Association between household food insecurity and infant growth in rural Bangladesh
Bibliographic record
Abstract
Food insecurity is a global concern, yet its association with child growth is not fully understood. This study in rural Bangladesh explored associations between household food insecurity, using standardized questions, and infant growth. We asked a published 10‐item, 6‐mo household food insecurity questionnaire at 6 and 12 mo postpartum to 6,333 mothers participating in an antenatal micronutrient supplementation trial. Child weight, length and mid‐upper arm circumference (MUAC) were measured at 6 and 12 mo. We compared growth to ordinal individual item and summed scores. Infant weight, length and MUAC at 6 and 12 mo of age were associated in a dose‐response direction with graded responses to each of 3 questions related to having few square meals, worrying about food, and needing to buy rice often (all p <0.05). Differences in mean weight, length and MUAC across the scale at 6 and 12 mo were 0.51 and 0.48 kg, 1.63 and 0.87 cm, and 0.64 cm and 0.39 cm, respectively. Updated surveillance data will be presented. Food insecurity is associated with poorer infant growth in rural Bangladesh. Grant Funding Source : Gates Foundation, Sight and Life, and a DSM doctoral fellowship for international micronutrient research
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".