Heterogeneity in the association between a dietary pattern high in fat, sugar, and sodium and adverse pregnancy outcomes by maternal characteristics: a United States pregnancy cohort study
Bibliographic record
Abstract
BACKGROUND: "Precision nutrition" aims to recognize variation in response to dietary patterns to inform tailored advice based on behavioral, social, environmental, genetic, and metabolic factors. OBJECTIVES: We sought to identify characteristics of pregnant individuals that modify the associations between a high fat, sugar, and sodium diet and poor perinatal outcomes. METHODS: We used data from 8054 participants in the Nulliparous Pregnancy Outcomes Study: monitoring mothers-to-be (8 United States medical centers, 2010‒2013), a prospective cohort study. Usual periconceptional dietary intake was assessed at 6‒13 wk of gestation using a food frequency questionnaire. The exposure was a high fat, sugar, and sodium dietary pattern compared with all other diet patterns. The outcome was a composite of 1 or more perinatal outcomes: preeclampsia, gestational diabetes, preterm birth, or small-for-gestational-age birth. We used the doubly robust learner, which enables the use of machine learning to identify maternal characteristics that modify the effect of the dietary pattern on the composite outcome. RESULTS: Approximately 29% had a dietary pattern that was high in fat, sugar, and sodium. One quarter had any adverse pregnancy outcome. The confounder-adjusted association between a high fat, sugar, and sodium dietary pattern and risk of the adverse composite pregnancy outcome was stronger among certain subgroups of the cohort than others, including individuals with a higher BMI, lower socioeconomic status, and non-Hispanic Black race/ethnicity. For instance, compared with other diet patterns, intake of a diet high in fat, sugar, and sodium was associated with 5.9 excess cases per 100 pregnancies {adjusted risk difference 0.059 [95% confidence interval (CI): 0.012, 0.11]} among individuals living in a high-poverty neighborhood, but 2.3 excess cases per 100 pregnancies (0.023; 95% CI: -0.011, 0.057) among those residing in a low-poverty neighborhood. CONCLUSIONS: This work may provide clues that contribute to a deeper understanding of the heterogeneity in dietary responses in pregnancy.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".