Measuring and Managing Obesity in Pregnancy Using the Edmonton Obesity Staging System: A Scoping Review
Bibliographic record
Abstract
Emerging evidence and clinical practice guidelines have highlighted that obesity, defined as a chronic disease characterised by excess or dysfunctional adipose tissue, may not be accurately measured or understood by solely relying on body mass index (BMI) which is a measure of size not functionality. An alternative to BMI, as proposed in the Canadian Adult Obesity Management Guideline, is the use of the Edmonton Obesity Staging System (EOSS). While the EOSS has been evaluated in both adult and paediatric populations, pregnant individuals remain an underrepresented clinical group in its application. Prenatal care relies on BMI for measurement of maternal obesity; however, the EOSS may be an adjunct or alternative method to consider. This scoping review aimed to summarise previous research on EOSS in pregnancy and to advise future directions. Only three cohort studies were identified, emphasising a critical gap in obesity research. Both BMI and higher EOSS stages (i.e., 3 and 4) were associated with prenatal complications (e.g., preeclampsia, venous thromboembolism, wound complications). Given that EOSS has been used in other populations and is noted to be an effective patient-centred tool to diagnose and manage obesity, future work may explore its use in pregnancy both in comparison to and in conjunction with BMI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".