Mother's dietary diversity and association with stunting among children <2 years old in a low socio‐economic environment: A case–control study in an urban care setting in Dhaka, Bangladesh
Bibliographic record
Abstract
Mothers are often responsible for preparing nutritious foods in their households. However, the quality of mother's diets is often neglected, which may affect both mother's and child's nutrition. Because no single food contains all necessary nutrients, diversity in dietary sources is needed to ensure a quality diet. We aimed to study the association between mother's dietary diversity and stunting in children <2 years attending Dhaka Hospital of icddr,b, a diarrhoeal disease hospital in Dhaka, Bangladesh. A case-control study (n = 296) was conducted from November 2016 to February 2017. Data were collected from mothers of stunted children <2 years (length-for-age z score [LAZ] < -2) as "cases" and nonstunted (LAZ ≥ -1) children <2 years as "controls." Mothers were asked to recall consumption of 10 defined food groups 24 hr prior to the interview as per Guidelines for Minimum Dietary Diversity for Women. Among the mothers of cases, 58% consumed <5 food groups during the last 24 hr, compared with 45% in control mothers (P = 0.03). Children whose mothers consumed <5 food groups were 1.7 times more likely to be stunted than children whose mothers consumed ≥5 food groups (P = 0.04). Intake of food groups such as pulses, dairy, eggs, and vitamin A rich fruit was higher in control mothers. Proportion of mother's illiteracy, short stature, monthly family income
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".