Advisory Committee Chair
Martha S Wingate
Advisory Committee Members
Julie K Preskitt
Bisakha Sen
Matthew Maenner
Sarah E O'Kelley
Document Type
Dissertation
Date of Award
2017
Degree Name by School
Doctor of Public Health (DrPH) School of Public Health
Abstract
Background: While there has been significant work done to explore disparities in autism spectrum disorder (ASD) diagnoses with respect to individual characteristics, little work has been done to examine the overall system and structure of the environment in which ASD identification is made and how it is related to diagnosis and services. The purpose of this study is to better understand the social-ecological factors that impact ASD diagnoses at the population level. Methods: In the first aim of this dissertation, a tailored social ecological model was developed and examined across variables in the 2011/12 National Survey of Children’s Health. In the second aim, a principal components analysis, cluster analysis, and multinomial regression were performed to understand the patterns of service provision in the 2011 Pathways to Services and Diagnosis Survey. Results: We found that race, sex, level of disability, insurance status, family financial burden, residence in a metropolitan statistical area, and whether or not a child had ever been a victim of or witness to violence were significant predictors of a parent-reported ASD diagnosis. It was also shown that 1) it was possible to use summated, factor-based scores based on medications, private/non-school-based services, school-based services, and services not covered by insurance to reduce dimensionality and represent certain aspects of the service and treatment experience of children with ASD; 2) Children with ASD differed in several ways – high and low users of services (both private and school-based), high and low users of medications, and high and low levels of reported non-covered services; and 3) the differences described above were clustered in multiple ways which are associated most closely with level of functional limitation and age at which a child was diagnosed with ASD. Conclusions: Disparities exist across a variety of measures of ASD diagnosis and service provision across social-ecological levels. Further research should incorporate longitudinal data at a variety of neighborhood, state, regional, and national levels.
Recommended Citation
Brisendine, Anne Elizabeth, "Autism Spectrum Disorders and Social-Ecological Models: Understanding how context drives prevalence" (2017). All ETDs from UAB. 1260.
https://digitalcommons.library.uab.edu/etd-collection/1260
