Comparison of Human Milk Fatty Acid Composition of Women From Cambodia and Australia
Bibliographic record
Abstract
BACKGROUND: Human milk is a rich source of omega-3 long-chain polyunsaturated fatty acids, which are postulated to be important for brain development. There is a lack of data on the human milk fatty acid composition of Cambodian women compared with data from Western women. Research Aim: The aim of this study was to determine the human milk fatty acid composition of women living in Cambodia and compare it with that of women living in Australia. METHOD: Human milk samples from Cambodian ( n = 67) and Australian ( n = 200) mothers were collected at 3 to 4 months postpartum. Fatty acid composition was analyzed using capillary gas chromatography followed by Folch extraction with chloroform/methanol (2:1 v/v), and fat content was measured gravimetrically. RESULT: Compared with Australian participants, human milk from Cambodian participants contained a significantly lower level of total fat (2.90 vs. 3.45 g/dL, p = .028), lower percentages of linoleic acid (9.30% vs. 10.66%, p < .0001) and α-linolenic acid (0.42% vs. 0.95%, p < .0001), but higher percentages of arachidonic acid (0.68% vs. 0.38%, p < .0001) and docosahexaenoic acid (0.40% vs. 0.23%, p < .0001). CONCLUSION: Differences in human milk fatty acid composition between Cambodian and Australian participants may be explained by differences in the dietary patterns between the two populations.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".