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

Allard E. Dembe, Xiaoxi Yao, Thomas M. Wickizer, Abigail B. Shoben, Xiuwen Dong

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Background: A standardized process using data from the 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. Am. J. Ind. Med. 57:1022-1031, 2014.

Original languageEnglish (US)
Pages (from-to)1022-1031
Number of pages10
JournalAmerican Journal of Industrial Medicine
Volume57
Issue number9
DOIs
StatePublished - Sep 2014

Keywords

  • Arthritis
  • Chronic disease
  • Musculoskeletal
  • NET
  • NLSY
  • O
  • Occupational exposure
  • Osteoarthritis

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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