Respiratory symptoms, lung function decrement and chronic obstructive pulmonary disease in pre-menopausal Indian women exposed to biomass smoke
Bibliographic record
Abstract
BACKGROUND: The impact of chronic exposure to smoke from biomass burning on respiratory health has been examined. METHODS: Six-hundred and eighty-one non-smoking women (median age 35 years) from eastern India who cook exclusively with biomass (wood, dung and crop residues) and 438 age-matched women from similar neighborhood who cook with liquefied petroleum gas (LPG) were examined. Pulmonary function test was done by spirometry. The concentrations of particulate matter having diameter of < 10 µm (PM10) and < 2.5 µm (PM2.5) in indoor air was measured by real-time aerosol monitor. RESULTS: Compared with LPG users, biomass users had greater prevalence of upper (50.9 versus 28.5%) and lower respiratory symptoms (71.8 versus 30.8%) and dyspnea (58.4 versus 19.9%). They showed reduction in all parameters measured by spirometer especially in mid-expiratory volume. PM10 and PM2.5 concentration in biomass using kitchen were 2-3-times more than LPG-using kitchen, and the decline in spirometry values was positively associated PM10 and PM2.5 levels in indoor air after controlling education, family income and kitchen location as potential confounders. Overall, 29.7% of biomass users and 16.4% of LPG users had deficient lung function, and restrictive type of deficiency was predominant. Chronic obstructive pulmonary disease (COPD) was diagnosed in 4.6% of biomass and 0.9% of LPG users. Women who predominantly used dung cake and did not possess separate kitchen had poorer lung function. CONCLUSION: Cumulative exposure to biomass smoke causes lung function decrement and facilitates COPD development even in non-smoking and relatively young pre-menopausal women.
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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 | 0.000 |
| 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) | 0.002 | 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".