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


CONCLUSIONS
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.
Center for Health Outcomes, Policy and Evaluation Studies, The Ohio State University, College of Public Health, Columbus, Ohio.
Allard E
AE
Dembe
Xiaoxi
X
Yao
Thomas M
TM
Wickizer
Abigail B
AB
Shoben
Xiuwen Sue
XS
Dong
D002908:Chronic Disease; D016208:Databases, Factual; D005260:Female; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009784:Occupational Diseases / Q000453:epidemiology*; D016273:Occupational Exposure / Q000706:statistics & numerical data*; D010003:Osteoarthritis / Q000453:epidemiology*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D016526:Workload / Q000706:statistics & numerical data*
NLSY; O*NET; arthritis; chronic disease; musculoskeletal; occupational exposure; osteoarthritis