Oral rehydration therapy and Zinc treatment among diarrhoeal children in India: Exploration from latest cross-sectional National Family Health Survey
Bibliographic record
Abstract
BACKGROUND AND AIMS: Diarrhoea is one of the deadliest diseases and causing death among children in India, but no systematic attempt is made to understand it especially its control using oral rehydration salts (ORS). It is well known that use of ORS and Zinc have been effective in containing diarrhoea among children. An attempt is made using large scale national data set in India to understand use of ORS and Zinc to control diarrhoea and their associated factors among diarrhoeal children under five in India. METHODS: Publicly available most recent cross-sectional National Family Health Survey data in India was used for the study. The multi-stage cluster sampling design was used with 2011 Census of India as a sampling frame. Households were selected using a Systematic Random Sampling design from selected primary sampling units in rural and urban clusters. From the selected households, the eligible children were those who suffered from diarrhoea in the two weeks preceding the survey and were less than 5 years old. Using this criterion, out of 232,920 children in the survey of less than five years, 16,213 sample diarrheal children found to be available for the study. Both descriptive and inferential statistical techniques were used to analyse the data. RESULTS: Across India, 61% and 31% of the children were given ORS and Zinc respectively. However, combined ORS + Zinc treatment was only around 24%. The treatment of ORS, Zinc, and combined ORS + Zinc supplementations were significantly higher among younger children, children of 24-35 age group mothers, children from rich wealth index groups, belong to Hindu religion and general caste compared to their counterparts. The logistic regression results showed that consumption of ORS among diarrhoeal children under five years of age depends upon size of a child at birth. For instance, diarrheal children who were very small size at birth compared to very large at birth, had 39% lower odds of consuming ORS (AOR = 0.61; CI 0.48, 0.78; p<0.001). Another important variable is place of first treatment sought for diarrheal children. That is children who first sought treatment in private hospital compared to government hospital had 52% lower odds of ORS consumption. The logistic regression adjusted AORs are similar with Zinc and ORS + Zinc supplementations. CONCLUSIONS: To improve the coverage and management of childhood diarrhoea in India, planning activities should focus not only on distribution, and increasing knowledge of ORS preparation especially for urban slum residents and rural disadvantaged groups through demonstration. There should be also proper focus on providing ongoing pathways to ensure proper supply chains.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".