The association between whole blood mercury and the risk of developing CVD among the Greenlandic population
Bibliographic record
Abstract
Introduction: The World Health Organization, estimated that 17.5 million people died from cardiovascular disease (CVD) in 2012 alone, accounting for 30% of global deaths and serving as the number one cause of death globally. Environmental pollutants, such as heavy metals (e.g. mercury) and persistent organic pollutants (POPs) (e.g. polychlorinated biphenyl (PCBs), may contribute to the burden of CVD, especially within the Arctic. The highest levels of whole blood mercury have been found in Greenland.\n\nObjective: To explore the association between whole blood mercury and the risk of developing CVD among the Greenlandic population. \n\nMethods: The continuous effects of whole blood mercury levels of incident CVD were investigated, among 3083 participants, from the population-based cohort study ‘Inuit Health in Transition Greenland survey 2005-2010’ using cox regression. Both univariate and multivariate analyses were conducted, adjusting for a range of potential confounders. Whole blood mercury was measured at inclusion. Participants were followed in the National Patient registries for Denmark and Greenland and in the cause of death register for CVD events. The overall incidence rates and the hazard ratio of CVD events among participants for overall CVD were calculated. Potential interactions with sex were also investigated.\n\nResults: The highest levels of whole blood mercury were found in men, who had a significantly higher median level of 19 μg/L, compared with women (15 μg/L (p<0.001)). The crude hazard ratio (HR) for developing overall CVD was 0.99 (95% CI 0.99-1.00) for any given level of whole blood mercury. After adjusting for several potential confounders, the HR remained 0.99 (95% CI 0.98-1.00). \n\nConclusion: The present study found no association between whole blood mercury and the risk of developing CVD among the Greenlandic population. Furture research on mercury should investigate genetic susceptibility of mercury among the Greenlandic population, as susceptibility to mercury, may be increased by genetic factors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".