Association between maternal dietary diversity during pregnancy and birth outcomes: evidence from a systematic review and meta-analysis
Bibliographic record
Abstract
Maternal nutrition is a key factor influencing birth and offspring health outcomes in later life. Dietary diversity (DD) is a proxy for the macro/micronutrient adequacy of an individual’s diet. There is inadequate comprehensive evidence regarding maternal nutrition during pregnancy, measured through DD and birth outcomes. This study aimed to provide extensive evidence on maternal DD during pregnancy and birth outcomes. A comprehensive search was performed using PubMed, HINARI, and Google Scholar databases up to January 17, 2024. Studies conducted among pregnant mothers and measuring maternal DD with an evaluation of birth outcomes (low birth weight, small for gestational age, preterm birth), in the global context without design restriction were included. The Newcastle Ottawa Scale and the Cochrane Risk of Bias tool were used to assess the risk of bias. The results are summarized in a table, and odds ratios were pooled where possible. Between-study heterogeneity was evaluated using I 2 statistics. Potential publication bias was assessed using a funnel plot and Egger’s regression test. To explore the robustness, a leave-one-out sensitivity analysis was conducted. Thirty-three studies were used to synthesize narrative evidence (low birth weight: 31, preterm birth: 9, and small for gestational age: 4). In contrast, 24 records for low birth weight, eight for preterm birth, and four for small for gestational age were used to pool the results quantitatively. Of the 31 studies, 17 reported a positive association between maternal DD and infant birth weight, 13 studies reported a neutral association (not statistically significant), and one study reported a negative association. Overall, inadequate DD increased the risk of low birth weight OR = 1.71, 95% CI; (1.24–2.18), with I 2 of 68.7%. No significant association was observed between maternal DD and preterm birth. Inadequate DD was significantly associated with small for gestational age (OR = 1.32, 95% CI; 1.15–1.49, and I 2 = 0.0%). Inadequate maternal DD is associated with an increased risk of low birth weight and small for gestational age but not preterm birth, underscoring the importance of promoting adequate DD during pregnancy. To address these issues, it is essential to implement and expand nutritional programs targeted at pregnant women, especially in low-resource settings, to ensure they receive diverse and adequate diets. Further research is needed to address the current limitations and to explore the long-term implications of maternal nutrition on child health. The study was prospectively registered on PROSPERO (registration number CRD42024513197). No funding was received for this study.
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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 | 0.018 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.030 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".