BACKGROUND: Health disparities in autistic people are well-documented. Less is known, however, about how health determinants intersect, including what factors make a difference, for whom, and under what conditions. Coincidence analysis (CNA) is a cross-case, mathematical approach that pinpoints minimally sufficient and necessary conditions for an outcome to appear, making it particularly well-suited to identify intersecting determinants and multiple paths to the same outcome. OBJECTIVES: Guided by the National Institute on Minority Health and Health Disparities Research Framework, the study aimed to identify difference-makers for "excellent/very good" overall health among autistic children. METHODS: The 2022 National Survey of Children's Health contains parent-reported data about 1231 autistic children with "excellent/very good" overall health. A literature review informed the selection of 62 potentially relevant factors for analysis. CNA was applied to develop a model for explaining parents' reporting "excellent/very good" health for their autistic children. RESULTS: Initial exploratory analyses identified 7 strongly related factors. The final model revealed a 2-pathway solution that accounted for 82% of the respondents with 80% consistency: (1) a combination of no intellectual disability, no difficulty with chronic pain, and high family resilience; or (2) a combination of no intellectual disability, no difficulty with chronic pain, and no history of being overweight. CONCLUSIONS: Combinations of health determinants accounted for differences in the reported overall health of autistic children. This nuanced explanation for "excellent/very good" health among autistic children can guide future interventions and practices aimed at modifiable determinants of health.
Quon et al. (2026) studied this question.
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