Association between metabolic syndrome and shift work in chemical plant workers

Abstract

Background: 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. Methods: 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. Results: 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 highdensity 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). Conclusions: 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.