This study aimed to investigate the association between lead exposure and serum gamma-glutamyl transpeptidase (γGT) levels as an oxidative stress marker in male steelworkers.

Data were collected during the annual health examination of workers in 2020. A total of 1,654 steelworkers were selected, and the variables for adjustment included the workers’ general characteristics, lifestyle, and occupational characteristics. The association between the blood lead level (BLL) and serum γGT level was investigated by multiple linear and logistic regression analyses. The BLL and serum γGT values that were transformed into natural logarithms were used in multiple linear regression analysis, and the tertile of BLL was used in logistic regression analysis.

The geometric mean of the participants’ BLLs and serum γGT level was 1.36 μg/dL and 27.72 IU/L, respectively. Their BLLs differed depending on age, body mass index (BMI), smoking status, drinking status, shift work, and working period, while their serum γGT levels differed depending on age, BMI, smoking status, drinking status, physical activity, and working period. In multiple linear regression analysis, the difference in models 1, 2, and 3 was significant, obtaining 0.326, 0.176, and 0.172 (all: p < 0.001), respectively. In the multiple linear regression analysis stratified according to drinking status, BMI, and age, BLLs were positively associated with serum γGT levels. Regarding the logistic regression analysis, the odds ratio of the third BLL tertile in models 1, 2, and 3 (for having an elevated serum γGT level within the first tertile reference) was 2.74, 1.83, and 1.81, respectively.

BLL was positively associated with serum γGT levels in male steelworkers even at low lead concentrations (< 5 μg/dL).

The study aimed to determine the association between shift work and metabolic syndrome and the prevalence of metabolic syndrome in the shift and day work groups among workers working in chemical plants.

Based on medical examination data collected in February 2019, 3,794 workers working at a chemical plant in Korea were selected. Multiple logistic regression analysis was performed by adjusting for age, sex, body mass index (BMI), drinking, exercise, smoking, employment period and organic compounds exposure.

The prevalence of metabolic syndrome in the entire study group was 23.4%, and the prevalence and components of metabolic syndrome in shift worker; waist circumference were higher than those of day workers (84.77 ± 8.64 vs. 83.41 ± 9.42, p < 0.001), systolic blood pressure (129.89 ± 9.47 vs. 127.57 ± 9.47, p < 0.001), diastolic blood pressure (81.22 ± 7.59 vs. 79.34 ± 7.46, p < 0.001), fasting blood glucose (99.27 ± 17.13 vs. 97.87 ± 13.07, p = 0.007), triglycerides (149.70 ± 101.15 vs. 133.55 ± 105.17, p < 0.001), and decreased high-density lipoprotein (53.18 ± 12.82 vs. 55.61 ± 14.17, p < 0.001). As a result of logistic regression analysis on the risk of metabolic syndrome, even after adjusting for age, sex BMI, drinking, smoking, exercise, employment period, organic compound exposure. the odds ratio (OR) for the shift group was 1.300 for daytime workers (Model 1, OR: 1.491; 95% confidence interval [CI]: 1.273–1.747; Model 2, OR: 1.260; 95% CI: 1.070–1.483; Model 3, OR: 1.309, 95% CI: 1.081–1.585; Model 4, OR: 1.300; 95% CI: 1.063–1.591).

Shift work in chemical plant workers increased the risk of metabolic syndrome, even after adjusting for general factors. To analyze the occupational cause and risk control, it is necessary to analyze the hazardous substances the workers were exposed to and their working environment. Additionally, a large-scale prospective analysis including general factors not analyzed in this study, such as eating habits, is required.