Electronic waste exposure and DNA damage: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Inappropriate processing and disposal of electronic waste (e-waste) expose workers and surrounding populations to hazardous chemicals, including clastogens and aneugens. Recently, considerable literature has grown around e-waste recycling, associated chemical exposures and intermediate health outcomes, including DNA damage. Micronuclei (MN) frequency has been widely used as a biomarker to investigate DNA damage in human populations exposed to genotoxic agents. We conducted a systematic review of published studies to assess DNA damage in e-waste-exposed populations and performed a meta-analysis to evaluate the association between e-waste exposure and DNA damage. METHODS: This systematic review with meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement checklist. Articles published in English from January 2000 through December 2020 investigating the associations between e-waste exposure and DNA damage were retrieved from the following three major databases: MEDLINE, ProQuest, and Scopus. Studies that reported the use of MN assay as a biomarker of DNA damage were included for meta-analysis. Studies that also reported other DNA damage biomarkers such as chromosomal aberrations, comet assay biomarkers, 8-hydroxy-2'-deoxyguanosine (8-OHdG), telomere length, apoptosis rate were reported using narrative synthesis. RESULTS: A total of 20 publications were included in this review, of which seven studies were within the occupational setting, and the remaining 13 studies were ecological studies. The review found six biomarkers of DNA damage (micronuclei, comets assay parameters (tail length, % tail DNA, tail moment, and olive tail moment), 8-OHdG, telomere length, apoptosis rate and chromosomal aberrations) which were assessed using seven different biological matrices (buccal cells, blood, umbilical cord blood, placenta, urine and semen). Most studies showed elevated levels of DNA damage biomarkers among e-waste exposed populations than in control populations. The most commonly used biomarkers were micronuclei frequency (n=9) in peripheral blood lymphocytes or buccal cells and 8-OHdG (n=7) in urine. The results of the meta-analysis showed that electronic waste recycling has contributed to an increased risk of DNA damage measured using MN frequency with a pooled estimate of the standardized mean difference (SMD) of 2.30 (95% CI: 1.36, 3.24, p<0.001) based on 865 participants. CONCLUSIONS: Taken together, evidence from this systematic review with meta-analysis suggest that occupational and non-occupational exposure to e-waste processing is associated with increased risk of DNA damage measured through MN assay and other types of DNA damage biomarkers. However, more studies from other developing countries in Africa, Latin America, and South Asia are needed to confirm and increase these results' generalizability.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".