A presentation of the ergonomic analysis of risk factors in productive sectors of Chile and their relation with upper limb musculoskeletal symptomatology
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2019Metadata
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Cerda, Leonidas
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A presentation of the ergonomic analysis of risk factors in productive sectors of Chile and their relation with upper limb musculoskeletal symptomatology
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This study aims to identify musculoskeletal health conditions present in a population that works in several different productive sectors in Chile in order to determine the physical risk factors in that type of labor and relation between these risk factors and upper limb musculoskeletal symptomatology. An analytic, nonexperimental, transversal association study was carried out with a sample of 390 worker’s tasks, confidence level of 95%, standard deviation of 5% and maximal variability. Representative task per trade-workers of six different sectors was evaluated. Results describe most representative physical risk factors. In industrial sector were: posture and strength; in service sector: repetitive movement and force factors; in mining sector: repetitive movement and posture and strength; in agriculture sector: repetitive movement, posture and recovery time; in construction sector: posture, repetitive movement and strength; in aquaculture sector: repetitive movement and recovery time. There was a high prevalence of musculoskeletal complaints, of 69,74% in the sample evaluated with Nordic Musculoskeletal Questionnaire. There was no association between musculoskeletal health condition and identification of risk factors (Fisher p-value 0,587). Statistically significant association was found between physical risk factors identified and specific productive sectors chosen (p-value = 0.0001). There is a high prevalence of musculoskeletal symptoms in all productive sectors studied. Productive sectors that present most specific risk factors are Aquaculture, Agriculture, and Industry Sector and this translates into a high prevalence of physical risk factors. The model of the applied tools is efficient to perform the surveillance of the ergonomic risk factors and the musculoskeletal health condition.
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URI: https://repositorio.uchile.cl/handle/2250/169676
DOI: 10.1007/978-3-319-96083-8_75
ISSN: 21945357
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Advances in Intelligent Systems and Computing, Volumen 820, Pages 570–578, 2019
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