Follow‐up and growing‐up formula promotion among Mexican pregnant women and mothers of children under 18 months old
Bibliographic record
Abstract
Milk formula sales have grown globally, particularly through follow-up formulas (FUF) and growing-up milks (GUM). Marketing strategies and weak regulatory and institutional arrangements are important contributors to caregivers' decisions about child feeding choices. This study describes maternal awareness, beliefs, and normative referents of FUFs and GUMs among Mexican pregnant women and mothers of children 0-18 months (n = 1044) through the lens of the theory of reasoned action (TRA). A cross-sectional survey was undertaken in two large metropolitan areas of Mexico. Descriptive analyses were conducted following the constructs of the TRA. One-third of the participants had heard about FUFs, mainly through health professionals (51.1%) and family (22.2%). Once they had heard about FUFs, the majority (80%) believed older infants needed this product due to its benefits (hunger satisfaction, brain development, and allergy management). One quarter of the participants were already using or intended to use FUFs; the majority had received this recommendation from doctors (74.6%) and mothers/mothers-in-law (25%). Similarly, 19% of the women had heard about GUMs. The pattern for the rest of TRA constructs for GUMs was similar to FUFs. Mexican women are exposed to FUFs and GUMs, once women know about them, the majority believe older infant and young children need these products, stating perceived benefits that match the poorly substantiated marketing claims of breast-milk substitutes. Health professionals, particularly doctors, act as marketing channels for FUFs and GUMs. Marketing of FUFs and GUMs represents a threat to breastfeeding in Mexico and a more protective regulatory and institutional environment is needed.
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 | 0.001 | 0.002 |
| 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".