Maternal obesity management: a narrative literature review of health policies
Bibliographic record
Abstract
Maternal obesity rates are increasing significantly, posing substantial risks to both mothers and their children. This study aims to introduce health policies addressing maternal obesity, identify preventive interventions, and highlight scientific gaps necessitating further research.We identified documents through electronic searches in PubMed, CINAHL Plus, EMBASE, and grey literature sources (ministry of health websites, national gynecology and obstetrics associations) from January 2013 to August 2023, updated in June 2024. The inclusion criteria focused on English-language documents discussing interventions or health policies that promote weight loss through lifestyle changes during pregnancy.A total of 22 documents (10 studies and 12 guidelines) were included. 12 studies (N=1244) identified via databases; included two Clinical Practice Guidelines (CPGs) from Canada and Singapore. Other 10 CPGs sourced from governmental websites and national associations: England (1), Australia (1), New Zealand (1), combined Australia and New Zealand (1), Canada (3), USA (1), Ireland (1), Germany (1). 10 guidelines focused on obesity in pregnancy, two on weight management during pregnancy. Covered interventions across pre-pregnancy, pregnancy, and postpartum periods (9 guidelines); pre-pregnancy and pregnancy (2); exclusively postpartum (1). Seven guidelines offered evidence-based recommendations on maintaining healthy weight in mothers, largely based on expert opinions.Maternal obesity poses significant risks to both mothers and children, underscoring the need for effective health policies and systems. However, few countries have integrated adequate responses into their healthcare policies and guidelines for professionals. Limited evidence exists on optimal practices to improve reproductive health outcomes in obese women. Hence, the crucial need to developing comprehensive guidelines and proactive strategies to manage maternal obesity. These measures can improve outcomes and reduce healthcare costs. Increased focus on research and policymaking is essential to protect the health of mothers and their children.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".