Early life nutrition, the developing immune system and subsequent allergic manifestations
Bibliographic record
Abstract
Over the last half-century, chronic disease incidence, including allergic manifestations (AM), has increased exponentially in developed nations and amongst the wealthy in developing nations. Concurrently, there has been a “nutrition transition” in the same populations. Dietary patterns have shifted from a prudent diet (high fruit and vegetable-, and omega-3 fatty acid intake; low omega-6 fatty acid intake) to a western-style diet (higher levels omega-6 fats, lower amounts of fresh fruits and vegetables, and omega-3 fats). While diet can impact health at any life stage, it is likely to be most important during the fetal and infancy periods, when the immune system is immature. Based on an extensive review of the literature, we considered this hypothesis for the 3 nutritional progressions from fetal life through infancy: prenatal nutrition, breastfeeding and introduction of solid foods. While there is little conclusive evidence to support that a prudent diet is protective against AM especially after birth, modest evidence suggests that a prenatal maternal nutrition high in n-3 and micronutrients (e.g. vitamins C, D and E) protect against AM. This indicates that there may be a window of opportunity during fetal development in which allergic manifestation risk may be altered. The effect of breastfeeding on the prevention AM is unresolved. Despite this, exclusive breastfeeding to 4-6 months should be encouraged as human milk contains numerous immunological properties and is associated with other health benefits. If breastfeeding is not possible, hydrolyzed formulas seem to confer a greater protective effect than traditional formulas. Solid foods should be introduced at age 4-6 months. The order of introduction seems to have little effect on AM. At present, it is impossible to conclusively state that a particular dietary pattern or food will alter AM risk in infants. Implications for research and practice are also discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".