Abstract: Objective To know the blood lead level of lead-exposed workers in Changzhou City,and discuss the influencing factors of abnormal blood lead,so as to provide basis for the prevention of lead poisoning. Methods Totally 3 677 documents of 193 lead related enterprises in Changzhou occupational health examination project from January to December 2021 were collected,the influencing factors of abnormal blood lead in lead-exposed workers were analyzed by logistic regression and evaluated by the receiver operating characteristic curve（ROC） curve. Results According to the international blood lead diagnostic standard,the abnormal blood lead rate of 3 677 lead-exposed workers in this study was 2.04%. The multivariate logistic analysis regression results showed that male（OR=5.468,95%CI：3.055-9.786,P<0.01）,blood pressure（OR=2.022,95%CI：1.095-3.733,P<0.05）,length of service exposed to harmful factors（OR=1.475,95%CI：1.153-1.888,P<0.05） and scale of the employer（OR=4.024, 95%CI：2.782-5.821,P<0.01） were all correlated with abnormal blood lead. In terms of the type of health examination,the abnormal blood lead rates of on-the-job health examination（OR=4.662,95%CI：1.387-15.670,P<0.05） and off-job health examination（OR=8.315,95%CI：1.635-42.300,P<0.05） were higher than those of pre-job health examination. In terms of industry categories,the abnormal blood lead rates of workers in electrical machinery and equipment manufacturing（OR=2.386,95%CI：1.080-5.268,P<0.05） and metal products manufacturing（OR=14.693,95%CI：7.153-30.182,P<0.01） were higher than those in other service manufacturing industries. Conclusion In order to effectively control their blood lead levels,reduce the risk of cardiovascular and nervous system diseases,and extend the occupational life of high-risk groups,regular monitoring of blood lead should be carried out for the people at high risk of lead exposure in electrical machinery and equipment manufacturing and metal products manufacturing industries.

Key words: Lead, Abnormal blood lead, Receiver operating characteristic curve, Occupational health examination