P2544Risk of cardiovascular death by long-term solid fuel use for cooking and implications of switching to clean fuels: a prospective cohort study of 340,000 chinese adults
Bibliographic record
Abstract
Background: Household air pollution from solid fuel use is estimated to be a leading cause of cardiovascular disease (CVD) mortality, but prospective evidence is limited. Purpose: To examine the association of solid fuel use for cooking with CVD deaths and the potential implications of switching from solid to clean fuels. Methods: In 0.5 million adults aged 30–79 years recruited from ten areas of China in 2004–2008, self-reported cooking frequency and primary fuel type used for cooking (clean fuels: electricity or gas; solid fuels: coal, wood or charcoal) were assessed. Duration of exposure was estimated based on information collected on the participant's three most recent residences. Mortality data up to 1 January 2017 were ascertained via linkage to death registries and hospitalisation records. The analyses were restricted to participants who cooked at least weekly throughout the recall period and had no self-reported prior history of CVD at baseline. Cox regression stratified for age-at-risk, sex and study areas yielded hazard ratios (HRs) adjusted for smoking, education, and other established confounders. Analyses also assessed the associations per 10 years longer duration of exposure.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".