Protein Requirements of Healthy Lactating Women Are Higher Than the Current Recommendations
Bibliographic record
Abstract
During lactation, a woman must eat an adequate amount of protein in order to maintain her own muscle mass, while also providing adequate nutrition to the infant through breast milk. The current Dietary Reference Intakes (DRI) for protein suggest, that healthy lactating women (0–6 mo postpartum) should consume an Estimated Average Requirement (EAR) of 1.05 g protein/kg/d. However, this recommendation is based on factorial calculations rather than direct experiments. Therefore, our objective was to determine the protein requirement for exclusively breastfeeding women, using the indicator amino acid oxidation (IAAO) technique. Eleven healthy women (31 ± 4.1y), exclusively breastfeeding (4.7 ± 1.2 mo postpartum), were randomly assigned to receive different test protein intakes ranging from 0.29–2.41 g/kg/d divided over 40 test intakes. Participants consumed eight hourly isocaloric and isonitrogenous meals, providing energy at 1.7 x resting energy expenditure. The diets consisted of a crystalline amino acid mixture based on the composition of egg protein, except phenylalanine and tyrosine which were maintained constant across intakes. Oxidation of the tracer amino acid (L-1–13C-phenylalanine), was used to determine protein requirements by measuring F13CO2 in breath samples, collected during each study day. A breakpoint (requirement) in F13CO2 was identified by linear regression crossover analysis. Our preliminary results suggest that the protein requirements for exclusively breastfeeding women (3–6 mo postpartum) is ∼1.7–1.9 g/kg/d. Our findings for dietary protein needs during lactation are higher than the current EAR of 1.05 g/kg/d recommended by the DRI, suggesting that the recommendations may be underestimated. Our results correspond well with our earlier findings of higher protein needs of 1.52 g/kg/d during late stages of pregnancy (∼36 wk gestation) determined using the IAAO method. Canadian Institutes of Health Research.
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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 | 0.000 |
| 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) | 0.002 | 0.001 |
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".