Infant and young child feeding practices in two provinces of Afghanistan: results from two rounds of large country-lot quality assurance sampling surveys
Bibliographic record
Abstract
Background: As per NNS 2013, about 58% of the infants aged 0-5 months were exclusively breastfed. The data also shows that only 41% infants 6-8 months of age were introduced solid, semi-solid and soft foods. Further only 28% of children aged 6-23 months received foods from four or more food groups during last 24 hours preceding the survey. Suboptimal IYCF practices are therefore considered to be an important contributor to the high rates of under nutrition in Afghanistan. The program monitoring at two time points was conducted to inform the program about the current status of the program activities and any course correction required. It was also meant to inform the government and other stakeholders on the feasibility of program strategies in improving IYCF practices and recommendations for scale-up programs.Methods: The program monitoring was performed before and after the (IYCN) program roll out in Wardak and Laghman provinces of Afghanistan. To understand and monitor the status of process and program indicators, a Large Country-Lot Quality Assurance Sampling (LC-LQAS) study design was adopted.Results: Minimum acceptable diet was observed to be 54% (95% CI: 46%, 61%) in the second round, which was 44% (95% CI: 35%, 53%) in the first round.Conclusions: Minimum acceptable diet among the children of age group 6-23 months was found to be consistently doing well in both the rounds. LC-LQAS was found to be an apt method to estimate the IYCN indicators at time points with low resource use.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".