Nutritional Status and Diet Quality in 7-10 Years Old School Going Children
Bibliographic record
Abstract
Diet quality index is a measure of the quality of diet using a composite of recommendation regarding the consumption of foods and nutrients.This study was undertaken to assess the nutritional status and observe the diet quality and their association in 7-9 years old school going children.The sample comprised 120 boys and girls who were randomly selected from three schools.Background information was collected using self-designed questionnaire; socio economic status was assessed using Kuppuswamy's socioeconomic status scale.Anthropometric measurements included height and weight.Weight for age and height for age Z scores were calculated using WHO reference.Twenty four hour dietary recall was used to collect information regarding diet and nutrient intake; nutrient adequacy ratio and mean adequacy ratio were calculated.Healthy Eating Index-Canadian was used to assess diet quality of the subjects.According to weight for age Z score, 5.8% were underweight and 0.83% were severely underweight.Nutrient adequacy was inadequate for energy and iron, and was 75% higher than normal for fat.As per HEI-C diet quality of all the subjects was poor.Diet quality was not associated with anthropometric measurements of the subjects.Weak positive correlation was observed in nutrient intake and diet quality score, and no significant association was found between nutritional status and diet quality (p>0.05) and socio economic status and diet quality (p>0.0.5) of children.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".