Delayed skeletal maturation is a major contributor to child height deficits in a low-income setting
Bibliographic record
Abstract
BACKGROUND: Studying the extent to which delayed skeletal maturation may contribute to childhood height deficits is important for assessing potential for recovery in heights. AIM: To investigate the discrepancy in height-for-age Z-scores (HAZ) based on chronological age (HAZ-CA) compared to bone age (HAZ-BA) and estimate proportion of HAZ deficits attributable to delayed maturation in both sexes. SUBJECTS AND METHODS: Using the WHO Growth References, HAZ-CA and HAZ-BA were calculated for Guatemala City children aged 6-8.99 years participating in the Universidad del Valle de Guatemala Longitudinal Study and attending a low or a very low SEP study school. A mixed effects model was developed to describe 1638 HAZ observations (Level 1) in 1107 children (Level 2) by HAZ-type, with interaction terms for HAZ-type by age, sex, school, and birth year. RESULTS: On average, skeletal age was delayed by 1.1 (SD 1.0) years. Mean HAZ-CA was -1.7 (0.9) and HAZ-BA -0.6 (0.9). Greater proportions of the total height deficit were attributable to delayed skeletal maturation in males (60-87%) versus females (49-63%), and at low- (58-87%) versus very low-SES school (49-71%). CONCLUSION: Delayed maturation contributes to height deficits, supporting the idea that opportunity for catch-up growth continues past early childhood in both sexes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".