Background: Chronic n-Hexane poisoning is prevalent among workers in small and micro printing industries in China. Despite this, there is limited research on occupational health risk assessment in these sectors. Conducting comprehensive risk assessments at key positions and proposing effective countermeasures are essential.

Methods: Data were collected from 84 key positions across 32 small and micro-sized printing enterprises. Air samples were tested for n-Hexane exposure levels in accordance with Chinese standards. Five risk assessment models were employed: COSHH, EPA, MOM, ICMM, and Technical Guide GBZ/T 289-2017 of China. The consistency of results across these models was analyzed.

Results: Workers in 84 job positions were categorized into four exposure groups, with exposure to n-Hexane for 8-10 h daily, 5-6 days weekly. Most positions operated with low automation levels (96.9% in printing, 5.9% in oil blending, and 42.9% in pasting), while others were manual. Localized ventilation rates were notably low in oil blending (23.5%), cleaning (14.3%), and pasting (9.5%) groups. n-Hexane concentrations exceeded Chinese occupational limits in 15.6% of printing, 17.7% of oil blending, and 21.4% of cleaning groups. Risk assessment models identified over 60% of work groups as high risk. Significant differences ( < 0.05) were found among the seven risk assessment methods. Consistency analysis revealed moderate agreement between the Chinese synthesis index and exposure index methods ( = 0.571,  < 0.01).

Conclusion: The Chinese synthesis and exposure index methods from Technical Guide GBZ/T 289-2017 are practical and reliable for assessing n-Hexane exposure risks in small and micro printing enterprises. Cleaning and printing roles were found to be at the highest risk for n-Hexane exposure. These findings provide valuable insights for targeted risk management strategies to protect workers' health in the industry.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11371762PMC
http://dx.doi.org/10.3389/fpubh.2024.1399081DOI Listing

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