manufacturer were linked deterministically. An ecological-level measure of physical job demand was also linked. This method successfully created a database containing over 100 variables for 9,101 hourly employees from eight geographically dispersed U.S. plants.

Results: Between 2002 and 2004, there were 3,563 traumatic injuries to 2,495 employees. The most common injuries were sprain/strains (32%), contusions (24%), and lacerations (14%). A multivariable logistic regression model revealed that physical job demand was the strongest predictor of injury risk, in a dose dependent fashion. Other strong predictors of injury included female gender, young age, short company tenure and short time on current job.

Conclusions: Employer administrative files are a useful source of data, as they permit the exploration of risk factors and potential confounders that are not included in many population-based surveys. The ability to link employer administrative files with injury surveillance data is a valuable analysis strategy for comprehensively studying workplace injuries, identifying salient risk factors, and targeting workforce populations disproportionately affected.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Accidents, Occupational / statistics & numerical data*
  • Adolescent
  • Adult
  • Age Factors
  • Aluminum
  • Databases, Factual
  • Female
  • Humans
  • Male
  • Metallurgy*
  • Middle Aged
  • Occupational Health / statistics & numerical data*
  • Personnel Management / statistics & numerical data*
  • Population Surveillance
  • Sex Factors
  • Task Performance and Analysis
  • United States

Substances

  • Aluminum