Fruit and vegetable intake and risk of wheezing and asthma: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it