[Analysis of blood lead level and its influencing factors in lead workers based on active monitoring].

Objective: To analyze the distribution characteristics of blood lead levels and their influencing factors among lead-exposed workers in Tianjin City in 2022 through active monitoring, and to provide a scientific basis for the prevention and control of occupational lead poisoning. Methods: In January 2022, 141 workers who were exposed to lead and its inorganic compounds in four lead related enterprises in Binhai New Area, Dongli District, and Wuqing District of Tianjin City in 2022 were selected as the research subjects for active monitoring of occupational health and collection of relevant data. Mann Whitney U test was used for inter group comparison of non normally distributed quantitative data, while Kruskal Wallis H test was used for inter group comparison of multiple data; The influencing factors of elevated blood lead were analyzed using multiple unconditional logistic regression. Results: 141 lead workers had an average age of (36.9±7.0) years and an average lead exposure length of (5.4±5.1) years; The median and quartiles of blood lead concentration [M (Q(1), Q(3)) ] were 23.73 (12.04, 39.73) μg/L, with a geometric mean of 22.27 μg/L; 129 individuals (91.49%) had blood lead levels below 100 μg/L, 12 individuals (8.51%) had blood lead levels between 100-400 μg/L, and no individuals had blood lead levels above 400 μg/L. Univariate analysis showed that there were statistically significant differences in blood lead concentrations among workers from different regions, genders, ages, lead exposure years, industry categories, and enterprise sizes (P<0.05). Multivariate logistic regression analysis showed that gender, age, and industry category were independent risk factors for elevated blood lead levels in workers (OR=9.66, 4.87, 2.30, P<0.05) . Conclusion: The blood lead concentrations of lead workers in Tianjin City are influenced by factors such as gender, age, and industry category. Strengthened supervision and management should be implemented for key populations and industries.