Using O*NET to estimate the association between work exposures and chronic diseases

Am J Ind Med. 2014 Sep;57(9):1022-31. doi: 10.1002/ajim.22342. Epub 2014 May 19.


Background: A standardized process using data from the Occupational Information Network (O*NET) is applied to estimate the association between long-term aggregated occupational exposure and the risk of contracting chronic diseases later in life. We demonstrate this process by analyzing relationships between O*NET physical work demand ratings and arthritis onset over a 32-year period.

Methods: The National Longitudinal Survey of Youth provided job histories and chronic disease data. Five O*NET job descriptors were used as surrogate measures of physical work demands. Logistic regression measured the association between those demands and arthritis occurrence.

Results: The risk of arthritis was significantly associated with handling and moving objects, kneeling, crouching, and crawling, bending and twisting, working in a cramped or awkward posture, and performing general physical activities.

Conclusion: This study demonstrates the utility of using O*NET job descriptors to estimate the aggregated long-term risks for osteoarthritis and other chronic diseases when no actual exposure data is available.

Keywords: NLSY; O*NET; arthritis; chronic disease; musculoskeletal; occupational exposure; osteoarthritis.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Chronic Disease
  • Databases, Factual
  • Female
  • Humans
  • Logistic Models
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Occupational Diseases / epidemiology*
  • Occupational Exposure / statistics & numerical data*
  • Osteoarthritis / epidemiology*
  • Risk Factors
  • United States / epidemiology
  • Workload / statistics & numerical data*