Relationship between gestational diabetes and serum trace element levels in pregnant women from Eastern Iran: a multivariate approach

The prevalence of gestational diabetes mellitus (GDM) has increased over the recent decades. Exposure to environmental contaminants may be a risk factor for the development of GDM, but this is heavily dependent on particular circumstances. Studies on various areas linking various factors are therefore needed. We examined the associations between serum trace element levels and incidents of GDM among 102 pregnant women (diabetic n = 60 and healthy n = 42) living in Birjand (Iran). Blood serum samples were analyzed for concentrations of elements linked to particulate matter air pollution such as As, Cd, Cu, Hg, Mn, Ni, V, and Zn. Concentrations of As (8.58 vs. 3.15 mu g/L), Cd (6.74 vs. 0.52 mu g/L), and Hg (2.60 vs. 0.90 mu g/L) were significantly higher in women with GDM. Risk difference (RD) estimation showed that As, 0.516 (0.355, 0.677); Cd, 0.719 (0.534, 0.904); and Hg, 0.505 (0.276, 0.735) increase GDM probability, while V lower that risk, -0.139 (-0.237, -0.042). With the principal component analysis, we were able to separate subjects according to their GDM status based on element levels. Such classification revealed very high efficiency with a true positive rate of 93%, according to linear discriminant analysis. GDM subjects presented higher levels of As, Cd, and Hg, indicating that these elements may disturb insulin metabolism and promote the development of GDM. Therefore, we conclude that systematic monitoring of trace elements followed by multivariate modeling in women planning pregnancy should be carried out to prevent the development of GDM.

Automated summary

The study found that concentrations of arsenic, cadmium, and mercury in pregnant women are associated with the incidence of GDM, while intake of vanadium helps reduce the probability of GDM. Classification based on element levels can effectively differentiate between GDM patients and healthy individuals, suggesting that systematic monitoring of trace elements and multivariate modeling can help prevent the development of GDM.