Oxidative Damage Modeling by Biomonitoring of Exposure to Metals for Manual Metal Arc Welders

Abstract

Background: Welding fumes consist of a wide range of complex metal component. Metals induced chronic obstructive pulmonary disease, bronchitis, metal fume fever, cancer, and functional changes in the lung. Since oxidative stress plays a role in this pathogenesis, it is characterized by airflow limitation. Objectives: This study focused on the anticipation of the oxidative stress biomarker in welders by assessing the amount of urinary metals and spirometry airflow index. Materials and Methods: We measured malondialdehyde (MDA), as a biomarker of oxidative stress, in urine from20 manual metal arc welders of a petroleum tank making plant. For controls, we recruited 20 ministerial workers who were matched with welders. Urine content of chromium, cadmium, and lead as well as spirometry airflow parameters such as expiratory volumes were applied to partial least square regression (PLS) model for predicting oxidative stress biomarker. Results: The Results revealed that metal urine concentration in welders was higher than controls but only the difference in chromium concentration was significant (P < 0.002). In the range of metals exposure, induction of oxidative stress for exposed group was observed by increase in urine MDA (11.17 ± 4.23 and 4.83 ± 1.82 mM in welders and controls, respectively; P < 0.01). Information of the metals urine concentration and FEV1/FVC, FEF25%-75% of spirometry index were subjected to PLS analysis to predict oxidative stress biomarker. This model was capable of predicting the concentration of MDA with the regression of R2 = 0.91. Conclusions: PLS predicts the oxidative stress biomarker with an acceptable sensitivity. According to our research, we can assess the level of oxidative stress as the sign of multi-metal toxicity by following the common biomonitoring assessment. This method could be useful for further engineering control procedures.