Mercury Exposure and Health Effects in Humans: A Systematic Review of Biomarker Evidence
Bibliographic record
Abstract
Mercury remains a long-lasting pollutant in the environment, known for its toxic effects on humans, especially from long-term exposure. This systematic review compiles recent findings on how mercury exposure affects human health, focusing on studies using biological markers. Research articles from 2000 to 2025 were retrieved from PubMed, Scopus, and Web of Science. Included studies were observational or experimental, involving human subjects with mercury detected in blood, hair, or urine, alongside health impact assessments. The review followed PRISMA standards, and risk of bias was evaluated using the Newcastle-Ottawa Scale. Out of all results, 40 studies met the criteria. Most showed increased health risks such as neurotoxic, kidney, and heart problems in people living near gold mining sites, industrial areas, or those frequently eating seafood. Blood and hair were the most used biomarkers. Sensitive groups like pregnant women and children showed greater vulnerability even at low exposure levels. Overall, mercury continues to pose a public health threat, highlighting the urgent need for stricter environmental policies and targeted protective actions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".