Mortality risk among Autistic children and young people: A nationwide birth cohort study
Bibliographic record
Abstract
Autism has been associated with increased mortality risk among adult populations, but little is known about the mortality risk among children and young people (0–24 years). We used a 15-year nationwide birth cohort study using linked health and non-health administrative data to estimate the mortality risk among Autistic children and young people in Aotearoa/New Zealand. Time-to-event analysis was used to determine the association between autism and mortality, controlling for sex, age, ethnicity, deprivation and rurality of residence. The participant population included 895,707 children of whom 11,919 (1.4%) were identified as Autistic. Autism was associated with a significantly higher mortality risk (hazard ratio = 2.35; 95% confidence interval = 1.80–3.06) compared to the general population. In addition, using stratified analyses, we found that this risk was significantly higher among females (hazard ratio = 5.40; 95% confidence interval = 3.42–8.52) compared to males (hazard ratio = 1.82; 95% confidence interval = 1.32–2.52). We also determined that among Autistic young people, mortality risk was significantly higher for those with a co-occurring intellectual disability (hazard ratio = 2.02; 95% confidence interval = 1.17–3.46). In this study, autism was associated with higher mortality in children and young people compared to the non-Autistic population. Increased efforts are required to better meet the health needs of this population. Lay abstract Existing literature indicates that Autistic people have shorter life expectancy, but little is known about the mortality risk among Autistic children and young people (0–24 years). We used a 15-year nationwide birth cohort study to estimate the mortality risk among Autistic children and young people in Aotearoa/New Zealand. The study included 895,707 children and 11,919 (1.4%) were Autistic. We found that autism was associated with a significantly higher mortality risk compared to the non-Autistic population. In addition, we found that this risk was significantly higher among females compared to males and for those with a co-occurring intellectual disability. Increased efforts are required to better meet the health needs of this 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".