A Report on the Anthropometric and Health Characteristics of Foreign Students at SRBIAU in 2023-2024
Bibliographic record
Abstract
This study aims to assess the anthropometric and health characteristics of foreign students at the Science and Research Branch of Islamic Azad University in Tehran, Iran, during the 2023-2024 period. A total of 400 non-Iranian students participated in this cross-sectional study. Anthropometric measurements, including weight, height, BMI, waist circumference, and body composition, were taken using standardized equipment. Physical activity levels, blood pressure, fasting blood sugar, and heart rate were also assessed. The results revealed a significant prevalence of overweight and obesity (21.75%), particularly among females (31.93%), and high rates of hypertension and prediabetes. The study found a high proportion of sedentary individuals (70.6%), which is a key contributor to the observed health risks. These findings highlight the importance of addressing obesity-related health issues, particularly in the context of non-communicable diseases (NCDs), and their economic impact. This data is crucial for the development of targeted health policies, such as medical tourism and insurance adjustments for individuals at higher health risks. The study concludes that proactive measures are essential to prevent and manage the health conditions prevalent in this population.
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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 | 0.000 |
| 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 | 0.000 |
| 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 | 0.001 |
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".