The next generation cohort: a description of a cohort at high risk for childhood onset type 2 diabetes
Bibliographic record
Abstract
Children of mothers with youth-onset (<18 years) type 2 diabetes (T2D) are at increased risk of youth-onset T2D. In Canada, the highest reported prevalence of youth-onset T2D is in First Nation youth, some of whom harbor a unique genetic predisposition HNF1α polymorphism which has been associated with age of onset and clinical presentation. To describe the characteristics of the Next Generation birth cohort (n=260) at 7-9 years (n=88) and 14-16 years of age (n=27). This is a cross-sectional study of offspring exposed in utero to T2D (Next Generation Birth Cohort). Annual assessments from age 7 include height and weight, and biochemical testing (glucose, insulin, lipids, HbA1c). Descriptive statistics were employed. χ2 tests and repeated-measures ANOVA were used to compare categorical and continuous characteristics, respectively. In total, 11.9% of the total cohort have developed T2D. Of those 14-16.9 years of age, 16.0% have developed T2D. 92% of the offspring ages 7-9 and 70.3% of offspring ages 14-16 are overweight or obese. Children had a significantly higher body mass index z-score than adolescents (2.9 v. 1.5, P=0.001). Comparing the different HNF1α genotypes (G/G wildtype, G/S heterozygote, S/S homozygote); HbA1c (GG: 5.5% v. G/S: 5.7% v. S/S: 8.8%; P=0.0052), insulin (GG: 103 v. G/S: 202; P=0.05) and T2D status (G/G: 5.7% v. G/S: 28.1% v. S/S: 72.7%; P<0.0001) were significantly different between groups. T2D is very common among adolescents of mothers with youth-onset T2D. Early childhood obesity and the HNF1α G319S allele are associated with the incidence of T2D in the Next Gen offspring.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".