Head Circumference Versus Length and Weight Deficits up to 2 Years of Age in Bangladesh
Bibliographic record
Abstract
Infant undernutrition, defined by length- and weight-based indices, is common in low- and middle-income countries (LMICs), but corresponding deficits in head size have received less attention. In a cohort of term newborns in Dhaka, Bangladesh, we compared the severity of deficits (vs. World Health Organization Growth Standards) in head circumference (HC), length and weight at birth and every 3 months until 2 years of age (n range across timepoints: 843-920). We estimated the mean and 25th, 50th and 75th percentiles of HC-, length- and weight-for-age z-scores (HCZ, LAZ and WAZ, respectively). Differences between HCZ and LAZ (or WAZ) were analyzed using paired t tests and quantile regression. We also derived HCZ using height-age instead of chronological age at 3-24 months. Mean HCZ was significantly higher than mean LAZ and WAZ at birth, but HCZ was significantly lower than LAZ at 6, 9 and 12 months and the HCZ and LAZ deficits were similar from 15 to 24 months. Mean HCZ was lower than WAZ at all ages beyond birth. Patterns were broadly consistent at the 25th, 50th and 75th percentiles. The HCZ deficit remained evident when HC was standardized using height-age at all ages beyond birth, indicating HC was reduced relative to body size. In conclusion, among term-born children in Dhaka, HCs were smaller than international standards at all ages up to 2 years, and there was no evidence of postnatal head sparing. Consideration should be given to routine measurement of HC in population health surveys in LMICs.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".