Autism and immigration, is there a link? Results from a Manitoba Study
Bibliographic record
Abstract
Objectives: To examine a possible association between parental immigration and autism spectrum disorder (ASD) in Manitoba, Canada. Methods: Electronic medical records of children diagnosed with ASD between 2016 and 2021 at Manitoba's only publicly funded referral site for ASD evaluation in children ≤6 years of age were reviewed. Children born in or outside of Canada whose parents/guardians (one or both) were foreign-born were identified to have 'immigrant' parents. The proportion of Manitoba's immigrant population (including non-permanent residents) was obtained from 2016 to 2021 Census data and compared to the proportion of children diagnosed with ASD who had immigrant parent(s). Descriptive statistics were used to compare the characteristics of children with ASD born to immigrants versus non-immigrant parents. Results: Among 1858 children diagnosed with ASD during the study period, 669 (36%) had immigrant parents. This proportion was greater than the proportion of immigrants (and non-permanent residents) living in Manitoba in 2016: 243,835/1,278,365 (19%, P < 0.001) and 2021: 291,910/1,342,153 (21.7%, P < 0.001). Those with immigrant parents had a lower rate of family history of ASD (16.3% versus 33.3% P < 0.001), and associated neurologic comorbidities (4.2% versus 6.4% P: 0.047). There were no statistical differences in rates of preterm birth (15.5% versus 12.36 P: 0.152) or use of Autism Diagnostic Observation Schedule-2 in diagnostic approach (30.3% versus 33% P: 0.321) between groups. Conclusions: There is an over-representation of immigrant families among young children diagnosed with ASD in Manitoba. Further studies are needed to understand mechanisms that may play a role in this association.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".