Association of urinary metals levels with type 2 diabetes risk in coke oven workers

Studies indicated that occupationally exposed to metals could result in oxidative damage and inflammation and increase cardiovascular diseases risk. However, epidemiological studies about the associations of metals exposure with diabetes risk among coke oven workers were limited.

This study aims to investigate the potential associations of 23 metals levels with the risk of diabetes among coke oven workers.

The analysis was conducted in a cross-sectional study including 1493 participants. Urinary metals and urinary polycyclic aromatic hydrocarbons (PAHs) metabolites levels were determined by inductively coupled plasma mass spectrometer and gas chromatograph-mass spectrometer respectively. Multivariate logistic regression was used to investigate the associations of urinary metal levels with diabetes risk with adjustment for potential confounding factors including gender, age, BMI, education, smoking, drinking, physical activity, hypertension, hyperlipidemia and urinary PAHs metabolites levels.

Compared with the normoglycemia group, the levels of urinary copper, zinc, arsenic, selenium, molybdenum, and cadmium were significantly higher in the diabetes group (all p < 0.05). Participants with the highest tertile of urinary copper and zinc had 2.12 (95%CI: 1.12-4.01) and 5.43 (95%CI: 2.61-11.30) fold risk of diabetes. Similar results were found for hyperglycemia risk. Besides, participants with the highest tertile of manganese, barium, and lead had 1.65(1.22-2.23), 1.60(1.19-2.16) and 1.45(1.05-1.99) fold risk of hyperglycemia when compared with the lowest tertlie.

The results indicated that the urinary copper and zinc levels were positively associated with the risk of diabetes and hyperglycemia among coke oven workers. Urinary manganese, barium and lead levels were also associated with increased risk of hyperglycemia independently of other traditional risk factors. These findings need further validation in prospective study with larger sample size.