Outdoor air pollution as a risk factor for Alzheimer’s disease: A systematic review
Bibliographic record
Abstract
Abstract Background Outdoor air pollution is a global issue which poses a significant health risk. Modern neuroimaging techniques have revealed the detrimental impact of air pollution on brain health, in particular the development and progression of neurodegenerative diseases such as Alzheimer’s disease (AD).(1) We conducted a systematic review to evaluate the effects of long‐term (months to years) exposure to outdoor air pollutants on the development and progression of AD using neuroimaging data. Method This review followed PRISMA guidelines and registered in PROSPERO (CRD42023482979). Four large databases (MEDLINE, Embase, Scopus, and CINAHL) were systematically searched using words relating to “air pollution”, “neuroimaging”, and “Alzheimer’s disease”. The population researched was kept broad to include all ages. There were no geographical limits applied, and so included all countries. Articles were exported to Endnote (Endnote X9.3.3, Clarivate US), where duplicate articles were removed. Remaining articles were uploaded to the Rayyan and screened for eligibility. The Newcastle Ottawa Scale was used to assess the quality of included papers. A narrative synthesis was conducted, which involved grouping papers that focused on the same neuroimaging outcome and comparing and contrasting between studies. Result Our search yielded 397 results, after removing duplicated (n=172), articles were removed at the title (n=192), abstract (n=8), and full text (n=17) stages. Eight articles met our inclusion criteria and focused on changes to white matter (n= 5), cortical thickness (n= 6), and grey matter (n= 2). Specific air pollutants (e.g., PM2.5) were associated with white matter reductions, and PM10 and NO2 with reduced cortical thickness. However, higher exposure to NOx and NO2 was linked to better performance in cognition tests. Exposure to PM2.5 was associated with reduced grey matter, with study participants showing greater cognitive impairment. Air pollution exposure was associated with brain structure changes which are commonly seen in AD‐related pathology. Conclusion Our results highlighted significant associations between specific air pollutant exposure and changes in different brain structures. Future research is needed to further investigate the relationship between air pollution exposure and cognitive decline. References: Block ML, Calderón‐Garcidueñas L. Air pollution: mechanisms of neuroinflammation and CNS disease. Trends Neurosci. 2009;32(9):506‐16.
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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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".