Environmental exposure to multiple chemical elements in Peruvian populations: a review of selected studies
Bibliographic record
Abstract
Background Population-based exposure assessments for heavy metals and metalloids (by governmental and private institutions) are common in Peru, but most studies generally focus on the analysis of a single chemical element, like lead or mercury, and lack an appropriate reference regarding the health impact on the exposed population. The complex/mixed chemical interactions within the human body have not yet been studied for all long-term health effects. Methods We reviewed laboratory results from five studies, between 2005-2013, that analysed multiple elements (between 13 and 17 chemical elements in each study) in spot urine samples from Peruvian communities considered exposed and not exposed. All laboratory analysis were performed using inductively coupled plasma mass spectrometry (ICP-MS) at the Environmental Health Laboratory Division of the Centers for Disease Control and Prevention (CDC) of the United States. Results Six chemical elements (total arsenic, caesium, cobalt, lead, molybdenum, and thallium) were present in almost all spot urine samples (>98% of participants), evidencing exposure (qualitative assessment). Exposure to other chemical elements like barium, cadmium, tungsten, antimony and uranium, varied among localities, while chemical elements like beryllium and platinum were rarely detected (<3% and <10% of participants, respectively) in spot urine samples. Most geometric means of urine concentration for total arsenic, lead, cadmium and mercury are higher for the Peruvian locations than for national estimates in Canada and the United States, but not in all locations. Conclusion Comparing averages across different populations can be misleading but comparing periodic values from the same population in the future could evidence an exposure trend. Future studies are needed to develop reference levels for exposed Peruvian populations. This study highlights potential health risks from exposure to environmental chemical elements and can be the first step towards understanding and mitigating human exposure to heavy metals and metalloids for known exposed populations in Peru.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".