Synergy and Attenuation of Work-Related Factors in Musculoskeletal Disorders: The Combined Risk Based on Data from
Eun-Soo Lee1, Myong-Hwan Kim1, Dongmug Kang1,2,3
1Department of Occupational and Environmental Medicine, Pusan National University Yangsan Hospital, Yangsan 50612, Republic of Korea.
Abstract:
Background and objectives: Musculoskeletal disorders (MSDs) account for more than 60% of compensated occupational diseases in Korea. Despite this burden, benchmarks of standardized ergonomic exposure and evidence on the combined effects of risk factors remain limited. This study aimed to construct a body part-specific ergonomic job exposure matrix (JEM) and evaluate the independent and interactive effects of ergonomic, demographic, and work-related factors. Materials and Methods: We analyzed the data of 210,500 workers from the 2nd-6th Korean Working Conditions Survey (2009-2020). A JEM for arms/neck, back, and legs was developed and validated (κ ≥ 0.79). Logistic regression models estimated adjusted odds ratios (aORs), and additive interactions were assessed using relative excess risk due to interaction (RERI), attributable proportion (AP), and the synergy index (SI). Results: High ergonomic exposure was strongly associated with MSDs across all body regions (aORs 2.3-2.5). Age > 45 years, long working hours (>52 h), and high job strain also increased risks (aORs 1.4-2.3). On the additive scale, ergonomic risk combined with older age showed consistent synergy (RERI up to 1.5; SI >1.5), whereas combinations with long working hours or job strain showed attenuation (RERI < 0; SI < 1). Women reported higher crude prevalence but lower adjusted odds (aOR ≈ 0.9). Conclusions: This nationally representative study demonstrates that ergonomic risk, age, long working hours, and job strain are major determinants of MSDs. The validated Korean JEM provides a standardized tool for surveillance and compensation. However, the cross-sectional design limits causal inference. Future longitudinal research with objective exposure measures is needed to strengthen causal inference and guide tailored prevention.
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