Blood metals and vitamin D status in a pregnancy cohort: A bidirectional biomarker analysis
Bibliographic record
Abstract
Low 25-hydroxyvitamin D (25OHD), a biomarker of vitamin D status, is associated with reduced immune function and adverse pregnancy outcomes, such as preterm birth. Observational studies indicate that long-term, high level exposure to metals such as cadmium (Cd) and lead (Pb) can impact a person's vitamin D status. However, the directionality of the association is uncertain, particularly for low-level exposures. We used three distinct longitudinal data analysis methods to investigate cross-sectional, longitudinal and bidirectional relationships of Cd and Pb biomarkers with 25-hydroxyvitamin D (25OHD) in a Canadian pregnancy cohort. Maternal whole blood Cd and Pb and plasma 25OHD concentrations were measured in the 1st (n = 1905) and 3rd (n = 1649) trimester and at delivery (25OHD only, n = 1542). Our multivariable linear regression analysis showed weak inverse associations between Cd and 25OHD concentrations cross-sectionally and longitudinally while the latent growth curve models showed weak associations with Pb on the 25OHD intercept. In the bidirectional analysis, using cross lagged panel models, we found no association between 1st trimester metals and 3rd trimester 25OHD. Instead, 1st trimester 25OHD was associated with 9% (-15%, -3%) lower 3rd trimester Cd and 3% (-7, 0.1%) lower Pb. These findings suggest the 25OHD may modify metal concentrations in pregnancy and demonstrates the value of controlling for contemporaneous effects and the persistence of a biomarker over time, in order to rule out reverse causation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".