Poor infant sleep quality a red flag for autism

Findings from a population-based Australian study suggest that poor infant sleep quality is associated with more pronounced autism characteristics and increased odds of an autism diagnosis.

The birth cohort study included 1,074 mother–infant pairs recruited from June 2010 to 2013 in Victoria, Australia’s Barwon region.

For the outcome measures, researchers used multiple questionnaires and checklists. Infant sleep characteristics was evaluated using the Brief Infant Sleep Questionnaire at 6 months (n=925) and at 12 months (n=885). Autism characteristics was reported by parents using the Child Behaviour Checklist for Ages 1½−5 (CBCL/1½−5; n=676) at 2 years and Strengths and Difficulties Questionnaire for report for ages 4−10 (SDQ/P4−10; n=791) at 4 years. Autism Diagnostic and Statistical Manual for Mental Disorders fifth edition diagnoses (n=64) were confirmed by 11.5 years.

At 6 months, every 10-percent increase (approximately 1 h) in night sleep duration was associated with fewer autism characteristics observed at 2 years (4.5-percent decrease on CBCL/1½–5; adjusted mean difference [AMD], −0.02, 95 percent confidence interval [CI], −0.04 to −0.01) and 4 years (4.5-percent decrease on SDQ/P4–10; AMD, −0.02, 95 percent CI, −0.03 to −0.007), as well as with 22-percent lower odds of an autism diagnosis by 11.5 years (adjusted odds ratio [AOR], 0.78, 95 percent CI, 0.65–0.94).

At 12 months, each 25-percent increase in sleep latency (approximately 5 min) was associated with more autism characteristics (1.5-percent increase on CBCL/1½–5; AMD, 0.006, 95 percent CI, 0.002–0.01) and 7.7-percent increased odds of an autism diagnosis (AOR, 1.08, 95 percent CI, 1.03–1.13).

Of note, among school-aged children who had received a diagnosis of autism, 42 percent reported use of melatonin in the previous month.

While the extent to which the findings reflect common determinants of poor sleep and autism is unclear, the study shows the potential of early monitoring of sleep issues for identifying children at risk of autism, according to the researchers.