Adolescent cognitive function and incident early-onset type 2 diabetes
Bibliographic record
Abstract
Background Cognitive function among apparently healthy adolescents has been associated with cardiovascular morbidity and mortality. We examined the relationship between global and subdomain cognitive scores in adolescence and early-onset type 2 diabetes (T2D) in men and women. Methods A nationwide, population-based study of 971,677 Israeli born adolescents (56% men; mean age 17.4 years) who were medically examined and their cognitive performance was assessed before compulsory military service during 1992–2010. Data included global and subdomain cognitive Z -scores (problem-solving, verbal abstraction and categorization, verbal comprehension, and mathematical abilities). Data were linked to the Israeli National Diabetes Registry. The relations between global and subdomain scores and incident T2D was determined using Cox proportional hazard models and logistic regression models. Analyses were conducted separately for men and women. Findings During 16,095,122 person-years, 3,570 individuals developed T2D. After adjustment, those in the low compared to the high quintile of global cognitive Z -score had the highest risk for T2D; HR 2.46, (95% CI 2.10–2.88) for men and 2.33 (95% CI 1.88–2.89) for women. A one-unit lower global cognitive Z -score was associated with 1.41 (95% CI 1.34–1.48) and 1.46 (95% CI 1.36–1.56) increased risks for men and women, respectively. The relationship was noted for the cognitive subdomains scores as well as for the global cognitive score, with no heterogeneity across cognitive subdomains. Interpretation This large nationally representative cohort suggests relationship between global, as well as subdomain cognitive scores in late adolescence, and incident early onset T2D in both sexes, which was independent of socioeconomic status. Funding None.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".