MERCURY EXPOSURE IN REMOTE FISH EATING POPULATIONS AND CARDIOVASCULAR RISK FACTORS
Bibliographic record
Abstract
Background and aims: More and more data suggest that the cardiovascular system should be considered a potential target for mercury. For example, work conducted in the Faeroe Islands in children and in Greenland suggests associations between mercury exposure and blood pressure and heart beat variability which are known risk factors for cardiac health. Other studies conducted in Europe suggest association between mercury and increase risk of myocardial infarction. Methods: We have studied three large remote fish eating communities in the Arctic, sub Arctic and South Pacific which are exposed to high doses of mercury (3 adults and 1 child cohorts) Mercury was measured in blood as well as potential confounding nutritional factors and Paraoxanase (PON) 1 activity. Heart Rate Variability (HRV) and blood pressure were also measured. Results: Mercury concentrations in blood averaged 86, 75, 49 and 81 nmol/L in adults from Nunavik, (Arctic Québec), French Polynesians, James Bay Crees Indians and Inuit newborn respectively. In most of these studies we found that mercury exposure was associated with decrease HRV and increase blood pressure. For example, in Inuit adults, we found that a 10 percent increase in blood mercury was associated with an increase of 0.2 mm Hg in systolic blood pressure after controlling for other factors. Concerning biomarkers, our results in Inuit adults suggest that in a multiple regression model adjusted for age, HDL-C, omega-3 fatty acids, and PON1 variants, blood mercury concentrations were negatively associated with PON1 activities [beta = -0.022, standard error (SE) = 0.005, p < 0.001), whereas blood selenium concentrations were positively associated with PON1 activities (beta = 0.024, SE = 0.004, p < 0.001). Conclusion: Since heart diseases represent the most important causes of death, even a slight negative impact on the cardiovascular system could be of greater public health relevance than any other health effects related to mercury exposure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".