Reducing musculoskeletal disorders in iron ore mine operators: A fuzzy-based intervention approach.

Abstract

Background: This study focuses on evaluating the exposure to whole-body vibration (WBV) and association of musculoskeletal disorders (MSDs) with various risk factors among dumper operators in the mining industry. Despite the issue's significance, prior research has been limited.

Objective: The study introduces a novel fuzzy-based approach for identifying, selecting, and prioritizing safety measures to mitigate MSD risks.

Methods: Data collection comprised face-to-face interviews, anthropometric measurements, Rapid Upper Limb Assessment (RULA) scoring for posture assessment, and the Nordic Musculoskeletal questionnaire for assessment of MSD prevalence. Multiple linear and logistic regression models were used to analyse the contributing risk factors to MSDs and WBV exposure. These risk factors formed the basis for a practical approach to select appropriate safety measures based on fuzzy based aggregation method of expert's judgment aimed at mitigating the risk of MSDs.

Results: The results revealed that the risk factors such as poor work posture, WBV exposure and poor seat design were significantly associated with neck (adjusted odds ratio aOR = 4.81), upper limb and shoulder (aOR = 3.28), upper back (aOR = 5.09), and lower back pain (aOR = 3.67) at p < 0.05. Using these factors to formulate safety measures to reduce MSD risk, the minimization of sharp turns and abrupt changes in elevation in designing the haul roads, scheduled maintenance practices, and ergonomic seat design were found as important safety measures in this study.

Conclusion: Our unique methodological approach in occupational health research could be highly beneficial for tailoring safety measures at the unit level with minimal effort.