Malnutrition and Associated Factors with Nutritional Status among Orphan Children: An Evidence-Based Study from Nepal
Bibliographic record
Abstract
Background: Malnutrition is a common public health problem among children in low and middle-income developing countries. Orphan's children are vulnerable and neglected groups in society and are more prone to malnutrition. The study aims to identify the prevalence of underweight, stunting, thinness, and factors associated with nutritional status among orphan children. Methods: Quantitative method & analytical cross-sectional research design were used to assess the nutritional status and its associated factors among orphan children in Pokhara Valley, Nepal. The sample size of 160 children was obtained by a simple random technique. The semi-structured questionnaire, digital bathroom scale, stadiometer was used as the data collection technique. Data management and analysis were done from Epi-info, SPSS 25 version, and WHO Anthro plus. Findings: The majority of children were malnourished (80.6%) with the prevalence of stunting (55.1%), thinness (13.8%), and overweight (6.9%). Prevalence of underweight, stunting, and thinness was high among the boys (85.5%, 26.3%, and 15.8%), but overweight was more prevalent among the girls (7.1%). Ethnicity, sex, age, stay duration in an orphanage, and education of caregivers was associated with the nutritional status of orphan children (p <0.05). Non-privileged children and children below 11 years were more prone to malnutrition. Conclusion: Malnutrition is highly prevalent in orphan children and needs to be addressed. There is still limited study available on the nutritional status of orphan children in Nepal. Nutritional status should be monitored regularly for early identification and timely intervention of malnutrition to promote the nutrition health status of orphan children
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".