Association of Household Utility of Cleaner Fuel With Lower Hypertension Prevalence and Blood Pressure in Chinese Adults
Bibliographic record
Abstract
Objectives: To investigate whether lower hypertension prevalence or blood pressure was associated with cleaner household fuel usage for cooking and heating among Chinese adults. Methods: We enrolled 44,862 Chinese adults at the baseline of the prospective urban and rural epidemiology (PURE) study in China during 2005–2009, as a subset of the PURE-global China site. Multilevel logistic regression and generalized linear mixed models were conducted to estimate the adjusted odds ratio (AOR) and regression coefficient for hypertension and blood pressure respectively, while subgroup analysis by ambient PM2.5 concentration and location was also examined. Results: Compared with the least clean household solid fuel group, gas (AOR = 0.91, 95% CI: 0.83, 0.99) or electricity (AOR = 0.72, 95% CI: 0.60, 0.87) was associated with significantly lower levels of hypertension prevalence and blood pressure, and a similar pattern of the association was consistently observed among participants with high ambient PM2.5 exposure and those living in urban areas. Conclusion: Household utility of cleaner fuel type was associated with lower hypertension prevalence and blood pressure in Chinese adults. Our study urges the utilization of cleaner household energy to mitigate the burden of hypertension.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".