Machine Learning study links reduced sleep and activity to premature birth

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New York: Lack of sleep and reduced physical activity during pregnancy may increase the risk of premature birth, according to a study.

The team used a machine learning (ML) algorithm to detect fine-grained changes in sleep and physical activity patterns of 1,000 women whose data was collected by devices worn by them throughout pregnancy.

“We showed that an artificial intelligence algorithm can build a ‘clock’ of physical activity and sleep during pregnancy, and can tell how far along a patient’s pregnancy is, but some patients don’t follow that clock. When patients’ sleep and activity levels don’t change on a typical trajectory, the study showed, it’s a warning sign for premature birth,” said Nima Aghaeepour, Associate Professor of anesthesiology, perioperative and pain medicine and of paediatrics at Stanford School of Medicine.

The study, published in the journal npj Digital Medicine, also identified a variety of risk factors for premature delivery, including greater levels of inflammation in the pregnant woman, specific immune-system changes, higher levels of stress, history of having a preterm birth and certain types of bacteria in the mother’s microbiome.

“Our patient population experiences a lot of adversity, and our preterm birth rates are much higher than at Stanford,” said co-author Sarah England, Professor of obstetrics and gynaecology at Washington University School of Medicine in St. Louis.

“The study participants included women experiencing a variety of stressors linked with higher rates of preterm birth, such as racism, low socioeconomic status and living in areas with higher crime rates,” said England.

Surprisingly, sleeping better and being more physically active than usual for her stage of pregnancy was linked with a 48 per cent reduction in risk for preterm delivery. Conversely, if a woman was sleeping worse and being less physically active than usual for her stage of pregnancy, her risk for preterm delivery was 44 per cent higher than for pregnant women with typical sleep and activity patterns.

“The results suggest that scientists should run studies to test whether tracking and modifying pregnant women’s sleep or physical activity could lower their prematurity risk. It’s telling us where to go for future interventions,” said Aghaeepour.

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