Longitudinal study of diet quality and change in asthma symptoms in adults, according to smoking status
Bibliographic record
Abstract
It has been hypothesised that increased asthma prevalence in westernised countries is associated with changes in lifestyle factors, including a poorer diet. However, little is known regarding the association between diet quality and asthma. In the diet-asthma association, the role of BMI as a potential mediator needs clarification; moreover, potential effect modification by non-diet sources of oxidants, such as smoking, merits investigation. We investigated the association between diet quality and change in asthma symptoms, as well as assessed effect modification by smoking, while accounting for BMI as a potential mediator. Using data from the French prospective Epidemiological study on the Genetics and Environment of Asthma study, we assessed diet quality using the Alternate Healthy Eating Index 2010 (AHEI-2010) at baseline and change in asthma symptoms (stable (reference), worsening, improved; mean follow-up time: 7 years). Mediation analysis was used to disentangle total and direct effects and the indirect effect mediated by BMI. The analyses included 969 adults (mean age 43 years; 49 % men; 42 % ever asthma). We observed a significant interaction between smoking and AHEI-2010 on change in asthma symptoms (P for interaction=0·04). Among never smokers (n 499), we observed a positive total effect (multivariable OR 1·39; 95 % CI 1·07, 1·80) and a positive direct effect (OR 1·41; 95 % CI 1·09, 1·80) of the AHEI-2010 (per ten-point increment) on improved symptoms. No indirect effect mediated through BMI was observed (OR 0·99; 95 % CI 0·91, 1·07). Among former and current smokers, all effects were statistically non-significant. Better diet quality was associated with improved asthma symptoms over time in never smokers, independently of BMI.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".