Growth-Curve Standards and the Assessment of Early Excess Weight Gain in Infancy
Bibliographic record
Abstract
OBJECTIVES: Increasing overweight and obesity are growing problems among children worldwide. Prevention requires an understanding of when excess weight gain begins and the determinants that place children at risk. The aim of our study was to illustrate how the growth curve used to assess growth influences the interpretation of weight gain and the age of onset of higher weight gains in infancy. METHODS: This was a longitudinal study of Canadian infants from birth to 18 months of age. Infant feeding pattern was recorded monthly, and weight and length of 73 infants were measured at 8 different ages. Weight, length, weight for length, and BMI z scores were compared with the Centers for Disease Control and Prevention 2000 growth curves and World Health Organization growth standard. RESULTS: Comparison with the Centers for Disease Control and Prevention growth curves showed that Canadian infants grew similarly or slightly slower than their US counterparts. Using the World Health Organization growth standard, an increase in body weight occurred between 6 and 9 months of age, associated with a change from breastfeeding to formula feeding and introduction of solid foods. When compared with the World Health Organization standards, breastfed infants followed the standards, but formula-fed infants deviated with higher weight for age. When compared with the Centers for Disease Control and Prevention charts, breastfed infants showed an apparent decline in weight for age beginning at approximately 6 months. CONCLUSIONS: The choice of growth curve is important to interpreting infant growth and identifying the onset of excess weight gain. Identification of the prevalence and age of onset of early excess weight gains among Canadian infants will be best achieved by using the World Health Organization growth standards.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".