Complex contaminant mixtures and their associations with intima-media thickness
Bibliographic record
Abstract
<p><strong>Background</strong></p> <p>The burden of cardiovascular disease (CVD) morbidity and mortality is higher among Indigenous persons, who also experience greater health disparities when compared to non-Indigenous Canadians, particularly in remote regions of Canada. Assessment of carotid intima-media thickness (cIMT), a noninvasive screening tool and can be used as biomarker to assess increased CVD risk. Few studies have examined environmental contaminant body burden and its association with cIMT.</p> <p><strong>Methods</strong></p> <p>Data from the Environment-and-Health Study in the <em>Eeyou Istchee</em> territory of northern Québec, Canada was used to assess complex body burden mixtures of POPs, metals and metalloids among (<em>n</em> = 535) Indigenous people between 15 and 87 years of age with cIMT. First, Principal Component Analysis (PCA) was used to reduce the complexity of the contaminant data. Second, based on the underlying PCA profiles from the biological data, we examined each of the prominent principal component (PC) axes on cIMT using multivariable linear regression models. Lastly, based on these PC axes, cIMT was also regressed on summed (Σ) organic compound concentrations, polychlorinated biphenyl, perfluorinated compounds, respectively, ∑10 OCs, ∑13 PCBs, ∑3PFCs, and nickel.</p> <p><strong>Results</strong></p> <p>Most organochlorines and PFCs loaded primarily on PC-1 (53% variation). Nickel, selenium, and cadmium were found to load on PC-5. Carotid-IMT was significantly associated with PC-1 <em>β</em> = 0.004 (95 % <em>CI</em> 0.001, 0.007), and PC-5 <em>β</em> = 0.013 (95 % <em>CI</em> 0.002, 0.023). However, the association appears to be greater for PC-5, accounting for 3% of the variation, and mostly represented by nickel. Results show that that both nickel, and ∑3PFCs were similarly associated with cIMT <em>β</em> = 0.001 (95 % <em>CI</em> 0.0003, 0.003), and <em>β</em> = 0.001 (95 % <em>CI</em> 0.0004, 0.002), respectively. But ∑10OCs was significantly associated with a slightly greater <em>β</em> = 0.004 (95 % <em>CI</em> 0.001, 0.007) cIMT change, though with less precision. Lastly, ∑13PCBs also increased <em>β</em> = 0.002 (95 % <em>CI</em> 0.0004, 0.003) cIMT after fully adjusting for covariates.</p> <p><strong>Conclusion</strong></p> <p>Our results suggest that environmental contaminants are associated with cIMT. This is important for the Cree from the <em>Eeyou Istchee</em> territory who may experience higher body burdens of contaminants than non-Indigenous Canadians.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".