Can Sleep & Digestive Disruption in Infants be Predictive of Autism or Other Disorders?

David J. Heeger and Carlos Fernandez-Granda aim to characterize normal sleep & digestion cycles of infants with large-scale data sample of unprecedented size

Parents of newborn babies often feel an enormous amount of anxiety. These parents might wonder: Is my baby’s sleep schedule normal? Should my baby be eating more or less often? How frequently should I have to change my baby’s diaper?

Until now, answers to these questions have been difficult to substantiate.

But David J. Heeger, Professor of Psychology and Neural Science, Silver Professor, and Carlos Fernandez-Granda, Assistant Professor of Mathematics and Data Science, are using big data to provide a more accurate characterization of normal infant development for parents, pediatricians, and other clinicians.

The researchers are funded by a seed grant from the Moore Sloan Data Science Environment, a cross-institutional initiative at NYU CDS. They have asked parents and caregivers of newborn babies to be citizen scientists by collecting data with the Baby Connect phone app.

Over 850 babies are already enrolled in the study; the researchers have gathered 1.2 million sleep events, 2.1 million feedings, and 1.3 million diaper changes so far. (Click here if you or someone you know might be interested in enrolling a baby in the study.)

When Heeger and Fernandez-Granda have completed the data collection process, they plan to use big data analytics to identify typical and atypical sleep and digestive development patterns in early infancy, and track how these cycles change with age. They have already compiled and analyzed some initial results.

“A large database on infant development will help doctors offer better, scientifically-based advice that parents can use to manage infant’s sleep and eating,” explains NYU neuroscientist David Heeger, adding that the findings will be distributed to assist parents, doctors, specialists, and teachers in their future care of young children.

By using big data analytics and neural networks, Heeger and Fernandez-Granda will also be able to determine if chronic sleep and digestive problems in early infancy can be predictive markers for autism spectrum disorder (ASD) or other developmental disorders.

The researchers point out, however, that any identified predictive markers would serve as opportunities for early intervention rather than concrete diagnostic evidence. They also anticipate that some deviations in sleeping or eating patterns will be attributable to parenting habits.

Parents and clinicians who are already familiar with the well-known height and weight chart may soon be familiar with a sleep and digestion chart driven by data from Heeger and Fernandez-Granda’s study. In the future, the team plans to apply for additional funding from foundations with a particular focus on autism.

For more about the Baby Sleep Study, click here.

By Paul Oliver

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