Cognitive Function and the Risk for Diabetes Among Young Men
Bibliographic record
Abstract
OBJECTIVE: Diabetes is a risk factor for an accelerated rate of cognitive decline and dementia. However, the relationship between cognitive function and the subsequent development of diabetes is unclear. RESEARCH DESIGN AND METHODS: We conducted a historical-prospective cohort study merging data collected at premilitary recruitment assessment with information collected at the Staff Periodic Examination Center of the Israeli Army Medical Corps. Included were men aged 25 years or older without a history of diabetes at the beginning of follow-up with available data regarding their general intelligence score (GIS), a comprehensive measure of cognitive function, at age 17 years. RESULTS: Among 35,500 men followed for a median of 5.5 years, 770 new cases of diabetes were diagnosed. After adjustment for age, participants in the lowest GIS category had a 2.6-fold greater risk for developing diabetes compared with those in the highest GIS category. In multivariable analysis adjusted for age, BMI, fasting plasma glucose, sociogenetic variables, and lifestyle risk factors, those in the lowest GIS category had a twofold greater risk for incident diabetes when compared with the highest GIS category (hazard ratio 2.1 [95% CI 1.5-3.1]; P < 0.001). Additionally, participants in the lowest GIS category developed diabetes at a mean age of 39.5 ± 4.7 years and those in the highest GIS group at a mean age of 41.5 ± 5.1 years (P for comparison 0.042). CONCLUSIONS: This study demonstrates that in addition to a potential causal link between diabetes and enhanced cognitive decline, lower cognitive function at late adolescence is independently associated with an elevated risk for future diabetes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".