Human Milk Micronutrients and Child Growth and Body Composition in the First 2 years: A Systematic Review
Bibliographic record
Abstract
Human milk (HM) provides a plethora of nutritional and non-nutritional compounds that support infant development. For many compounds, concentrations vary substantially among mothers and across lactation, and their impact on infant growth is poorly understood. We systematically searched MEDLINE, Embase, the Cochrane Library, Scopus, and Web of Science to synthesize evidence published between 1980 and 2022 on HM components and anthropometry through 2 y of age among term-born infants. Outcomes included weight-for-length, length-for-age, weight-for-age, body mass index (in kg/m2)–for–age, and growth velocity. From 9992 abstracts screened, 144 articles were included and categorized based on their reporting of HM micronutrients, macronutrients, or bioactive components. Micronutrients (vitamins and minerals) are reported here, based on 28 articles involving 2526 mother-infant dyads. Studies varied markedly in their designs, sampling times, geographic and socioeconomic settings, reporting practices, and the HM analytes and infant anthropometrics measured. Meta-analysis was not possible because data were sparse for most micronutrients. The most-studied minerals were zinc (15 articles, 1423 dyads) and calcium (7 articles, 714 dyads). HM iodine, manganese, calcium, and zinc concentrations were positively associated with several outcomes (each in ≥2 studies), whereas magnesium (in a single study) was negatively associated with linear growth during early lactation. However, few studies measured HM intake, adjusted for confounders, provided adequate information about complementary and formula feeding, or adequately described HM collection protocols. Only 4 studies (17%) had high overall quality scores. The biological functions of individual HM micronutrients are likely influenced by other HM components; yet, only 1 study analyzed data from multiple micronutrients simultaneously, and few addressed other HM components. Thus, available evidence on this topic is largely inconclusive and fails to address the complex composition of HM. High-quality research employing chronobiology and systems biology approaches is required to understand how HM components work independently and together to influence infant growth and to identify new avenues for future maternal, newborn, or infant nutritional interventions.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".