Determinants of fatty acid content and composition of human milk fed to infants born weighing <1250 g
Bibliographic record
Abstract
BACKGROUND: Infants born at very low birth weight (VLBW) are vulnerable to deficits in fatty acids (FAs) but little is known of factors that influence the intakes or composition of their human milk feeds. OBJECTIVES: We aimed to identify sources of variability in the fat composition of human milk fed to VLBW infants and examine the impact of milk source (mother's own or donor) on fat and FA intakes. METHODS: Serial samples of mother's milk (n = 476) and donor milk (n = 53) fed to infants born weighing <1250 g (n = 114 infants from 100 mothers) were collected [Optimizing Mothers' Milk for Preterm Infants (OptiMoM) randomized clinical trial]. Fat and FA were analyzed using a mid-infrared human milk analyzer and GC with flame ionization detection. RESULTS: At full enteral feeding, donor milk is estimated to provide 1.3 g · kg-1 · d-1 less total fat than mature mother's milk (recommended intake: 4.8 g · kg-1 · d-1), and 5-9 mg · kg-1 · d-1 less DHA (22:6n-3) and arachidonic acid (20:4n-6) (estimated average requirement: 55-60 and 35-45 mg · kg-1 · d-1, respectively) than colostrum or transitional milk. Similar deficits were observed in measured intakes of a subset of OptiMoM infants. In multivariable-adjusted models, maternal ethnicity had medium to large [≥0.5 SD score (SDS)] effects on DHA, SFAs, and MUFAs. Mothers with prepregnancy BMI in overweight and obese categories had higher milk total fat (β: 0.35; 95% CI: 0.10, 0.61 and β: 0.46; 95% CI: 0.16, 0.77 SDS, respectively). Those with BMI ≥30 in addition had higher proportions of SFAs (β: 0.61; 95% CI: 0.33, 0.89 SDS) and lower DHA (β: -0.54; 95% CI: -0.89, -0.20 SDS). Other factors, such as gestational age and income, were also associated with FA composition. CONCLUSIONS: The fat and FA content of human milk fed to VLBW infants is variable. Care must be taken to ensure fat and FA intakes meet recommendations, particularly when feeding a high proportion of donor milk.This trial was registered at clinicaltrials.gov as NCT02137473.
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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 | 0.003 |
| 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 | 0.001 | 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".