ArticleBiological trace element research2026
Association Between Metal Mixtures and C-Reactive Protein Levels: A Study Based on Occupational Populations in China.
Article in Biological trace element research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This study aimed to systematically investigate the relationship between mixed heavy metal exposure and serum C-reactive protein (CRP) level using an integrated multi-model statistical strategy. This study included 568 participants from the Manganese-Exposed Workers Healthy Cohort. Serum CRP and 20 blood metal concentrations were measured. Key metals were selected via LASSO regression and overall mixture effects and metal contributions were quantified by Quantile g-computation; and joint effects, nonlinearity, and interactions were evaluated using Bayesian Kernel Machine Regression (BKMR). LASSO regression identified 9 key metals (Calcium, Nickel, Copper, Titanium, Tin, Vanadium, Selenium, Arsenic, Rubidium). GLM revealed inverse linear associations for Ca, Se, Rb, and Ni, and a positive association for Cu with CRP. Quantile g-computation showed the overall mixture was significantly inversely associated with CRP (HR = 0.955, 95% CI: 0.918, 0.996), with calcium contributing the largest negative weight (-0.31). BKMR indicated that the overall mixture effect showed a monotonic decreasing trend across exposure quantiles, with a significant positive association at lower quantiles (0.25-0.5). BKMR also identified a significant positive interaction for tin (posterior mean = 0.051, 95% CI: 0.004, 0.098), with calcium showing the highest posterior inclusion probability (PIP = 0.972). This study suggests that metal mixtures exert exposure-level-dependent effects on CRP with complex interactions. Calcium may act as a central regulator, while tin shows amplified effects at higher co-exposure levels. These findings advance mechanistic understanding of mixture toxicology and inform exposure-level-specific risk assessment.
Indexed as
Identifiers
42521926What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.