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Study of Correlation Between Subjective Symptoms and Ergonomic Load Index of Automobile Assembly Workers

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 576))

Abstract

For studying the effect of work-related ergonomic risk factors on automobile assembly workers’ health, the author investigated subjective symptoms, work management, work space, and work environment with environmental measurement and questionnaire. The Mann–Whitney U test and multivariate logistic regression were used to analyze the correlation between subjective symptoms and ergonomic risk factors. Results: The rank of incidence of six subjective symptoms is irritability, dizziness, insomnia, tinnitus, headache, chest tightness, and founding that those are statistically significant with work system satisfaction, work space satisfaction, and environmental satisfaction (P < 0.05). The occurrence of subjective symptoms is related to the work-related ergonomic load level (OR > 1). The height of the operation, the position of the equipment, and the air circulation are the main risk factors for the spontaneous symptoms. Conclusion: The incidence rate of assembly workers’ subjective symptoms is higher, which is related to the working system, work space, and work environment and is not relevant to the work training system.

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Acknowledgements

This study was supported by the National Key R&D Program of China, Grant No. 2016YFC0801700.

Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of China Academy of Safety Science and Technology.

All subjects who participated in the experiment were provided with and signed an informed consent form.

All relevant ethical safeguards have been met with regard to subject protection.

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Correspondence to Deshan Yin .

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Yin, D., Zhang, X., Zhao, Y., Zhou, S. (2020). Study of Correlation Between Subjective Symptoms and Ergonomic Load Index of Automobile Assembly Workers. In: Long, S., Dhillon, B. (eds) Man–Machine–Environment System Engineering . MMESE 2019. Lecture Notes in Electrical Engineering, vol 576. Springer, Singapore. https://doi.org/10.1007/978-981-13-8779-1_27

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