Household air pollution from solid fuel use as a dose-dependent risk factor for cognitive impairment in northern China
Bibliographic record
Abstract
Abstract The relationship between exposure to household air pollution (HAP) from solid fuel use and cognition remains poorly understood. Among 401 older adults in peri-urban northern China enrolled in the INTERMAP-China Prospective Study, we estimated the associations between exposure to HAP and z-standardized domain-specific and overall cognitive scores from the Montreal Cognitive Assessment. Interquartile range increases in exposures to fine particulate matter (53.2-µg/m3) and black carbon (0.9-µg/m3) were linearly associated with lower overall cognition [− 0.13 (95% confidence interval: − 0.22, − 0.04) and − 0.10 (− 0.19, − 0.01), respectively]. Using solid fuel indoors and greater intensity of its use were also associated with lower overall cognition (range of point estimates: − 0.13 to − 0.03), though confidence intervals included zero. Among individual cognitive domains, attention had the largest associations with most exposure measures. Our findings indicate that exposure to HAP may be a dose-dependent risk factor for cognitive impairment. As exposure to HAP remains pervasive in China and worldwide, reducing exposure through the promotion of less-polluting stoves and fuels may be a population-wide intervention strategy to lessen the burden of cognitive impairment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".