Prenatal and childhood exposures to heavy metals and their associations with child cognition, motor skills, behaviour and mental health
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Exposure to arsenic (As), cadmium (Cd), lead (Pb) and mercury (Hg), prenatally and in childhood could pose a significant risk to children's neurodevelopmental outcomes. A mini-review synthesized the findings of original peer-reviewed prospective cohort studies that investigated associations between prenatal and/or childhood exposure to As, Cd, Pb and Hg and chemical mixtures that included these metals, and cognitive, motor, behaviour and mental health outcomes in children and adolescents. Scopus, OVID Medline, EMBASE and PsychINFO were searched for relevant studies published in English between January 01, 2022, and June 30, 2025. Of the 1089 studies identified, 77 met the criteria for inclusion. Thirty-four different cohorts for 18 countries were included, and sample sizes ranged from 48 to 96,165. Exposure was primarily assessed using biological samples such as maternal and child blood, cord blood, and maternal and child urine. The findings of this review provide strong support for the contention that higher levels of prenatal and childhood exposure to As, Cd, Pb and Hg, and their mixtures are linked with adverse cognitive, motor, behavioural and mental health outcomes in children. There is some suggestion that these effects may differ by child sex. Prenatal and childhood exposure to these toxic metals has lasting consequences for children's neurodevelopment. Future research that examines the effects of prenatal, early childhood and continued exposure to these toxic metals on adult neurodevelopment is critical. Further, the potential mitigating effects of maternal and child nutrition and the influences of the psychosocial environment on long term outcomes are areas in need of future study.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it