Total dairy consumption in relation to overweight and obesity in children and adolescents: A systematic review and meta‐analysis
Bibliographic record
Abstract
A systematic review and meta-analysis of cross-sectional and prospective cohort studies was conducted to assess the associations between total dairy consumption and its different subtypes with the prevalence and incidence of overweight, obesity, and overweight/obesity in children and adolescents. A literature search was conducted in Medline through PUBMED and Cochrane Library databases until October 18, 2021. Articles reporting the risk estimates as odd ratios (OR), risk ratios (RR), or hazard ratios and their corresponding 95% confidence interval (CI) for the association between dairy product consumption and the risk of overweight and/or obesity were included. In the meta-analysis from cross-sectional studies, results showed an inverse association between total dairy consumption and obesity prevalence (OR (95% CI): 0.66 (0.48-0.91). No significant associations were found between milk or yogurt and obesity prevalence risk. Regarding prospective studies, total milk consumption was positively associated with overweight prevalence (OR (95% CI): 1.13 (1.01-1.26)) and incidence (RR (95%CI): 1.17 (1.01-1.35)) risk. Evidence from pooled analysis of cross-sectional studies suggested an inverse association between total dairy consumption and obesity. However, there is limited and no conclusive evidence to confirm an inverse relationship from pooled analysis of prospective studies in children and adolescents.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".