Early Autism Diagnosis Factors in Brazilian Children, 2013–2019

22,483 outpatient records from Brazil's Unified Health System investigate factors for early diagnosis of autism and pervasive developmental disorders. The study, authored by Vânia Reis Girianelli, uses Poisson regression to estimate relative risks based on demographic and referral variables. Early identification improved but still represented about 30% of diagnoses made during the period.

Use Cases

• Modeling the association between patient residence and early diagnosis based on the finding that children living in the same municipality as the diagnosis center had a higher rate.
• Analyzing the impact of referral source on diagnostic timing based on the reported higher rates for primary care and spontaneous demand referrals.
• Investigating regional disparities in early diagnosis based on the finding that the North region had lower rates compared to others.
• Studying temporal trends in early diagnosis rates from 2013 to 2019, as the description notes changes from 2014 onward.

Strengths

• Contains 22,483 patient records, providing a substantial sample size for analysis.
• Covers a 7-year time range (2013–2019), allowing for longitudinal trend observation.
• Includes specific statistical results, such as relative risk estimates and confidence intervals for various factors.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the underlying raw dataset is unknown, which may limit suitability assessment.
• Data may reflect geographic and institutional bias inherent to a single national healthcare system study.

Provenance

Source

Record of Outpatient Health Actions (RAAS) from Brazil's Unified Health System.

Collection Method

Exploratory cross-sectional study based on first appointment records.

Time Range

2013–2019

Geography

Brazil, with a focus on the Southeast region (57.7% of subjects).