What are the consequences of PM air pollution exposure on elderly behavior? A systematic review
Bibliographic record
Abstract
Environmental pollution poses a significant risk to human health. Particulate matter (PM) found in polluted air is particularly of concern due to its ability to penetrate the blood-brain barrier (BBB) and impact the central nervous system (CNS), affecting sensory, cognitive, and emotional well-being. The aim of this review is to provide a comprehensive overview on the latest evidence regarding the association between PM exposure and behavioral outcomes in adult and older populations. Searches were conducted across PubMed, Web of Science, and Scopus up to August 2023, with articles selected and screened following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 27 articles meeting the criteria were included, and their risk of bias was evaluated using the Newcastle Ottawa Scale. The studies primarily focused on PM2.5 and PM10 in regions such as Europe, the USA, and Asia. While data on the impact of PM exposure on sensory variables were limited, suggesting an adverse effect, overall findings indicated a link between PM exposure and worsened cognitive function, increased risk of dementia, depressive symptoms, and anxiety. Some studies highlighted sex-dependent effects of PM exposure, with women experiencing a higher prevalence of adverse effects. This review underscores the importance of further research to understand the specific cognitive aspects affected by PM exposure, particularly in relation to dementia risk. • 27 studies examined associations between PM and behavioral variables in the adult and elderly population. • The studies showed positive relationships between PM and olfactory dysfunction, cognitive decline, depression and anxiety. • In general, aspects related to memory are the most frequent after PM exposure. • Some studies highlighted sex-dependent effects of PM exposure. Women exhibited a higher prevalence of adverse effects. • Further research is needed to study links between PM exposure and dementia risk.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.005 | 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".