Socioeconomic Inequalities in Child Malnutrition in Bangladesh: Do They Differ by Region?
Bibliographic record
Abstract
Socioeconomic inequality in child malnutrition is well-evident in Bangladesh. However, little is known about whether this inequality differs by regional contexts. We used pooled data from the 2011 and 2014 Bangladesh Demographic and Health Survey to examine regional differences in socioeconomic inequalities in stunting and underweight among children under five. The analysis included 14,602 children aged 0-59 months. We used logistic regression models and the Concentration index to assess and quantify wealth- and education-related inequalities in child malnutrition. We found stunting and underweight to be more concentrated among children from poorer households and born to less-educated mothers. Although the poverty level was low in the eastern regions, socioeconomic inequalities were greater in these regions compared to the western regions. The extent of socioeconomic inequality was the highest in Sylhet and Chittagong for stunting and underweight, respectively, while it was the lowest in Khulna. Regression results demonstrated the protective effects of socioeconomic status (SES) on child malnutrition. The regional differences in the effects of SES tend to diverge at the lower levels of SES, while they converge or attenuate at the highest levels. Our findings have policy implications for developing programs and interventions targeted to reduce socioeconomic inequalities in child malnutrition in subnational regions of Bangladesh.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".