{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T15:24:00Z","timestamp":1792596240522,"version":"4.5.0"},"reference-count":44,"publisher":"American Medical Association (AMA)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n In universal health care settings, trends in autism spectrum disorder (ASD) diagnosis remain poorly characterized, yet are critical for identifying inequities that persist despite more equitable health care access.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To describe temporal trends in ASD diagnosis and in perinatal risk factors for ASD across maternal socioeconomic and immigration factors.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This is a population-based retrospective cohort study of children born in Ontario, Canada (2002-2020), linked to maternal health, immigration, and census data. Children were followed up from age 1 year until ASD diagnosis, death, out-migration, or April 2020. Data analysis was performed between August 2024 and March 2026.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Maternal socioeconomic indicators (area-level deprivation, ethnic diversity, income, Ontario Drug Benefit enrollment, and rural vs urban residence) and immigration characteristics (immigration status, category, time since immigration, region of origin, and country income level). Perinatal risk factors included maternal diabetes, maternal age 35 years or older, severe maternal morbidity, and prematurity.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n ASD was identified using a validated administrative algorithm. Incidence rates were calculated per 10 000 person-years and cumulative incidence per 1000 live births at 8 years. Temporal trends were estimated using negative binomial regression with interaction terms between birth year and covariates.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Of 2\u202f319\u202f302 children (1\u202f188\u202f270 male [51.2%]), 29 374 (1.3%) met ASD criteria, with 80.0% (23\u202f068 children) receiving a diagnosis by age 8 years and 78.5% of cases (23\u202f071 cases) occurring in male children. Diagnosis increased by 10% per birth cohort (95% CI, 10%-11%). Disparities in ASD diagnosis by socioeconomic and immigration characteristics widened across birth cohorts: by the 2012 birth cohort, diagnosis was 2.2-fold (95% CI, 2.0-2.4\u2013fold) higher in the most vs least deprived neighborhoods, 2.0-fold (95% CI, 1.8-2.2\u2013fold) higher in the most vs least ethnically diverse areas, and lower in rural vs urban regions. Diagnosis was 1.4-fold (95% CI, 1.3-1.5\u2013fold) higher among children of immigrant mothers, with the highest rates among mothers from low- and middle-income regions. Diabetes during pregnancy, severe maternal morbidity, and prematurity were more common in marginalized populations, with disparities in maternal diabetes widening over time.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this cohort study of more than 2.3 million mother-child pairs, ASD diagnoses occurred disproportionately among children from socioeconomically disadvantaged and immigrant families, with disparities widening over time. The higher prevalence of maternal diabetes, obstetric complications, and prematurity in these populations may have contributed to these differences.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.37174","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T15:00:31Z","timestamp":1791471631000},"page":"e2637174","source":"Crossref","is-referenced-by-count":1,"title":["Disparities in Autism Spectrum Disorder and Perinatal Risk Factors"],"prefix":"10.1001","volume":"9","author":[{"given":"Francesca","family":"del Giorgio","sequence":"first","affiliation":[{"name":"Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B\u00e9n\u00e9dicte","family":"Driollet","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, 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