A systematic review and meta-analysis of the association of all types of beverages high in fructose with asthma in children and adolescents
Bibliographic record
Abstract
Abstract Background Asthma has become the most common chronic condition among children in recent decades. Environmental factors, including food, drive its rise. Sweetened beverages are a staple of children’s diets and cause various health issues. Therefore, this research aims to evaluate the association of all types of high fructose beverages with asthma in children. Method We assessed observational studies published before November 2023, obtained from PubMed, Scopus, and Web of Science. The quality of articles was assessed by using the Newcastle-Ottawa Scale. Studies with a pediatric population under 18 years that indicate the association between all kinds of beverages containing high fructose and asthma and evaluated risk estimates with 95% confidence intervals were included. We also followed Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). Results In the final analysis, we included eleven studies with 164,118 individuals. Twenty-one effect sizes indicated a significant positive association between sugar-sweetened beverages (SSBs) consumption and odds of asthma (OR: 1.28; 95% CI: 1.15–1.42; P value < 0.001). Three effect sizes showed that total excess free fructose (tEFF) intake increases children’s asthma odds by 2.7 times (pooled OR: 2.73; 95% CI: 1.30–5.73; P value =0.008). However, five effect sizes in 100% fruit juice failed to show statically association with asthma prevalence in children (pooled OR: 1.43; 95%CI: 0.91–2.23; P value =0.12). Conclusion In summary, SSB and tEFF raised asthma probabilities. No relationship was found between fruit juice and asthma in children and adolescents. We need more cohort studies with correct age selection to identify the precise link.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".