Predicting Poor Sleep Quality in Young Adults on the Autism Spectrum

Poster Presentation
Saturday, May 12, 2018: 11:30 AM-1:30 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
A. L. Richdale1, L. P. Lawson2 and M. Uljarevic3,4, (1)Olga Tennison Autism Research Centre, La Trobe University, Melbourne, Australia, (2)Olga Tennison Autism Research Centre, La Trobe University OTARC, Melbourne, Australia, (3)Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, (4)Stanford Autism Center, Department of Psychiatry and Behavioral Sciences, Stanford University, CA
Background: Poor sleep quality, primarily insomnia symptoms, is commonly reported in individuals on the autism spectrum across the lifespan. Poor sleep quality in autism has been associated with problematic behaviours and poor mental health, but most research is in children under 18 years. Arousal has been hypothesised to underlie insomnia symptoms in both autism and in non-autistic populations. Consistent with an arousal hypothesis, anxiety, cognitive and somatic pre-sleep arousal, and sensory modulation have been shown to be associated with poor sleep in children with autism. However, little is known about the predictors of poor sleep quality in older cohorts.

Objectives: Our aim was to examine the ability of factors associated with arousal to predict sleep problem classification in young adults on the autism spectrum.

Methods: Participants were 64 young people on the autism spectrum, with a mean age of 19.06 (SD=2.56) years (70% male) who are members of the Australian Longitudinal Study of School Leavers with Autism (SASLA). Their mean Autism Quotient-Short (AQ) total score was 76.50 (SD=10.25; clinical screening cutoff >65). Our measures associated with arousal were sensory interests (Repetitive Behaviours Questionnaire-Adult [RBQ-Sensory]; 3 items), autonomic symptoms (COMPASS-31; 31 items), and intolerance of uncertainty (transdiagnostic factor underlying anxiety [IU-12]; 12-items). The Pittsburgh Sleep Quality Index (PSQI) was used to classify sleep quality.

Results: All variables except age were significantly associated with PSQI total score (all p < .01), and females had significantly higher COMPASS-31 and IU-12 scores than males (all p < .05). Fifty percent of males, and 63% of females had a PSQI score greater than 5 (p = .49). A logistic regression was used to classify membership of the sleep problem (PSQI > 5) and no sleep problem (PSQI < 6) groups. The independent variables entered were gender, AQ, RBQ-Sensory, COMPASS-31 and IU-12. The model was significant (p = .001) and explained between 29.8% and 39.8% of variance, and correctly classified 77.2% of sleep cases with a positive predictive value of 79.3%. Only RBQ-sensory made a significant unique contribution to the model, with an OR of 1.83.

Conclusions: We have identified that factors associated with arousal are significantly associated with poor sleep quality among young adults on the autism spectrum. Further, it was found that sensory interests were uniquely associated with an increased likelihood of having poor sleep quality. Sensory issues have previously been reported to be a predictor of poor sleep in children with autism and non-autistic infants, children and adults. Given the potential deleterious effects of poor sleep, it is important to understand variables associated with poor sleep in autism as this informs development of prevention and intervention strategies, and such variables may be targets for intervention.