OBJECTIVE: To estimate the three-year cumulative risk of work-related upper limb disorders (WRULDs) in a cohort of automotive industry workers and to provide a first test of the ability of the European Assembly Worksheet (EAWS) methodology to predict WRULDs. METHODS: 292 workers were investigated by reviewing workers' medical records during the period from 2012-2015 to determine their exposure to biomechanical overload according to EAWS risk scores (0-25, low risk, Green zone; 26-50, medium risk, Yellow zone; >50, High risk; Red zone). RESULTS: The risks were 0.83%, 5.71%, and 11.88% for the Control (unexposed), Green and Yellow Groups, respectively. Only the comparison between the Yellow/Control Groups was significant (p = 0.0014). In total, we observed 17 cases of musculoskeletal disorders (MSDs) (14 symptomatic and 3 cases detected by physical examination). CONCLUSIONS: The EAWS is a useful tool for the preliminary risk assessments of biomechanical overload among automotive industry workers. The finding of mainly non-specific disorders highly suggests that health surveillance should aim to identify not only full-blown diseases but also symptomatic cases.
Work-related upper limb disorders and risk assessment among automobile manufacturing workers: A retrospective cohort analysis
Greco A.;Pedata P.;Caputo F.;Chiodini P.;Miraglia N.
2019
Abstract
OBJECTIVE: To estimate the three-year cumulative risk of work-related upper limb disorders (WRULDs) in a cohort of automotive industry workers and to provide a first test of the ability of the European Assembly Worksheet (EAWS) methodology to predict WRULDs. METHODS: 292 workers were investigated by reviewing workers' medical records during the period from 2012-2015 to determine their exposure to biomechanical overload according to EAWS risk scores (0-25, low risk, Green zone; 26-50, medium risk, Yellow zone; >50, High risk; Red zone). RESULTS: The risks were 0.83%, 5.71%, and 11.88% for the Control (unexposed), Green and Yellow Groups, respectively. Only the comparison between the Yellow/Control Groups was significant (p = 0.0014). In total, we observed 17 cases of musculoskeletal disorders (MSDs) (14 symptomatic and 3 cases detected by physical examination). CONCLUSIONS: The EAWS is a useful tool for the preliminary risk assessments of biomechanical overload among automotive industry workers. The finding of mainly non-specific disorders highly suggests that health surveillance should aim to identify not only full-blown diseases but also symptomatic cases.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
