Dietary Diversity and Its Related Factors among Adolescents: A Survey in Ahvaz-Iran
Bibliographic record
Abstract
INTRODUCTION: Healthy growth and development essentially need a balanced diet of nutrients and vitamins which includes a variety of foods from different food groups. The primary aim of this study was to assess the dietary diversity (DD) and its related factors among adolescents' high school girls in Ahvaz-Iran. METHODOLOGY: This was a cross-sectional study which it was structured based on the WHO & FAO's dietary diversity questionnaire. The study population consisted of 506 high school girls aged 15 to 18. Data about diet, socio-demographic and anthropometric characteristics were gathered. A dietary diversity score (DDS) and anthropometric of girls were measured. The relation of DDS with anthropometric measures and economic situation were assessed. RESULTS: The mean DDS was 6.81±1.75. A total of 18.85% and 8.3% of participants were overweight and obese respectively. In participants with scores ? six, Body Mass Index, waist circumference and waist-hip ratio were slightly greater than in individuals with scores less than six, however it was not significant except for waist hip ratio. The Logistic Regression showed that; weak economical situation was a risk for poor DDS (OR= 3.5, CI= 1.06-10.6, p=0.03). CONCLUSION: The FAO's third version of guidelines is a good indicator for measuring DDS. The results of this study indicate that high school girls' knowledge and practice about dietary diversity are not good and need to be improved by educational classes.
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 | 0.001 | 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 | 0.000 |
| 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".