The Impact of Surveillance Method and Record Source on Autism Prevalence: Collaboration with Utah Maternal and Child Health Programs
- First Online:
- 173 Downloads
With the increasing number of Utah children identified with autism spectrum disorders (ASDs), information on the prevalence and characteristics of these children could help Maternal Child Health (MCH) programs develop population building activities focused on prevention, screening, and education. The purpose of this study is to describe Utah’s autism registry developed in collaboration with state MCH programs and assess the impact of different record-based surveillance methods on state ASD prevalence rates. The study was conducted using 212 ASD cases identified from a population of 26,217 eight year olds living in one of the three most populous counties in Utah (Davis, Salt Lake, and Utah) in 2002. ASD prevalence was determined using two records based approaches (administrative diagnoses versus abstraction and clinician review) by source of record ascertainment (education, health, and combined). ASD prevalence ranged from 7.5 per 1000 (95% CI 6.4–8.5) to 3.2 per 1000 (95% CI 2.5–3.9) varying significantly (P < .05) based on method and record source. The ratio of male-to-female ranged from 4.7:1 to 6.4:1. No significant differences were found between the two case ascertainment methods on 18 of the 23 case characteristics including median household income, parental education, and mean age of diagnosis. Broad support is needed from both education and health sources as well as collaboration with MCH programs to address the growing health concerns, monitoring, and treatment needs of children and their families impacted by autism spectrum disorders.
KeywordsAutism spectrum disorders Surveillance Prevalence Maternal child health Epidemiology
- 1.Autism and Developmental Disabilities Monitoring Network Surveillance Year 2002 Principal Investigators. (2007). Prevalence of autism spectrum disorders—autism and developmental disabilities monitoring network, 14 Sites, United States, 2002. MMWR, 56(SS-1), 12–28.Google Scholar
- 3.Fombonne, E. (2006). Past and future perspectives in autism epidemiology. In S. O. Molden & J. L. R. Rubenstein (Eds.), Understanding autism (pp. 25–48). Baca Raton, FL: Taylor and Francis Group.Google Scholar
- 8.Pinborough-Zimmerman, J., & McMahon, W. (2008). Autism: An urgent public health and education concern. The Utah Special Educator, Monograph Edition, 28(3)8–9.Google Scholar
- 9.Kogan, M. D., Strickland, B. B., Blumberg, S. J., Singh, G. K., Perrin, J. M., & van Dyck, P. C. (2008). A national profile of the health care experiences and family impact of autism spectrum disorder among children in the United States, 2005–2006. Pediatrics, 112(6), e1149–e1158. doi:10.1542/peds.2008-1057.CrossRefGoogle Scholar
- 11.Utah Registry of Autism and Developmental Disabilities. http://health.utah.gov/autism. Accessed on April 6, 2009.
- 12.U.S. Department of Health and Human Services. (2007). Maternal and child health services title V block grant program: Guidance and forms for the title V application/annual report fourth edition. Rockville, MD: Maternal and Child Health Bureau, pp. 5–31.Google Scholar
- 14.Mind Institute 2002 M.I.N.D. The epidemiology of autism in California. Report to the legislature on the principal findings from the epidemiology of autism in California: A comprehensive pilot study. http://www.mindfully.org/Health/2002/Autism-In-California-MIND17oct02.htm. Accessed on January 08, 2009.
- 16.Rice, C., Baio, J., Van Naarden Braun, K., Doernberg, N., Meaney, F. J., Kirby, R. S., et al. (2007). Determining the prevalence of the autism spectrum disorders (ASDs) in the United States: Methodology used by the CDC-funded ADDM. Paediatric and Perinatal Epidemiology, 21(2), 179–190. doi:10.1111/j.1365-3016.2007.00801.x.CrossRefPubMedGoogle Scholar
- 17.Van Naarden Braun, K., Pettygrove, S., Daniels, J., et al. (2007). Evaluation of a methodology for a collaborative multiple source surveillance network for autism spectrum disorders—autism and developmental disabilities monitoring network, 14 sites, United States, 2002. MMWR, 29–40.Google Scholar
- 20.Utah Code––Title 26––Utah Health Code. http://www.le.state.ut.us/~code/TITLE26/TITLE26.htm. Accessed on March 6, 2008.
- 21.International Classification of Diseases. (1988). Clinical modification (9th Rev.). Washington, DC: Public Health Service, US Dept of Health and Human Services.Google Scholar
- 22.United States Department of Education. http://idea.ed.gov/explore/view/p/,root,regs,300,A,300%252E8,c. Accessed on April 6, 2009.
- 23.Governor’s Office of Planning and Budget, Utah Population Estimates Committee. http://www.governor.utah.gov/dea/UPEC.html. Accessed on April 6, 2009.
- 24.Pinborough-Zimmerman, J., Satterfield, R., Miller, J., Bilder, D., Hossain, S., & McMahon, W. (2007). Communication disorders: Prevalence and comorbid intellectual disability, autism and emotional/behavioral disorders. American Journal of Speech-Language Pathology, 16(4), 359–367. doi:10.1044/1058-0360(2007/039).CrossRefPubMedGoogle Scholar
- 25.Utah Birth Defect Network. http://hlunix.hl.state.ut.us/birthdefect. Accessed on October 7, 2008.
- 26.Utah Department of Health’s Baby Watch Early Intervention Program. http://www.utahbabywatch.org. Accessed on October 7, 2008.
- 27.Utah Department of Health’s Child Health Advanced Records Management Program. http://charm.health.utah.gov. Accessed on October 7, 2008.
- 28.Utah Department of Health’s Center for Health Data IBIS-PH. http://ibis.health.utah.gov. Accessed on October 7, 2008.
- 29.Bilder, D., Pinborough-Zimmerman, J., Miller, J., & McMahon, W. (2009). Prenatal, perinatal and neonatal factors associated with autism spectrum disorders. Pediatrics, in press.Google Scholar
- 30.U.S. Department of Health and Human Services, Maternal and Child Health Bureau. Maternal child health bureau programs: Children with special health care needs MCHB objective. http://mchb.hrsa.gov/programs/default.htm. Accessed on April 6, 2009.