Health Status of Young Girls in Selected Area of Bangladesh
Bibliographic record
Abstract
Background:Adolescence, a period of transition between childhood and adulthood, occupies a crucial position in the life of human beings. Hence, it is essential to improve health status through interventions. Objective:To assess and compare nutritional status of adolescent school girls in nutritional intervention and non-intervention area. Methods: A cross-sectional analytic study was conducted at Laxmipur sadar upazila as nutrition intervention area & neighboring Chatkhil upazila as non–nutrition intervention area. A total of 367 adolescent girls of age 10-19 years were selected purposively of them 177 and 190 were selected from intervention and non-intervention area respectively. Anthropometric data of the study subjects were collected by using standard techniques. Body mass index (BMI) and anemia were classified according to WHO cut off levels. Results:Study reveals that hemoglobin status was 72.3% normal, 20.3% mild anemia and 7.3% moderate anemia in intervention area and 51.6% normal, 43.7% mild anemia and 4.7% moderate anemia in non-intervention area. Significant difference was found both BMI and hemoglobin status among intervention and non-intervention area. Significant difference was found between intervention and non-intervention area of different illness, typhoid and jaundice. Conclusion:This study concludes that health status was better in intervention area than non-intervention area so community-based intervention is effective for better health status of young girls.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
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".