Sleep and the gut microbiota in preschool-aged children
Bibliographic record
Abstract
Sleep plays a significant role in the mental and physical development of children. Emerging evidence in animals and human adults indicates a relationship between sleep and the gut microbiota; however, it is unclear whether the sleep of preschoolers during a key developmental period, associates with features of their gut microbiota. The objective of this study was to assess the relationship between sleep and gut microbiota in preschool-aged children (4.37 ± 0.48 years, n = 143). Sleep measures included total night-time sleep (TST), sleep efficiency (SE), and wake-time after sleep onset (WASO) assessed using actigraphy. Beta-diversity differences between children with low and high TST (p = .048) suggest gut microbiota community differences. Particularly, relative abundance of Bifidobacterium was higher in the high TST group and Bacteroides, was higher in children who had greater SE and less WASO (LDA score >2). In contrast, some Lachnospiraceae members including Blautia and Coprococcus 1 were associated with shorter night-time sleep duration and less efficiency, respectively. We also found a group of fecal metabolites, including specific neuroactive compounds and immunomodulating metabolites were associated with greater sleep efficiency and less time awake at night. Notably, tryptophan and its metabolizing products were higher in children who had higher SE or lower WASO (LDA score >2); concentration of propionate was higher in children with less WASO (p = .036). Overall, our results reveal a novel association between sleep and gut microbiota in preschool-aged children. Longer night-time sleep and greater sleep efficiency were associated with specific commensal bacteria that may regulate sleep through modulating neurotransmitter metabolism and the immune system.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".