Diabetes in pregnancy among First Nations women in Alberta, Canada: a retrospective analysis
Bibliographic record
Abstract
BACKGROUND: In addition to increasing the risk of adverse birth outcomes, diabetes in pregnancy is thought to be an important driver of the epidemic of type 2 diabetes affecting Canada's First Nations population. The relative contributions of gestational diabetes mellitus (GDM) and pre-existing diabetes are not well understood. We generated a comprehensive epidemiological profile of diabetes in pregnancy over a 10-year period among the First Nations population of Alberta, Canada. METHODS: De-identified administrative data for 427,058 delivery records were obtained for the years 2000-2009. Pregnancy risk factors and delivery outcomes were described and compared by ethnicity (First Nations vs. non-First Nations) and diabetes status. Age-adjusted prevalence values for GDM and pre-existing diabetes were calculated and were compared by ethnicity. Longitudinal changes over time were also examined. Predictors were explored using logistic regression analysis. RESULTS: First Nations women had more antenatal risk factors and adverse infant outcomes that were compounded by diabetes. First Nations descent was an independent predictor of diabetes in pregnancy (p < 0.001). GDM prevalence was significantly higher among First Nations (6.1%) compared to non-First Nations women (3.8%; p < 0.001), but prevalence values increased significantly over time only in non-First Nations women (4.5 average annual percent change; p < 0.05). The prevalence of pre-existing diabetes was stable over time in both groups, but First Nations women experienced a 2.5-fold higher overall prevalence compared with non-First Nations women (1.5% vs. 0.6%, respectively; p < 0.001). CONCLUSIONS: Although First Nations women experience a higher overall prevalence of diabetes in pregnancy, the lack of increase in the prevalence over time is encouraging. However, because high-risk pregnancies and poor outcomes are more common among First Nations women, particularly those with diabetes, strategies to improve perinatal care must be implemented.
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 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 | 0.001 | 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 | 0.000 |
| 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".