The association of maternal plant-based diets and the growth of breastfed infants
Bibliographic record
Abstract
Background:Studies are needed to further understand how different plant-based dietary patterns of mothers relate to infant growth. Thus, we investigated the association between maternal plant-based diets and infant growth in breastfed infants during the first 4 months of life.Methods:This cross-sectional study included 290 Iranian mothers and infants. Maternal dietary intake was assessed using a 168-question validated semi-quantitative food frequency questionnaire (FFQ). Three plant-based diet indices (PDIs) were then created to evaluate dietary intakes. Eighteen food groups were classified in three main categories by scoring method: wholeplant diet, healthy plant diet, and animal and unhealthy plant diet.Results:Participants in the top tertile of unhealthy PDI (uPDI) had a lower intake of potassium,phosphorus, zinc, magnesium, calcium, folate and vitamin C, B1, B2, and B3. The upper tertileof uPDI was associated with stunting at 4-month in infants (uPDI: odds ratio [OR] = 3.27, 95%CI= 1.32, 8.10). There were no significant associations between plant-based diet scores and anthropometric indices, including weight, weight status and head circumference (P> 0.05).Conclusion:In conclusion, higher adherence to uPDI may be associated with stuntingamong Iranian infants. Other PDIs were not associated with anthropometric measures. Future studies are needed to further understand the association between plant-based diets and infant growth.
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 | 0.000 |
| 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) | 0.001 | 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".