Characterizing variability in total mercury hair:blood ratio in the general Canadian population
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: The body burden of mercury in humans can be measured through hair or blood biomarkers. To compare results from different studies, it is often required to convert mercury in hair to an equivalent level in blood, using a default hair:blood ratio of 250:1 by the World Health Organization (WHO). However, the actual ratio may vary within and between populations. The objectives of this study were to analyze the hair:blood mercury ratio in the general Canadian population, explore factors associated with higher/lower ratios, and determine if the standard ratio of 250:1 is supported. METHODS: The Canadian Health Measures Survey (CHMS) Cycle 5 (2016-2017) measured total mercury (THg) in both hair and blood of 1168 participants 20-59 years of age. We calculated geometric mean (GM) concentrations of THg for this entire sample and subgroups. The subgroups included biological sex, women of childbearing age, race, hair treatments, categories of blood and hair selenium, urinary arsenobetaine/arsenocholine, categories of blood and hair mercury, and food consumption. We calculated a hair:blood ratio for each participant and determined population-level ratios from the GMs of the distributions. Differences by subgroups, and agreement with the WHO ratio of 250:1, were tested. The combined effect of factors on the THg hair:blood ratio was explored using staged regression analysis. RESULTS: For participants with paired hair and blood mercury measurements, the GM of the hair:blood THg ratio was 293 (95%CI:273-316), and significantly >250. In women of childbearing age, the ratio did not differ from 250. The GMs of the ratio were higher (i.e.>300) for second tertile blood selenium (365, 95%CI:307-433), third and fourth quartiles hair mercury (347, 95%CI:308-390 and 376, 95%CI:336-422), and consumers of shellfish (338, 95%CI:308-371). Shellfish consumption was the only statistically significant factor associated with the hair:blood ratio as identified in the regression model. CONCLUSIONS: The mean hair:blood THg ratio among Canadians generally exceeded the default ratio of 250:1. Higher ratios were observed in certain subgroups, such as seafood consumers, and shellfish consumption was the most important variable associated with the ratio. Our results suggest that population-specific hair:blood THg ratios be considered, if possible, when converting mercury levels from hair to blood to better characterize the variation around the conversion.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".