The Impact of Maternal Employment on Infant Weight-, Length- and BMI-for-Age Based upon WHO Growth Chart Standards
Bibliographic record
Abstract
Background: The infancy is a time of phenomenal growth and development. Infant of working mothers have a special concern as they have less time for their infant care. Objective: The present study aims to assess length, weight and BMI of Jordanian infants in nursery in reference to WHO growth chart standard for age Z-score and to study the impact of mothers’ work on their infant’s growth. Methods: A cross-sectional observational study was conducted on 92 infants aged between 3-12 months randomly and recruited from nurseries in Amman, Jordan. All selected infants their mothers are employed and working for at least 8 hour per day. The participants were divided according to gender (male; female) and age group as the following: 3-6 months; 7-9 months; and 10-12 months. Results: The prevalence of overweight or obesity was 15.2% in all studied infants. Overweight or obesity was more prevalent among female infants aged 3-6 months and among male infants aged 7-12 months. No infant (0.00%) regardless of gender or age group was underweight, stunting nor wasting per WHO standards of BMI for age z-score. Conclusion: Most infants of Jordanian working mothers seemingly have normal growth in weight and length and few of them were overweight or obese according to WHO standard of BMI for age z-score. These indicated that Jordan work polices support working mothers and their infants to have better health and development.
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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 | 0.003 |
| 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 | 0.000 |
| 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".