Human semen quality and environmental and occupational exposure to pollutants: A systematic review.
Bibliographic record
Abstract
Background: The aim of the present systematic review was to evaluate the correlation between the exposure to environmental and/or occupational pollutants and possible alteration of semen quality, focalizing the attention on the studies performed using a biomonitoring approach. Methods: The review was conducted from inception to May 11 2023, according to the PRISMA Statement 2020 and using the following databases: Scopus, Pubmed and Web of Science. The protocol was registered on PROSPERO (CRD42023405607). Studies were considered eligible if they reported data about the association between exposure to environmental pollutants and alteration of semen quality using human biomonitoring. The quality assessment was carried out by the use of the Newcastle-Ottawa Quality Assessment Scale. Results: In total, 21 articles were included, conducted in several countries. The main matrices used for biomonitoring were urine and blood and the most sought-after contaminants were bisphenols, phthalates, pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, heavy metals and other inorganic trace elements. The results of the studies demonstrated a significant positive correlation between the increase of the pollutants' levels in the biological matrices examined and some alterations of the semen quality indicators, such as a decrease in motility, concentration and morphology of the spermatozoa. Conclusions: Male fertility can be negatively affected by the exposure to environmental and/or occupational pollutants. Human biomonitoring programs may be considered a useful tool for specific surveillance programs devoted to early highlight subjects who are more exposed to environmental pollutants in order to reduce risk exposure.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".