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Exposure to heavy metals and trace elements and risk of dyslipidemia: a nested case-control analysis in rural adults

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Overview

Nested case-control study within a cohort from rural Ningxia, China (782 participants: 391 dyslipidemia cases, 391 controls at 1:1 matching). Serum concentrations of 15 trace metals measured by ICP-AES. Conditional logistic regression, BKMR, and WQS regression used to examine associations between individual and combined metal exposures and dyslipidemia.

Dyslipidemia was defined following the 2016 Chinese Guidelines for Prevention and Treatment of Dyslipidemia in Adults: total cholesterol at least 6.22 mmol/L (high TC), triglycerides at least 2.26 mmol/L (high TG), or HDL-C below 1.04 mmol/L (low HDL).

Key numbers

n=782 (391 cases, 391 matched controls).

Single-metal associations (conditional logistic regression, fully adjusted):

  • Lithium (Li): OR=0.654 (95% CI: 0.436, 0.981); negative association with dyslipidemia.
  • Tin (Sn): OR=0.800 (95% CI: 0.649, 0.985); negative association with dyslipidemia.
  • Other metals: no significant individual associations reported.

Mixture findings:

  • BKMR: lithium exhibited a negative correlation with dyslipidemia across the entire exposure range.
  • Interactions identified in BKMR: between lithium and nickel, between tin and manganese, and between nickel and manganese.
  • WQS: overall metal mixture effect was not statistically significant; lithium (7.6%) and tin (16.8%) accounted for the dominant weights in the negative direction.

Evidence Fitness

Context only. Nested case-control design is stronger than pure cross-sectional for temporality (cases and controls drawn from a prospective cohort), but serum metal measurements at enrollment may not reflect long-term exposure. The finding that lithium and tin are negatively associated with dyslipidemia, and that the mixture effect is not significant overall, distinguishes this paper from studies finding positive mixture-harm associations. The identified interactions (lithium-nickel, tin-manganese, nickel-manganese) represent statistical interactions in BKMR and require independent replication.

Methods (brief)

Nested case-control from Ningxia cohort. Serum metals by ICP-AES (15 metals: B, V, chromium (Cr), Mn, nickel (Ni), arsenic (As), Se, Sr, Mo, cadmium (Cd), Cs, Ba, Tl, lead (Pb), Li, Sn, Mg, Fe, Cu, Zn measured with four standard curves spanning 0.05-20 ug/L). Conditional logistic regression; BKMR; WQS.

Implications

Certification: The finding that essential and trace metals (lithium, tin) are protective for dyslipidemia in this population highlights that metal mixture effects on metabolic outcomes are not uniformly harmful, and that the net mixture direction depends on which metals are present and at what levels.

Courses: Useful case study for mixture effects that go in protective rather than harmful directions.

App: No food concentration data.

Microbiome: Not applicable.

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