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Using O*NET to estimate the association between work exposures and chronic diseases
Author(s) -
Dembe Allard E.,
Yao Xiaoxi,
Wickizer Thomas M.,
Shoben Abigail B.,
Dong Xiuwen Sue
Publication year - 2014
Publication title -
american journal of industrial medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.7
H-Index - 104
eISSN - 1097-0274
pISSN - 0271-3586
DOI - 10.1002/ajim.22342
Subject(s) - kneeling , medicine , logistic regression , work (physics) , physical therapy , arthritis , gerontology , environmental health , pathology , alternative medicine , mechanical engineering , engineering
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. Am. J. Ind. Med. 57:1022–1031, 2014. © 2014 Wiley Periodicals, Inc.