Stuttering and Incident Type 2 Diabetes: A Population-Based Study of 2.2 Million Adolescents
Bibliographic record
Abstract
PURPOSE: To investigate the association between stuttering in adolescence and incident type 2 diabetes in young adulthood. METHODS: This nationwide population-based study included 2 193 855 adolescents of age 16 to 20 years who were assessed for military service between 1980 and 2013. Diagnoses of stuttering in adolescence were confirmed by a speech-language pathologist. Diabetes status for each individual as of December 31, 2016, was determined by linkage to the Israeli National Diabetes Registry. Relationships were analyzed using regression models adjusted for socioeconomic variables, cognitive performance, coexisting morbidities, and adolescent body mass index. RESULTS: Analysis was stratified by sex (Pinteraction = 0.035). Of the 4443 (0.4%) adolescent men with stuttering, 162 (3.7%) developed type 2 diabetes, compared with 25 678 (2.1%) men without stuttering (adjusted odds ratio [OR] 1.3; 95% CI, 1.1-1.6). This relationship persisted when unaffected brothers of men with stuttering were used as the reference group (adjusted OR = 1.5; 95% CI, 1.01-2.2), or when the analysis included only adolescents with unimpaired health at baseline (adjusted OR = 1.4; 95% CI, 1.1-1.7). The association was stronger in later birth cohorts, with an adjusted OR of 2.4 (1.4-4.1) for cases of type 2 diabetes before age 40. Of the 503 (0.1%) adolescent women with stuttering 7 (1.4%) developed type 2 diabetes, compared with 10 139 (1.1%) women without stuttering (OR = 2.03; 95% CI, 0.48-2.20). CONCLUSIONS: Adolescent stuttering is associated with an increased risk for early-onset type 2 diabetes among men.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".