Gestational Age at Birth and ‘Body-Mind’ Health at 5 Years of Age: A Population Based Cohort Study
Bibliographic record
Abstract
Numerous studies have identified the effects of prematurity on the neonate's physical health, however few studies have explored the effects of prematurity on both the physical and mental health of the child as they develop. Secondary analysis of data from the Millennium Cohort Study, a longitudinal study of infants (n = 18 818, born 2000-2002 in the United Kingdom) was performed. Effects of gestational age at birth on health outcomes at 5 years were measured using parental rating of their children's general health and severity of behavior problems. The association between parent's general health ratings and behavior problem ratings was low: 86% of those reporting serious behavior problems (5% of the sample, n = 764) rated their child as being in excellent, very good, or good health. Still, a gradient of increasing risk of poorer outcome with decreasing gestational age was observed for a composite health measure (poor/fair health and/or serious behavior problems), suggesting an association with prematurity for this composite assessment of health status. The greatest contribution to the childhood composite health measure at 5 years was for children born at 32-36 weeks gestation: population attributable fractions for having poor outcomes was 3.4% (Bonferroni-adjusted 95% confidence interval 1.1%-6.2%), compared to 1% (0.2-2.3) for birth at less than 32 weeks. Results suggest that preterm children, by school entry, are not only at high risk of physical health problems, but also of behavioral health problems. The recognition of, and response to comprehensive health and well-being outcomes related to prematurity are important in order to correctly plan and deliver adequate paediatric health services and policies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".