Derived patterns of musculoskeletal symptoms and their relationships with ergonomic factors among electronic assembly workers: A latent class analysis

Introduction: Multi-site musculoskeletal symptoms (MSS) are considered to be more common and have more serious consequences than single-site MSS. This study aimed to determine whether derived patterns of MSS may be identified in electronic assembly workers and if extracted MSS classes are associated with personal and work-related factors. Method: A cross-sectional questionnaire study was performed with 700 participating electronic assembly workers. The questionnaire included individual factors, psychosocial and physical exposures, and MSS. The derived patterns of MSS and their relationships with ergonomic factors were analyzed using latent class analysis (LCA) and multinomial logistic regression models (MLRM). Results: The 1-year prevalence of MSS affecting only one body site or two or more body sites was 14.9% and 32.7%, respectively. The results of LCA showed three distinct classes of MSS patterns, which were labelled 'MSS in most sites' (5.0%), 'MSS in neck and shoulder' (27.0%), and 'MSS in one or no site' (68.0%). The results of MLRM showed that the 'MSS in neck and shoulder' was associated with job tenure (OR 5.579, 95% CI 2.488-12.511), excessive dynamic and static loads (OR 3.868, 95% CI 1.702- 8.793 and OR 5.270, 95% CI 2.020-13.747, respectively); while the 'MSS in most sites' was associated with high job demands (OR 4.528, 95% CI 1.647-12.445) and excessive dynamic loads (OR 111.554, 95% CI 4.996-2490.793). Conclusions: The results showed unique patterns of MSS among electronic assembly workers that were associated with personal and work-related factors. Practical applications: The findings highlight that the high prevalence of multi-site MSS in this group should be a focus. It also provides further evidence that LCA considering the number and location of anatomical sites involving MSS can be used to determine distinct classes of MSS patterns, which is of great significance for the epidemiological study and management of MSS in the future. (c) 2022 National Safety Council and Elsevier Ltd. All rights reserved.