Relationship between diet, nutritional aspects and sleep quality in a pediatric population
Bibliographic record
Abstract
Introduction: The relationship between diet and sleep has been studied in adults. However, there is little evidence in the pediatric population. The objective of this review was to analyze in a narrative way the relationship between diet, some nutritional aspects and sleep quality in population under 14 years. A quick review was performed in MEDLINE (PubMed) and Cochrane with a search strategy combining MeSH terms and keywords. Studies were selected to estimate diet and evaluate nutritional status and sleep in children using different tools. The risk of bias from the 14 selected studies was determined with validated tools (AMSTAR 2, Newcastle Ottawa scale [NOS] and Risk of Bias [Rob2]). Adherence to some dietary patterns such as the Mediterranean, high consumption of fruits and vegetables, tryptophan intake or substitution of saturated fatty acids by unsaturated fats were associated with better sleep quality. The consumption of ultra-processed products, the "unhealthy fast food" or the high intake of simple sugars hinder an adequate rest. On the other hand, an association between a high body mass index and lack of sleep was observed in young people under 14. In conclusion, the collected studies showed a significant association between some dietary patterns, food groups and nutrients with sleep quality. "Unhealthy" dietary factors were associated with poorer sleep quality. However, healthier and recommended habits and diets were associated with improved sleep hygiene. On the other hand, the lack of hours of rest in the youth population increases height, weight and BMI. Further research is needed in this direction.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".