Is residential ambient air limonene associated with asthma in the Canadian population?
Bibliographic record
Abstract
Introduction: Exposure to limonene, a volatile organic compound, is commonplace. It may be used in the manufacture of personal care products and household cleaners. Its effect on asthma is unknown. Objective: We investigated the influence of limonene on asthma in a population-based sample of approximately 4,000 Canadians between six and seventy nine years old. Methods: During the cross-sectional Canada Health Measures Survey, carried out between 2012 and 2013, participants were asked if they wheezed or had a diagnosis of asthma, and underwent spirometry and measurement of the fraction of exhaled nitric oxide (FeNO). These variables were tested for an association with limonene concentrations measured in their household air samples, using linear regression analysis adjusting for age, sex, smoking, education and household income. Results: An interquartile (IQR) increase in log air limonene concentration was associated with an approximate 17% adjusted relative increase in wheezing with an odds ratio of 1.17 (95% CI 1.16, 1.18). The mean change in log FeNO for an IQR increase in limonene was twice as large for children, 2.89 ppb (95% CI 1.88, 4.43) compared to adults, 1.44 ppb (95%CI 1.16, 1.79). Among boys, the odds ratio was 1.50 (95% CI 1.48, 1.52) between an IQR increase in limonene and a diagnosis of asthma. Conclusions: This study provides evidence suggesting that household exposure to limonene may increase the prevalence of asthma in the general population. If the association were causal, the burden of illness due to asthma in Canada could potentially be reduced by education on how to minimize 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".