Factors to Predict Occupational Knee Pain Among Healthcare Workers: Cross-Sectional Study - Anung Putri Illahika; Bambang Widiwanto; Yoyok Subagio; Khansa Dary Darmawan; Sekar Arum Kusumaningadi; Tara Mandiricha; Agung Cendekia Putra Nusantara (The Indonesian Journal of Occupational Safety and Health, 2026)
Introduction: Knee pain is a common musculoskeletal problem among healthcare workers, often linked to degenerative changes and biomechanical stressors related to occupational demands. The predictive value of age and body composition is generally unclear, although they are considered confounding factors. Identifying specific indicators is important for implementing workplace health interventions. Methods: The present study was a cross-sectional survey of 121 hospital-based healthcare workers in Indonesia. Body composition (fat mass and body mass index) was analyzed using a Tanita BC-418 bioelectrical impedance analysis (BIA) system. Knee pain was determined from the Western University and McMaster University Osteoarthritis Index (WOMAC) questionnaires. Controlling for age, multiple regression analysis was employed to examine the independent effects of fat mass and BMI with knee pain severity. Results: The regression model was significant (F(3.117) = 3.12, p = 0.029, R2 = 0.074) accounting for 7.4% of the variation in WOMAC sub-scores on average amongst participants in the sample. Fat mass was an independent predictor of knee pain severity (B = 0.28, p = 0.017), while age (B = 0.12, p = 0.18) and BMI (B = 0.09, p = 0.29) were not significantly associated. The VIFs for all variables were less than 1.6 with no linear correlation apparent. Conclusion: These results indicate that fat mass percentage is associated with the degree of knee pain in healthcare workers to a greater extent than BMI or age. These findings suggest that it may help support early knee pain prevention strategies by integrating body composition assessment into occupational health programs.