Temporal and Geographical Variability of Prevalence and Incidence of Autism Spectrum Disorder Diagnoses in Children in Catalonia, Spain
Bibliographic record
Abstract
This study aims to estimate the prevalence of autism spectrum disorders (ASD) in 2017 and the ASD diagnosis incidence between 2009 and 2017 in children living in Catalonia region in Spain, and their temporal and geographical variability. We used administrative data for all children aged 2-17 years who were insured in the public Catalan Health System between 2009 and 2017. We identified all ASD cases diagnosed between 2009 and 2017 (ICD-9 codes 299.0, 299.1, 299.8, and 299.9). We estimated the ASD prevalence in 2017 and the overall annual incidence between 2009 and 2017, then stratified by sex, age group, and healthcare area. We used Poisson regression models to assess temporal trends in the incidence and mixed-effects Poisson regression models to assess geographical variability. We observed an ASD prevalence of 1.23% (95% confidence interval [CI] 1.21-1.25) in 2017, with 1.95% (95% CI 1.92-1.99) for boys and 0.46% (95% CI 0.44-0.48) for girls, the highest prevalence being in 11- to 17-year-olds (1.80%, 95% CI 1.76-1.83). The ASD diagnosis incidence increased from 0.07% (95% CI 0.06-0.09) in 2009 to 0.23% (95% CI 0.21-0.24) in 2017, with a higher increase in girls, and in children aged 2-5 years at the time of diagnosis. We only observed geographical differences in prevalence in the 2017 data. We also detected a threefold increase in the diagnosis incidence overall, which was even more pronounced in girls and at early ages. In conclusion, the ASD prevalence observed in this study was 1.23% in 2017, with a sex ratio of 4.5 in favor of boys, which is consistent with previous studies. Autism Res2019. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorders (ASD) are currently well known in our society as one of the most common neurodevelopmental disorders during childhood. The results of our study showed that, in 2017 in Catalonia, slightly more than one in a 100 children had an ASD diagnosis, it was more common in boys than in girls, and also in older children. In addition, between 2009 and 2017, we observed an increase in the number of new cases diagnosed each year. The data presented in this study will assist in planning and evaluating the needs of health services in this geographical region.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".