Abstract 33: Population Trends in Gestational Diabetes From 2000-2019: An Emerging Urban Epidemic?
Bibliographic record
Abstract
Introduction: There is little information describing rates of gestational diabetes (GDM) over the last two decades among population sub-groups, particularly within an urban context. Hypotheses: Rates of GDM will increase over time, particularly among rural dwelling women and those living in low socio-economic neighbourhoods. Research Design and Methods: We performed a registry-based administrative cohort study of women that delivered a child between 2000 and-2019 (n = 293 514) in the entire province of Manitoba, Canada. GDM was defined as incident diabetes diagnosis between 21 weeks’ gestation and 6 weeks’ postpartum using ICD-10-CM codes (O24, E12-E14). Difference-in-differences analyses were used to compare incident rates of GDM during two time periods 2000-2009 (period 1) and 2010-2019 (period 2) for the entire population in Manitoba, Canada and among women in rural/urban areas, and low vs high income areas. Geospatial mapping examined changes in rates of GDM by neighbourhood-level. Results: Between period 1 and period 2, the number of deliveries increased from 51.3 /1000 (11,525 per year) to 53.8/1000 (12, 534 per year). During period 1 age standardized rates of GDM were 2 to 3-fold higher in women over 35 years old, compared to women 18-25 yrs (2.2 vs 4.7%). Between period 1 and period 2, incident rates of GDM in the province increased 3.5-fold (2.5 vs 8.7%), with trends more pronounced among women over 35 yrs compared to women 18-25 yrs (absolute difference-in-difference: 3.83%; 95% CI: 3.12 to 4.53%) and women living in urban areas, compared to women in rural areas (absolute difference-in-difference: 1.68%; 95% CI: 1.37 to 1.99%). Geospatial mapping suggests that the increased incidence of GDM in urban areas is occurring in neighbourhoods with a larger representation of new immigrants. Conclusions: Rates of GDM increased over 3-fold from 2000-2019, affecting 9% of pregnancies in 2019, particularly among women over 35 years old (14% of pregnancies) and women living in urban areas (10% of pregnancies). Geospatial mapping suggests urban trends in GDM are occurring in areas where recently immigrated women have settled.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".