Children Malnutrition in Northwestern, Central and Southern Regions of Iran: Does Geographic Location Matter?
Bibliographic record
Abstract
INTRODUCTION: Malnutrition is one of the most important morbidity and mortality causes in children. In comparison with healthy children malnourished children are at higher risk of illness and death as 60 percent of more than 7 million deaths in children aged less than five years are attributed to the malnutrition. The present study is intended to determine the prevalence of malnutrition in West Azerbaijan and compare with Kermanshah and Isfahan provinces. MATERIALS & METHODS: The current survey is a cross-sectional study which is conducted with the aim of determining the nutritional status of children aged less than five years in three West Azerbaijan, Kermanshah and Isfahan provinces using ENA software and has been performed since 16th until 30th October, 2011 with the cooperation of the Office of Community Nutrition Improvement and the United Nations Children's Fund (UNICEF). Research data are collected by questionnaire and according WHO index, percentage of children with malnutrition (underweight, wasting, stunting) were calculated. Chi-square test was used to assess the relationship between variables and malnutrition. RESULTS: The rate of underweight, stunting, and wasting in West Azerbaijan was 2.3%, 7.3% and 1.4%, respectively. Wasting rate in boys was higher than in girls while stunting and underweight were more common in girls but differences were not significant. Results showed that the percentage prevalence of stunting in rural areas was higher than in urban areas, and this difference was significant. (p < 0.03) prevalence of overweight in West Azarbijan, Kermanshah and Isfahan was 5.1%, 4.5% and 3.7%, respectively. Also, Prevalence of obesity in West Azarbijan, Kermanshah and Isfahan was 1.3%, 0.7% and 0.1%, respectively. CONCLUSION: Given the differences between various provinces and regions of the country which are as a result of the differences between the levels of development in these areas, the necessity of designing and implementing targeted strategies are required for different areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".