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Early diagnosis of autism and other developmental disorders, Brazil, 2013–2019

ABSTRACT

OBJECTIVE

To investigate the factors associated with the early diagnosis of autism and other types of pervasive developmental disorder (PDD) in children treated at the Psychosocial Care Center for Children and Adolescents of the Unified Health System, from 2013 to 2019,in Brazil.

METHODS

An exploratory cross-sectional study, based on data from the Record of Outpatient Health Actions (RAAS) of the first appointment of children aged 1 to 12 years. The gross (RRg) and adjusted (RRa) relative risks and respective 95% confidence intervals (95%CI) were estimated using the Poisson regression model with robust variance estimation.

RESULTS

Of the 22,483 children included in the study, the majority were male (81.9%), lived in the same municipality where they were diagnosed (96.8%) and in the Southeast region (57.7%). Early diagnosis was higher for childhood autism (RRg = 1.48; 95%CI 1.27–1.71) , PDD without subtype designation (RRg = 1.55; 95%CI 1.34–1.80), other PDD (RRg = 1.48; 95%CI 1.21–1.81) and PDD not otherwise specified (RRg = 1.44; 95%CI 1.22–1.69) than for atypical autism. Children residing in the same municipality where the diagnosis was made had a higher rate of early diagnosis (RRg = 1.31; 95%CI 1.10–1.55) than the others; as well as those referred by primary care (RRg = 1.51; 95%CI 1.37–1.68) and by spontaneous demand (RRg = 1.45; 95%CI 1.31–1.61) than those from other types of referral. Early diagnosis was higher from 2014 and lower in the North region than in the other regions. In the multiple analysis, the magnitude of RRa was similar to that of RRg.

CONCLUSIONS

Early identification of autism and other PDD has improved in Brazil, but it still represents about 30% of the diagnoses made. The variables included in the model were significant, but still explain little of the early diagnosis of children with autism and other PDD.

Autism Spectrum Disorder; Epidemiology; Child Development Disorders, Pervasive; Early Diagnosis; Analytical Epidemiology; Psychosocial Support Systems; Unified Health System

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E-mail: revsp@usp.br