Association between exposure to metalworking fluid aerosols, occupational noise and chronic kidney disease: a cross-sectional study in China – BMC Public Health

Participants and procedures

From June to August 2022, we conducted a cross-sectional study of employees working in three automobile machining enterprises in Wuxi City, Jiangsu Province. Multi-stage sampling method was used in this study, and the sampling strategy was as follows: Three companies were randomly selected from the seven automotive machinery processing companies in Wuxi City, including one representative of large-sized, medium-sized, and small-sized companies. Employees were randomly selected to participate in the study according to the number of employees in these companies. A total of group of 2,830 individuals sampled: 1,400 individuals were sampled from large enterprises (≥ 3,000 employees), 1,200 from medium-sized enterprises (between 500 and 3,000 employees), and 230 from small enterprises (

where α = 0.05, p = 0.108 (according to the China Cardiovascular Health and Disease Report 2021, the prevalence of CKD is 10.8% [3]), q = 1 − p, and d = 0.15p. According to the formula, the final sample size required 1,468 active employees.

To improve the accuracy of the results, we used specific inclusion and exclusion criteria to further select the subjects. The inclusion criteria were as follows: (1) 1 year or more in service; (2) willingness to accept occupational health examination and custom questionnaire survey. The exclusion criteria were as follows: (1) employed for less than 1 year (n = 35); (2) pregnancy (n = 2); (3) a history of previous solid organ transplantation (n = 1); (4) a recent history of taking cephalosporins, aminoglycoside antibiotics, flucytosine, cisplatin, cimetidine, trimethoprim, or other drugs (n = 22); (5) the response rate of the questionnaire less than 80% or refusing occupational health examinations (n = 32). There were no significant differences in the general demographic characteristics of responders and nonresponders (Additional file 1: Table S1). Finally, 2,738 on-the-job workers were included in the study. The participants mainly included the following types of work: numerical control machining center (CNC) operators, CNC maintenance workers, material transporters, sandblasters, anode oxygenators, managers, and security guards.

MWF aerosols assessment

To ensure the validity and authenticity of the measurements, occupational exposure to MWF aerosols of the workers in the CNC workshops was measured in line with the NIOSH Metalworking Fluids All Categories Method 5524 [22]. In accordance with the Chinese specifications of air sampling for hazardous substances monitoring in the workplace (GBZ.159–2004), the workers were randomly selected for individual sampling according to the number of workers in each type of occupational category. Namely, when the number of workers in each occupation type was  10, four individuals were randomly selected [23]. Ultimately 52 workers were selected for sampling. Each individual sampling pump was calibrated with a representative calibrator prior to sampling. The personal sampling pump was worn on the worker’s chest in the breathing zone approximately 25 cm from the nose, and sampling was performed at a flow rate of 2 L/minute on three consecutive days between 8:00 a.m. and 4:00 p.m. We calculated the 8-hour time-weighted average (8-h TWA) concentration in accordance with the Specifications of air sampling for hazardous substances monitoring in the workplace GBZ.159–2004 as follows [23]:

where C_TWA represents 8-h TWA (mg/m³), c represents concentration of harmful substances in sample solution (µg/mL), v represents total volume of sample solution (mL), and F represents sampling flow rate (mL/minute). A job exposure matrix (JEM) [24] for MWF aerosols was used, which combined sampling data with workshop distribution, occupational category, workflow, historical workshop occupational monitoring data, and consultation with local industrial hygienists to fully assess the exposure of each worker. To further analyze the impact of exposure, we divided MWF aerosols exposure into four groups based on the interquartile spacing of the 8-h TWA of each worker for the discussion: 0 3; 0.40 mg/m³ 3; 0.46 mg/m³ 3; and 0.49 mg/m³ 3.

The following formula was used to calculate the cumulative exposure dose [25]:

where C represents the daily cumulative exposure dose (mg/m³), C_TWA represents 8-h TWA, and T_j is the number of hours of work in the corresponding position per day.

Occupational noise assessment

Individual noise exposure sampling of the workers using personal noise dosimeters and selecting workers were performed in accordance with the Chinese measurement of physical factors in the workplace Part 8: Noise GBZ/T 189.8–2007 [26]. The workers were randomly selected for individual sampling according to the number of workers in each type of occupational category the workers were randomly selected for individual sampling according to the number of workers in each type of occupational category. Namely, when the number of workers in each occupation type was  10, four individuals were randomly selected [26]. Ultimately 33 workers were selected for sampling. The sampling equipment included sound level calibrator HS6020 Level-SD-1137 and personal sound exposure meter ASV5910. The personal noise dosimeter was set to A-weighting and slow gear, and took the value of the equivalent sound level L_Aeq. The personal sound exposure meter was calibrated to an error of less than 0.5 dB(A) with a calibrator before each measurement. The personal sound exposure meter was worn on the worker’s front chest about 10 cm from the external ear canal during the measurements. Samples were taken on three consecutive days between 8:00 a.m. and 4:00 p.m. The 8-hour equivalent sound level was calculated, and the average of the three measurements was used as the worker’s noise exposure level. We recorded the measurement details, including workshops, date, position, operating procedure, and measurement duration. We calculated the 8-hour equivalent sound level using the following equation [26]:

where L_EX,8 h is normalization of equivalent continuous A-weighted sound pressure level to a normal 8 h working day, expressed in dB(A); T_e is the actual working time of a working day, expressed in hours; L_{Aeq, Te} is the equivalent sound level of the actual working day, expressed in dB(A); and T₀ is the standard working time (8 h). We used a JEM [24] for occupational noise, which combined sampling data with workshop distribution, occupational category, workflow, historical workshop occupational monitoring data, and equipment replacement to fully assess the exposure of each worker. To further analyze the impact of noise exposure, we divided occupational noise exposure into four groups based on the interquartile spacing of the L_EX,8 h for the discussion: 0 EX,8 h ≤ 84.85 dB(A); 84.86 dB(A) EX,8 h ≤ 89.70 dB(A); 89.71 dB(A) EX,8 h ≤ 91.96 dB(A); and 91.97 dB(A) EX,8 h ≤ 105.19 dB(A).

CKD

Morning fasting venous blood and morning urine were uniformly collected from the study participants at the Affiliated Branch of Wuxi Eighth People’s Hospital on the day of physical examination. After centrifugation of the blood samples in the hospital’s laboratory department, the samples were tested for serum creatinine using the Direxion CS-100 automatic biochemistry analyzer; and urine albumin and urine creatinine were tested in the hospital’s laboratory using the automated urine microalbumin creatinine analyzer ACR-300. The corresponding eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration 2021 (CKD-EPI) creatinine estimation eGFR equation [27]. The diagnostic criteria for CKD were urinary albumin/creatinine ratio (UACR) of ≥ 30 mg/g and reduced renal function (eGFR − 1. 1.73 m^− 2) lasting longer than 3 months, in line with the Guidelines for the Chinese Early Evaluation and Management of Chronic Kidney Disease [28].

Covariates

We used a self-administered questionnaire to collect covariates, which consisted mainly of basic demographic characteristics (sex, age, body mass index [BMI], ethnicity, marital status), occupational history (use of protective equipment [masks and earplugs], length of service), and risk factors considered to be related to renal function (physical exercise, smoking, drinking, hypertension, diabetes, and family history of kidney disease) [29].

Sex was categorized as male and female. Age was categorized as less than 30 years, 30 to 40 years, 40 to 50 years, and 50 years and older. The use of protective equipment (masks and earplugs) was categorized as yes and no. The ethnicity was divided into Han and ethnic minorities. Marital status was classified as unmarried, married, and divorced. The length of service was categorized as less than 5 years, 5 to 10 years, and more than 10 years. The family history of kidney disease was categorized as yes and no. Referring to the classification of BMI by the China Obesity Working Group, BMI was categorized as below 24 kg/m² and 24 kg/m² and above [30]. The individual’s physical activity level was divided into three groups, namely high, moderate, and low [25]. Patients diagnosed with hypertension in accordance with the Chinese Guidelines for the Prevention and Treatment of Hypertension 2018 were categorized as yes and no [31]. In line with the Chinese Diabetes Diagnostic Guidelines 2022, participants were classified as diabetes and non-diabetes [32]. Smoking was classified as nonsmoking, occasional smoking (smoking less than one cigarette per day but at least four cigarettes per week), and frequent smoking (smoking at least one cigarette per day for 6 months or more) [33]. Drinking was classified as no alcohol, occasional drinking (drinking less than once a week), and regular drinking (drinking at least once a week for 6 months or more) [33].

Statistical analysis

SPSS 26 and R 4.2 were used for data analysis. Descriptive statistical methods were used to describe the distribution of general demographic characteristics. The composition ratio of count data was analyzed by the chi-square test. Binary logistic regression was used to analyze the relationship among occupational MWF aerosols, noise exposure, and prevalence of CKD. Smooth curve fitting [34] was used to evaluate the potential nonlinear relationships of MWF aerosols and occupational noise with CKD. A segmented regression model was used to analyze the threshold effect, based on the assumption that prevalence of by MWF aerosols and occupational noise is a threshold response, one potential breakpoint was assumed [35]. Model 1 was not adjusted for any confounders. Model 2 was adjusted for physical exercise, smoking and drinking (the factors with statistically significant differences in univariate analyses). The Delta method introduced by Hosmer and Lemeshow [36] was used to estimate the confidence intervals of relative excess risk of interaction (RERI), attributable proportion of interaction (AP), and synergy index (S), to determine whether there was a specific interaction between MWF aerosols exposure and noise exposure on CKD in workers. In this study, bilateral statistical tests were used, and the test level was α = 0.05.

Ethical considerations

All the participants signed an informed consent form after learning about research-related information. The study was approved by the Ethics Committee of Nantong University (2013-L073).