Motivators for Adherence and Drivers of Taboo‐Breaking Behaviour Regarding Food Taboos Among Rural Pregnant Women in Bangladesh: Findings From Formative Research
Bibliographic record
Abstract
Understanding the influence of cultural practices on maternal health is crucial in addressing the nutritional challenges faced by pregnant women in rural Bangladesh. Despite improvements in maternal and child health indicators, food taboos remain prevalent, impacting nutritional and health outcomes of vulnerable populations. This qualitative study explored food taboos and factors related to their adherence or breaking, among rural pregnant women in Bangladesh, where a total of 90 participants, including 21 pregnant women, 23 mothers-in-law, 20 husbands, and 26 healthcare workers, were interviewed through 29 in-depth interviews and 11 focus group discussions. Nearly half of the participants adhered to food taboos, citing beliefs about their negative consequences on pregnancy and baby health. Commonly restricted animal source foods included white carp, trout, duck meat, and mutton, due to fears of convulsions, speech disorders, or undesirable traits in the baby. Raw papayas and pineapples were avoided due to beliefs they could cause miscarriage. Adherence to these taboos was related to the pregnant mother's desire to avoid harm to her child, preference for vaginal delivery, avoid financial stress of caesarean section, profound respect for her elders, early age at marriage, and primiparity. Factors enabling the breaking of food taboos included nutritional counselling by healthcare workers, increased family understanding of maternal nutrition, reduced reinforcement of taboos, and the lack of negative consequences from consuming tabooed foods. The findings underscore the need to use scientific evidence to challenge food taboos by enhancing nutritional counselling programmes and engaging family members and community elders to foster dietary changes for pregnant women.
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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".