Overview
Community-based cross-sectional study measuring plasma concentrations of 20 metals in 1,312 Chinese adults, examining associations between single and combined metal exposure with serum uric acid levels and hyperuricemia (serum uric acid above 420 umol/L in men or 360 umol/L in women). The analysis used generalized linear regression, BKMR, WQS, and quantile g-computation. A mediation analysis quantified the contribution of insulin resistance (measured by the triglyceride-glucose index) to the metal-hyperuricemia pathway, and a benchmark dose model estimated the BMDL for selenium.
Key numbers
n=1,312 adults. 20 plasma metals measured.
Mixture findings:
- All three mixture models (BKMR, WQS, quantile g-computation) consistently identified selenium as the key contributor to hyperuricemia in the metal mixture.
- Selenium was positively associated with serum uric acid (beta=0.18, 95% CI: 0.04, 0.32) and hyperuricemia (OR=1.51, 95% CI: 1.08, 2.11) in single-pollutant models.
- Triglyceride-glucose index mediated the selenium-hyperuricemia association, indicating that the pathway runs at least partially through insulin resistance.
- BMDL for selenium in relation to hyperuricemia risk was calculated.
This paper illustrates that an essential element (selenium) can dominate a metal mixture’s association with a specific metabolic outcome, and that the mixture effect is not attributable to the toxic metals alone.
Evidence Fitness
Context only. Cross-sectional design; temporality not established. Plasma metals reflect recent exposure; dietary sources not disaggregated. The finding that selenium drives the mixture association with hyperuricemia through an insulin-resistance pathway has implications for interpreting multi-metal studies but does not constitute food contamination data.
Methods (brief)
Community-based cross-sectional study. Plasma metals by ICP-MS. Serum uric acid measured enzymatically. TyG index calculated as ln(triglycerides in mg/dL times fasting glucose in mg/dL divided by 2). Hyperuricemia defined as SUA above 420 umol/L in men or 360 umol/L in women. GLM, BKMR, WQS, and quantile g-computation analyses. Benchmark dose modeling for selenium.
Implications
Certification: Demonstrates that selenium status interacts with metal mixture endpoints; relevant to the interpretation of selenium as a potentially protective or harmful element depending on context and outcome.
Courses: Useful case study showing that essential elements can be the dominant term in a mixture model, complicating the standard “toxic metals cause harm” narrative.
App: No food concentration data.
Microbiome: Potential insulin-resistance-gut axis crosswalk; not primary focus.
Related evidence
- Selenium
- Single-metal regulatory limits systematically underprotect against dietary heavy-metal exposure
Update history
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