Association Between Zinc and Pediatric Metabolic Syndrome: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: The increasing prevalence of metabolic syndrome (MetS) in the pediatric population underscores a critical need for understanding dietary and micronutrient factors, including the role of zinc in metabolic regulation. Despite the well-known importance of zinc in metabolic functions, there are contradictory results regarding its association with pediatric MetS. Objectives: We aimed to perform a comprehensive review of the studies on the association between serum zinc level and dietary zinc intake with MetS in children and adolescents. Methods: This is a systematic review and meta-analysis study conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The related studies in English published up to the end of May 2024 were searched in PubMed, Scopus, and Web of Science. The observational studies with high quality (assessed using the Newcastle-Ottawa scale [(NOS)]) were included. Odds ratios (ORs) and 95% confidence intervals (CIs) comparing the risk of MetS in lower levels of zinc versus higher levels were also extracted from each study. Results: Of 444 initially identified records, four eligible studies were selected for the review. The pooled analysis revealed no significant association between zinc levels (food intake or serum level) and the presence of MetS (P=0.41; OR=1.22, 95% CI, 0.92%, 1.62%). Heterogeneity was not substantial (I2=0.00). Conclusions: The non-significant association of serum zinc level and dietary zinc intake with MetS in children and adolescents, coupled with substantial heterogeneity across included studies, highlights the complexity of the association between zinc and MetS among youths. This underscores the necessity for further longitudinal studies on the association of low zinc levels and the risk of MetS in children and adolescents.
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.
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 | 0.009 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".