Descriptive analysis of whole blood concentrations of toxic, essential, and trace elements in adult females from the MIREC-ENDO study
Bibliographic record
Abstract
BACKGROUND: Exposure to toxic elements and deficiencies/excessive exposure to essential elements is associated with adverse health effects. Robust biomonitoring data exist for select elements in the general population of Canada, but data are limited for several essential/trace elements, especially among females approaching menopause, a critical and understudied life stage. OBJECTIVE: To describe whole blood concentrations of toxic, essential, and trace elements in females enrolled in a 2018-2021 follow-up of the Canadian Maternal-Infant Research on Environmental Chemicals cohort, and examine differences in concentrations by sociodemographic and obstetrical history characteristics. METHODS: We analyzed whole blood samples (n = 288) for concentrations of 21 elements. For 14 elements with >50% detection, we calculated Spearman correlations and compared geometric means across strata of participant characteristics. RESULTS: Element concentrations were similar or lower than reported for similarly aged females in Canada. Participants seemed to have adequate concentrations of essential elements except for zinc, where most were below the proposed zinc adequacy biomonitoring equivalent (6017 μg/L whole blood). The strongest correlations (ρ = 0.41-0.63) were observed between toxic elements which may share exposure sources (mercury/arsenic), and essential elements associated with blood cell production/function (iron/cobalt/copper/zinc/manganese/selenium). Participants' geometric mean element concentrations were generally 1.1-2.0 times higher among peri-/post-menopausal participants (lead), those with unknown menopausal status (iron), older participants (cadmium), younger participants (iron, beryllium), smokers (lead, cadmium), non-smokers (selenium), lower BMI (lead, mercury, arsenic, cesium), higher BMI (manganese, copper), higher household income (nickel), and higher education (mercury, arsenic, cesium). CONCLUSIONS: We provide important biomonitoring data for elements among adult females approaching the menopausal transition.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".