Inequalities in nutritional status among under five children in Haryana state, India: Role of social determinants
Bibliographic record
Abstract
Background: Under-nutrition is a major cause of ill health and childhood mortality in India. So far, little attempt has been made to assess whether improvements in nutritional status have masked widening socioeconomic inequalities or produced slower progress among the poor and the disadvantaged. Aims & objective: We undertook this study to estimate the burden of under-nutrition among children less than five years in four districts of Haryana and explore the inequalities in rates of malnutrition across different social and economic groups. Material & Methods: A community based cross-sectional survey was carried out in four districts of Haryana namely Ambala, Karnal, Panchkula and Yamunanagar. Multi-stage stratified random sampling technique was used to select 2763 children under 5 years of age. Standard anthropometric methods were used. Rates of underweight (WAZ ? -2 z-score), wasting (WHZ ? -2 z-score) and stunting (HAZ ? -2 z-score) were estimated. Multivariate logistic regression was used to determine risk factors and evaluate inequalities across population by social and economic sub-groups. Results: The prevalence of underweight, stunting and wasting in four districts of Haryana was 37.4%, 38.2% and 16.4% respectively. Similarly, 12.7%, 13.2% and 3.5% of under-weight children were severely underweight, stunted and wasted respectively. Age of the child, social group and wealth status were significant predictors of malnutrition. The odds of underweight and stunting increased among the poorest by 2.3 and 1.8 times respectively as compared to the richest category. Conclusion: There is persistent problem of under-nutrition in Haryana mostly among the poor, uneducated, and among children of women who do not take ANC care/ breastfeed. Actions on social determinants need urgent prioritization.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".