Maternal Diet during Exclusive Breastfeeding can Predict Food Preference in Preschoolers: A Cross-Sectional Study of Mother-Child Dyads in Enugu, South-East Nigeria
Bibliographic record
Abstract
Background: The relationship between food preference in early childhood and prenatal exposure to flavor in the amniotic fluid is well documented. Although its association with flavor transmission in the breast milk has also been noted, it is poorly reported in this country. Objective: The present study aims to determine the relationship between mothers’ dietary exposure during exclusive breastfeeding and food preference in their preschool-aged children. Methods: Two hundred and twenty (220) mother-child dyads who met the study criteria were enrolled. A pre-tested, structured questionnaire was administered to the mothers. The relationship between maternal consumption of flour-based snacks and staple foods during exclusive breastfeeding and the child’s preference for these foods was determined using risk estimates. After controlling for potential confounders, logistic regression was used for multivariate analysis. Statistical significance was determined at p < 0.05 and all the risk estimates were presented as odds ratios (OR) at 95% confidence intervals (CI). Results: The relationship between daily maternal exposure to staple foods during exclusive breastfeeding and the children’s preference for this variety of food was not statistically significant (p = 0.847, OR= 1.083, 95% CI = 0.481-2.437). However, the children’s preference for flour-based snacks was significantly related to weekly or fourth-nightly maternal exposure to similar diet during exclusive breast feeding (p = 0.035, OR = 2.405, 95% C.I = 1.064 - 5.435). Conclusion: Transmission of flavor in the breast milk may contribute in shaping children’s feeding behavior early in life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".