Early life lead exposure as a risk factor for aggressive and violent behaviour in young adults: A systematic review
Bibliographic record
Abstract
This review was aimed at synthesising individual level evidence on the association between early life lead exposure and aggressive or violent behaviours in young adults. We conducted comprehensive searches in 17 electronic databases between September 19th and October 30th, 2019 and updated September 1st, 2024 using PubMed and Scopus databases. Two reviewers independently screened all records and full texts, extracted data from included studies, and assessed risk of bias using the Newcastle Ottawa tool. Results were pooled by random effects meta-analysis. Relevant subgroup and sensitivity analyses were carried out. Six out of 2874 studies were found eligible. All were conducted in high income countries. The definition of violence varied across studies. Blood lead level was associated with an increased risk of arrest or conviction for violent crime with a pooled OR of 1.17 for each 5 μg/dl rise (95 % CI: 1.10–1.23). There was insufficient data to conduct a dose response meta-analysis. Despite some heterogeneity, studies consistently reported an association between lead exposure in childhood and violent behaviour in young adulthood. Better reported studies, particularly from lower resourced settings, are needed to confirm these results. Environmental lead control may help to reduce aggressive and violent behaviour in young adults. • Systematic review of lead exposure in childhood and violent behaviour in young adults • Lead exposure in childhood is associated with violent behaviour in young adults. • Environmental lead control may help to reduce aggressive and violent behaviour. • More high-quality studies are required from lower resourced settings.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".