A Scoping Review of Perinatal Outcomes for Canadian Individuals with Obesity 1980–2020
Bibliographic record
Abstract
Background: Pre-pregnancy obesity has long been associated with a higher risk of antepartum, intrapartum, and postpartum complications, leading to classifying all patients within the WHO obese body mass index range (BMI ≥30 kg/m2) as high-risk. Excessive risk classification can lead to over-treatment and iatrogenic harm. Research supporting these increased risks comes from a variety of countries with different baseline population health and perinatal health care systems. Recent research documents that parturients with high pre-pregnancy BMI can have uncomplicated pregnancies and births. Here, the relationship between obesity and perinatal outcomes in a Canadian population is investigated using Canada as a model of a country with stable nutrition sufficiency and universal access to health care. Methods: We searched electronic databases PubMed, Ovid MEDLINE, and CINAHL for peer-reviewed articles in English that examined perinatal outcomes of singleton pregnancies in Canada between 1980 and 2020 based on pre-pregnancy obesity as the exposure of interest. Results: The search yielded 1946 results. After full-text screening, 21 articles met criteria for analysis. The impact of obesity on preterm labour, preterm birth, post-term delivery, labour induction, post-partum hemorrhage, and parturient morbidity and mortality in Canada remains inconclusive. The risk of hypertensive disorders, gestational diabetes, shoulder dystocia, and cesarean section delivery was significantly elevated as BMI increased. Operative vaginal delivery was less common in those with pre-pregnancy obesity. Conclusions: Though certain adverse perinatal outcomes are associated with increasing pre-pregnancy BMI, given the wide range of results and range of risk values, further research is required to better delineate comorbid risk factors that contribute to poorer outcomes. Nation-specific outcomes that reflect the accessibility of perinatal care and population health are a necessary baseline for the development of accurate health management guidelines.
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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 | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.039 | 0.067 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".