Fruit and vegetable intake and risk of wheezing and asthma: a systematic review and meta-analysis
Bibliographic record
Abstract
Major bibliographic databases were searched for studies examining the relationship between fruit and vegetable consumption and the risk of wheezing and asthma. Random-effects models were used to pool study results. Subgroup analyses were conducted by fruit and vegetable categories, study design, and age group. Twelve cohorts, 4 population-based case-control studies, and 26 cross-sectional studies published between January 1990 and July 2013 were identified. For the meta-analysis of adults and children, the relative risk (RR) and confidence intervals (CI) when comparing the highest intake group with the lowest intake group were 0.78 (95%CI, 0.70-0.87) for fruit and 0.86 (95%CI, 0.75-0.98) for vegetables. High intake of fruit and vegetables (RR = 0.76; 95%CI, 0.68-0.86 and RR = 0.83; 95%CI, 0.72-0.96) reduced the risk of childhood wheezing. Total intake of fruit and vegetables had a negative association with risk of asthma in adults and children (RR = 0.54; 95%CI, 0.41-0.69). Consuming fruit and vegetables during pregnancy had no association with the risk of asthma in offspring. High intake of fruit and vegetables may reduce the risk of asthma and wheezing in adults and children.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.017 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".