Assessment of Risk of Musculoskeletal Disorders among Crane Operators in a Steel Plant: A Data Mining-Based Analysis

Abstract

Prevalence of musculoskeletal disorders (MSD) among industrial workers is often measured through the Nordic Musculoskeletal Questionnaire (NMQ) survey that captures the MSD complaints across different body parts. The outcomes of such a survey are reported in terms of relative frequency of MSD complaints for the body parts affected and are analyzed through t test, analysis of variance, or logistic regression. The study augments the analysis of NMQ data using relative risk, a statistical measure of prevalence, and classification and regression tree (CART), a data mining–based decision tree. The integrated analysis is done for 76 crane operators of a steel plant in India that considers operators, task, and workplace characteristics as predictors of MSD. The relative risk indices for each of the predictor categories compare the risk of prevalence of MSD. The outcomes of CART-based analysis are objective importance scores that quantify the contributions of the predictors toward the occurrence and severity of MSD. A risk priority index is computed to prioritize the predictor variables with categories in terms of their contribution. The study shows that the lower back and neck and shoulder are the most affected and account for 78.75% of the MSD complaints. CART shows that crane height contributes the maximum for MSD occurrences of both lower back and neck and shoulder. However, for MSD severity, while crane height contributes the most for neck and shoulder, cabin feature (static or movable) contributes the maximum for the lower back.