What is in the Caribbean Baby? Assessing Prenatal Exposures and Potential Health Outcomes to Environmental Contaminants in 10 Caribbean Countries
Bibliographic record
Abstract
OBJECTIVE: To assess prenatal exposures and potential health outcomes to environmental toxicants such as persistent organic pollutants (POPs), commonly used pesticides, and two heavy metals--mercury (Hg) and lead (Pb)--in 10 Caribbean countries. SUBJECTS AND METHODS: For each participating Caribbean island, approximately 50 maternal blood and urine samples were collected and analysed for POPs such as polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs), other common classes of pesticides used in the Caribbean such as organophosphates (OP), carbamates, chlorophenols and pyrethroids, and for Hg and Pb. Data obtained from the participating countries were compared with those from the United States of America and Canada. RESULTS: A total of 438 samples were analysed from 10 Caribbean countries. Persistent organic pollutants was detected in almost all samples, however, these were generally low compared with comparable North American results. Evidence of exposure to PBDEs, OPs, carbamates and chlorophenols was also established. Caribbean pyrethroid concentrations were generally much higher than those recorded for North American women. Caribbean Pb maternal blood levels were generally lower than in North America, whereas Hg blood levels were two to three times higher. In almost all of the samples taken in this study, exposures to multiple chemicals were taking place at the same time. CONCLUSIONS: This first Caribbean-wide exploratory biomonitoring study on the concentrations of several toxicants in maternal samples taken from 10 Caribbean countries clearly reinforces the need for Caribbean primary care physicians and other public health officials to encourage their patients, and in particular pregnant women, to reduce their exposures to these environmental contaminants as far as it is feasible to do so.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".