Environmental exposure to microplastics: a scoping review on human health effects
Bibliographic record
Abstract
Background: Microplastics are omnipresent environmental contaminants leading to unavoidable human exposure. However, little is known about the health effects of microplastics exposure on humans. This review explored the existing evidence for the potential adverse effects of microplastics and research gaps. Methods: An electronic search of published articles was conducted in PubMed, Scopus, EMBASE, Cochrane databases, and Google Scholar using a combination of subject heading and text word terms for microplastics and human health effects with specific inclusion and exclusion criteria. Letters, comments or notes, conference abstracts, and editorials were excluded. Additional keywords were developed after the preliminary screening to incorporate relevant articles. Google Scholar search, followed by a focused search, was performed to gather grey literature. The initial search resulted in 16,983 and 23 published articles and grey literature, respectively. A total of 4,817 unique citations were retrieved after filtering out duplicates. The title and abstract screening process resulted in 119 articles. After full article review and investigating their references, 63 articles were finalized. Every document was reviewed by at least two of the researchers. Results: Literature has reported that exposure to microplastics might occur through ingestion, inhalation, and dermal contact due to its presence in foods, air, and consumer products. Microplastics exposure might cause particle toxicity through oxidative stress, inflammatory lesions, and increased uptake or translocation. Failure of the immune system to eliminate synthetic particles might lead to chronic inflammation and increase cancer risk. Moreover, microplastics have been found to release their constituents, pathogenic organisms, and adsorbed contaminants. Conclusion: Knowledge regarding microplastic toxicity is still limited and primarily influenced by exposure concentration, particle components, adsorbed contaminants, organs involved, and individual susceptibility. Further research is warranted to understand the risk of human health due to exposure to microplastics, which requires human exposure assessment, understanding of pathogenesis, and quantifying the effects.
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 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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".