Background: Epidemiological studies about the effect of essential metal mixture on fasting plasma glucose (FPG) levels among elderly people are sparse. The object of this study was to examine the associations of single essential metals and essential metal mixture with FPG levels in Chinese community-dwelling elderly people.
Methods: The study recruited 2348 community-dwelling elderly people in total. Inductively coupled plasma-mass spectrometry was adopted to detect the levels of vanadium (V), selenium (Se), magnesium (Mg), cobalt (Co), calcium (Ca), and molybdenum (Mo) in urine. The relationships between single essential metals and essential metal mixture and FPG levels were evaluated by linear regression and Bayesian kernel machine regression (BKMR) models, respectively.
Results: In multiple-metal linear regression models, urine V and Mg were negatively related to the FPG levels (β = - 0.016, 95 % CI: - 0.030 to - 0.003 for V; β = - 0.021, 95 % CI: - 0.033 to - 0.009 for Mg), and urine Se was positively related to the FPG levels (β = 0.024, 95 % CI: 0.014-0.034). In BKMR model, the significant relationships of Se and Mg with the FPG levels were also found. The essential metal mixture was negatively associated with FPG levels in a dose-response pattern, and Mg had the maximum posterior inclusion probability (PIP) value (PIP = 1.0000), followed by Se (PIP = 0.9968). Besides, Co showed a significant association with decreased FPG levels in older adults without hyperlipemia and in women.
Conclusions: Both Mg and Se were associated with FPG levels, individually and as a mixture. The essential metal mixture displayed a linear dose-response relationship with reduced FPG levels, with Mg having the largest contribution to FPG levels, followed by Se. Further prospective investigations are necessary to validate these exploratory findings.
Keywords: Bayesian kernel machine regression; Elderly people; Essential metal mixture; Fasting blood glucose.
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