Abstract:
Background Under the guidance of achieving carbon peaking and carbon neutrality goals, the demand for lithium-ion batteries has increased significantly. However, during the production, use, and maintenance of lithium-ion batteries, workers are inevitably exposed to various occupational hazards, and some chemicals are nephrotoxic.
Objective To evaluate the kidney function and potential determinants among male workers in a lithium-ion battery-related enterprise in Shanghai.
Methods The data of occupational health examination carried out by an occupational disease prevention and control institution for workers in a lithium-ion battery-related enterprise in Shanghai were collected. The workers participating pre-employment occupational health examination were treated as a control group, and the other group was recruited from those participating periodic health examination. Serum creatinine, urea nitrogen, uric acid, and renal ultrasound were used to assess the kidney function of workers. Kidney function was classified according to the reference range of kidney function indicators in Diagnostics (9th Edition, national planning textbook for high education in medicine). Binary logistic regression and generalized linear regression were used to identify potential determinants of abnormal values in kidney function indicators in workers.
Results There were 6184 workers in the control group (pre-employment) with a mean age of (27.40±4.50) years. There were 3526 workers on the job with a mean age of (29.40±4.99) years and the median time of service was 2.00 (1.00, 3.42) years. The prevalence rates of high serum creatinine, high urea nitrogen, and high uric acid, and abnormal kidney ultrasound among the control group were 0.66%, 2.47%, 30.32%, and 10.12%, respectively; the indicators in the on-the-job workers were 0.96%, 3.35%, 38.25%, and 12.68%, respectively, significantly higher than those in the control group (P<0.05). After adjusting for worker age, length of service, smoking status, drinking status, hypertension, and hyperglycemia, the binary logistic regression models showed that regular smokers had a higher risk of high urea nitrogen than nonsmokers (OR=1.411, 95%CI: 1.011, 1.969). The risk of high uric acid was lower in older workers (OR=0.966, 95%CI: 0.953, 0.979), and higher in workers with more years of service (≤1 year, OR=1.295, 95%CI: 1.093, 1.534; >1-3 years, OR=1.747, 95%CI: 1.494, 2.042; >3 years, OR=1.866, 95%CI: 1.511, 2.304), hypertension (OR=1.400, 95%CI: 1.055, 1.859), and hyperglycemia (OR=1.565, 95%CI: 1.221, 2.006). Workers who were older (OR=1.038, 95%CI: 1.022, 1.054) and had longer working years (>1-3 years, OR=1.518, 95%CI: 1.201, 1.920), occasional smoking habits (OR=1.239, 95%CI: 1.039, 1.478), regular drinking habits (OR=1.875, 95%CI: 1.139, 3.087), and hypertension (OR=1.465, 95%CI: 1.075, 1.998) were at a higher risk of renal ultrasound abnormalities. The generalized linear models showed that length of service (>1-3 years, β=1.120, 95%CI: 0.360, 1.880; >3 years, β=1.451, 95%CI: 0.543, 2.358), smoking status (occasional, β=0.818, 95%CI: 0.156, 1.479; regular, β=0.841, 95%CI: 0.066, 1.616), and hypertension (β=2.742, 95%CI: 1.390, 4.094) were the influencing factors of serum creatinine concentration in the workers. Age (β=0.014, 95%CI: 0.009, 0.019) and length of service (>1-3 years, β=0.079, 95%CI: 0.012, 0.146) were the influencing factors of urea nitrogen. Age (β=−1.759, 95%CI: −2.288, −1.231), length of service (≤1 year, β=10.676, 95%CI: 4.035, 17.316; >1-3 years, β=26.117, 95%CI: 19.962, 32.272; >3 years, β=34.558, 95%CI: 26.116, 43.001), hypertension (β=23.162, 95%CI: 11.617, 34.707), and hyperglycemia (β=15.017, 95%CI: 4.853, 25.180) were the influencing factors of uric acid.
Conclusion The prevalence of abnormal kidney function of workers in selected lithium-ion battery-related enterprise is varied by age, length of service, smoking status, drinking status, hypertension, and hyperglycemia. There may be a trend that the longer the time working in a lithium-ion battery-related enterprise, the worse the workers' kidney function. Therefore, the enterprise should pay attention to the possible reasons for their changes and take targeted interventions.