Journal Article
Co-exposure of serum calcium, selenium and vanadium is nonlinearly associated with increased risk of type 2 diabetes mellitus in a Chinese population
Lv, Y; Xie, L; Dong, C; Yang, R; Long, T; Yang, H; Chen, L; Zhang, L; Chen, X; Luo, X; Huang, S; Yang, X; Lin, R; Zhang, H
Chemosphere
ISSN: 0045-6535
EISSN: 1879-1298
BACKGROUND: Metals play an important role in type 2 diabetes mellitus (T2DM). This study aimed to explore the association of T2DM risk with single metal exposure and multi-metal co-exposure.
METHODS: A case-control study with 223 T2DM patients and 302 controls was conducted. Serum concentrations of 19 metals were determined by inductively coupled plasma mass spectrometry (ICP-MS). Those metals with greater effects were screened out and co-exposure effects of metals were assessed by least absolute shrinkage and selection operator (LASSO) regression.
RESULTS: Serum calcium (Ca), selenium (Se) and vanadium (V) were found with greater effects. Higher levels of Ca and Se were associated with increased T2DM risk (OR = 2.23, 95%CI: 1.38-3.62, Ptrend = 0.002; OR = 3.16, 95%CI: 1.82-5.50, Ptrend < 0.001), but higher V level was associated with decreased T2DM risk (OR = 0.58, 95%CI: 0.34-0.97, Ptrend < 0.001). Serum Ca and V concentrations were nonlinearly associated with T2DM risk (Poverall < 0.001, Pnonliearity < 0.001); however, Se concentration was linearly associated with T2DM risk (Poverall < 0.001, Pnonliearity = 0.389). High co-exposure score of serum Ca, Se and V was associated with increased T2DM risk (OR = 3.50, 95%CI: 2.08-5.89, Ptrend < 0.001) as a non-linear relationship (Poverall < 0.001, Pnonliearity = 0.003).
CONCLUSIONS: This study suggest that higher levels of serum Ca and Se were associated with increased T2DM risk, but higher serum V level was associated with decreased T2DM risk. Moreover, co-exposure of serum Ca, Se and V was nonlinearly associated with T2DM risk, and high co-exposure score was positively associated with T2DM risk.
metal co-exposure; LASSO regression; restricted cubic splines regression; nonlinear relationship; type 2 diabetes mellitus
