Maternal nutritional risk factors for pre-eclampsia incidence: findings from a narrative scoping review
Bibliographic record
Abstract
Abstract Background Pre-eclampsia is a leading cause of maternal mortality and morbidity that involves pregnancy-related stressors on the maternal cardiovascular and metabolic systems. As nutrition is important to support optimal development of the placenta and for the developing fetus, maternal diets may play a role in preventing pre-eclampsia. The purpose of this scoping review is to map the maternal nutritional deficiencies and imbalances associated with pre-eclampsia incidence and discuss evidence consistency and linkages with current understandings of the etiology of pre-eclampsia. Methods A narrative scoping review was conducted to provide a descriptive account of available research, summarize research findings and identify gaps in the evidence base. Relevant observational studies and reviews of observational studies were identified in an iterative two-stage process first involving electronic database searches then more sensitive searches as familiarity with the literature increased. Results were considered in terms of their consistency of evidence, effect sizes and biological plausibility. Results The review found evidence for associations between nutritional inadequacies and a greater risk of pre-eclampsia. These associations were most likely mediated through oxidative stress, inflammation, maternal endothelial dysfunction and blood pressure in the pathophysiology of pre-eclampsia. Maternal nutritional risk factors for pre-eclampsia incidence with the strongest consistency, effect and biological plausibility include vitamin C and its potential relationship with iron status, vitamin D (both on its own and combined with calcium and magnesium), and healthy dietary patterns featuring high consumption of fruits, vegetables, whole grains, fish, seafood and monounsaturated vegetable oils. Foods high in added sugar, such as sugary drinks, were associated with increased risk of pre-eclampsia incidence. Conclusion A growing body of literature highlights the involvement of maternal dietary factors in the development of pre-eclampsia. Our review findings support the need for further investigation into potential interactions between dietary factors and consideration of nutritional homeostasis and healthy dietary patterns. Further research is recommended to explore gestational age, potential non-linear relationships, dietary diversity and social, cultural contexts of food and meals.
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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 | 0.001 |
| 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) | 0.855 | 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".