Depressive symptoms during pregnancy in relation to fish consumption and intake of n‐3 polyunsaturated fatty acids
Bibliographic record
Abstract
An inverse association between depression and the n-3 fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), primarily obtained from fish consumption, is observed in both observational and experimental research and is biologically plausible. Study objectives were to examine whether prenatal depressive symptoms were associated with lower intakes of fish or EPA+DHA. Pregnant women (n = 2394) completed a telephone interview between 10 and 22 weeks' gestation in London, Ontario, 2002-05. Depressive symptoms were measured using the Center for Epidemiologic Studies - Depression Scale (CES-D). Intakes of fish and EPA+DHA were measured using a validated food-frequency questionnaire. Sequential multiple regression was used to examine associations of depressive symptoms with intake of fish and EPA+DHA, respectively, while controlling for sociodemographic, health and lifestyle variables. The mean CES-D score was 9.9 (SD 8.0). Intake of EPA+DHA was dichotomised at the median value of 85 mg/day. Fish consumption and intake of EPA+DHA were not associated with prenatal depressive symptoms after adjustment for confounders; however, depressive symptoms were significantly higher for lower intakes of EPA+DHA among current smokers and women of single/separated/divorced marital status. The adjusted difference in CES-D scores between intake categories of EPA+DHA was -2.4 [95% CI -4.2, -0.4] for current smokers and -2.8 [95% CI -5.2, -0.4] for women of single marital status. Although pregnant women may be at risk for low concentrations of EPA and DHA, an association between low intakes of EPA+DHA and increased depressive symptoms was only observed among current smokers and women of single marital status.
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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 | 0.000 | 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".