Maternal Essential Fatty Acid Status During Pregnancy and Postpartum in the Alberta Pregnancy Outcomes and Nutrition (APrON) Study and Infant Outcomes
Bibliographic record
Abstract
Docosahexaenoic (DHA) and arachidonic (AA) acids are essential fatty acids found in breast milk and are important for the infant’s brain development and cognitive functions such as those that regulate sleep and crying. The overall goal of this research was to use a large maternal infant cohort, Alberta Pregnancy Outcomes and Nutrition (APrON), to establish the relationship between maternal intake and status of DHA and AA across pregnancy and at three months postpartum, their levels in breast milk and infant sleep and crying outcomes. The cohort participants were mainly older women with a healthy BMI and high socioeconomic status. Dietary intake of DHA and AA was estimated using 24-hr recalls collected at each trimester and at three months postpartum. Food Processor (version 10.6; ESHA Research, Salem, Ore., USA) output was used to estimate AA (n=129, n=564, n=497, n=485 at the four time points, respectively) and a previously established nutrient n-3 database for DHA. DHA from supplement intake was estimated using Supplement Intake Questionnaire (SIQ) and the total DHA intake form diet and supplement was included in the analysis at each time point (n=239, n=998, n=882, n=827, respectively). Maternal blood samples were collected at the same four time points, and the relative percent and concentration of fatty acids in serum PL were assessed by gas liquid chromatography (GLC) (n=280, n=1059, n=713, n=907, respectively). Breast milk samples (n=1038) were obtained at the third month of lactation, and the relative fatty acid composition of DHA and AA was determined using GLC. Brief Infant Sleep Questionnaire (n=785) and Crying Patterns Questionnaire data (n=839) were used to assess the reported durations of infant sleep and crying, and whether parents considered them to be problematic. Statistical analyses were completed using SPSS Version 23.0 (IBM Corporation, Armonk, NY, USA). While AA intake did not change during pregnancy or lactation, DHA intake increased from the second to the third trimester (p=0.01), and the median DHA intake estimate for the cohort did not meet the European Consensus recommendation of 200 mg/day at any time point in the study. The serum concentrations of both DHA and AA increased during pregnancy and decreased postpartum and the relative proportion of DHA followed the same pattern (p<0.001 for all). Postpartum, DHA concentration in serum PL was 35±20 µg/mL (2.0±0.9%) and AA at 136±56 µg/mL (7.9±2.1%). The DHA proportion of fatty acids in breast milk (median: 0.2%, IQR: 0.1-0.3%) was found to be lower than the reported global average, while AA (median: 0.8%, IQR: 0.5-1.4%) was found to be higher. Breast milk content of DHA was significantly correlated to postpartum DHA concentration in the serum and estimated DHA intake (p<0.001 for all). The proportion of AA in breast milk was found to directly relate to serum concentration (p<0.001) but not dietary intake. Using the data in this study, to achieve a breast milk concentration (0.30-0.64%), women need to consume DHA of 340-1600 mg/day or maintain a maternal PL DHA status of at least 45 µg/mL or 2.7% (w/w) of total serum PL fatty acids. No relationships were found between DHA or AA in breast milk and parental reported infant sleep or crying behaviour. In summary, approximately 75% of women in the APrON cohort were not meeting current dietary recommendations for DHA. The mean concentration of DHA in breast milk at three months postpartum was below the level considered optimal. Using this cohort, we have identified dietary intake recommendations and a maternal status reference that could be useful as a target for dietary interventions to optimize the concentration of DHA in breast milk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".