Contributing factors for low consumption of animal food among children aged 6-23 months in alive and thrive intervention areas of Bangladesh
Bibliographic record
Abstract
Introduction: In Bangladesh about two-thirds of total food consumption is rice as \nmain staple food, especially for the poor, in addition to some vegetables, pulses and \nsmall quantities of fish, meat, egg, etc. if and when available. The similar dietary \npattern and practices were found for under-two children in the intervention areas of \nAlive and Thrive (A& T) project where mothers were counseled on appropriate \ncomplementary feeding practice as a component of Infant and Young Child Feeding \n(IYCF). BRAG-RED intended to explore these issues to recognize the gaps that might \nbe addressed to increase the consumption of protein from animal foods among the \nchildren through the IYCF interventions in A& T areas. \nObjective: This study aims to identify the barriers leading to low consumption of \nanimal foods by children aged 6-23 months in A & T intervention areas; and to assess \ntheir knowledge and practices of dietary intake through 24-hour recall. \nMethods: Mixed methods were chosen to find comprehensive information in 12 \nupazi/as, 3 from each of Barguna, Sylhet, Chittagong and Dinajpur districts. The Pusti \nKormi (PK), Shasthya Shebika (SS), and mothers/caregivers enrolled in the A& T \nintervention areas were selected for interview; and those who had involvement in \nproviding the services. In addition, other programme staff from the supervisory level \nwho involved in providing services was also interviewed. \nFindings: The study revealed from the quantitative findings that, in intervention areas \nintake from animal sources was 7 -12g at 1 years and 18g at 2 years where the \nrecommended dietary average (RDA) was 14g for less than one years and 16g for \nless than 2 years. On the other hand in control areas at both age groups the intake \nratio was lower. From the qualitative findings majors contributing factors for feeding \nfrom animal sources was, lack of knowledge, lack of awareness on protein deficiency, \nbarriers from the family members, myth, etc. Almost similar barriers was found from \nthe quantitative findings like; financial crisis (80.3%), mothers lack of knowledge and \nawareness (67%), unavailability of the products in near local market (5%), etc. \nConclusion: Food consumption from animal sources might be increased among less \nthan two years children by reducing those barriers, by strengthening efforts in the \nawareness development process in creating demand for appropriate IYCF services at \nhousehold level especially intake foods from animal sources to improve children's \nnutritional 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".