Frequency and clinical characteristics of children and young people with type 2 diabetes at diagnosis from five world regions between 2012 and 2021: data from the SWEET Registry
Bibliographic record
Abstract
Abstract Aims/hypothesis The diagnosis of type 2 diabetes is increasing in young people worldwide. This study evaluated the frequency and clinical characteristics of young people presenting with type 2 diabetes from the multinational SWEET e.V Registry 2012–2021, including the first years of the COVID-19 pandemic. Methods This is a longitudinal observational study based on the SWEET Registry, which collects demographic and clinical data on children and adolescents with diabetes from centres worldwide, with the diagnosis and classification of diabetes provided locally by each centre according to International Society for Paediatric and Adolescent Diabetes definitions. By July 2022, the SWEET Registry included 96,931 individuals from 130 centres with a total of 1,154,555 visits. Data were analysed by region: Europe (EU), Australia and New Zealand (AU/NZ), South America (SA), North America (NA) and Asia/Middle East and Africa (AS/AF). Trends in proportions for the two-year periods, calculated as cases with type 2 diabetes diagnoses over all cases with diabetes diagnoses, were estimated using logistic regression models adjusted for age at onset and sex. Results Overall, there were 2819 of 58,170 new cases (4.8%) with type 2 diabetes: 614 in EU, 293 in AU/NZ, 79 in SA, 1211 in NA and 622 in AS/AF. The proportion of type 2 diabetes increased from 3.2% to 6.0% from 2012/2013 to 2020/2021, a relative rate of increase of 9% per two-year period (95% CI 5.9, 12.3; p<0.001). In the two-year period of the COVID-19 pandemic, type 2 diabetes continued to follow the observed trend, with a proportion of 6.0% in 2020–2021 compared with 5.4% in 2018–2019. High variability in the proportion of type 2 diabetes was observed across regions, with the lowest values observed in EU and the highest in NA. A significant increase in the proportion of type 2 diabetes was observed in EU, AU/NZ and NA. The median HbA1c was not uniform and was highest in AS/AF (85 mmol/mol [9.9%]; IQR 55–111 [7.2–12.3%]) and lowest in EU (63 mmol/mol [7.9%]; IQR 48–99 [6.5–11.2%]), and the difference between EU and NA (median value 73 mmol/mol [8.8%]; IQR 50–105 [6.7–11.8%]) was statistically significant (p=0.047). There was also a difference in BMI SD score by region: the lowest median BMI SD score was 2.2 (IQR 1.4–2.7) in AS/AF and the highest was 3.1 (IQR 2.5–3.6) in AU/NZ. Conclusions/interpretation The multinational SWEET data from the years 2012 to 2021 inclusive support recent findings of a worldwide increase in type 2 diabetes in young people, albeit with regional differences. This increase highlights the need for ongoing preventive measures and available advanced treatment modalities worldwide. Graphical Abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".