Incidence of childhood type 1 diabetes worldwide. Diabetes Mondiale (DiaMond) Project Group.
Bibliographic record
Abstract
OBJECTIVE: To investigate and monitor the patterns in incidence of childhood type 1 diabetes worldwide. RESEARCH DESIGN AND METHODS: The incidence of type 1 diabetes (per 100,000 per year) from 1990 to 1994 was determined in children < or =14 years of age from 100 centers in 50 countries. A total of 19,164 cases were diagnosed in study populations totaling 75.1 million children. The annual incidence rates were calculated per 100,000 population. RESULTS: The overall age-adjusted incidence of type 1 diabetes varied from 0.1/100,000 per year in China and Venezuela to 36.8/100,000 per year in Sardinia and 36.5/100,000 per year in Finland. This represents a >350-fold variation in the incidence among the 100 populations worldwide. The global pattern of variation in incidence was evaluated by arbitrarily grouping the populations with a very low (<1/100,000 per year), a low (1-4.99/100,000 per year), an intermediate (5-9.99/100,000 per year), a high (10-19.99/100,000 per year), and a very high (> or =20/100,000 per year) incidence. Of the European populations, 18 of 39 had an intermediate incidence, and the remainder had a high or very high incidence. A very high incidence (> or =20/ 100,000 per year) was found in Sardinia, Finland, Sweden, Norway Portugal, the U.K., Canada, and New Zealand. The lowest incidence (<1/100,000 per year) was found in the populations from China and South America. In most populations, the incidence increased with age and was the highest among children 10-14 years of age. CONCLUSIONS: The range of global variation in the incidence of childhood type 1 diabetes is even larger than previously described. The earlier reported polar-equatorial gradient in the incidence does not seem to be as strong as previously assumed, but the variation seems to follow ethnic and racial distribution in the world population.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".