Type 2 Diabetes Mellitus in Children and Adolescents: Early Prevention and Non-Drug Therapy
Bibliographic record
Abstract
The global rate of type 2 diabetes mellitus (T2DM) in youth has increased dramatically in the last 30 years. This increase mirrors the global epidemic of childhood obesity. Studies show that, compared to adults who develop T2DM, youth with T2DM ultimately suffer from more harmful symptoms. The prevalence of T2DM and obesity in youth signals a significant public health issue that financially burdens governments, families, and individuals. Since evidence suggests that T2DM in youth is different from both type 1 and type 2 diabetes in adults, researchers and clinicians face many difficulties in developing new treatments. Most treatment efforts have relied on drugs; however, recent studies suggest that non-drug therapy also effectively reduces obesity and diabetic symptoms. Healthier eating, increased physical exercise, and positive mental health, are often underappreciated factors towards managing obesity. Yet these lifestyle changes empower both young and older patients to independently fight diseases and attain better health. To manage the global health risk of obesity, further research addressing the prevention and nondrug early intervention of T2DM and obesity in youth is urgently needed. The present review focuses on the latest updates in the field.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".