New research from Stanford School of Medicine reveals that reduced sleep and physical activity during pregnancy are associated with an increased risk of preterm birth. The study, which analyzed data from more than 1,000 women wearing wearable devices throughout their pregnancies, found that deviations from normal patterns of sleep and activity were warning signs for premature delivery.
Why Sleep and Activity Matter in Pregnancy
During pregnancy, sleep is expected to become more disrupted and physical activity to decrease. However, some women experience accelerated changes in sleep and activity patterns relative to their gestational age, putting them at a higher risk of delivering their babies early. The study’s findings suggest that artificial intelligence algorithms can identify these deviations and act as a “clock” to track a patient’s pregnancy progress.
The Impact of Preterm Birth
Preterm birth, defined as a baby being born three or more weeks early, affects 10.5% of births in the United States and carries significant health risks. Premature newborns can experience complications in their eyes, lungs, brain, and digestive system, and it is currently the leading cause of death for children under the age of five worldwide.
Identifying at-Risk Pregnancies
While various risk factors for preterm delivery have been identified, doctors struggle to reliably determine which pregnancies are at risk. Even when a mother’s risk is known, effective treatments to extend the pregnancy closer to the due date are currently limited due to ethical concerns. However, if researchers can identify sleep and activity patterns that reduce the risk of preterm birth, interventions to help expectant mothers adopt better sleep and exercise habits could be developed.
The Study’s Approach
The Stanford Medicine team collaborated with researchers at Washington University in St. Louis to collect data from 1,083 pregnant women. Actigraphy devices similar to smartwatches were used to collect physical activity and light exposure measurements every minute from the first trimester until the babies were born. Additional data on gestational age, medical conditions, complications, and birth details were obtained from the participants’ electronic medical records.
What the Machine Learning Model Revealed
Using the movement and light exposure data, the research team developed a machine learning model of activity and sleep during pregnancy. They found that sleep and physical activity patterns changed over the course of pregnancy, with increased sleep disruption and decreased activity being common as the pregnancy progressed. Deviations from these patterns significantly predicted preterm birth risk.
The Importance of Consistent Sleep Habits
While the study’s findings are preliminary, they provide important insights for preventing prematurity. By tracking and modifying pregnant women’s sleep or physical activity, researchers believe it may be possible to lower the risk of preterm delivery. Maintaining good sleep habits, such as consistent bedtimes and wake-up times, sufficient sleep duration, and exposure to natural light during the day, is recommended as a low-risk approach to reduce the risk of preterm birth.
Future Directions for Intervention
The circadian clock, which regulates various biological pathways related to premature birth, is a potential target for intervention. Further studies will investigate whether improving sleep and physical activity during pregnancy could modify these pathways, particularly those involving inflammation and the immune response. The researchers hope that by focusing on this overarching regulator, they can effectively control individual systems that contribute to preterm birth.
While more research is needed to fully understand the implications, the encouraging results suggest that advising pregnant women to maintain regular sleep schedules and engage in physical activity has little downside. If sleep and activity can be used to modulate biology in the right direction, it could provide a valuable means of reducing the rate of preterm birth.