Diet quality during pregnancy and its association with social factors: 3D Cohort Study (Design, Develop, Discover)
Bibliographic record
Abstract
Good diet quality during pregnancy provides adequate nutrition to support both the mothers and the fetus. The objective of this study is to describe the distribution of diet quality during pregnancy and to study the association between social factors and diet quality during pregnancy in a Canadian population. This study was based on 1535 pregnant women who provided dietary information in the 3D Cohort Study in Quebec, Canada. A 3-day food record was used to collect dietary intake in the second trimester of pregnancy. A Canadian adaption of the Healthy Eating Index (HEI-C) 2010 was used to quantify diet quality. Univariate and multiple linear regression models were used to calculate unadjusted and adjusted effect estimates and confidence intervals for the association between social factors and HEI-C. The mean HEI-C 2010 score in this study was 62.9 (SD: 11.2). Only 4.5% and 8.3% of the pregnant women consumed the recommended amounts of whole grains and 'greens and beans', respectively. Diet quality was lower in some subgroups of pregnant women. After multivariable adjustment, lower diet quality was observed in participants who were less educated, younger, overweight or obese before pregnancy, or parous. There was an interaction between ethnicity and immigration status on diet quality in pregnancy. These findings could be useful for health practitioners and policymakers in developing strategies to improve the diet quality of pregnant women.
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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 | 0.004 | 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) | 0.000 | 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".