Long-Term occupational exposure to heavy metals (lead, mercury, aluminum) and risk of dementia: A systematic review and meta-analysis
Bibliographic record
Abstract
Background: Dementia, is a major global health challenge. Occupational exposure to heavy metals such as lead, mercury, and aluminum is common in several industries, yet their long-term contribution to dementia risk remains uncertain. Objective: To systematically review and meta-analyze epidemiological evidence on the association between chronic occupational exposure to lead, mercury, or aluminum and risk of dementia or AD. Methods: Following PRISMA 2020 guidelines, PubMed, Web of Science, and Embase were searched through August 2025 for observational studies assessing long-term occupational heavy metal exposure and dementia outcomes. Study quality was assessed using the Newcastle–Ottawa Scale. Random-effects meta-analyses pooled odds ratios (ORs), and heterogeneity was evaluated using the I² statistic. Results: Fifteen studies involving over 10,000 participants met inclusion criteria. Chronic lead exposure was not significantly associated with dementia risk (OR ≈ 1.10, 95% CI 0.90–1.35). Mercury exposure showed a non-significant trend toward increased risk (OR ≈ 1.15, 95% CI 0.80–1.60). In contrast, chronic aluminum exposure was associated with a significantly higher risk of dementia (OR ≈ 1.50, 95% CI 1.20–1.90), with moderate heterogeneity. Conclusion: Long-term aluminum exposure appears to increase dementia risk, whereas evidence for lead and mercury remains inconclusive. Further longitudinal studies with precise exposure assessment are warranted.
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How this classification was reachedexpand
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 | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".