Complementary feeding practices and associated factors among Mongolian children 6–23 months of age
Bibliographic record
Abstract
Little is known about factors influencing children's dietary intake in Mongolia, a country undergoing rapid nutrition transition. Using nationally representative data from the 2017 Mongolia National Nutrition Survey, we assessed the nutritional status of children aged <2 years and examined household, maternal, and child factors associated with feeding practices among children aged 6-23 months (n = 938). Multivariable logistic regression models were used to identify predictors of minimum meal frequency (MMF), minimum dietary diversity (MDD), and minimum acceptable diet (MAD). The prevalence of child stunting (length/height-for-age Z-score < -2 SD) was 6.3%, and the prevalence of overweight (weight-for-height Z-score > +2 SD) was 16.8%. The prevalence of anaemia and iron deficiency was 39.0% and 32.2%, respectively, and 73.5% and 85.5% of children had inadequate vitamin A and vitamin D status, respectively. Of children aged 6-23 months, 92.1% (n = 864) had MMF, 49.6% (n = 465) had MDD, and 43.8% (n = 411) achieved MAD. Increased household wealth was positively associated with all three indicators, whereas severe food insecurity was not associated with MMF, MDD, or MAD. Older child age (odds ratio, 95% CI: 1.09 [1.06, 1.12]; p < .001) and maternal dietary diversity (odds ratio, 95% CI: 2.36 [1.67, 3.34]; p < .001) were positively associated with child MDD. Nutrition-specific and nutrition-sensitive efforts are needed to improve the dietary quality of infants and young children in Mongolia and reduce the high burdens of child micronutrient deficiency and overweight in the country.
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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 | 0.000 |
| 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".