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J Pediatr ; 202: 258-264.e1, 2018 11.
Artículo en Inglés | MEDLINE | ID: mdl-30220443

RESUMEN

OBJECTIVE: To explore associations between level of adverse childhood experiences (ACEs) and unmet healthcare needs among children with autism spectrum disorder (ASD) using a population-based sample. STUDY DESIGN: Cross-sectional data from the 2011-2012 National Survey of Child Health were analyzed to estimate prevalence of unmet healthcare needs among children with ASD, aged 2-17 years (ASD = 1624; estimated population = 1 174 871). Multivariate Poisson and logistic regression models were used to estimate the relationship between reported ACEs and unmet healthcare needs among children with ASD. RESULTS: After we adjusted for all other variables, children with ASD who experienced 1-2 ACEs and 3+ ACEs were associated with 1.78 (P < .05) and 2.53 (P < .01) times the incidence rate of unmet healthcare needs in comparison with children without ACEs. Compared with children who experienced 0 ACEs, the adjusted odds of any unmet healthcare need were 2.34 (P < .01) and 2.66 (P < .01) for children with 1-2 ACEs and 3 + ACEs, respectively. CONCLUSION: Although limited to cross-sectional data, our study provides compelling evidence on the link between ACEs and unmet healthcare needs among children with ASD. It advances understanding of risk factors in the child and community context that contribute to health disparities and negatively impact healthcare access and use in this population.


Asunto(s)
Experiencias Adversas de la Infancia/estadística & datos numéricos , Trastorno del Espectro Autista/terapia , Servicios de Salud del Niño/organización & administración , Niños con Discapacidad/rehabilitación , Necesidades y Demandas de Servicios de Salud , Adolescente , Trastorno del Espectro Autista/diagnóstico , Trastorno del Espectro Autista/epidemiología , Niño , Preescolar , Estudios Transversales , Niños con Discapacidad/estadística & datos numéricos , Femenino , Accesibilidad a los Servicios de Salud/estadística & datos numéricos , Humanos , Modelos Logísticos , Masculino , Evaluación de Resultado en la Atención de Salud , Estudios Retrospectivos , Medición de Riesgo , Factores Socioeconómicos , Estados Unidos
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