Environmental risk factors for all-cause dementia, Alzheimer's disease dementia, vascular dementia, and mild cognitive impairment: An umbrella review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Mitigation of environmental risk factors for neurocognitive disorders could reduce the number of incident cases. We sought to synthesize the literature on environmental risk factors for dementia and mild cognitive impairment. METHODS: We conducted an umbrella review and meta-analysis. Multiple databases were systematically searched to identify systematic reviews and meta-analyses of longitudinal studies examining environmental risk factors for dementia or mild cognitive impairment. We used random effects multi-level, meta-analytic models to synthesize risk ratios for each risk factor while accounting for overlap in the studies within reviews. As a secondary objective, we examined risk factors for two common phenotypes of dementia: Alzheimer's disease dementia and vascular dementia. RESULTS: A total of 19 reviews containing 37 meta-analyses were included umbrella review. We found 9 factors where exposure was associated with higher risks of all-cause dementia: fine particulate matter, particulate matter, nitrogen dioxide, nitrogen oxides, carbon monoxide, shift work, night shift work, chronic noise, and extremely-low frequency magnetic fields. Neighbourhood greenness was associated with a lower risk of all-cause dementia. In a narrative review, we found that exposure to sulfur dioxide, proximity to roadways, ionizing radiation, aluminum, solvents, pesticides, and environmental tobacco smoke were also associated with dementia. We also found that fine particulate matter, extremely-low frequency magnetic fields, sulfur dioxide, chronic noise, and pesticides were related to Alzheimer's disease dementia. Fine particulate matter, particulate matter, and chronic noise were related to vascular dementia. No systematic review reported on mild cognitive impairment. CONCLUSION: Achieving stronger air quality targets has the potential to reduce population-level dementia risk. Neighbourhood (i.e., greenness and chronic noise) and occupational (i.e., shift work) characteristics are associated with dementia and are viable public health intervention points. Additional research should examine the relationship between other environmental risk factors and mild cognitive impairment and specific types of dementia.
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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 | 0.017 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".