Developing UK ASD Research Capacity: Regional and UK ASD Research Databases Include Children with Similar Characteristics

Thursday, May 17, 2012
Sheraton Hall (Sheraton Centre Toronto)
3:00 PM
F. Warnell1, M. Johnson2, H. McConachie2 and J. Parr1, (1)Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom, (2)Institute of Health and Society, Newcastle University, Newcastle upon Tyne, United Kingdom
Background:  ASD research often requires large numbers of participants, or participants with uncommon characteristics. To improve recruitment to studies, and enable families to take part in research, we developed two large databases: the Database of Children with ASD in the North East (Daslne) from 2003, and a pilot national database, the Autism Spectrum Database-UK (ASD-UK) from 2011.

Objectives: To identify the similarities and differences between the children included in Daslne (shown representative of the Regional population, McConachie et al., 2009 Archives of Disease in Childhood) and the children recruited in the first 6 months to the national ASD-UK. To show ASD researchers from the UK and abroad the extent to which the databases include children who are broadly representative of the overall childhood ASD population. 

Methods:  Children with ASD are identified in North East England through local ASD assessment teams, and lists held by education. For ASD-UK, parents are approached through Child Development Teams. All parents give informed consent, and complete information packs about themselves and their child (or children) with ASD, and siblings. Child’s diagnosis data are validated through information obtained from clinicians. For this analysis, data on child characteristics were compared.

Results:  After 8 years, Daslne includes 1038 children – around 55% of children aged 2-18 diagnosed with ASD from the population. After 6 months’ recruitment, 203 children have been included on ASD-UK. Due to its sampling method, ASD-UK includes a slightly higher proportion of children diagnosed before age 6 years than Daslne (61% vs. 55% respectively); 14% of Daslne children were diagnosed when aged 9 or over. Related to age at diagnosis and local diagnostic practice, the databases vary somewhat in proportions of children with parent-reported specific diagnoses: Autism 19% ASD-UK vs. 26% Daslne, Asperger syndrome 13% vs. 23%, and ASD 64% vs. 45% respectively. The proportions of boys and girls with specific diagnoses are, however, similar between ASD-UK and Daslne: Autism: boys 74% vs. 83%; girls 26% vs. 17%; Asperger syndrome: boys 93% vs. 88%; girls 7% vs. 12%; ASD: boys 87% vs. 86%; girls 13% vs. 14%.   Learning disability is more common in ASD-UK than Daslne children (42% vs. 32% respectively). However, the proportion of children receiving statutory educational support is very similar (54% vs. 51% respectively). School age children from the databases are similarly likely to attend mainstream school (57 vs. 51%), or a support unit attached to a mainstream school (10% vs. 11%).

Conclusions:  Despite their different sampling frames, and differences in the methods of recruitment for Daslne and ASD-UK, many of the characteristics of the children included in the databases are very similar. The large number of children that will be recruited through ASD-UK seem likely to be as representative of the overall ASD population as our large and successful Regional database. Researchers wishing to recruit from ASD-UK and the population-based Daslne can identify which is more scientifically appropriate for their study, knowing that the two databases are both as representative as possible of the ASD child population.

| More