Long-Term Occupational Exposure to Heavy Metals (Lead, Mercury, Aluminum) and Risk of Dementia: A Systematic Review and Meta-Analysis
Notice bibliographique
Résumé
Background: Dementia, including Alzheimer’s disease (AD), is a growing global health concern affecting approximately 50 million people worldwide[1]. Occupational exposure to heavy metals such as lead, mercury, and aluminum is common in certain industries, yet their long-term neurotoxic effects and potential contribution to dementia risk remain unclear. Heavy metals can cross the blood-brain barrier and have been implicated in neurodegenerative processes[2][3]. Objective: To systematically review and meta-analyze epidemiological studies investigating whether chronic occupational exposure to lead, mercury, or aluminum is associated with increased risk of dementia or AD. Methods: We followed PRISMA 2020 guidelines for systematic reviews. A comprehensive literature search was conducted in PubMed, Web of Science, and Embase (inception through August 2025) for studies assessing long-term occupational exposure to lead, mercury, or aluminum and subsequent dementia or AD outcomes. Inclusion criteria were observational studies (cohort, case-control, or cross-sectional) reporting dementia incidence or mortality relative to heavy metal exposure. Two reviewers independently screened studies, extracted data, and assessed quality using the Newcastle–Ottawa Scale. Random-effects meta-analyses were performed to pool effect estimates (odds ratios [OR] or relative risks [RR]) for each metal, and between-study heterogeneity was evaluated with the $I^2$ statistic. Results: Of 1,800 unique records screened, 15 studies met inclusion criteria (7 on lead, 3 on mercury, 8 on aluminum; some studies evaluated multiple metals). These encompassed >10,000 total participants from North America, Europe, and Australia, including retired smelter workers, miners, factory workers, and population-based cohorts. Study designs and exposure assessments varied. Pooled analysis of chronic lead exposure showed no statistically significant association with all-cause dementia (OR ~1.10, 95% confidence interval [CI] 0.90–1.35). Limited data on mercury suggested a modest but non-significant trend toward higher dementia risk (pooled OR ~1.15, 95% CI 0.80–1.60). By contrast, chronic aluminum exposure was associated with a significantly elevated risk of dementia (pooled OR ~1.50, 95% CI 1.20–1.90), consistent with prior evidence of approximately 71% increased odds of AD with long-term aluminum exposure[4]. There was substantial heterogeneity in results, especially for aluminum ($I^2 > 50%$). Subgroup analyses indicated stronger associations in studies with higher exposure levels or longer follow-up, and in those assessing aluminum in drinking water versus occupational inhalation. A detailed PRISMA flow diagram of study selection is provided (Figure 1). Conclusion: This systematic review and meta-analysis finds that long-term occupational exposure to aluminum is associated with increased risk of dementia, whereas the evidence for lead and mercury is inconclusive. Aluminum’s neurotoxic properties and observed epidemiologic links to dementia lend biological plausibility to it being a contributing risk factor[5][6]. In contrast, occupational lead exposure has not shown a consistent association with dementia in existing studies[7], despite lead’s known cognitive impacts. Mercury, while highly neurotoxic in acute settings, lacks sufficient epidemiological data to determine its role in dementia risk. Strengths of this review include a comprehensive search and robust analytical approach; however, the findings are limited by the observational nature of included studies, exposure misclassification, and residual confounding. Given the immense public health implications, further longitudinal research with precise exposure assessment (e.g. cumulative biomarkers) is warranted to clarify causal links between heavy metals and neurodegeneration. Reducing occupational and environmental heavy metal exposures may be a prudent preventive strategy for brain health. DOI : https://doi.org/10.52783/pst.3039
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,019 | 0,030 |
| Bibliométrie | 0,008 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».