Over-Time Estimates of Sociodemographic Disparities in Autism Identification in U.S. Elementary Schools

Abstract

Whether and to what extent sociodemographic disparities in school-based autism identification have been occurring in U.S. elementary schools is currently unclear. We investigated for disparities attributable to race, ethnicity, biological sex, family income, and language use by analyzing repeated cross-sectional data collected on very large samples of U.S. fourth graders participating in the National Assessment of Educational Progress from 2003 to 2022 (ns = 103,150–205,860). Multivariable logistic regression models accounting for potential confounds including student-level academic achievement and school-level resources repeatedly indicated that students of color, females, students from low-income families, and multilingual learners (MLs) are less likely to be identified with autism while attending U.S. elementary schools. These disparities have been largely stable over time, particularly for Black students, females, and MLs. Health and educational policies that ensure equal access to autism supports and services in U.S. elementary schools including by students from historically marginalized communities are warranted.