Total, methyl and inorganic mercury concentrations in blood and environmental exposure sources in newcomer women in Toronto, Canada
Bibliographic record
Abstract
Measurements of total blood Hg (tHg), often used as a proxy for methyl Hg (MeHg) concentrations, are most commonly the focus of population-based studies. Data on Hg species in biomarkers can allow for a more nuanced characterization of environmental exposure sources and risk but their availability is limited, especially for newcomer populations. The purpose of the Metals in Newcomer Women (MNW) study was to address existing data gaps on metal concentrations and exposure sources in newcomer women (19-45 years) and to examine tHg, MeHg and inorganic Hg (iHg) in the blood of East and South Asian women recently arrived to Toronto. Study participants were recruited in 2015 (n = 211). Total Hg concentrations were determined using both ICP-Q-MS and isotope dilution (ID)-SPME-GC-ICP-MS. A sample subset (n = 76) was chosen for the analysis of blood MeHg and iHg concentrations (also using ID-SPME-GC-ICP-MS). Hierarchical regression models were used to assess associations between blood tHg concentrations and environmental exposure factors for MNW participants. For the sample subset, a log-linear model was used to examine associations between blood iHg and MeHg concentrations and fish consumption patterns. The geometric mean (GM) blood tHg concentration was 1.05 µg/L (95% CI: 0.88-1.25), which was elevated compared to Canadian-born women (GM: 0.57 µg/L; 95% CI: 0.49-0.66), in a specialized data analysis of the Canadian Health Measures Survey (CHMS). GM concentrations for iHg and MeHg were 0.21 µg/L (95% CI: 0.16-0.28) and 2.66 µg/L (95% CI: 2.00-3.55), respectively. Significant distal determinants associated with blood tHg concentrations were: level of educational attainment, having lived in a coastal/fishing community prior to arrival, and global region of origin. Use of iron supplements and consumption of higher mercury fish species were also associated with tHg concentrations in the fully adjusted model. The study results demonstrate that blood Hg concentrations in newcomer women are slightly elevated, with some individuals in exceedance of recommended concentrations for women of reproductive age. The consumption of fish species low in Hg is recommended for newcomer women, especially those who consume fish frequently.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".