Thinness among the Rural Primary School Children of Bali Gram Panchayat, Arambag, Hooghly District, West Bengal, India
Bibliographic record
Abstract
Background: Primary school age is a dynamic period of physical growth and mental development of the child. Research indicates that nutritional deficiencies and poor health in primary school age children are among the causes of low school enrolment, high absenteeism, early dropout and poor classroom performance. Chronic undernutrition is linked to slower cognitive development and serious health impairments later in life that reduce the quality of life. The thinness (low BMI for age) may be one of the tool to measure the level of undernutrition. Objective: The objective of the present study was to assess the different grades of thinness by using age and sex specific cut off values based on body mass index (BMI). Materials and Methods: The present cross-sectional study was conducted at Bali-Gram Panchayat, Arambagh, West Bengal, India. The data were collected from 618 rural Bengalee primary school children comprising of both boys (304) and girls (314) within the age group 5-11 years. The measurements (height in cm. and weight in kg) were taken following standard methods Thinness was evaluated using the age and sex specific cut-off points of BMI. Results: The overall (age combined) prevalence of thinness among the boys was slightly higher (83.2%) in comparison to the prevalence of thinness among the girls (81.5%). The prevalence of thinness was higher in case of lower age group children among both boys and girls and it gradually decreases with the increase of age. The rate of grade III thinness (30.5%) was greater among the girls than others while among the boys it was higher in grade I (32.9%) category. It indicates the severity of thinness was much more among the girls than the boys. Although there was no significant sex difference between the two sexes. Conclusion: The prevalence of undernutrition as measured by thinness was significantly higher than the national level scenario. In spite of the Mid Day Meal scheme which is running for more than 20 years, the result is dissatisfactory. The competent authority should look into the matter seriously for better nutritional and health condition of the 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".