Underweight in the first 2 years of life and nutrition risk in later childhood: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Children with underweight in the first 2 years have lower body mass index z-score (zBMI) and height-for-age z-score (HAZ) in later childhood. It is not known if underweight in the first 2 years is associated with nutrition risk in later childhood. OBJECTIVE: (1) Determine the relationship between underweight (zBMI < -2) in the first 2 years and nutrition risk measured by the Nutrition Screening for Toddlers and Preschoolers (NutriSTEP) score from 18 months to 5 years. (2) Explore the relationship between underweight in the first 2 years and the NutriSTEP subscores for eating behaviours and dietary intake from 18 months to 5 years. METHODS: This was a prospective study, including healthy full-term children in Canada aged 0-5 years. zBMI was calculated using measured heights and weights and the WHO growth standards. NutriSTEP score was measured using a parent-completed survey and ranged from 0 to 68. Nutrition risk was defined as a score ≥21. Linear mixed effects models were used. RESULTS: Four thousand nine hundred twenty-nine children were included in this study. At enrolment, 51.9% of participants were male. The prevalence of underweight children was 8.8%. Underweight in the first 2 years was associated with higher NutriSTEP (0.79, 95% CI: 0.29,1.29), higher eating behaviour subscore (0.24, 95% CI: 0.03, 0.46) at 3 years and higher odds of nutrition risk (OR: 1.39, 95% CI: 1.07,1.82) at 5 years. CONCLUSIONS: Children with underweight in the first 2 years had higher nutrition risk in later childhood. Further research is needed to understand the factors which influence these relationships.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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".