Metal Concentrations in Newcomer Women and Environmental Exposures: A Scoping Review
Bibliographic record
Abstract
Newcomer women from developing countries are recognized to be at risk for elevated exposures to environmental contaminants and associated negative health effects. As such, data on exposure sources and contaminant body burden concentrations is critical in the development of effective public health policies and interventions in support of newcomer health. We conducted a scoping review to gather evidence on important toxic metals of health concern, lead (Pb), mercury (Hg) and cadmium (Cd), and their concentrations and potential exposure sources among newcomer women. An initial 420 articles were identified through the databases MEDLINE, EMBASE and Scopus, many reporting by ethnicity rather than newcomer/immigrant status. Several articles reported metal concentrations for other biomarkers but did not include blood, nor stratify results. From the remainder, we selected a total of 10 articles for full textual review, which reported blood Pb, Hg or Cd levels for newcomer women and/or stratified blood metal results according to foreign birth or country of origin. Three of the articles reported higher Pb, Hg and Cd concentrations in newcomer women compared to their native-borne counterparts. Exposures identified as contributing to elevated Pb, Hg and Cd blood concentrations included: pica behaviour, the use of lead-glazed cookware or eye cosmetics, and fish/shellfish consumption. The review revealed a limited availability of data on metal body burden concentrations, exposure sources and routes among newcomer women specifically. More research is needed to better understand the extent to which newcomer women are disproportionately at risk of elevated metal exposures due to either country of origin or current exposures and to inform relevant, multi-national risk management strategies.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".