Abstract 4354457: Environmental Toxic Metal Exposure and Change in the Cardiac Biomarkers among US adults from 2015-2023: A Trend and Mixture Approach
Bibliographic record
Abstract
Background: Toxic metal exposure is a growing public health concern due to its potential long-term effects on cardiovascular health. However, limited studies have evaluated the cumulative effects of metal mixtures on cardiac biomarkers in a nationally representative population. Objective: To examine the association between exposure to a mixture of environmental toxic metals and changes in cardiac biomarkers C-reactive protein (CRP), high-density lipoprotein (HDL), and total cholesterol (TC) among US adults. Methods: Data are obtained from three pooled survey data from the National Health and Nutrition Examination Survey (NHANES) 2015–2023, comprising 21730 adult participants. Cardiac biomarkers include CRP, HDL, and TC. Exposure variables consist of blood levels of lead, cadmium, mercury, manganese, and selenium. Weighted Quantile Sum (WQS) regression is used to estimate the effect of metal mixtures on cardiac biomarkers. Trend analysis is performed across NHANES cycles using survey-weighted generalized linear models. Results: The study population has a mean age of 42.1 years (SD: 20.9). Among cardiac biomarkers, the weighted mean (SD) of CRP is 3.46 mg/L (7.06), HDL is 53.95 mg/dL (15.40), and total cholesterol (TC) is 182.64 mg/dL (41.26). For toxic metal exposures, mean levels are lead 0.94 µg/dL (SD: 1.06), cadmium 0.36 µg/L (SD: 0.47), mercury 1.12 µg/L (SD: 1.82), manganese 9.90 µg/L (SD: 3.64), and selenium 2.35 µg/L (SD: 0.35). Trend analysis shows a statistically significant increase in CRP levels over time (p = 0.002), while HDL and TC showed no significant trends (p > 0.45). In multivariable WQS models, toxic metal mixture exposure is significantly associated with all three cardiac biomarker changes. Specifically, a per-quantile increase in toxic metal mixture is associated with a 6.57% (4.00% - 9.20%) increase in CRP levels, a 3.17% (2.47% - 3.87%) increase in HDL, and a 7.01% (6.37% - 7.65%) increase in total cholesterol. Manganese (64.9%) and cadmium (32.2%) have a high contribution in CRP, while lead and mercury primarily influence HDL and TC. Conclusions: Exposure to mixtures of toxic metals is significantly associated with increases in key cardiac biomarkers, including CRP, HDL, and TC. These findings suggest that even low-level environmental exposure may have cumulative effects on cardiovascular health over time. Further studies should focus on longitudinal studies to reduce environmental metal exposure in vulnerable populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".