Diabetes in the young: a population‐based study of South Asian, Chinese and White people
Bibliographic record
Abstract
AIMS: Rates of diabetes mellitus in the young have not been quantified on a population level, particularly in South Asian and Chinese populations, which bear high rates of diabetes. We determined the incidence of diabetes (Type 2 diabetes and diabetes using insulin only) and rates of hospitalizations among South Asian, Chinese and White people aged 5-29 years with newly diagnosed diabetes. METHODS: People with newly diagnosed diabetes (1997-2006) in British Columbia, Canada were identified using population-based administrative data and pharmacy databases. Age-standardized incidence rates were calculated for people with diabetes prescribed insulin only and those with Type 2 diabetes. They were followed for up to 8 years for all hospitalizations and diabetes-related complications. RESULTS: There were 712 South Asians, 498 Chinese and 6176 White people aged 5-29 years with diabetes. Most youth with diabetes had Type 2 diabetes (South Asian 86.4%; Chinese 87.1% and White 61.8%). The incidence of diabetes on insulin only was highest in White people compared with the other groups. The incidence of Type 2 diabetes was highest in South Asians, particularly in 20-29-year-olds, with rates 2.2 times that of White people and 3.1 times that of Chinese people. Hospitalization and diabetes-related complications were uncommon in all groups. CONCLUSION: The incidence of Type 2 diabetes is higher than previously estimated among youth and is now surpassing diabetes on insulin only. Significant reductions in Type 2 diabetes screening ages in South Asians need to be considered and prevention efforts are urgently required in childhood and adolescence. Global estimates need to consider the epidemic of Type 2 diabetes in the young.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".