Publication Date

Spring 2026

Degree Type

Thesis

Degree Name

Master of Arts (MA)

Department

Economics

Advisor

Paul-Vincent Lombardi; Ari Ne’eman; Patralekha Ukil

Abstract

Diagnostic identification of neurodevelopmental conditions (NDCs) in children varies by socioeconomic and demographic characteristics, raising concerns about the equitable and efficient allocation of public services. This study uses data from the National Health Interview Survey for 2019–2024 to examine prevalence trends and socioeconomic predictors of parent-reported diagnoses of autism, intellectual disability (ID), attention-deficit/hyperactivity disorder (ADHD), and learning disabilities (LD). Subgroups defined by co-occurrence are analyzed to reveal patterns that aggregate categories obscure. Prevalence rose substantially for autism (2.5% to 4.1%) and ADHD (8.6% to 13.0%), while ID prevalence remained stable. The autism increase was driven entirely by autism without ID. Survey-weighted logistic regression identified predictors common across conditions, including lower family income, public insurance, older parental age, and father absence, while poverty strongly predicted autism without ID but not autism with ID, and racial/ethnic minorities showed substantially lower ADHD and LD diagnosis odds. The consistent association between father absence and NDC diagnosis prompted a supplementary analysis of divorce and separation, which found elevated odds across all conditions (ranging from 1.38 to 2.31). Results suggest that disparities in diagnostic identification prevent publicly financed services from reaching all children whose needs warrant them, and that family-level supports should accompany child-focused interventions.

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Available for download on Sunday, July 25, 2027

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