Health Effects of Household Solid Fuel Use: Findings from 11 Countries within the Prospective Urban and Rural Epidemiology Study
Bibliographic record
Abstract
BACKGROUND: Household air pollution (HAP) from solid fuel use for cooking affects 2.5 billion individuals globally and may contribute substantially to disease burden. However, few prospective studies have assessed the impact of HAP on mortality and cardiorespiratory disease. OBJECTIVES: Our goal was to evaluate associations between HAP and mortality, cardiovascular disease (CVD), and respiratory disease in the prospective urban and rural epidemiology (PURE) study. METHODS: We studied 91,350 adults 35–70 y of age from 467 urban and rural communities in 11 countries (Bangladesh, Brazil, Chile, China, Colombia, India, Pakistan, Philippines, South Africa, Tanzania, and Zimbabwe). After a median follow-up period of 9.1 y, we recorded 6,595 deaths, 5,472 incident cases of CVD (CVD death or nonfatal myocardial infarction, stroke, or heart failure), and 2,436 incident cases of respiratory disease (respiratory death or nonfatal chronic obstructive pulmonary disease, pulmonary tuberculosis, pneumonia, or lung cancer). We used Cox proportional hazards models adjusted for individual, household, and community-level characteristics to compare events for individuals living in households that used solid fuels for cooking to those using electricity or gas. RESULTS: We found that 41.8% of participants lived in households using solid fuels as their primary cooking fuel. Compared with electricity or gas, solid fuel use was associated with fully adjusted hazard ratios of 1.12 (95% CI: 1.04, 1.21) for all-cause mortality, 1.08 (95% CI: 0.99, 1.17) for fatal or nonfatal CVD, 1.14 (95% CI: 1.00, 1.30) for fatal or nonfatal respiratory disease, and 1.12 (95% CI: 1.06, 1.19) for mortality from any cause or the first incidence of a nonfatal cardiorespiratory outcome. Associations persisted in extensive sensitivity analyses, but small differences were observed across study regions and across individual and household characteristics. DISCUSSION: Use of solid fuels for cooking is a risk factor for mortality and cardiorespiratory disease. Continued efforts to replace solid fuels with cleaner alternatives are needed to reduce premature mortality and morbidity in developing countries. https://doi.org/10.1289/EHP3915.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".