Abstract
0383 Use of an ONET based job exposure matrix to predict prevalence of Carpal Tunnel Syndrome in a large pooled cohort
Occupational and environmental medicine (London, England), Vol.71(Suppl 1), pp.A48-A49
06/2014
DOI: 10.1136/oemed-2014-102362.150
Abstract
Objectives To determine if job title based physical exposure measures predicted prevalent carpal tunnel syndrome (CTS) in a large pooled cohort of workers. Method We pooled baseline examination data from six prospective cohort studies, restricting analyses to those employed at least 1 year. CTS was defined as median neuropathy plus typical symptoms. Physical exposure estimates for static strength, dynamic strength, time spent making repetitive motions, and time handling objects were extracted from the Occupational Network (O*NET) database using Standard Occupational Classification codes based on reported job title. Three exposure categories of high force/ high repetition, low force/ low repetition, and mixed high and low exposures were entered into logistic regression models adjusting for age, gender, body mass index (BMI), diabetes, rheumatoid arthritis, employed time and study site. Results Of 3562 in the pooled cohort, 7.6% met a prevalent CTS definition with mean employed time of 7.9 years (SD 8.2). Compared to subjects with low job requirements for dynamic strength and repetitive motion, those with mixed exposures or high exposures showed increased prevalence of CTS (OR 1.46; 95% CI: 1.01–2.11 and OR 2.32; 95% CI: 1.15–4.67, respectively). Similar dose dependent associations of combined exposures were shown for all exposure combinations tested, with high/high combinations having the largest effect sizes (OR range 2.32–3.17) relative to the low force/low repetition exposure combinations. Conclusions Use of job-title based exposures was useful for demonstrating associations with prevalent CTS. Jobs with combined high exposures of force and repetition showed consistently greater risk of CTS compared to jobs with lower exposure levels.
Details
- Title: Subtitle
- 0383 Use of an ONET based job exposure matrix to predict prevalence of Carpal Tunnel Syndrome in a large pooled cohort
- Creators
- Ann Marie Dale - Washington University in St. Louis School of MedicineAngelique Zeringue - Washington University in St. LouisCarisa Harris-Adamson - University of California, BerkeleyMatt Thiese - University of California, San FranciscoStephen Bao - United States Department of StateSue Burt - National Institute for Occupational Safety and HealthLinda Merlino - University of IowaArun Garg - University of Wisconsin–MilwaukeeEllen Eisen - University of California, BerkeleyFred Gerr - University of IowaKurt Hegmann - University of UtahJay Kapellusch - University of Wisconsin–MilwaukeeDavid Rempel - University of California, San FranciscoBarbara Silverstein - United States Department of StateBradley Evanoff - Washington University in St. Louis
- Resource Type
- Abstract
- Publication Details
- Occupational and environmental medicine (London, England), Vol.71(Suppl 1), pp.A48-A49
- DOI
- 10.1136/oemed-2014-102362.150
- ISSN
- 1351-0711
- eISSN
- 1470-7926
- Language
- English
- Date published
- 06/2014
- Academic Unit
- Occupational and Environmental Health; Epidemiology
- Record Identifier
- 9984364526802771
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