Associations of household solid fuel for heating and cooking with hypertension in Chinese adults
Bibliographic record
Abstract
OBJECTIVE: The association between indoor air pollution resulting from household solid fuel use for heating and cooking with hypertension or blood pressure (BP) remains less clear. This study aims to rectify these knowledge gaps in a large Chinese population. METHODS: During 2005-2009, 44 007 individuals aged 35-70 years with complete information on household solid fuel use for cooking and heating were recruited from 279 urban and rural communities of 12 centers. Solid fuel referred to charcoal, coal, wood, agriculture crop, animal dung or shrub. Annual concentration of ambient atmospheric particulate matter that have a diameter of less than 2.5 μm for all communities was collected. Generalized linear mixed models using community as the random effect were performed to estimate the association with hypertension prevalence or BP after considering ambient atmospheric particulate matter that have a diameter of less than 2.5 μm and a comprehensive set of potential confounding factors at the individual and household level. RESULTS: A total of 47.6 and 61.2% of participants used household solid fuel for heating and cooking, respectively. Solid fuel use for heating was not associated with an increase in hypertension prevalence (adjusted odds ratio = 1.08, 95% confident interval: 0.98, 1.20) or elevated SBP (0.62 mmHg, 95% confident interval: -0.24, 1.48). No association was found between solid fuel for cooking and hypertension or BP, and no additional risk was observed among participants who had both exposures to solid fuel for heating and cooking compared with those used for heating only. CONCLUSION: The current large Chinese study revealed a statistically insignificant increase in the association between solid fuel use for heating and hypertension prevalence or BP. As this cross-sectional study has its inherent limitation on causality, findings from this study would have to be confirmed by prospective cohort studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".