Birth month associations with height, head circumference, and limb lengths among peruvian children
Bibliographic record
Abstract
Associations between season of birth and body size, morbidity, and mortality have been widely documented, but it is unclear whether different parts of the body are differentially sensitive, and if such effects persist through childhood. This may be relevant to understanding the relationship between early life environment and body size and proportions. We investigated associations between birth month and anthropometry among rural highland (n = 162) and urban lowland (n = 184) Peruvian children aged 6 months to 8 years. Stature; head-trunk height; total limb, ulna, tibia, hand, and foot lengths; head circumference; and limb measurements relative to head-trunk height were converted to internal age-sex-specific z scores. Lowland and highland datasets were then analyzed separately for birth month trends using cosinor analysis, as urban conditions likely provide a more consistent environment compared with anticipated seasonal variation in the rural highlands. Among highland children birth month associations were significant most strongly for tibia length, followed by total lower limb length and stature, with a peak among November births. Results were not significant for other measurements or among lowland children. The results suggest a prenatal or early postnatal environmental effect on growth that is more marked in limb lengths than trunk length or head size, and persists across the age range studied. We suggest that the results may reflect seasonal variation in maternal nutrition in the rural highlands, but other hypotheses such as variation in maternal vitamin D levels cannot be excluded.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".