Does the impact of a plant-based diet during pregnancy on birth weight differ by ethnicity? A dietary pattern analysis from a prospective Canadian birth cohort alliance
Bibliographic record
Abstract
OBJECTIVE: Birth weight is an indicator of newborn health and a strong predictor of health outcomes in later life. Significant variation in diet during pregnancy between ethnic groups in high-income countries provides an ideal opportunity to investigate the influence of maternal diet on birth weight. SETTING: Four multiethnic birth cohorts based in Canada (the NutriGen Alliance). PARTICIPANTS: 3997 full-term mother-infant pairs of diverse ethnic groups who had principal component analysis-derived diet pattern scores-plant-based, Western and health-conscious-and birth weight data. RESULTS: No associations were identified between the Western and health-conscious diet patterns and birth weight; however, the plant-based dietary pattern was inversely associated with birth weight (β=-67.6 g per 1-unit increase; P<0.001), and an interaction with non-white ethnicity and birth weight was observed. Ethnically stratified analyses demonstrated that among white Europeans, maternal consumption of a plant-based diet associated with lower birth weight (β=-65.9 g per 1-unit increase; P<0.001), increased risk of small-for-gestational age (SGA; OR=1.46; 95% CI 1.08 to 1.54;P=0.005) and reduced risk of large-for-gestational age (LGA; OR=0.71; 95% CI 0.53 to 0.95;P=0.02). Among South Asians, maternal consumption of a plant-based diet associated with a higher birth weight (β=+40.5 g per 1-unit increase; P=0.01), partially explained by cooked vegetable consumption. CONCLUSIONS: Maternal consumption of a plant-based diet during pregnancy is associated with birth weight. Among white Europeans, a plant-based diet is associated with lower birth weight, reduced odds of an infant born LGA and increased odds of SGA, whereas among South Asians living in Canada, a plant-based diet is associated with increased birth weight.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".