Nutritional status of preschool children (aged 24 to 59 months) and chickpea production and consumption in Ethiopia
Bibliographic record
Abstract
Child under-nutrition is a major public health concern in developing countries including Ethiopia. Poor quality diet is the major determinant factor contributing to child undernutrition. Pulse crop production and consumption can improve children’s nutrient quality and dietary diversity. This study aimed to compare the nutritional status and child health, dietary intake, and wealth index of preschool children among pulse crop producer and non-producer families in Ethiopia. The study hypothesized that children living in families who grew pulses and consumed pulses (rather than selling their crop) would have better nutritional status due to availability of this protein-rich food source. A cross-sectional survey was conducted to determine demographic background, child feeding and caring practice and varieties and amount of pulse crop produced at the household level. A simple random sampling technique was used to select a sample of 432 children aged 24-59 months from central Ethiopia the Data was entered to SPSS v 20, WHO Anthro-plus software used to calculate the anthropometry indices, child dietary intake, level of chickpea production and consumption and wealth index, were computed using logistic regression. Chickpea (cicer arietinum L) was produced by 55.3% of the participants. Most (60.7%) of the children from chickpea producer families were high pulse consumers whereas only 15.5% of children from non-producers were high chickpea consumers (the difference in proportion is significant at p-value<0.001). Close to 60 % of the children of the non-producer families had a low dietary diversity score (that is <3) compared with 18.8 % from the producer families (p-value <0.001). The study revealed that nutritional status of children in both producer and non-producer families were 41.0 % stunted, 16.1 % underweight and 6.1 % wasted. Stunting and underweight were significantly inversely associated with chickpea production at p-value <0.001whereas for chickpea consumption, both stunting and underweight was significant at P < 0.05. However, wasting was not significantly associated with either production or consumption of chickpeas. In conclusion, chickpea production and consumption by families had a positive relationship with nutritional status of children. The authors recommend that engaging smallholder farmers in both chickpea production and consumption has potential in improving the dietary diversity and in turn benefit nutritional status of preschool children at the household level and therefore supporting smallholder farmer in chickpea production and consumption will help to contribute to decreasing the prevalence of under nutrition in the country. Key words: chickpea, preschool children, chickpea consumption, chickpea production, nutritional status
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".