Sex‐specific and dose‐response relationships of urinary cobalt and molybdenum levels with glucose levels and insulin resistance in U.S. adults

Journal of Environmental Sciences(2023)

Cited 11|Views23
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Abstract
Growing studies have linked metal exposure to diabetes risk. However, these studies had inconsistent results. We used a multiple linear regression model to investigate the sex-specific and dose-response associations between urinary metals (cobalt (Co) and molybdenum (Mo)) and diabetes-related indicators (fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), homeostasis model assessment for insulin resistance (HOMA-IR), and insulin) in a cross-sectional study based on the United States National Health and Nutrition Examination Survey. The urinary metal concentrations of 1423 eligible individuals were stratified on the basis of the quartile distribution. Our results showed that the urinary Co level in males at the fourth quartile (Q4) was strongly correlated with increased FPG (β = 0.61, 95% CI: 0.17–1.04), HbA1c (β = 0.31, 95% CI: 0.09–0.54), insulin (β = 8.18, 95% CI: 2.84–13.52), and HOMA–IR (β = 3.42, 95% CI: 1.40–5.44) when compared with first quartile (Q1). High urinary Mo levels (Q4 vs. Q1) were associated with elevated FPG (β = 0.46, 95% CI: 0.17–0.75) and HbA1c (β = 0.27, 95% CI: 0.11–0.42) in the overall population. Positive linear dose-response associations were observed between urinary Co and insulin (Pnonlinear = 0.513) and HOMA–IR (Pnonlinear = 0.736) in males, as well as a positive linear dose-response relationship between urinary Mo and FPG (Pnonlinear = 0.826) and HbA1c (Pnonlinear = 0.376) in the overall population. Significant sex-specific and dose-response relationships were observed between urinary metals (Co and Mo) and diabetes-related indicators, and the potential mechanisms should be further investigated.
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Key words
Bayesian kernel machine regression,Cobalt,Diabetes,Insulin resistance,Molybdenum
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