Variations in the nutritional status of school going children in four rural districts of PUNJAB, PAKISTAN
Bibliographic record
Abstract
Childhood is the time when maximum growth in relations to size, intellectual, emotional and psychological improvement takes place. Nutrition is an important factor for healthiness and wellbeing. The current study objective was to evaluate the nutritional status of school going children i.e., prevalence of underweight, stunting, and thinness across four districts of Punjab (Okara, Bhawalnagar, Layyah and Rajanpur). This cross-sectional study was carried out from April to August 2016 on 399 school going children (48 female and 351 male) of ages between 9 and16 years. Age, height, and weight had been taken in years, centimeter and kilogram respectively. According to the results, 23.1%, 17.5%, and 28.1% children were found to be underweight, slimness (thinness) and stunting in population (Okara, Bhawalnagar, Layyah, and Rajanpur districts). Moreover, 22.2% male children was found underweight, 30.8% stunted, and 13.7% was thin. Regarding the female participants 29.2% were underweight, 8.3% stunted, and 45.8% thinness, indicating female children has more prevalence of underweight and thinness than male children but the prevalence of stunting is more in male participants than female. These results will be useful for policy makers while developing nutritional intervention programs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".