Gestational age at birth and sleep duration in early childhood in three population-based cohorts
Bibliographic record
Abstract
BACKGROUND: Both preterm and post-term births have been associated with neonatal morbidity and mortality, including adverse impact on neurodevelopment. Important neural maturational processes take place during sleep in newborns, but findings on gestational duration and sleep in early childhood are contradictory and often derive from small clinical samples. We studied the association of gestational age at birth with sleep duration in early childhood in three population-based cohorts. METHODS: Gestational age at birth and sleep duration were assessed in three population-based cohort studies in The Netherlands (n = 6471), Singapore (n = 862), and Canada (n = 583). Gestational age at birth was assessed using ultrasound in pregnancy in combination with date of birth, and caregivers repeatedly reported on child sleep duration at three, six, 24, and 36 months of age. Generalized estimating equations were used, which were adjusted for confounders, and findings were pooled in a meta-analysis. RESULTS: Children born preterm (<37 weeks of gestation) showed longer sleep duration than children born at term; and children born post-term (≥42 weeks of gestation) showed shorter sleep duration. The meta-analysis indicated a small negative effect of gestational age on child sleep duration (effect size -0.11), when assessed in children born at term only. CONCLUSION: In early childhood, children with a lower gestational age have a longer sleep duration, even when they are born at term (37-42 weeks of gestation). These subtle yet consistent findings point to the importance of maturational processes during sleep, not only in premature children but also in children born at term after shorter gestational duration.
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 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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.012 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".