Maternal and neonatal risk factors for type 1 diabetes mellitus among children in Newfoundland and Labrador
Bibliographic record
Abstract
This population-based case-control study was carried out to investigate mother and infant risk factors for diabetes among children aged 0 to 15 years. Maternal risk factors of interest included mother’s age, delivery method, marital status, education, mother’s T1DM status and hypertension. Infant risk factors included birth order, prematurity or full-term birth, size-for-gestational-age and birth weight. Diabetes cases were identified using the Newfoundland & Labrador Diabetes Database (NLDD) for childhood diabetes maintained by the Janeway Pediatric Research Unit. The Newfoundland and Labrador Centre for Health Information’s Live Birth System (LBS) was used to obtain mother’s demographic and clinical data related to the pregnancy and birth. Two-hundred and sixty-six cases identified from the NLDD were linked to the LBS. Three control subjects were selected for each case. Multivariate conditional logistic regression was carried out to assess the risk factors associated with the development of T1DM. C-section delivery was associated with increased risk of T1DM (HR 1.41, p=0.015) when birth weight and gestational age were included in the regression model. This study presented a unique opportunity to use clinical and administrative data to examine risk factors associated with T1DM, a health issue of great significance in Newfoundland and Labrador. Findings may have an impact on health practice, health care planning and future research related to T1DM among children.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".