Exposure to Ambient Air Pollution and Cognitive Impairment in Community-Dwelling Older Adults: The Korean Frailty and Aging Cohort Study
Bibliographic record
Abstract
The aim of this study was to investigate the associations between ambient air pollutants and cognitive impairment in Korean older adults. The cognitive function of 2,896 participants aged 70 to 84 years was measured using the Korean version of the mini-mental state examination, the digit span test, the word list learning test, and the frontal assessment battery. After matching the average concentrations of particulate matter (PM) <10 μm in size (PM10) and <2.5 μm (PM2.5), NO2, CO, SO2, and O3 between 2013 and 2017, the association between air pollutants and cognitive scales was analyzed using a linear mixed regression and a multiple logistic regression analysis (after adjusting for age, sex, health related behaviors, socioeconomic status, comorbidity, and meteorological data). Exposure to PM2.5, PM10, NO2, SO2, and CO was associated with cognitive impairment above and beyond age or education level effects. Specifically, PM2.5 was negatively associated with most components of the cognitive scales (interquartile range for PM2.5: 2.0 μg/m3, odds ratio for poor global cognition: 2.28, 95% confidence interval: 1.60–3.26). These associations may be affected by sex, residence area, or alcohol intake. Conclusively, air pollutants, especially PM2.5, were associated with cognitive impairment, including global cognition, attention, memory, and executive function in Korean older adults aged ≥70 years.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".