Parent-Child Reciprocity in Infant Feedingand Infant Weight Development: Bio-Psycho-Social Interactions
Bibliographic record
Abstract
Rapid weight gain in infancy (RWG) is a risk factor for overweight in childhood and adulthood. Formula feeding (FF) is a hypothesised cause, although mechanisms are unclear (e.g. due to feeding from a bottle or the nutritional content of formula milk). Emerging evidence indicates biopsychosocial interactions between parental feeding and child weight, but few studies have examined infant feeding modality (IFM) and weight in the critical first year of life. Part one of this thesis (Studies 1-3) triangulates epidemiology and the twin design to examine biopsychosocial interactions in a population-based cohort of n=2404 British twins born in 2007 (Gemini). In Study 1, infants fed with combinations of breastfeeding and FF, compared to being exclusively breastfed (EBF), had steeper weight gain trajectories across the first year of life. Both FF infants and those breastfed from a bottle showed steeper weight gain than those EBF from the breast, implicating bottle-feeding as a potential mechanism in RWG. The weight gain of twins discordant for IFMs did not differ and pointed towards potential reciprocity in infant feeding decisions: twins fed with more bottle or formula were smaller than their co-twin in early infancy. Study 2 explored reciprocity using bi-directional epidemiological analyses and twins discordant for IFMs. Slower early weight gain, and maternal concern for slow weight gain, predicted the introduction of formula milk. Study 3 explored whether FF is responsive to children’s genetic liability towards slow early weight gain (i.e. gene-environment correlation), and whether breastfeeding buffers the expression of genetic influence on RWG (i.e. gene-environment interaction). No evidence of gene-environment interplay was found. The second part of this thesis (Study 4) describes the development of BRIGHT (Baby Responsive Intervention for Growth & Health Tracking), a digital intervention aiming to reduce RWG among FF infants by supporting responsive bottle-feeding, integrating insights from Studies 1-3.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".