Evaluation of a Public Health Intervention to Lower Mercury Exposure from Fish Consumption in Bermuda
Bibliographic record
Abstract
OBJECTIVES: To assess the efficacy of a public health intervention to reduce blood mercury (Hg) concentration levels in pregnant Bermudian women. METHODS: In 2003, we conducted a study entitled "Prenatal exposure of the Bermudian Population to Environmental Contaminants" which provided Bermuda's first baseline data on prenatal exposure to several environmental contaminants, including Hg. The mean Hg concentration from 42 healthy newborns measured in umbilical cord blood was 41.3 nmol/L, ranging from 5-160 nmol/L. This concentration was much higher than expected, being approximately 8 times the general levels found in Canada and the U.S. Furthermore, we estimated that 85% of total Hg measured was in the form of methylmercury (MeHg), indicating that seafood consumption was the primary source of Hg exposure during pregnancy in Bermuda. Locally sourced seafood was identified as the most significant possible contributory source of Hg exposure. In 2005 the authors began a complementary research programme to study the levels of Hg in local commercial fish species. Coming out of this research were specific local fish consumption guidelines issued by the Department of Health advising pregnant women to avoid those local fish species found to be high in Hg while still encouraging consumption of fish species having lower Hg levels. RESULTS: In 2010, under another research initiative, we returned to Bermuda to carry out another evaluation of Hg in human blood. Hg was measured in the blood of 49 pregnant women. The arithmetic mean Hg blood concentration was 6.6 nmol/L and the geometric mean 4.2 nmol/L. The maximum concentration found was 24 nmol/L. CONCLUSIONS: Hg exposure of Bermudian pregnant women has dropped significantly by a factor of around 5 since the foetal cord blood study in 2003.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".