Upper Limb Musculosketal Disorders: Quantifying Risk

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DESCRIPTION: This multi-center prospective cohort study will: (i) Determine baseline prevalence rates and subsequent incidence rates over a 3 year period for specific distal upper extremity disorders and symptoms for 3 levels of job physical exposures (low, medium, high), (ii) Quantify job and individual risk factors (e.g., force, posture, repetition, etc.), (iii) Validate existing job analysis methods (especially American Conference of Governmental Hygienists (ACGIH) Threshold Limit Value (TLV) for Hand Activity (HAL), Strain Index (SI) and Washington State Checklist), and (iv) develop a final model for determining MSD risks. A cohort of 600 workers (study drop-outs replaced) from 5 very different industries with a total worker population of over 10,000 in two diverse states will participate in the study to help ensure generalizability of the study results. To maximize objectivity and accuracy, job physical exposures will rely primarily on measurements to quantify exposures. To maximize clinical and epidemiological validity and reliability, all participants will have health outcomes assessments by Certified Hand Therapists and qualified physicians. These will include: baseline questionnaires, structured interviews and standardized physical examinations. Changes in job physical exposures will be monitored monthly. Specific disorders and symptoms will be assessed monthly using a symptom questionnaire on all, and structured interviews/physical examinations on those with symptoms. Senior physicians experienced in evaluating worker populations will provide electrodiagnostic testing (at baseline, and during monthly follow-up if new symptoms develop) to those workers with CTS-like symptoms. Job physical exposure and health outcomes assessment teams will be blinded to each other throughout the field observation phase. Multivariate logistic regression (MLR) models and survival analyses will be utilized to explore relationships between job physical risk factors and specific disorders, aggregate disorders and symptoms. In addition to quantifying ergonomic risk factors, interactions between various job, psychosocial and individual risk factors will be explored. This project is expected to result in the ability to improve the existing ergonomic job evaluation models that have robust predictive capabilities for a broad range of industries.